22 pages, 8177 KiB  
Article
Validity, Test-Retest Reliability and Long-Term Stability of Magnetometer Free Inertial Sensor Based 3D Joint Kinematics
by Wolfgang Teufl, Markus Miezal, Bertram Taetz, Michael Fröhlich and Gabriele Bleser
Sensors 2018, 18(7), 1980; https://doi.org/10.3390/s18071980 - 21 Jun 2018
Cited by 83 | Viewed by 9913
Abstract
The present study investigates an algorithm for the calculation of 3D joint angles based on inertial measurement units (IMUs), omitting magnetometer data. Validity, test-retest reliability, and long-term stability are evaluated in reference to an optical motion capture (OMC) system. Twenty-eight healthy subjects performed [...] Read more.
The present study investigates an algorithm for the calculation of 3D joint angles based on inertial measurement units (IMUs), omitting magnetometer data. Validity, test-retest reliability, and long-term stability are evaluated in reference to an optical motion capture (OMC) system. Twenty-eight healthy subjects performed a 6 min walk test. Three-dimensional joint kinematics of the lower extremity was recorded simultaneously by means of seven IMUs and an OptiTrack OMC system. To evaluate the performance, the root mean squared error (RMSE), mean range of motion error (ROME), coefficient of multiple correlations (CMC), Bland-Altman (BA) analysis, and intraclass correlation coefficient (ICC) were calculated. For all joints, the RMSE was lower than 2.40°, and the ROME was lower than 1.60°. The CMC revealed good to excellent waveform similarity. Reliability was moderate to excellent with ICC values of 0.52–0.99 for all joints. Error measures did not increase over time. When considering soft tissue artefacts, RMSE and ROME increased by an average of 2.2° ± 1.5° and 2.9° ± 1.7°. This study revealed an excellent correspondence of a magnetometer-free IMU system with an OMC system when excluding soft tissue artefacts. Full article
(This article belongs to the Section Physical Sensors)
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27 pages, 10604 KiB  
Review
An Overview of Non-Destructive Testing Methods for Integrated Circuit Packaging Inspection
by Pouria Aryan, Santhakumar Sampath and Hoon Sohn
Sensors 2018, 18(7), 1981; https://doi.org/10.3390/s18071981 - 21 Jun 2018
Cited by 111 | Viewed by 19668
Abstract
The article provides a review of the state-of-art non-destructive testing (NDT) methods used for evaluation of integrated circuit (IC) packaging. The review identifies various types of the defects and the capabilities of most common NDT methods employed for defect detection. The main aim [...] Read more.
The article provides a review of the state-of-art non-destructive testing (NDT) methods used for evaluation of integrated circuit (IC) packaging. The review identifies various types of the defects and the capabilities of most common NDT methods employed for defect detection. The main aim of this paper is to provide a detailed review on the common NDT methods for IC packaging addressing their principles of operation, advantages, limitations and suggestions for improvement. The current methods such as, X-ray, scanning acoustic microscopy (SAM), infrared thermography (IRT), magnetic current imaging (MCI) and surface acoustic waves (SAW) are explicitly reviewed. The uniqueness of the paper lies in comprehensive comparison of the current NDT methods, recommendations for the improvements, and introduction of new candidate NDT technologies, which can be adopted for IC packaging. Full article
(This article belongs to the Section Physical Sensors)
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17 pages, 5963 KiB  
Article
Optimal Design of a Planar Textile Antenna for Industrial Scientific Medical (ISM) 2.4 GHz Wireless Body Area Networks (WBAN) with the CRO-SL Algorithm
by Rocío Sánchez-Montero, Carlos Camacho-Gómez, Pablo-Luís López-Espí and Sancho Salcedo-Sanz
Sensors 2018, 18(7), 1982; https://doi.org/10.3390/s18071982 - 21 Jun 2018
Cited by 26 | Viewed by 5583
Abstract
This paper proposes a low-profile textile-modified meander line Inverted-F Antenna (IFA) with variable width and spacing meanders, for Industrial Scientific Medical (ISM) 2.4-GHz Wireless Body Area Networks (WBAN), optimized with a novel metaheuristic algorithm. Specifically, a metaheuristic known as Coral Reefs Optimization with [...] Read more.
This paper proposes a low-profile textile-modified meander line Inverted-F Antenna (IFA) with variable width and spacing meanders, for Industrial Scientific Medical (ISM) 2.4-GHz Wireless Body Area Networks (WBAN), optimized with a novel metaheuristic algorithm. Specifically, a metaheuristic known as Coral Reefs Optimization with Substrate Layer (CRO-SL) is used to obtain an optimal antenna for sensor systems, which allows covering properly and resiliently the 2.4–2.45-GHz industrial scientific medical bandwidth. Flexible pad foam has been used to make the designed prototype with a 1.1-mm thickness. We have used a version of the algorithm that is able to combine different searching operators within a single population of solutions. This approach is ideal to deal with hard optimization problems, such as the design of the proposed meander line IFA. During the optimization phase with the CRO-SL, the proposed antenna has been simulated using CST Microwave Studio software, linked to the CRO-SL by means of MATLAB implementation and Visual Basic Applications (VBA) code. We fully describe the antenna design process, the adaptation of the CRO-SL approach to this problem and several practical aspects of the optimization and details on the algorithm’s performance. To validate the simulation results, we have constructed and measured two prototypes of the antenna, designed with the proposed algorithm. Several practical aspects such as sensitivity during the antenna manufacturing or the agreement between the simulated and constructed antenna are also detailed in the paper. Full article
(This article belongs to the Section Sensor Networks)
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23 pages, 6667 KiB  
Article
Smart Road Traffic Accidents Reduction Strategy Based on Intelligent Transportation Systems (TARS)
by Abdulaziz Aldegheishem, Humera Yasmeen, Hafsa Maryam, Munam Ali Shah, Amjad Mehmood, Nabil Alrajeh and Houbing Song
Sensors 2018, 18(7), 1983; https://doi.org/10.3390/s18071983 - 21 Jun 2018
Cited by 48 | Viewed by 17845
Abstract
Traffic accidents have become an important problem for governments, researchers and vehicle manufacturers over the last few decades. However, accidents are unfortunate and frequently occur on the road and cause death, damage to infrastructure, and health injuries. Therefore, there is a need to [...] Read more.
Traffic accidents have become an important problem for governments, researchers and vehicle manufacturers over the last few decades. However, accidents are unfortunate and frequently occur on the road and cause death, damage to infrastructure, and health injuries. Therefore, there is a need to develop a protocol to avoid or prevent traffic accidents at the extreme level in order to reduce human loss. The aim of this research is to develop a new protocol, named as the Traffic Accidents Reduction Strategy (TARS), for Vehicular Ad-hoc NETworks (VANETs) to minimize the number of road accidents, decrease the death rate caused by road accidents, and for the successful deployment of the Intelligent Transportation System (ITS). We have run multiple simulations and the results showed that our proposed scheme has outperformed DBSR and POVRP routing protocols in terms of the Message Delivery Ratio (MDR), Message Loss Ratio (MLR), Average Delay, and Basic Safety Message. Full article
(This article belongs to the Special Issue Advances on Vehicular Networks: From Sensing to Autonomous Driving)
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20 pages, 745 KiB  
Article
Road Anomalies Detection System Evaluation
by Nuno Silva, Vaibhav Shah, João Soares and Helena Rodrigues
Sensors 2018, 18(7), 1984; https://doi.org/10.3390/s18071984 - 21 Jun 2018
Cited by 44 | Viewed by 6472
Abstract
Anomalies on road pavement cause discomfort to drivers and passengers, and may cause mechanical failure or even accidents. Governments spend millions of Euros every year on road maintenance, often causing traffic jams and congestion on urban roads on a daily basis. This paper [...] Read more.
Anomalies on road pavement cause discomfort to drivers and passengers, and may cause mechanical failure or even accidents. Governments spend millions of Euros every year on road maintenance, often causing traffic jams and congestion on urban roads on a daily basis. This paper analyses the difference between the deployment of a road anomalies detection and identification system in a “conditioned” and a real world setup, where the system performed worse compared to the “conditioned” setup. It also presents a system performance analysis based on the analysis of the training data sets; on the analysis of the attributes complexity, through the application of PCA techniques; and on the analysis of the attributes in the context of each anomaly type, using acceleration standard deviation attributes to observe how different anomalies classes are distributed in the Cartesian coordinates system. Overall, in this paper, we describe the main insights on road anomalies detection challenges to support the design and deployment of a new iteration of our system towards the deployment of a road anomaly detection service to provide information about roads condition to drivers and government entities. Full article
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23 pages, 13957 KiB  
Article
An Effective Image Denoising Method for UAV Images via Improved Generative Adversarial Networks
by Ruihua Wang, Xiongwu Xiao, Bingxuan Guo, Qianqing Qin and Ruizhi Chen
Sensors 2018, 18(7), 1985; https://doi.org/10.3390/s18071985 - 21 Jun 2018
Cited by 28 | Viewed by 5169
Abstract
Unmanned aerial vehicles (UAVs) are an inexpensive platform for collecting remote sensing images, but UAV images suffer from a content loss problem caused by noise. In order to solve the noise problem of UAV images, we propose a new methods to denoise UAV [...] Read more.
Unmanned aerial vehicles (UAVs) are an inexpensive platform for collecting remote sensing images, but UAV images suffer from a content loss problem caused by noise. In order to solve the noise problem of UAV images, we propose a new methods to denoise UAV images. This paper introduces a novel deep neural network method based on generative adversarial learning to trace the mapping relationship between noisy and clean images. In our approach, perceptual reconstruction loss is used to establish a loss equation that continuously optimizes a min-max game theoretic model to obtain better UAV image denoising results. The generated denoised images by the proposed method enjoy clearer ground objects edges and more detailed textures of ground objects. In addition to the traditional comparison method, denoised UAV images and corresponding original clean UAV images were employed to perform image matching based on local features. At the same time, the classification experiment on the denoised images was also conducted to compare the denoising results of UAV images with others. The proposed method had achieved better results in these comparison experiments. Full article
(This article belongs to the Special Issue High-Performance Computing in Geoscience and Remote Sensing)
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12 pages, 1861 KiB  
Article
Electrochemical Determination of Nitrite by Au Nanoparticle/Graphene-Chitosan Modified Electrode
by Rijian Mo, Xuehua Wang, Qiong Yuan, Xiemin Yan, Tiantian Su, Yanting Feng, Lulu Lv, Chunxia Zhou, Pengzhi Hong, Shengli Sun, Zhe Wang and Chengyong Li
Sensors 2018, 18(7), 1986; https://doi.org/10.3390/s18071986 - 21 Jun 2018
Cited by 50 | Viewed by 5465
Abstract
A highly sensitive nitrite (NO2) electrochemical sensor is fabricated using glassy carbon electrode modified with Au nanoparticle and grapheme oxide. Briefly, this electrochemical sensor was prepared by drop-coating graphene oxide-chitosan mixed film on the surface of the electrode and then [...] Read more.
A highly sensitive nitrite (NO2) electrochemical sensor is fabricated using glassy carbon electrode modified with Au nanoparticle and grapheme oxide. Briefly, this electrochemical sensor was prepared by drop-coating graphene oxide-chitosan mixed film on the surface of the electrode and then electrodepositing a layer of Au nanoparticle using cyclic voltammetry. The electrochemical behavior of NO2 on the sensor was investigated by cyclic voltammetry and amperometric i-t curve. The results showed that the sensor exhibited better electrocatalytic activity for NO2 in 0.1 mol/L phosphate buffer solution (PBS) (pH 5.0). The oxidation peak current was positively correlated with NO2 concentration in the ranges of 0.9 µM to 18.9 µM. The detection limit was estimated to be 0.3 µM. In addition, the interference of some common ions (e.g., NO3, CO32−, SO42−, Cl, Ca2+ and Mg2+) and oxidizable compound including sodium sulfite and ascorbic acid in the detection of nitrite was also studied. The results show that this sensor is more sensitive and selective to NO2. Therefore, this electrochemical sensor provided an effective tool for the detection of NO2. Full article
(This article belongs to the Section Chemical Sensors)
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10 pages, 4715 KiB  
Article
Theoretical Analysis of a Microring Resonator Array with High Sensitivity and Large Dynamic Range Based on a Multi-Scale Technique
by Wenqin Mo, Huiyun Liu, Fang Jin, Junlei Song and Kaifeng Dong
Sensors 2018, 18(7), 1987; https://doi.org/10.3390/s18071987 - 21 Jun 2018
Cited by 3 | Viewed by 3507
Abstract
By using a multi-scale measurement technique, a high-sensitivity and large dynamic-range sensor array, which consisted of a single resonator and a series of cascaded resonators with a sensing ring and a reference ring, was modeled, and its transmission properties were investigated theoretically and [...] Read more.
By using a multi-scale measurement technique, a high-sensitivity and large dynamic-range sensor array, which consisted of a single resonator and a series of cascaded resonators with a sensing ring and a reference ring, was modeled, and its transmission properties were investigated theoretically and numerically. We also set forth the principle of a multi-scale measurement technique based on the transmission spectrum of a resonator. This sensor array could have a nearly tenfold increase in sensitivity, and an improved dynamic range in an arrow wavelength range. The simulated results were in good agreement with the theoretical analysis. Full article
(This article belongs to the Special Issue Optical Waveguide Based Sensors)
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16 pages, 3835 KiB  
Article
Reliability Evaluation and Robust Design of a Sensor in an Entire Roller-Embedded Shapemeter
by Haimiao Wu, Guohua Cui, Dan Zhang and Hongmin Liu
Sensors 2018, 18(7), 1988; https://doi.org/10.3390/s18071988 - 21 Jun 2018
Cited by 8 | Viewed by 3556
Abstract
The intermittence of the shape detection signal associated with an entire roller-embedded shapemeter roll, used in a seven-pass cold reversible rolling process, is considered. A transient interference at the sensor top surface and the distance between the sensor top surface and the roll [...] Read more.
The intermittence of the shape detection signal associated with an entire roller-embedded shapemeter roll, used in a seven-pass cold reversible rolling process, is considered. A transient interference at the sensor top surface and the distance between the sensor top surface and the roll outer surface are developed, and a sensor reliability evaluation model is derived. The reliability of the sensor is evaluated via the random perturbation method, and the reliability sensitivity of design variables is proposed. The analysis reveals that the reliability is smallest in the third rolling pass. Of the design variables considered, the initial interference exhibits the largest reliability sensitivity and has the greatest influence on the sensor reliability. A reliability robust design model of the initial interference is therefore developed. A new shapemeter roll is fabricated and tested in a 1050 reversible cold rolling mill. The test results are consistent with the theoretical results, thereby validating the proposed model. The selection of an appropriate initial interference provides an important means of overcoming the adverse effects associated with the thermal deformation of sensor contact surfaces. Full article
(This article belongs to the Special Issue Sensors for MEMS and Microsystems)
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10 pages, 2420 KiB  
Communication
Experimental Demonstration of Remote and Compact Imaging Spectrometer Based on Mobile Devices
by Jie Chen, Fuhong Cai, Rongxiao He and Sailing He
Sensors 2018, 18(7), 1989; https://doi.org/10.3390/s18071989 - 21 Jun 2018
Cited by 24 | Viewed by 4145
Abstract
Imaging spectrometers show great potential for environmental and biomedical sensing applications. Selfie sticks, which are tools used to take photographs or videos, have gained global popularity in recent years. Few people have connected these two objects, and few people have researched the application [...] Read more.
Imaging spectrometers show great potential for environmental and biomedical sensing applications. Selfie sticks, which are tools used to take photographs or videos, have gained global popularity in recent years. Few people have connected these two objects, and few people have researched the application of imaging spectrometers to perform scientific monitoring in point-of-use scenarios. In this paper, we develop a compact imaging spectrometer (35 g in weight, 18 mm in diameter, and 72 mm in length) that can be equipped on a motorized selfie stick to perform remote sensing. We applied this system to perform environmental and facial remote sensing via motorized scanning. The absorption of chlorophyll and hemoglobin can be found in the reflectance spectra, indicating that our system can be used in urban greening monitoring and point-of-care testing. In addition, this compact imaging spectrometer was also easily attached to an underwater dome port and a quad-rotor unmanned aerial vehicle to perform underwater and airborne spectral detection. Our system offers a route toward mobile imaging spectrometers used in daily life. Full article
(This article belongs to the Section Remote Sensors)
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13 pages, 4125 KiB  
Article
UV Light Illumination Can Improve the Sensing Properties of LaFeO3 to Acetone Vapor
by Heng Zhang, Hongwei Qin, Chengyong Gao, Guangjun Zhou, Yanping Chen and Jifan Hu
Sensors 2018, 18(7), 1990; https://doi.org/10.3390/s18071990 - 21 Jun 2018
Cited by 15 | Viewed by 3437
Abstract
The synthesized LaFeO3 nanocrystalline sensor powders show positive response to sensing acetone vapor at 200 °C. The responses to acetone vapor (at 0.5, 1, 2, 5, 10 ppm) are 1.18, 1.22, 1.89, 3.2 and 7.83. To make the sensor operate at a [...] Read more.
The synthesized LaFeO3 nanocrystalline sensor powders show positive response to sensing acetone vapor at 200 °C. The responses to acetone vapor (at 0.5, 1, 2, 5, 10 ppm) are 1.18, 1.22, 1.89, 3.2 and 7.83. To make the sensor operate at a lower optimum temperature, UV light illumination 365 nm is performed. Response of the sensor has a larger improvement under 365 nm UV light illumination than without it. The responses to acetone vapor (at 0.5, 1, 2, 5, 10 ppm) are 1.37, 1.85, 3.16, 8.32 and 14.1. Furthermore, the optimum operating temperature is reduced to 170 °C. As the relative humidity increases, the resistance and sensitivity of sensor are reduced. The sensor shows good selectivity toward acetone when compared with other gases. Since the detection of ultralow concentrations of acetone vapor is possible, the sensor can be used to preliminarily judge diabetes in the general public, as a high concentration of acetone is exhaled in breath of diabetic patients. The sensor shows a good stability, which is further enhanced under UV light illumination. The sensor shows better stability when under 365 nm UV light illumination. Whether under light illumination or not. The LaFeO3 material shows good performance as a sensor when exposed to acetone vapor. Full article
(This article belongs to the Section Chemical Sensors)
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19 pages, 310 KiB  
Review
A Systematic Survey on Sensor Failure Detection and Fault-Tolerance in Ambient Assisted Living
by Nancy E. ElHady and Julien Provost
Sensors 2018, 18(7), 1991; https://doi.org/10.3390/s18071991 - 21 Jun 2018
Cited by 38 | Viewed by 5870
Abstract
Ambient Assisted Living (AAL) systems aim to enable the elderly people to stay active and live independently into older age by monitoring their behaviour, provide the needed assistance and detect early signs of health status deterioration. Non-intrusive sensors are preferred by the elderly [...] Read more.
Ambient Assisted Living (AAL) systems aim to enable the elderly people to stay active and live independently into older age by monitoring their behaviour, provide the needed assistance and detect early signs of health status deterioration. Non-intrusive sensors are preferred by the elderly to be used for the monitoring purposes. However, false positive or negative triggers of those sensors could lead to a misleading interpretation of the status of the elderlies. This paper presents a systematic literature review of the sensor failure detection and fault tolerance in AAL equipped with non-intrusive, event-driven, binary sensors. The existing works are discussed, and the limitations and research gaps are highlighted. Full article
(This article belongs to the Special Issue Smart Homes)
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19 pages, 29569 KiB  
Article
A Method to Track Targets in Three-Dimensional Space Using an Imaging Sonar
by Danxiang Jing, Jun Han and Jin Zhang
Sensors 2018, 18(7), 1992; https://doi.org/10.3390/s18071992 - 21 Jun 2018
Cited by 13 | Viewed by 3663
Abstract
This paper introduces a methodology applying an imaging sonar for three-dimensional (3D) target tracking underwater. The key process in this work involves obtaining the target’s position in space using two images of the same scene, acquired by an adaptive resolution imaging sonar (ARIS) [...] Read more.
This paper introduces a methodology applying an imaging sonar for three-dimensional (3D) target tracking underwater. The key process in this work involves obtaining the target’s position in space using two images of the same scene, acquired by an adaptive resolution imaging sonar (ARIS) at different positions. A data association algorithm was designed to connect the same target in image sequences. The goal of this work was to track multiple targets in 3D space. The ARIS provides sequences of bi-dimensional images from the backscattered energy according to the range and azimuth. The challenge involved determining the missing elevation information for the observed object within the sonar detection range. By computing the geometrical transformation between the acquisition planar images and the cubical space, using only the sonar information that included the posture and moving speed of the ARIS, the target’s elevation information was obtained. To evaluate the performance of the proposed method, an indoor experiment was conducted using the ARIS. On the basis of the experimental results, we confirmed that the proposed method effectively obtained the target’s position in 3D space. A moving target simulation was also conducted, and the results showed that this method was effective for moving targets. Finally, a field experiment was performed to obtain the vertical distribution and track the 3D trajectories of fish. Full article
(This article belongs to the Section Physical Sensors)
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20 pages, 5224 KiB  
Article
Design and Modeling of a Test Bench for Dual-Motor Electric Drive Tracked Vehicles Based on a Dynamic Load Emulation Method
by Zhe Wang, Haoliang Lv, Xiaojun Zhou, Zhaomeng Chen and Yong Yang
Sensors 2018, 18(7), 1993; https://doi.org/10.3390/s18071993 - 21 Jun 2018
Cited by 14 | Viewed by 9118
Abstract
Dual-motor Electric Drive Tracked Vehicles (DDTVs) have attracted increasing attention due to their high transmission efficiency and economical fuel consumption. A test bench for the development and validation of new DDTV technologies is necessary and urgent. How to load the vehicle on a [...] Read more.
Dual-motor Electric Drive Tracked Vehicles (DDTVs) have attracted increasing attention due to their high transmission efficiency and economical fuel consumption. A test bench for the development and validation of new DDTV technologies is necessary and urgent. How to load the vehicle on a DDTV test bench exactly the same as on a real road is a crucial issue when designing the bench. This paper proposes a novel dynamic load emulation method to address this problem. The method adopts dual dynamometers to simulate both the road load and the inertia load that are imposed on the dual independent drive systems. The vehicle’s total inertia equivalent to the drive wheels is calculated with separate consideration of vehicle body, tracks and road wheels to obtain a more accurate inertia load. A speed tracking control strategy with feedforward compensation is implemented to control the dual dynamometers, so as to make the real-time dynamic load emulation possible. Additionally, a MATLAB/Simulink model of the test bench is built based on a dynamics analysis of the platform. Experiments are finally carried out on this test bench under different test conditions. The outcomes show that the proposed load emulation method is effective, and has good robustness and adaptability to complex driving conditions. Besides, the accuracy of the established test bench model is also demonstrated by comparing the results obtained from the simulation model and experiments. Full article
(This article belongs to the Special Issue Mechatronic Systems for Automatic Vehicles)
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15 pages, 9345 KiB  
Article
Investigation of Gasochromic Rhodium Complexes Towards Their Reactivity to CO and Integration into an Optical Gas Sensor for Fire Gas Detection
by Carolin Pannek, Karina R. Tarantik, Katrin Schmitt and Jürgen Wöllenstein
Sensors 2018, 18(7), 1994; https://doi.org/10.3390/s18071994 - 21 Jun 2018
Cited by 10 | Viewed by 4504
Abstract
The detection of the toxic gas carbon monoxide (CO) in the low ppm range is required in different applications. We present a study of the reactivity of different gasochromic rhodium complexes towards the toxic gas carbon monoxide (CO). Therefore, variations of binuclear rhodium [...] Read more.
The detection of the toxic gas carbon monoxide (CO) in the low ppm range is required in different applications. We present a study of the reactivity of different gasochromic rhodium complexes towards the toxic gas carbon monoxide (CO). Therefore, variations of binuclear rhodium complexes with different ligands were prepared. They were characterized by FTIR spectroscopy, 1H NMR spectroscopy, and differential scanning calorimetry. All complexes are spectroscopically distinguishable and temperature stable up to at least 187 °C. The gasochromic behavior of all different compounds was tested. Therefore, the compounds were dissolved in toluene and exposed to 100 ppm CO for 10 min to investigate their gas sensitivity and reaction velocity. The changes in the transmission spectra were recorded by UV/vis spectroscopy. Furthermore, a significant influence of the solvent to the color dyes’ gasochromic reaction and behavior was observed. After characterization, one complex was transferred as sensing element into an optical gas sensor. Two different measurement principles (reflection- and waveguide-based) were built up and tested towards their capability as gasochromic CO sensors. Finally, different gas-dependent measurements were carried out. Full article
(This article belongs to the Special Issue Colorimetric Nanosensors)
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18 pages, 1201 KiB  
Article
GSOS-ELM: An RFID-Based Indoor Localization System Using GSO Method and Semi-Supervised Online Sequential ELM
by Fagui Liu and Dexiang Zhong
Sensors 2018, 18(7), 1995; https://doi.org/10.3390/s18071995 - 21 Jun 2018
Cited by 17 | Viewed by 3662
Abstract
With the rapid development of indoor positioning technology, radio frequency identification (RFID) technology has become the preferred solution due to its advantages of non-line-of-sight, non-contact and rapid identification. However, the accuracy of existing RFID indoor positioning algorithms is easily affected by the tag [...] Read more.
With the rapid development of indoor positioning technology, radio frequency identification (RFID) technology has become the preferred solution due to its advantages of non-line-of-sight, non-contact and rapid identification. However, the accuracy of existing RFID indoor positioning algorithms is easily affected by the tag density and algorithm efficiency, and their environmental robustness is not strong enough. In this paper, we have introduced an RFID positioning algorithm based on the Glowworm Swarm Optimization (GSO) fused with semi-supervised online sequential extreme learning machine (SOS-ELM), which is called the GSOS-ELM algorithm. The GSOS-ELM algorithm automatically adjusts the regularization weights of the SOS-ELM algorithm through the GSO algorithm, so that it can quickly obtain the optimal regularization weights under different initial conditions; at the same time, the semi-supervised characteristics of the GSOS-ELM algorithm can significantly reduce the number of labeled reference tags and reduce the cost of positioning systems. In addition, the online learning phase of the GSOS-ELM algorithm can continuously update the system to perceive changes in the environment and resist the environmental interference. We have carried out experiments to study the influence factors and validate the performance, both the simulation and testbed experiment results show that compared with other algorithms, our proposed GSOS-ELM localization system can achieve more accurate positioning results and has certain adaptability to the changes of the environment. Full article
(This article belongs to the Special Issue Applications of Wireless Sensors in Localization and Tracking)
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22 pages, 29542 KiB  
Article
A Novel Approach to Relative Radiometric Calibration on Spatial and Temporal Variations for FORMOSAT-5 RSI Imagery
by Tang-Huang Lin, Min-Chung Hsiao, Hai-Po Chan and Fuan Tsai
Sensors 2018, 18(7), 1996; https://doi.org/10.3390/s18071996 - 21 Jun 2018
Cited by 2 | Viewed by 2870
Abstract
Radiometric calibration for imaging sensors is a crucial procedure to ensure imagery quality. One of the challenges in relative radiometric calibration is to correct detector-level artifacts due to the fluctuation in discrepant responses (spatial) and electronic instability (temporal). In this paper, the integration [...] Read more.
Radiometric calibration for imaging sensors is a crucial procedure to ensure imagery quality. One of the challenges in relative radiometric calibration is to correct detector-level artifacts due to the fluctuation in discrepant responses (spatial) and electronic instability (temporal). In this paper, the integration of the empirical mode decomposition (EMD) with Hilbert–Huang transform (HHT) in relative radiometric calibration was explored for a new sensor, FS-5 RSI (remote sensing instrument onboard the FORMOSAT-5 satellite). The key intrinsic mode functions (IMFs) analyzed by HHT were examined with the pre-flight datasets of the FS-5 RSI in temporal and spatial variations. The results show that the EMD–HHT method can stabilize and improve the radiometric quality of the FS-5 imagery as well as boost its application ability to a new level. It is noticed that the IMFs of the spatial variation would be disturbed by the instability of the temporal variation. The relative response discrepancies among detector chips can be well calibrated after considering the temporal effect. Taking a test imagery dataset of gain setting G2 as an example, the standard deviation (STD) of the discrepancy in the digital number after calibration was dramatically scaled down compared to the original ones (e.g., PAN: 66.31 to 1.85; B1: 54.19 to 1.90; B2: 36.50 to 1.49; B3: 32.43 to 1.56; B4: 37.67 to 1.20). The good performance of pre-flight imagery indicates that the EMD–HHT approach could be highly practical to the on-orbit relative radiometric calibration of the FS-5 RSI sensor and is applicable to other optical sensors. To our knowledge, the proposed EMD–HHT approach is used for the first time to explore relative radiometric calibration for optical sensors. Full article
(This article belongs to the Section Remote Sensors)
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12 pages, 2224 KiB  
Article
Nitric Oxide Analysis Down to ppt Levels by Optical-Feedback Cavity-Enhanced Absorption Spectroscopy
by Lucile Richard, Daniele Romanini and Irène Ventrillard
Sensors 2018, 18(7), 1997; https://doi.org/10.3390/s18071997 - 22 Jun 2018
Cited by 25 | Viewed by 6348
Abstract
Monitoring nitric oxide at the trace level is required in a large range of applications. We report on a trace gas analyzer optimized for nitric oxide measurements by Optical Feedback Cavity Enhanced Absorption Spectroscopy with an interband cascade laser at 5.3 µm. The [...] Read more.
Monitoring nitric oxide at the trace level is required in a large range of applications. We report on a trace gas analyzer optimized for nitric oxide measurements by Optical Feedback Cavity Enhanced Absorption Spectroscopy with an interband cascade laser at 5.3 µm. The short response time of the instrument allows for reaching the level of 50 ppt in only 180 ms. Its stability enables averaging up to 12 min to reach a detection limit of 0.9 ppt. Absolute concentration calibration requires to account for the optical saturation effect that results from the intense absorption line intensity addressed here, in the mid infrared region, in contrast to instruments that are operating in the near infrared region. Full article
(This article belongs to the Special Issue Spectroscopy Based Sensors)
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22 pages, 5494 KiB  
Article
DC-Link Voltage and Catenary Current Sensors Fault Reconstruction for Railway Traction Drives
by Fernando Garramiola, Javier Poza, Jon Del Olmo, Patxi Madina and Gaizka Almandoz
Sensors 2018, 18(7), 1998; https://doi.org/10.3390/s18071998 - 22 Jun 2018
Cited by 7 | Viewed by 4228
Abstract
Due to the importance of sensors in control strategy and safety, early detection of faults in sensors has become a key point to improve the availability of railway traction drives. The presented sensor fault reconstruction is based on sliding mode observers and equivalent [...] Read more.
Due to the importance of sensors in control strategy and safety, early detection of faults in sensors has become a key point to improve the availability of railway traction drives. The presented sensor fault reconstruction is based on sliding mode observers and equivalent injection signals, and it allows detecting defective sensors and isolating faults. Moreover, the severity of faults is provided. The proposed on-board fault reconstruction has been validated in a hardware-in-the-loop platform, composed of a real-time simulator and a commercial traction control unit for a tram. Low computational resources, robustness to measurement noise, and easiness to tune are the main requirements for industrial acceptance. As railway applications are not safety-critical systems, compared to aerospace applications, a fault evaluation procedure is proposed, since there is enough time to perform diagnostic tasks. This procedure analyses the fault reconstruction in the steady state, delaying the decision-making in some seconds, but minimising false detections. Full article
(This article belongs to the Special Issue Sensors for Fault Detection)
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6 pages, 181 KiB  
Editorial
Sensing and Connection Systems for Assisted and Autonomous Driving and Unmanned Vehicles
by Sergio Saponara
Sensors 2018, 18(7), 1999; https://doi.org/10.3390/s18071999 - 22 Jun 2018
Cited by 12 | Viewed by 3694
Abstract
The special issue, “Sensors, Wireless Connectivity and Systems for Autonomous Vehicles and Smart Mobility” on MDPI Sensors presents 12 accepted papers, with authors from North America, Asia, Europe and Australia, related to the emerging trends in sensing and navigation systems (i.e., sensors plus [...] Read more.
The special issue, “Sensors, Wireless Connectivity and Systems for Autonomous Vehicles and Smart Mobility” on MDPI Sensors presents 12 accepted papers, with authors from North America, Asia, Europe and Australia, related to the emerging trends in sensing and navigation systems (i.e., sensors plus related signal processing and understanding techniques in multi-agent and cooperating scenarios) for autonomous vehicles, including also unmanned aerial and underwater ones. Full article
13 pages, 2725 KiB  
Article
A Correction Approach for the Inclined Array of Hydrophones in Synthetic Aperture Sonar
by Haoran Wu, Jinsong Tang and Heping Zhong
Sensors 2018, 18(7), 2000; https://doi.org/10.3390/s18072000 - 22 Jun 2018
Cited by 8 | Viewed by 3550
Abstract
A correction approach for the inclined array of hydrophones is proposed to prevent decline of the image quality in SAS. In this approach, the 2-way exact acoustic propagation path of the inclined array is transformed into the sum of a single root term [...] Read more.
A correction approach for the inclined array of hydrophones is proposed to prevent decline of the image quality in SAS. In this approach, the 2-way exact acoustic propagation path of the inclined array is transformed into the sum of a single root term and an offset term, where the single root term is the 2-way ideal propagation path and the offset term contains all errors cause by the inclined array. The correction for the offset term is separated into two steps: phase correction and delay correction. The phase correction is performed on the echo signal of each receiving hydrophone in the 2-D time domain by a phase multiplication and the delay correction is performed on the echo signal of each receiving hydrophone in the range frequency domain by a phase multiplication with a linear function of range frequency at the reference range. Finally, the effectiveness of the proposed approach is examined by the simulation experiments. Full article
(This article belongs to the Special Issue Ultrasonic Sensors 2018)
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9 pages, 2334 KiB  
Article
Optical-Spectrometry-Based Method for Immunosuppressant Medicine Level Detection in Aqueous Solutions
by Marcin Marzejon, Monika Kosowska, Daria Majchrowicz, Barbara Bułło-Piontecka, Michał Wąsowicz and Małgorzata Jędrzejewska-Szczerska
Sensors 2018, 18(7), 2001; https://doi.org/10.3390/s18072001 - 22 Jun 2018
Cited by 1 | Viewed by 4471
Abstract
In this paper, an investigation into detecting immunosuppressive medicine in aqueous solutions using a spectrometry-based technique is described. Using optical transmissive spectrometry, absorbance measurements in the spectra range from 250 nm to 1000 nm were carried out for different cyclosporine A (CsA) concentrations [...] Read more.
In this paper, an investigation into detecting immunosuppressive medicine in aqueous solutions using a spectrometry-based technique is described. Using optical transmissive spectrometry, absorbance measurements in the spectra range from 250 nm to 1000 nm were carried out for different cyclosporine A (CsA) concentrations in aqueous solutions. The experiment was conducted for samples both with and without interferent substances—glucose and sodium chloride. Using a dedicated algorithm, the measured data was analyzed and a high correlation coefficient R2 = 0.8647 was achieved. The experiment showed that the described technique allowed for the detection of various CsA concentration levels in a selective, label-free and simple way. This method could be used in medicine, veterinary medicine and laboratory diagnostics. Full article
(This article belongs to the Special Issue Spectroscopy Based Sensors)
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10 pages, 12090 KiB  
Article
Hydrodynamic Tweezers: Trapping and Transportation in Microscale Using Vortex Induced by Oscillation of a Single Piezoelectric Actuator
by Xiaoming Liu, Qing Shi, Yuqing Lin, Masaru Kojima, Yasushi Mae, Qiang Huang, Toshio Fukuda and Tatsuo Arai
Sensors 2018, 18(7), 2002; https://doi.org/10.3390/s18072002 - 22 Jun 2018
Cited by 20 | Viewed by 4490
Abstract
The demand for a harmless noncontact trapping and transportation method in manipulation and measurement of biological micro objects waits to be met. In this paper, a novel micromanipulation method named “Hydrodynamic Tweezers” using the vortex induced by oscillating a single piezoelectric actuator is [...] Read more.
The demand for a harmless noncontact trapping and transportation method in manipulation and measurement of biological micro objects waits to be met. In this paper, a novel micromanipulation method named “Hydrodynamic Tweezers” using the vortex induced by oscillating a single piezoelectric actuator is introduced. The piezoelectric actuator is set between a micropipette and a copper beam. Oscillating the actuator at a certain frequency causes the resonance of the copper beam and extend 1D straight oscillation of the piezoelectric actuator to 2D circular oscillation of the micropipette, which induces a micro vortex after putting the micropipette into fluid. The induced vortex featuring low pressure in its core area can trap the object nearby. A robotic micromanipulator is utilized to transport the trapped objects together with the micropipette. Experiments of trapping and transportation microbeads are carried out to characterize the key parameters. The results show that the trapping force can be controlled by adjusting peak-peak voltage of the sinusoidal voltage input into the piezoelectric actuator. Full article
(This article belongs to the Special Issue Piezoelectric Micro- and Nano-Devices)
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19 pages, 4749 KiB  
Article
Fusion of Infrared Thermal Image and Visible Image for 3D Thermal Model Reconstruction Using Smartphone Sensors
by Ming-Der Yang, Tung-Ching Su and Hung-Yu Lin
Sensors 2018, 18(7), 2003; https://doi.org/10.3390/s18072003 - 22 Jun 2018
Cited by 53 | Viewed by 6191
Abstract
Thermal infrared imagery provides temperature information on target objects, and has been widely applied in non-destructive testing. However, thermal infrared imagery is not always able to display detailed textures of inspected objects, which hampers the understanding of geometric entities consisting of temperature information. [...] Read more.
Thermal infrared imagery provides temperature information on target objects, and has been widely applied in non-destructive testing. However, thermal infrared imagery is not always able to display detailed textures of inspected objects, which hampers the understanding of geometric entities consisting of temperature information. Although some commercial software has been developed for 3D thermal model displays, the software requires the use of expensive specific thermal infrared sensors. This study proposes a cost-effective method for 3D thermal model reconstruction based on image-based modeling. Two smart phones and a low-cost thermal infrared camera are employed to acquire visible images and thermal images, respectively, that are fused for 3D thermal model reconstruction. The experiment results demonstrate that the proposed method is able to effectively reconstruct a 3D thermal model which extremely approximates its corresponding entity. The total computational time for the 3D thermal model reconstruction is intensive while generating dense points required for the creation of a geometric entity. Future work will improve the efficiency of the proposed method in order to expand its potential applications to in-time monitoring. Full article
(This article belongs to the Special Issue Ubiquitous Massive Sensing Using Smartphones)
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17 pages, 18598 KiB  
Article
Multi-Object Tracking with Correlation Filter for Autonomous Vehicle
by Dawei Zhao, Hao Fu, Liang Xiao, Tao Wu and Bin Dai
Sensors 2018, 18(7), 2004; https://doi.org/10.3390/s18072004 - 22 Jun 2018
Cited by 54 | Viewed by 7111
Abstract
Multi-object tracking is a crucial problem for autonomous vehicle. Most state-of-the-art approaches adopt the tracking-by-detection strategy, which is a two-step procedure consisting of the detection module and the tracking module. In this paper, we improve both steps. We improve the detection module by [...] Read more.
Multi-object tracking is a crucial problem for autonomous vehicle. Most state-of-the-art approaches adopt the tracking-by-detection strategy, which is a two-step procedure consisting of the detection module and the tracking module. In this paper, we improve both steps. We improve the detection module by incorporating the temporal information, which is beneficial for detecting small objects. For the tracking module, we propose a novel compressed deep Convolutional Neural Network (CNN) feature based Correlation Filter tracker. By carefully integrating these two modules, the proposed multi-object tracking approach has the ability of re-identification (ReID) once the tracked object gets lost. Extensive experiments were performed on the KITTI and MOT2015 tracking benchmarks. Results indicate that our approach outperforms most state-of-the-art tracking approaches. Full article
(This article belongs to the Special Issue Sensors Signal Processing and Visual Computing)
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19 pages, 17989 KiB  
Article
Digital Holography as Computer Vision Position Sensor with an Extended Range of Working Distances
by Miguel Asmad Vergara, Maxime Jacquot, Guillaume J. Laurent and Patrick Sandoz
Sensors 2018, 18(7), 2005; https://doi.org/10.3390/s18072005 - 22 Jun 2018
Cited by 5 | Viewed by 3798
Abstract
Standard computer vision methods are usually based on powerful contact-less measurement approaches but applications, especially at the micro-scale, are restricted by finite depth-of-field and fixed working distance of imaging devices. Digital holography is a lensless, indirect imaging method recording the optical wave diffracted [...] Read more.
Standard computer vision methods are usually based on powerful contact-less measurement approaches but applications, especially at the micro-scale, are restricted by finite depth-of-field and fixed working distance of imaging devices. Digital holography is a lensless, indirect imaging method recording the optical wave diffracted by the object onto the image sensor. The object is reconstructed numerically by propagating the recorded wavefront backward. The object distance becomes a computation parameter that can be chosen arbitrarily and adjusted to match the object position. No refractive lens is used and usual depth-of-field and working distance limitations are replaced by less restrictive ones tied to the laser-source coherence-length and to the size and resolution of the camera sensor. This paper applies digital holography to artificial visual in-plane position sensing with an extra-large range-to-resolution ratio. The object is made of a pseudoperiodic pattern allowing a subpixel resolution as well as a supra field-of-observation displacement range. We demonstrate an in-plane resolution of 50 nm and 0.002deg. in X, Y and θ respectively, over a working distance range of more than 15 cm. The allowed workspace extends over 12×10×150mm3. Digital holography extends the field of application of computer vision by allowing an extra-large range of working distances inaccessible to refractive imaging systems. Full article
(This article belongs to the Section Physical Sensors)
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13 pages, 2656 KiB  
Article
Hydrogen Sulfide Gas Detection via Multivariate Optical Computing
by Bin Dai, Christopher Michael Jones, Megan Pearl, Mickey Pelletier and Mickey Myrick
Sensors 2018, 18(7), 2006; https://doi.org/10.3390/s18072006 - 22 Jun 2018
Cited by 20 | Viewed by 5698
Abstract
Hydrogen-sulfide gas is a toxic, colorless gas with a pungent odor that occurs naturally as a decomposition by-product. It is critical to monitor the concentration of hydrogen sulfide. Multivariate optical computing (MOC) is a method that can monitor analytes while minimizing responses to [...] Read more.
Hydrogen-sulfide gas is a toxic, colorless gas with a pungent odor that occurs naturally as a decomposition by-product. It is critical to monitor the concentration of hydrogen sulfide. Multivariate optical computing (MOC) is a method that can monitor analytes while minimizing responses to interferences. MOC is a technique by which an analogue calculation is performed entirely in the optical domain, which simplifies instrument design, prevents the drift of a calibration, and increases the strength and durability of spectroscopic instrumentation against physical perturbation when used for chemical detection and identification. This paper discusses the detection of hydrogen-sulfide gas in the ultraviolet (UV) spectral region in the presence of interfering gaseous species. A laboratory spectroscopic measurement system was set up to acquire the UV spectra of H2S and interference gas mixtures in high-pressure/high-temperature (HPHT) conditions. These spectra were used to guide the design and fabrication of a multivariate optical element (MOE), which has an expected measurement relative accuracy of 3.3% for H2S, with a concentration in the range of 0–150 nmol/mL. An MOC validation system with the MOE was used to test three samples of H2S and mercaptans mixtures under various pressures, and the relative accuracy of H2S measurement was determined to be 8.05%. Full article
(This article belongs to the Special Issue Spectroscopy Based Sensors)
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14 pages, 1439 KiB  
Article
A Novel Ship-Tracking Method for GF-4 Satellite Sequential Images
by Libo Yao, Yong Liu and You He
Sensors 2018, 18(7), 2007; https://doi.org/10.3390/s18072007 - 22 Jun 2018
Cited by 29 | Viewed by 4968
Abstract
The geostationary remote sensing satellite has the capability of wide scanning, persistent observation and operational response, and has tremendous potential for maritime target surveillance. The GF-4 satellite is the first geostationary orbit (GEO) optical remote sensing satellite with medium resolution in China. In [...] Read more.
The geostationary remote sensing satellite has the capability of wide scanning, persistent observation and operational response, and has tremendous potential for maritime target surveillance. The GF-4 satellite is the first geostationary orbit (GEO) optical remote sensing satellite with medium resolution in China. In this paper, a novel ship-tracking method in GF-4 satellite sequential imagery is proposed. The algorithm has three stages. First, a local visual saliency map based on local peak signal-to-noise ratio (PSNR) is used to detect ships in a single frame of GF-4 satellite sequential images. Second, the accuracy positioning of each potential target is realized by a dynamic correction using the rational polynomial coefficients (RPCs) and automatic identification system (AIS) data of ships. Finally, an improved multiple hypotheses tracking (MHT) algorithm with amplitude information is used to track ships by further removing the false targets, and to estimate ships’ motion parameters. The algorithm has been tested using GF-4 sequential images and AIS data. The results of the experiment demonstrate that the algorithm achieves good tracking performance in GF-4 satellite sequential images and estimates the motion information of ships accurately. Full article
(This article belongs to the Special Issue Satellite and Airborne Remote Sensing for Earth Monitoring)
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11 pages, 968 KiB  
Review
Future of Smart Cardiovascular Implants
by Anubhav Bussooa, Steven Neale and John R. Mercer
Sensors 2018, 18(7), 2008; https://doi.org/10.3390/s18072008 - 22 Jun 2018
Cited by 43 | Viewed by 8029
Abstract
Cardiovascular disease remains the leading cause of death in Western society. Recent technological advances have opened the opportunity of developing new and innovative smart stent devices that have advanced electrical properties that can improve diagnosis and even treatment of previously intractable conditions, such [...] Read more.
Cardiovascular disease remains the leading cause of death in Western society. Recent technological advances have opened the opportunity of developing new and innovative smart stent devices that have advanced electrical properties that can improve diagnosis and even treatment of previously intractable conditions, such as central line access failure, atherosclerosis and reporting on vascular grafts for renal dialysis. Here we review the latest advances in the field of cardiovascular medical implants, providing a broad overview of the application of their use in the context of cardiovascular disease rather than an in-depth analysis of the current state of the art. We cover their powering, communication and the challenges faced in their fabrication. We focus specifically on those devices required to maintain vascular access such as ones used to treat arterial disease, a major source of heart attacks and strokes. We look forward to advances in these technologies in the future and their implementation to improve the human condition. Full article
(This article belongs to the Section Biosensors)
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12 pages, 4402 KiB  
Article
Flash Smelting Copper Concentrates Spectral Emission Measurements
by Luis Arias, Sergio Torres, Carlos Toro, Eduardo Balladares, Roberto Parra, Claudia Loeza, Camilo Villagrán and Pablo Coelho
Sensors 2018, 18(7), 2009; https://doi.org/10.3390/s18072009 - 22 Jun 2018
Cited by 28 | Viewed by 4820
Abstract
In this paper, we report on spectral features emitted by a reaction shaft occurring in flash smelting of copper concentrates containing sulfide copper minerals such as chalcopyrite (CuFeS2), bornite (Cu5FeS4) and pyrite (FeS2). Different combustion [...] Read more.
In this paper, we report on spectral features emitted by a reaction shaft occurring in flash smelting of copper concentrates containing sulfide copper minerals such as chalcopyrite (CuFeS2), bornite (Cu5FeS4) and pyrite (FeS2). Different combustion conditions are addressed, such as sulfur-copper ratio and oxygen excess. Temperature and spectral emissivity features are estimated for each case by using the two wavelength method and radiometric models. The most relevant results have shown an increasing intensity behavior for higher sulfur-copper ratios and oxygen contents, where emissivity is almost constant along the visible spectrum range for all cases, which validates the gray body assumption. CuO and FeO emission line features along the visible spectrum appear to be a sensing alternative for describing the combustion reactions. Full article
(This article belongs to the Special Issue Optical Sensing and Imaging, from UV to THz Range)
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45 pages, 5395 KiB  
Review
Recent Advances in Enhancement Strategies for Electrochemical ELISA-Based Immunoassays for Cancer Biomarker Detection
by Sunil K. Arya and Pedro Estrela
Sensors 2018, 18(7), 2010; https://doi.org/10.3390/s18072010 - 22 Jun 2018
Cited by 90 | Viewed by 14238
Abstract
Electrochemical enzyme-linked immunosorbent assay (ELISA)-based immunoassays for cancer biomarker detection have recently attracted much interest owing to their higher sensitivity, amplification of signal, ease of handling, potential for automation and combination with miniaturized analytical systems, low cost and comparative simplicity for mass production. [...] Read more.
Electrochemical enzyme-linked immunosorbent assay (ELISA)-based immunoassays for cancer biomarker detection have recently attracted much interest owing to their higher sensitivity, amplification of signal, ease of handling, potential for automation and combination with miniaturized analytical systems, low cost and comparative simplicity for mass production. Their developments have considerably improved the sensitivity required for detection of low concentrations of cancer biomarkers present in bodily fluids in the early stages of the disease. Recently, various attempts have been made in their development and several methods and processes have been described for their development, amplification strategies and testing. The present review mainly focuses on the development of ELISA-based electrochemical immunosensors that may be utilized for cancer diagnosis, prognosis and therapy monitoring. Various fabrication methods and signal enhancement strategies utilized during the last few years for the development of ELISA-based electrochemical immunosensors are described. Full article
(This article belongs to the Section Biosensors)
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9 pages, 3104 KiB  
Article
Insect-Mimetic Imaging System Based on a Microlens Array Fabricated by a Patterned-Layer Integrating Soft Lithography Process
by Minwon Seo, Jong-Mo Seo, Dong-il “Dan” Cho and Kyo-in Koo
Sensors 2018, 18(7), 2011; https://doi.org/10.3390/s18072011 - 22 Jun 2018
Cited by 7 | Viewed by 3862
Abstract
In nature, arthropods have evolved to utilize a multiaperture vision system with a micro-optical structure which has advantages, such as compact size and wide-angle view, compared to that of a single-aperture vision system. In this paper, we present a multiaperture imaging system using [...] Read more.
In nature, arthropods have evolved to utilize a multiaperture vision system with a micro-optical structure which has advantages, such as compact size and wide-angle view, compared to that of a single-aperture vision system. In this paper, we present a multiaperture imaging system using a microlens array fabricated by a patterned-layer integrating soft lithography (PLISL) process which is based on a molding technique that can transfer three-dimensional structures and a gold screening layer simultaneously. The imaging system consists of a microlens array, a lens-adjusting jig, and a conventional (charge-coupled device) CCD image sensor. The microlens array has a light screening layer patterned among all the microlenses by the PLISL process to prevent light interference. The three-dimensionally printed jig adjusts the microlens array on the conventional CCD sensor for the focused image. The manufactured imaging system has a thin optic system and a large field-of-view of 100 degrees. The developed imaging system takes multiple images at once. To show its possible applications, multiple depth plane images were reconstructed based on the taken subimages with a single shot. Full article
(This article belongs to the Section Physical Sensors)
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23 pages, 3607 KiB  
Article
Adaptive Interacting Multiple Model Algorithm Based on Information-Weighted Consensus for Maneuvering Target Tracking
by Ziran Ding, Yu Liu, Jun Liu, Kaimin Yu, Yuanyang You, Peiliang Jing and You He
Sensors 2018, 18(7), 2012; https://doi.org/10.3390/s18072012 - 22 Jun 2018
Cited by 19 | Viewed by 3695
Abstract
Networked multiple sensors are used to solve the problem of maneuvering target tracking. To avoid the linearization of nonlinear dynamic functions, and to obtain more accurate estimates for maneuvering targets, a novel adaptive information-weighted consensus filter for maneuvering target tracking is proposed. The [...] Read more.
Networked multiple sensors are used to solve the problem of maneuvering target tracking. To avoid the linearization of nonlinear dynamic functions, and to obtain more accurate estimates for maneuvering targets, a novel adaptive information-weighted consensus filter for maneuvering target tracking is proposed. The pseudo measurement matrix is computed with unscented transform to utilize the information form of measurements, which is necessary for consensus iterations. To improve the maneuvering target tracking accuracy and get a unified estimation in each sensor node across the entire network, the adaptive current statistical model is exploited to update the estimate, and the information-weighted consensus protocol is applied among neighboring nodes for each dynamic model. Based on posterior probabilities of multiple models, the final estimate of each sensor is acquired with weighted combination of model-conditioned estimates. Experimental results illustrate the superior performance of the proposed algorithm with respect tracking accuracy and agreement of estimates in the whole network. Full article
(This article belongs to the Special Issue Data and Information Fusion for Wireless Sensor Networks)
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16 pages, 5405 KiB  
Article
Feature Selection Method Based on High-Resolution Remote Sensing Images and the Effect of Sensitive Features on Classification Accuracy
by Yi Zhou, Rui Zhang, Shixin Wang and Futao Wang
Sensors 2018, 18(7), 2013; https://doi.org/10.3390/s18072013 - 22 Jun 2018
Cited by 48 | Viewed by 4869
Abstract
With the advent of high spatial resolution remote sensing imagery, numerous image features can be utilized. Applying a reasonable feature selection approach is critical to effectively reduce feature redundancy and improve the efficiency and accuracy of classification. This paper proposes a novel feature [...] Read more.
With the advent of high spatial resolution remote sensing imagery, numerous image features can be utilized. Applying a reasonable feature selection approach is critical to effectively reduce feature redundancy and improve the efficiency and accuracy of classification. This paper proposes a novel feature selection approach, in which ReliefF, genetic algorithm, and support vector machine (RFGASVM) are integrated to extract buildings. We adopt the ReliefF algorithm to preliminary filter high-dimensional features in the feature database. After eliminating the sorted features, the feature subset and the C and γ parameters of support vector machine (SVM) are encoded into the chromosome of the genetic algorithm. A fitness function is constructed considering the sample identification accuracy, the number of selected features, and the feature cost. The proposed method was applied to high-resolution images obtained from different sensors, GF-2, BJ-2, and unmanned aerial vehicles (UAV). The confusion matrix, precision, recall and F1-score were applied to assess the accuracy. The results showed that the proposed method achieved feature reduction, and the overall accuracy (OA) was more than 85%, with Kappa coefficient values of 0.80, 0.83 and 0.85, respectively. The precision of each image was more than 85%. The time efficiency of the proposed method was two-fold greater than SVM with all the features. The RFGASVM method has the advantages of large feature reduction and high extraction performance and can be applied in feature selection. Full article
(This article belongs to the Section Remote Sensors)
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19 pages, 25247 KiB  
Article
Land Cover Classification with GF-3 Polarimetric Synthetic Aperture Radar Data by Random Forest Classifier and Fast Super-Pixel Segmentation
by Yuyuan Fang, Haiying Zhang, Qin Mao and Zhenfang Li
Sensors 2018, 18(7), 2014; https://doi.org/10.3390/s18072014 - 22 Jun 2018
Cited by 21 | Viewed by 3970
Abstract
Chinese Gaofen-3 (GF-3), a vital satellite for high-resolution earth observation, was the first C-band polarimetric synthetic aperture radar (SAR) launched in China with a resolution of up to one meter. Polarimetric SAR can obtain the complete physical scattering mechanisms of targets, thereby having [...] Read more.
Chinese Gaofen-3 (GF-3), a vital satellite for high-resolution earth observation, was the first C-band polarimetric synthetic aperture radar (SAR) launched in China with a resolution of up to one meter. Polarimetric SAR can obtain the complete physical scattering mechanisms of targets, thereby having the potential to differentiate objects. In this paper, several classification methods are briefly summarized and the types of features that should be chosen during classification are discussed. A pre-classification step is introduced to reduce the workload of precise labeling. The Random Forest classifier, which performs well for many other classification tasks, is used for the initial land cover classification. Then, based on a polarimetric constant false-alarm rate (CFAR) edge detector, a fast super-pixel generation method for polarimetric SAR image is proposed, which does not require the adjustment of parameters in advance. Following that, majority vote is conducted on the initial classification result based on the super-pixels, so that the classification result can be optimized to better meet the mapping requirements. The experimental results based on GF-3 polarimetric SAR data verify the effectiveness of proposed procedure and demonstrate that GF-3 data has excellent performance in land cover classification. Full article
(This article belongs to the Special Issue First Experiences with Chinese Gaofen-3 SAR Sensor)
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37 pages, 13766 KiB  
Article
Low Cost Photonic Sensor for in-Line Oil Quality Monitoring: Methodological Development Process towards Uncertainty Mitigation
by Patricia Lopez, Jon Mabe, Guillermo Miró and Leire Etxeberria
Sensors 2018, 18(7), 2015; https://doi.org/10.3390/s18072015 - 22 Jun 2018
Cited by 18 | Viewed by 8313
Abstract
Lubricant and hydraulic fluid ageing impacts the performance of the machines, gears, transmissions or automatisms where they are being used. This manuscript describes the work accomplished for bringing an innovative measurement concept for analysing the physical- chemical properties of these fluids, to a [...] Read more.
Lubricant and hydraulic fluid ageing impacts the performance of the machines, gears, transmissions or automatisms where they are being used. This manuscript describes the work accomplished for bringing an innovative measurement concept for analysing the physical- chemical properties of these fluids, to a real industrial product ready to be integrated into different industrial equipment. The steps taken to deal with uncertainties and evolving requirements while progressing in the sensor development are described, covering the stages of theoretical formulation of the problem, optical and fluidic simulations, sensor prototype development and tests. The sensor working principle is based on a combination of transmittance and diffuse reflectance photonic inspection of the fluid sample that is collected in a microcavity through a standard hydraulic fitting. Photonics, electronics, micro-mechanics, fluidics, data processing and analysis has been merged with a deep knowledge in the lubricant degradation process to develop a sensor solution that is able to measure the Oil Degradation Index, Oil Oxidation, Acid Number, Ruler and Membrane Patch Colorimetry data from an inservice lubricating oil sample. The photonic micro sensor presented here offers a powerful tool that operates directly immersed in the fluid, at an economic cost and compacted size for inline oil degradation monitoring. Full article
(This article belongs to the Section Physical Sensors)
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51 pages, 4536 KiB  
Article
European In-Situ Snow Measurements: Practices and Purposes
by Roberta Pirazzini, Leena Leppänen, Ghislain Picard, Juan Ignacio Lopez-Moreno, Christoph Marty, Giovanni Macelloni, Anna Kontu, Annakaisa Von Lerber, Cemal Melih Tanis, Martin Schneebeli, Patricia De Rosnay and Ali Nadir Arslan
Sensors 2018, 18(7), 2016; https://doi.org/10.3390/s18072016 - 22 Jun 2018
Cited by 53 | Viewed by 12673
Abstract
In-situ snow measurements conducted by European institutions for operational, research, and energy business applications were surveyed in the framework of the European Cooperation in Science and Technology (COST) Action ES1404, called “A European network for a harmonised monitoring of snow for the benefit [...] Read more.
In-situ snow measurements conducted by European institutions for operational, research, and energy business applications were surveyed in the framework of the European Cooperation in Science and Technology (COST) Action ES1404, called “A European network for a harmonised monitoring of snow for the benefit of climate change scenarios, hydrology, and numerical weather prediction”. Here we present the results of this survey, which was answered by 125 participants from 99 operational and research institutions, belonging to 38 European countries. The typologies of environments where the snow measurements are performed range from mountain to low elevated plains, including forests, bogs, tundra, urban areas, glaciers, lake ice, and sea ice. Of the respondents, 93% measure snow macrophysical parameters, such as snow presence, snow depth (HS), snow water equivalent (SWE), and snow density. These describe the bulk characteristics of the whole snowpack or of a snow layer, and they are the primary snow properties that are needed for most operational applications (such as hydrological monitoring, avalanche forecast, and weather forecast). In most cases, these measurements are done with manual methods, although for snow presence, HS, and SWE, automatized methods are also applied by some respondents. Parameters characterizing precipitating and suspended snow (such as the height of new snow, precipitation intensity, flux of drifting/blowing snow, and particle size distribution), some of which are crucial for the operational services, are measured by 74% of the respondents. Parameters characterizing the snow microstructural properties (such as the snow grain size and shape, and specific surface area), the snow electromagnetic properties (such as albedo, brightness temperature, and backscatter), and the snow composition (such as impurities and isotopes) are measured by 41%, 26%, and 13% of the respondents, respectively, mostly for research applications. The results of this survey are discussed from the perspective of the need of enhancing the efficiency and coverage of the in-situ observational network applying automatic and cheap measurement methods. Moreover, recommendations for the enhancement and harmonization of the observational network and measurement practices are provided. Full article
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19 pages, 4027 KiB  
Article
Single-Input and Multiple-Output Surface Acoustic Wave Sensing for Damage Quantification in Piezoelectric Sensors
by Lavish Pamwani, Anowarul Habib, Frank Melandsø, Balpreet Singh Ahluwalia and Amit Shelke
Sensors 2018, 18(7), 2017; https://doi.org/10.3390/s18072017 - 22 Jun 2018
Cited by 10 | Viewed by 4059
Abstract
The main aim of the paper is damage detection at the microscale in the anisotropic piezoelectric sensors using surface acoustic waves (SAWs). A novel technique based on the single input and multiple output of Rayleigh waves is proposed to detect the microscale cracks/flaws [...] Read more.
The main aim of the paper is damage detection at the microscale in the anisotropic piezoelectric sensors using surface acoustic waves (SAWs). A novel technique based on the single input and multiple output of Rayleigh waves is proposed to detect the microscale cracks/flaws in the sensor. A convex-shaped interdigital transducer is fabricated for excitation of divergent SAWs in the sensor. An angularly shaped interdigital transducer (IDT) is fabricated at 0 degrees and ±20 degrees for sensing the convex shape evolution of SAWs. A precalibrated damage was introduced in the piezoelectric sensor material using a micro-indenter in the direction perpendicular to the pointing direction of the SAW. Damage detection algorithms based on empirical mode decomposition (EMD) and principal component analysis (PCA) are implemented to quantify the evolution of damage in piezoelectric sensor material. The evolution of the damage was quantified using a proposed condition indicator (CI) based on normalized Euclidean norm of the change in principal angles, corresponding to pristine and damaged states. The CI indicator provides a robust and accurate metric for detection and quantification of damage. Full article
(This article belongs to the Special Issue Ultrasonic Sensors 2018)
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24 pages, 1821 KiB  
Article
On Maximizing the Throughput of Packet Transmission under Energy Constraints
by Weiwei Wu, Guangli Dai, Yan Li and Feng Shan
Sensors 2018, 18(7), 2018; https://doi.org/10.3390/s18072018 - 23 Jun 2018
Cited by 3 | Viewed by 3269
Abstract
More and more Internet of Things (IoT) wireless devices have been providing ubiquitous services over the recent years. Since most of these devices are powered by batteries, a fundamental trade-off to be addressed is the depleted energy and the achieved data throughput in [...] Read more.
More and more Internet of Things (IoT) wireless devices have been providing ubiquitous services over the recent years. Since most of these devices are powered by batteries, a fundamental trade-off to be addressed is the depleted energy and the achieved data throughput in wireless data transmission. By exploiting the rate-adaptive capacities of wireless devices, most existing works on energy-efficient data transmission try to design rate-adaptive transmission policies to maximize the amount of transmitted data bits under the energy constraints of devices. Such solutions, however, cannot apply to scenarios where data packets have respective deadlines and only integrally transmitted data packets contribute. Thus, this paper introduces a notion of weighted throughput, which measures how much total value of data packets are successfully and integrally transmitted before their own deadlines. By designing efficient rate-adaptive transmission policies, this paper aims to make the best use of the energy and maximize the weighted throughput. What is more challenging but with practical significance, we consider the fading effect of wireless channels in both offline and online scenarios. In the offline scenario, we develop an optimal algorithm that computes the optimal solution in pseudo-polynomial time, which is the best possible solution as the problem undertaken is NP-hard. In the online scenario, we propose an efficient heuristic algorithm based on optimal properties derived for the optimal offline solution. Simulation results validate the efficiency of the proposed algorithm. Full article
(This article belongs to the Special Issue Green Communications and Networking for IoT)
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19 pages, 7233 KiB  
Article
Rectification of Images Distorted by Microlens Array Errors in Plenoptic Cameras
by Suning Li, Yanlong Zhu, Chuanxin Zhang, Yuan Yuan and Heping Tan
Sensors 2018, 18(7), 2019; https://doi.org/10.3390/s18072019 - 23 Jun 2018
Cited by 11 | Viewed by 6416
Abstract
A plenoptic cameras is a sensor that records the 4D light-field distribution of target scenes. The surface errors of a microlens array (MLA) can cause the degradation and distortion of the raw image captured by a plenoptic camera, resulting in the confusion or [...] Read more.
A plenoptic cameras is a sensor that records the 4D light-field distribution of target scenes. The surface errors of a microlens array (MLA) can cause the degradation and distortion of the raw image captured by a plenoptic camera, resulting in the confusion or loss of light-field information. To address this issue, we propose a method for the local rectification of distorted images using white light-field images. The method consists of microlens center calibration, geometric rectification, and grayscale rectification. The scope of its application to different sized errors and the rectification accuracy of three basic surface errors, including the overall accuracy and the local accuracy, are analyzed through simulation of imaging experiments. The rectified images have a significant improvement in quality, demonstrating the provision of precise light-field data for reconstruction of real objects. Full article
(This article belongs to the Section Physical Sensors)
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19 pages, 2449 KiB  
Article
Modeling and Characterization of Traffic Flows in Urban Environments
by Jorge Luis Zambrano-Martinez, Carlos T. Calafate, David Soler, Juan-Carlos Cano and Pietro Manzoni
Sensors 2018, 18(7), 2020; https://doi.org/10.3390/s18072020 - 23 Jun 2018
Cited by 64 | Viewed by 7500
Abstract
Currently, one of the main challenges faced in large metropolitan areas is traffic congestion. To address this problem, adequate traffic control could produce many benefits, including reduced pollutant emissions and reduced travel times. If it were possible to characterize the state of traffic [...] Read more.
Currently, one of the main challenges faced in large metropolitan areas is traffic congestion. To address this problem, adequate traffic control could produce many benefits, including reduced pollutant emissions and reduced travel times. If it were possible to characterize the state of traffic by predicting future traffic conditions for optimizing the route of automated vehicles, and if these measures could be taken to preventively mitigate the effects of congestion with its related problems, the overall traffic flow could be improved. This paper performs an experimental study of the traffic distribution in the city of Valencia, Spain, characterizing the different streets of the city in terms of vehicle load with respect to the travel time during rush hour traffic conditions. Experimental results based on realistic vehicular traffic traces from the city of Valencia show that only some street segments fall under the general theory of vehicular flow, offering a good fit using quadratic regression, while a great number of street segments fall under other categories. Although in some cases such discrepancies are related to lack of traffic, injecting additional vehicles shows that significant mismatches still persist. Thus, in this paper we propose an equation to characterize travel times over a segment belonging to the sigmoid family; specifically, we apply logistic regression, being able to significantly improve the curve fitting results for most of the street segments under analysis. Based on our regression results, we performed a clustering analysis of the different street segments, showing that they can be classified into three well-defined categories, which evidences a predictable traffic distribution using the logistic regression throughout the city during rush hours, and allows optimizing the traffic for automated vehicles. Full article
(This article belongs to the Special Issue Advances on Vehicular Networks: From Sensing to Autonomous Driving)
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17 pages, 10926 KiB  
Article
A Fast and Robust Non-Sparse Signal Recovery Algorithm for Wearable ECG Telemonitoring Using ADMM-Based Block Sparse Bayesian Learning
by Yunfei Cheng, Yalan Ye, Mengshu Hou, Wenwen He, Yunxia Li and Xuesong Deng
Sensors 2018, 18(7), 2021; https://doi.org/10.3390/s18072021 - 23 Jun 2018
Cited by 16 | Viewed by 5201
Abstract
Wearable telemonitoring of electrocardiogram (ECG) based on wireless body Area networks (WBAN) is a promising approach in next-generation patient-centric telecardiology solutions. In order to guarantee long-term effective operation of monitoring systems, the power consumption of the sensors must be strictly limited. Compressed sensing [...] Read more.
Wearable telemonitoring of electrocardiogram (ECG) based on wireless body Area networks (WBAN) is a promising approach in next-generation patient-centric telecardiology solutions. In order to guarantee long-term effective operation of monitoring systems, the power consumption of the sensors must be strictly limited. Compressed sensing (CS) is an effective method to alleviate this problem. However, ECG signals in WBAN are usually non-sparse, and most traditional compressed sensing recovery algorithms have difficulty recovering non-sparse signals. In this paper, we proposed a fast and robust non-sparse signal recovery algorithm for wearable ECG telemonitoring. In the proposed algorithm, the alternating direction method of multipliers (ADMM) is used to accelerate the speed of block sparse Bayesian learning (BSBL) framework. We used the famous MIT-BIH Arrhythmia Database, MIT-BIH Long-Term ECG Database and ECG datasets collected in our practical wearable ECG telemonitoring system to verify the performance of the proposed algorithm. The experimental results show that the proposed algorithm can directly recover ECG signals with a satisfactory accuracy in a time domain without a dictionary matrix. Due to acceleration by ADMM, the proposed algorithm has a fast speed, and also it is robust for different ECG datasets. These results suggest that the proposed algorithm is very promising for wearable ECG telemonitoring. Full article
(This article belongs to the Special Issue Sensors for Health Monitoring and Disease Diagnosis)
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15 pages, 688 KiB  
Article
A Context-Aware Edge-Based VANET Communication Scheme for ITS
by Chang An, Celimuge Wu, Tsutomu Yoshinaga, Xianfu Chen and Yusheng Ji
Sensors 2018, 18(7), 2022; https://doi.org/10.3390/s18072022 - 24 Jun 2018
Cited by 24 | Viewed by 4934
Abstract
We propose a context-aware edge-based packet forwarding scheme for vehicular networks. The proposed scheme employs a fuzzy logic-based edge node selection protocol to find the best edge nodes in a decentralized manner, which can achieve an efficient use of wireless resources by conducting [...] Read more.
We propose a context-aware edge-based packet forwarding scheme for vehicular networks. The proposed scheme employs a fuzzy logic-based edge node selection protocol to find the best edge nodes in a decentralized manner, which can achieve an efficient use of wireless resources by conducting packet forwarding through edges. A reinforcement learning algorithm is used to optimize the last two-hop communications in order to improve the adaptiveness of the communication routes. The proposed scheme selects different edge nodes for different types of communications with different context information such as connection-dependency (connection-dependent or connection-independent), communication type (unicast or broadcast), and packet payload size. We launch extensive simulations to evaluate the proposed scheme by comparing with existing broadcast protocols and unicast protocols for various network conditions and traffic patterns. Full article
(This article belongs to the Special Issue Advances on Vehicular Networks: From Sensing to Autonomous Driving)
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15 pages, 8302 KiB  
Article
Mechanical Structural Design of a Piezoresistive Pressure Sensor for Low-Pressure Measurement: A Computational Analysis by Increases in the Sensor Sensitivity
by Anh Vang Tran, Xianmin Zhang and Benliang Zhu
Sensors 2018, 18(7), 2023; https://doi.org/10.3390/s18072023 - 24 Jun 2018
Cited by 83 | Viewed by 14210
Abstract
This paper proposes a novel micro-electromechanical system (MEMS) piezoresistive pressure sensor with a four-petal membrane combined with narrow beams and a center boss (PMNBCB) for low-pressure measurements. The stresses induced in the piezoresistors and deflection of the membrane were calculated using the finite [...] Read more.
This paper proposes a novel micro-electromechanical system (MEMS) piezoresistive pressure sensor with a four-petal membrane combined with narrow beams and a center boss (PMNBCB) for low-pressure measurements. The stresses induced in the piezoresistors and deflection of the membrane were calculated using the finite element method (FEM). The functions of the relationship between the dimension variables and mechanical performance were determined based on the curve fitting method, which can provide an approach for geometry optimization of the sensor. In addition, the values in the equations were varied to determine the optimal dimensions for the proposed membrane. Then, to further improve the sensitivity of the sensor, a series of rectangular grooves was created at the position of the piezoresistors. The proposed diaphragm was compared to existing diaphragms, and a considerable increase in the sensitivity and a considerable decrease in nonlinearity error could be achieved by using the proposed sensor. The simulation results suggest that the sensor with the PMNBCB structure obtained a high sensitivity of 34.67 mV/kPa and a low nonlinearity error of 0.23% full-scale span (FSS) for the pressure range of 0–5 kPa. The proposed sensor structure is a suitable selection for MEMS piezoresistive pressure sensors. Full article
(This article belongs to the Section Physical Sensors)
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14 pages, 3539 KiB  
Article
Compressive Sensing Based Multilevel Fast Multipole Acceleration for Fast Scattering Center Extraction and ISAR Imaging
by Wei Zhu, Ming Jiang, Xin He and Jun Hu
Sensors 2018, 18(7), 2024; https://doi.org/10.3390/s18072024 - 25 Jun 2018
Cited by 2 | Viewed by 3254
Abstract
In recent years, Compressive Sensing (CS) theory has been very popular in the data sensing and process area as it utilizes the sparsity and measurement matrix to reconstruct the compressible signal from limited samples successfully. In this paper, CS is introduced into an [...] Read more.
In recent years, Compressive Sensing (CS) theory has been very popular in the data sensing and process area as it utilizes the sparsity and measurement matrix to reconstruct the compressible signal from limited samples successfully. In this paper, CS is introduced into an efficient numerical method, multilevel fast multipole acceleration (MLFMA), for the electromagnetic (EM) scattering problem over a wide incident angle. This allows composition of a new kind of incident wave, which obtains efficient and reliable data for scattering centers extraction with low complexity. The resulting data from CS-based MLFMA are processed for ISAR) imaging. Simulation results show the received data for ISAR imaging from MLFMA with CS can outperform the data from MLFMA, which achieves a similar quality of ISAR imaging. Additionally, the computation complexity is improved by CS through the reduced matrix computation for fewer incident waves. It makes ISAR imaging using real data feasible and meaningful. Full article
(This article belongs to the Special Issue New Paradigms in Data Sensing and Processing for Edge Computing)
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15 pages, 3591 KiB  
Article
The SDN Approach for the Aggregation/Disaggregation of Sensor Data
by Yi-Bing Lin, Shie-Yuan Wang, Ching-Chun Huang and Chia-Ming Wu
Sensors 2018, 18(7), 2025; https://doi.org/10.3390/s18072025 - 25 Jun 2018
Cited by 27 | Viewed by 4782
Abstract
In many Internet of Things (IoT) applications, large numbers of small sensor data are delivered in the network, which may cause heavy traffics. To reduce the number of messages delivered from the sensor devices to the IoT server, a promising approach is to [...] Read more.
In many Internet of Things (IoT) applications, large numbers of small sensor data are delivered in the network, which may cause heavy traffics. To reduce the number of messages delivered from the sensor devices to the IoT server, a promising approach is to aggregate several small IoT messages into a large packet before they are delivered through the network. When the packets arrive at the destination, they are disaggregated into the original IoT messages. In the existing solutions, packet aggregation/disaggregation is performed by software at the server, which results in long delays and low throughputs. To resolve the above issue, this paper utilizes the programmable Software Defined Networking (SDN) switch to program quick packet aggregation and disaggregation. Specifically, we consider the Programming Protocol-Independent Packet Processor (P4) technology. We design and develop novel P4 programs for aggregation and disaggregation in commercial P4 switches. Our study indicates that packet aggregation can be achieved in a P4 switch with its line rate (without extra packet processing cost). On the other hand, to disaggregate a packet that combines N IoT messages, the processing time is about the same as processing N individual IoT messages. Our implementation conducts IoT message aggregation at the highest bit rate (100 Gbps) that has not been found in the literature. We further propose to provide a small buffer in the P4 switch to significantly reduce the processing power for disaggregating a packet. Full article
(This article belongs to the Special Issue Internet of Things and Ubiquitous Sensing)
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20 pages, 21565 KiB  
Article
UAVs, Hyperspectral Remote Sensing, and Machine Learning Revolutionizing Reef Monitoring
by Mark Parsons, Dmitry Bratanov, Kevin J. Gaston and Felipe Gonzalez
Sensors 2018, 18(7), 2026; https://doi.org/10.3390/s18072026 - 25 Jun 2018
Cited by 65 | Viewed by 9847
Abstract
Recent advances in unmanned aerial system (UAS) sensed imagery, sensor quality/size, and geospatial image processing can enable UASs to rapidly and continually monitor coral reefs, to determine the type of coral and signs of coral bleaching. This paper describes an unmanned aerial vehicle [...] Read more.
Recent advances in unmanned aerial system (UAS) sensed imagery, sensor quality/size, and geospatial image processing can enable UASs to rapidly and continually monitor coral reefs, to determine the type of coral and signs of coral bleaching. This paper describes an unmanned aerial vehicle (UAV) remote sensing methodology to increase the efficiency and accuracy of existing surveillance practices. The methodology uses a UAV integrated with advanced digital hyperspectral, ultra HD colour (RGB) sensors, and machine learning algorithms. This paper describes the combination of airborne RGB and hyperspectral imagery with in-water survey data of several types in-water survey of coral under diverse levels of bleaching. The paper also describes the technology used, the sensors, the UAS, the flight operations, the processing workflow of the datasets, the methods for combining multiple airborne and in-water datasets, and finally presents relevant results of material classification. The development of the methodology for the collection and analysis of airborne hyperspectral and RGB imagery would provide coral reef researchers, other scientists, and UAV practitioners with reliable data collection protocols and faster processing techniques to achieve remote sensing objectives. Full article
(This article belongs to the Special Issue UAV or Drones for Remote Sensing Applications)
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31 pages, 2043 KiB  
Review
Ambient Sensors for Elderly Care and Independent Living: A Survey
by Md. Zia Uddin, Weria Khaksar and Jim Torresen
Sensors 2018, 18(7), 2027; https://doi.org/10.3390/s18072027 - 25 Jun 2018
Cited by 148 | Viewed by 18062
Abstract
Elderly care at home is a matter of great concern if the elderly live alone, since unforeseen circumstances might occur that affect their well-being. Technologies that assist the elderly in independent living are essential for enhancing care in a cost-effective and reliable manner. [...] Read more.
Elderly care at home is a matter of great concern if the elderly live alone, since unforeseen circumstances might occur that affect their well-being. Technologies that assist the elderly in independent living are essential for enhancing care in a cost-effective and reliable manner. Elderly care applications often demand real-time observation of the environment and the resident’s activities using an event-driven system. As an emerging area of research and development, it is necessary to explore the approaches of the elderly care system in the literature to identify current practices for future research directions. Therefore, this work is aimed at a comprehensive survey of non-wearable (i.e., ambient) sensors for various elderly care systems. This research work is an effort to obtain insight into different types of ambient-sensor-based elderly monitoring technologies in the home. With the aim of adopting these technologies, research works, and their outcomes are reported. Publications have been included in this survey if they reported mostly ambient sensor-based monitoring technologies that detect elderly events (e.g., activities of daily living and falls) with the aim of facilitating independent living. Mostly, different types of non-contact sensor technologies were identified, such as motion, pressure, video, object contact, and sound sensors. Besides, multicomponent technologies (i.e., combinations of ambient sensors with wearable sensors) and smart technologies were identified. In addition to room-mounted ambient sensors, sensors in robot-based elderly care works are also reported. Research that is related to the use of elderly behavior monitoring technologies is widespread, but it is still in its infancy and consists mostly of limited-scale studies. Elderly behavior monitoring technology is a promising field, especially for long-term elderly care. However, monitoring technologies should be taken to the next level with more detailed studies that evaluate and demonstrate their potential to contribute to prolonging the independent living of elderly people. Full article
(This article belongs to the Section Physical Sensors)
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18 pages, 1316 KiB  
Article
Immunogold Nanoparticles for Rapid Plasmonic Detection of C. sakazakii
by Mohamed A. Aly, Konrad J. Domig, Wolfgang Kneifel and Erik Reimhult
Sensors 2018, 18(7), 2028; https://doi.org/10.3390/s18072028 - 25 Jun 2018
Cited by 19 | Viewed by 7237
Abstract
Cronobacter sakazakii is a foodborne pathogen that can cause a rare, septicemia, life-threatening meningitis, and necrotizing enterocolitis in infants. In general, standard methods for pathogen detection rely on culture, plating, colony counting and polymerase chain reaction DNA-sequencing for identification, which are time, equipment [...] Read more.
Cronobacter sakazakii is a foodborne pathogen that can cause a rare, septicemia, life-threatening meningitis, and necrotizing enterocolitis in infants. In general, standard methods for pathogen detection rely on culture, plating, colony counting and polymerase chain reaction DNA-sequencing for identification, which are time, equipment and skill demanding. Recently, nanoparticle- and surface-based immunoassays have increasingly been explored for pathogen detection. We investigate the functionalization of gold nanoparticles optimized for irreversible and specific binding to C. sakazakii and their use for spectroscopic detection of the pathogen. We demonstrate how 40-nm gold nanoparticles grafted with a poly(ethylene glycol) brush and functionalized with polyclonal antibodies raised against C. sakazakii can be used to specifically target C. sakazakii. The strong extinction peak of the Au nanoparticle plasmon polariton resonance in the optical range is used as a label for detection of the pathogens. Individual binding of the nanoparticles to the C. sakazakii surface is also verified by transmission electron microscopy. We show that a high degree of surface functionalization with anti-C. sakazakii optimizes the detection and leads to a detection limit as low as 10 CFU/mL within 2 h using a simple cuvette-based UV-Vis spectrometric readout that has great potential for further optimization. Full article
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9 pages, 2700 KiB  
Article
Mechanism and Characteristics of Humidity Sensing with Polyvinyl Alcohol-Coated Fiber Surface Plasmon Resonance Sensor
by Yu Shao, Ying Wang, Shaoqing Cao, Yijian Huang, Longfei Zhang, Feng Zhang, Changrui Liao and Yiping Wang
Sensors 2018, 18(7), 2029; https://doi.org/10.3390/s18072029 - 25 Jun 2018
Cited by 46 | Viewed by 5070
Abstract
A surface plasmon resonance (SPR) sensor based on a side-polished single mode fiber coated with polyvinyl alcohol (PVA) is demonstrated for relative humidity (RH) sensing. The SPR sensor exhibits a resonant dip in the transmission spectrum in ambient air after PVA film coating, [...] Read more.
A surface plasmon resonance (SPR) sensor based on a side-polished single mode fiber coated with polyvinyl alcohol (PVA) is demonstrated for relative humidity (RH) sensing. The SPR sensor exhibits a resonant dip in the transmission spectrum in ambient air after PVA film coating, and the resonant wavelength shifts to longer wavelengths as the thickness of the PVA film increases. When RH changes, the resonant dip of the sensor with different film-thicknesses exhibits interesting characteristics for optical spectrum evolution. For sensors with initial wavelengths between 550 nm and 750 nm, the resonant dip shifts to longer wavelengths with increasing RH. The averaged sensitivity increases firstly and then drops, and shows a maximal sensitivity of 1.01 nm/RH%. Once the initial wavelength of the SPR sensor exceeds 850 nm, an inflection point of the resonant wavelength shift can be observed with RH increasing, and the resonant dip shifts to shorter wavelengths for RH values exceeding this point, and sensitivity as high as −4.97 nm/RH% can be obtained in the experiment. The sensor is expected to have potential applications in highly sensitive and cost effective humidity sensing. Full article
(This article belongs to the Section Physical Sensors)
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17 pages, 7941 KiB  
Article
Six Degrees of Freedom Displacement Measurement System for Wafer Stage Composed of Hall Sensors
by Bo Zhao, Weijia Shi, Jiawei Zhang, Ming Zhang, Xue Qi, Jiaxin Li, Feng Li and Jiubin Tan
Sensors 2018, 18(7), 2030; https://doi.org/10.3390/s18072030 - 25 Jun 2018
Cited by 5 | Viewed by 4823
Abstract
This paper proposes a decoupled six degrees of freedom (DOF) displacement measurement methodology, which is accomplished by utilizing six pairs of permanent magnets and six Hall sensors. Firstly, the coordinate transformation was mathematically derived, which represented the relationships between the main coordinate system [...] Read more.
This paper proposes a decoupled six degrees of freedom (DOF) displacement measurement methodology, which is accomplished by utilizing six pairs of permanent magnets and six Hall sensors. Firstly, the coordinate transformation was mathematically derived, which represented the relationships between the main coordinate system of the motion system and each body coordinate system of the Hall sensors. With the aid of an ellipsoid function and the least squares method, only the output voltages of the six Hall sensors were required to decouple the six-DOF displacement and inclination of the motion platform with high accuracy. Finally, the experimental measurements demonstrate the effectiveness of the six DOF displacement measurement methodology, based on which the maximum errors of displacements can reach 0.23 mm and the maximum errors of inclinations can reach 0.07°. Full article
(This article belongs to the Section Physical Sensors)
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15 pages, 1977 KiB  
Article
A Network Equivalent-Based Algorithm for Adaptive Parameter Tuning in 802.15.4 WSNs
by Yipeng Wang, Wei Yang, Ruisong Han and Kaiming You
Sensors 2018, 18(7), 2031; https://doi.org/10.3390/s18072031 - 25 Jun 2018
Cited by 4 | Viewed by 2369
Abstract
Previous studies have shown that in many wireless sensor network applications the IEEE 802.15.4 carrier sense multiple access with collision avoidance (CSMA/CA) mechanism with default parameters cannot guarantee the constraints of reliability, time efficiency, or energy efficiency. Although many adaptive parameter tuning algorithms [...] Read more.
Previous studies have shown that in many wireless sensor network applications the IEEE 802.15.4 carrier sense multiple access with collision avoidance (CSMA/CA) mechanism with default parameters cannot guarantee the constraints of reliability, time efficiency, or energy efficiency. Although many adaptive parameter tuning algorithms have been proposed, many of them cannot correctly identify the changes of the network condition and are unable to effectively perform the parameter tuning operation. Considering the randomness that CSMA/CA brings about, for most of the proposed algorithms, it is a challenge to distinguish significant violations that were caused by actual changes of the network from the general fluctuations that were due to CSMA/CA. In this paper, we propose a lightweight algorithm called the network equivalent adaptive parameter tuning (NEAPT) algorithm. It is fully distributed and can work without any predefined information or acknowledgement. NEAPT not only takes reliability as an evaluation of a network condition, but it proposes a synthetic value, called the equivalent node number, and takes it as another reference for a network condition. Simulation results show that by taking both reliability and the equivalent node number into consideration, NEAPT can effectively identify the network changes and provide adequate and steady performances for wireless sensor networks (WSNs) in both stationary and dynamic conditions. Full article
(This article belongs to the Section Sensor Networks)
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12 pages, 2820 KiB  
Article
Complexity of Daily Physical Activity Is More Sensitive Than Conventional Metrics to Assess Functional Change in Younger Older Adults
by Wei Zhang, Michael Schwenk, Sabato Mellone, Anisoara Paraschiv-Ionescu, Beatrix Vereijken, Mirjam Pijnappels, A. Stefanie Mikolaizak, Elisabeth Boulton, Nini H. Jonkman, Andrea B. Maier, Jochen Klenk, Jorunn Helbostad, Kristin Taraldsen and Kamiar Aminian
Sensors 2018, 18(7), 2032; https://doi.org/10.3390/s18072032 - 25 Jun 2018
Cited by 21 | Viewed by 5816
Abstract
The emerging mHealth applications, incorporating wearable sensors, enables continuous monitoring of physical activity (PA). This study aimed at analyzing the relevance of a multivariate complexity metric in assessment of functional change in younger older adults. Thirty individuals (60–70 years old) participated in a [...] Read more.
The emerging mHealth applications, incorporating wearable sensors, enables continuous monitoring of physical activity (PA). This study aimed at analyzing the relevance of a multivariate complexity metric in assessment of functional change in younger older adults. Thirty individuals (60–70 years old) participated in a 4-week home-based exercise intervention. The Community Balance and Mobility Scale (CBMS) was used for clinical assessment of the participants’ functional balance and mobility performance pre- and post- intervention. Accelerometers worn on the low back were used to register PA of one week before and in the third week of the intervention. Changes in conventional univariate PA metrics (percentage of walking and sedentary time, step counts, mean cadence) and complexity were compared to the change as measured by the CBMS. Statistical analyses (21 participants) showed significant rank correlation between the change as measured by complexity and CBMS (ρ = 0.47, p = 0.03). Smoothing the activity output improved the correlation (ρ = 0.58, p = 0.01). In contrast, change in univariate PA metrics did not show correlations. These findings demonstrate the high potential of the complexity metric being useful and more sensitive than conventional PA metrics for assessing functional changes in younger older adults. Full article
(This article belongs to the Special Issue Data Analytics and Applications of the Wearable Sensors in Healthcare)
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13 pages, 2268 KiB  
Article
Improved Visualization of Hydroacoustic Plumes Using the Split-Beam Aperture Coherence
by Ann E. A. Blomberg, Thomas C. Weber and Andreas Austeng
Sensors 2018, 18(7), 2033; https://doi.org/10.3390/s18072033 - 25 Jun 2018
Cited by 7 | Viewed by 4475
Abstract
Natural seepage of methane into the oceans is considerable, and plays a role in the global carbon cycle. Estimating the amount of this greenhouse gas entering the water column is important in order to understand their environmental impact. In addition, leakage from man-made [...] Read more.
Natural seepage of methane into the oceans is considerable, and plays a role in the global carbon cycle. Estimating the amount of this greenhouse gas entering the water column is important in order to understand their environmental impact. In addition, leakage from man-made structures such as gas pipelines may have environmental and economical consequences and should be promptly detected. Split beam echo sounders (SBES) detect hydroacoustic plumes due to the significant contrast in acoustic impedance between water and free gas. SBES are also powerful tools for plume characterization, with the ability to provide absolute acoustic measurements, estimate bubble trajectories, and capture the frequency dependent response of bubbles. However, under challenging conditions such as deep water and considerable background noise, it can be difficult to detect the presence of gas seepage from the acoustic imagery alone. The spatial coherence of the wavefield measured across the split beam sectors, quantified by the coherence factor (CF), is a computationally simple, easily available quantity which complements the acoustic imagery and may ease the ability to automatically or visually detect bubbles in the water column. We demonstrate the benefits of CF processing using SBES data from the Hudson Canyon, acquired using the Simrad EK80 SBES. We observe that hydroacoustic plumes appear more clearly defined and are easier to detect in the CF imagery than in the acoustic backscatter images. Full article
(This article belongs to the Special Issue Sensor Signal and Information Processing)
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19 pages, 6321 KiB  
Article
A Robust Step Detection Algorithm and Walking Distance Estimation Based on Daily Wrist Activity Recognition Using a Smart Band
by Duong Trong Bui, Nhan Duc Nguyen and Gu-Min Jeong
Sensors 2018, 18(7), 2034; https://doi.org/10.3390/s18072034 - 25 Jun 2018
Cited by 14 | Viewed by 5099
Abstract
Human activity recognition and pedestrian dead reckoning are an interesting field because of their importance utilities in daily life healthcare. Currently, these fields are facing many challenges, one of which is the lack of a robust algorithm with high performance. This paper proposes [...] Read more.
Human activity recognition and pedestrian dead reckoning are an interesting field because of their importance utilities in daily life healthcare. Currently, these fields are facing many challenges, one of which is the lack of a robust algorithm with high performance. This paper proposes a new method to implement a robust step detection and adaptive distance estimation algorithm based on the classification of five daily wrist activities during walking at various speeds using a smart band. The key idea is that the non-parametric adaptive distance estimator is performed after two activity classifiers and a robust step detector. In this study, two classifiers perform two phases of recognizing five wrist activities during walking. Then, a robust step detection algorithm, which is integrated with an adaptive threshold, peak and valley correction algorithm, is applied to the classified activities to detect the walking steps. In addition, the misclassification activities are fed back to the previous layer. Finally, three adaptive distance estimators, which are based on a non-parametric model of the average walking speed, calculate the length of each strike. The experimental results show that the average classification accuracy is about 99%, and the accuracy of the step detection is 98.7%. The error of the estimated distance is 2.2–4.2% depending on the type of wrist activities. Full article
(This article belongs to the Section Physical Sensors)
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12 pages, 1762 KiB  
Article
DNA-Based Sensor for the Detection of an Organophosphorus Pesticide: Profenofos
by Giulia Selvolini, Ioana Băjan, Oana Hosu, Cecilia Cristea, Robert Săndulescu and Giovanna Marrazza
Sensors 2018, 18(7), 2035; https://doi.org/10.3390/s18072035 - 25 Jun 2018
Cited by 79 | Viewed by 6216
Abstract
In this work, we propose an electrochemical DNA aptasensor for the detection of profenofos, an organophosphorus pesticide, based on a competitive format and disposable graphite screen-printed electrodes (GSPEs). A thiol-tethered DNA capture probe, which results to be complementary to the chosen aptamer sequence, [...] Read more.
In this work, we propose an electrochemical DNA aptasensor for the detection of profenofos, an organophosphorus pesticide, based on a competitive format and disposable graphite screen-printed electrodes (GSPEs). A thiol-tethered DNA capture probe, which results to be complementary to the chosen aptamer sequence, was immobilised on gold nanoparticles/polyaniline composite film-modified electrodes (AuNPs/PANI/GSPE). Different profenofos solutions containing a fixed amount of the biotinylated DNA aptamer were dropped onto the realized aptasensors. The hybridisation reaction was measured using a streptavidin-alkaline phosphatase enzyme conjugate, which catalyses the hydrolysis of 1-naphthyl -phosphate. The 1-naphtol enzymatic product was detected by means of differential pulse voltammetry (DPV). The aptasensor showed itself to work as a signal off sensor, according to the competitive format used. A dose response curve was obtained between 0.10 μM and 10 μM with a detection limit of 0.27 μM. Full article
(This article belongs to the Special Issue Sensors for Emerging Environmental Markers and Contaminants)
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19 pages, 7043 KiB  
Article
Single Chip-Based Nano-Optomechanical Accelerometer Based on Subwavelength Grating Pair and Rotated Serpentine Springs
by Qianbo Lu, Jian Bai, Kaiwei Wang, Peiwen Chen, Weidong Fang and Chen Wang
Sensors 2018, 18(7), 2036; https://doi.org/10.3390/s18072036 - 26 Jun 2018
Cited by 20 | Viewed by 4780
Abstract
Optical coupling between subwavelength grating pairs allows for the precise measurement of lateral or vertical displacement of grating elements and gives rise to different types of displacement and inertial sensors. In this paper, we demonstrate a design for a nano-optomechanical accelerometer based on [...] Read more.
Optical coupling between subwavelength grating pairs allows for the precise measurement of lateral or vertical displacement of grating elements and gives rise to different types of displacement and inertial sensors. In this paper, we demonstrate a design for a nano-optomechanical accelerometer based on a subwavelength grating pair that can be easily fabricated by a single Silicon-on-insulator (SOI) chip. The parameters of the subwavelength grating pair-based optical readout, including period, duty cycle, thickness of grating and metal film, and the distance of the air gap, were optimized by combining a genetic algorithm and rigorous coupled wavelength analysis (RCWA) to obtain the optimal sensitivity to the displacement of suspended grating element and the acceleration. A corresponding mechanical design was also completed to meet the highly sensitive acceleration measurement requirement while considering the mechanical cross-axis sensitivity, dynamic range, bandwidth, and fabrication feasibility. This device was verified by both RCWA and finite-different-time-domain methods, and a tolerance analysis was also completed to confirm that it is able to achieve the extremely high optical displacement sensitivity of 1.8%/nm, acceleration-displacement sensitivity of 1.56 nm/mg, and acceleration measurement sensitivity of more than 2.5%/mg, which is almost one order of magnitude higher than any reported counterparts. This work enables a single SOI-based high performance accelerometer, and provides a theoretical basis and fabrication guides for the design. Full article
(This article belongs to the Special Issue Integrated MEMS Sensors for the IoT Era)
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11 pages, 1575 KiB  
Article
An Exception Handling Approach for Privacy-Preserving Service Recommendation Failure in a Cloud Environment
by Lianyong Qi, Shunmei Meng, Xuyun Zhang, Ruili Wang, Xiaolong Xu, Zhili Zhou and Wanchun Dou
Sensors 2018, 18(7), 2037; https://doi.org/10.3390/s18072037 - 26 Jun 2018
Cited by 48 | Viewed by 4095
Abstract
Service recommendation has become an effective way to quickly extract insightful information from massive data. However, in the cloud environment, the quality of service (QoS) data used to make recommendation decisions are often monitored by distributed sensors and stored in different cloud platforms. [...] Read more.
Service recommendation has become an effective way to quickly extract insightful information from massive data. However, in the cloud environment, the quality of service (QoS) data used to make recommendation decisions are often monitored by distributed sensors and stored in different cloud platforms. In this situation, integrating these distributed data (monitored by remote sensors) across different platforms while guaranteeing user privacy is an important but challenging task, for the successful service recommendation in the cloud environment. Locality-Sensitive Hashing (LSH) is a promising way to achieve the abovementioned data integration and privacy-preservation goals, while current LSH-based recommendation studies seldom consider the possible recommendation failures and hence reduce the robustness of recommender systems significantly. In view of this challenge, we develop a new LSH variant, named converse LSH, and then suggest an exception handling approach for recommendation failures based on the converse LSH technique. Finally, we conduct several simulated experiments based on the well-known dataset, i.e., Movielens to prove the effectiveness and efficiency of our approach. Full article
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18 pages, 2621 KiB  
Review
On the Determination of Uncertainty and Limit of Detection in Label-Free Biosensors
by Álvaro Lavín, Jesús De Vicente, Miguel Holgado, María F. Laguna, Rafael Casquel, Beatriz Santamaría, María Victoria Maigler, Ana L. Hernández and Yolanda Ramírez
Sensors 2018, 18(7), 2038; https://doi.org/10.3390/s18072038 - 26 Jun 2018
Cited by 108 | Viewed by 9791
Abstract
A significant amount of noteworthy articles reviewing different label-free biosensors are being published in the last years. Most of the times, the comparison among the different biosensors is limited by the procedure used of calculating the limit of detection and the measurement uncertainty. [...] Read more.
A significant amount of noteworthy articles reviewing different label-free biosensors are being published in the last years. Most of the times, the comparison among the different biosensors is limited by the procedure used of calculating the limit of detection and the measurement uncertainty. This article clarifies and establishes a simple procedure to determine the calibration function and the uncertainty of the concentration measured at any point of the measuring interval of a generic label-free biosensor. The value of the limit of detection arises naturally from this model as the limit at which uncertainty tends when the concentration tends to zero. The need to provide additional information, such as the measurement interval and its linearity, among others, on the analytical systems and biosensor in addition to the detection limit is pointed out. Finally, the model is applied to curves that are typically obtained in immunoassays and a discussion is made on the application validity of the model and its limitations. Full article
(This article belongs to the Special Issue Label-Free Biosensors)
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16 pages, 6365 KiB  
Article
A Strap-Down Inertial Navigation/Spectrum Red-Shift/Star Sensor (SINS/SRS/SS) Autonomous Integrated System for Spacecraft Navigation
by Zhaohui Gao, Dejun Mu, Yongmin Zhong and Chengfan Gu
Sensors 2018, 18(7), 2039; https://doi.org/10.3390/s18072039 - 26 Jun 2018
Cited by 17 | Viewed by 3244
Abstract
This paper presents a new Strap-down Inertial Navigation System/Spectrum Red-Shift/Star Sensor (SINS/SRS/SS) system integration methodology to improve the autonomy and reliability of spacecraft navigation using the spectrum red-shift information from natural celestial bodies such as the Sun, Jupiter and the Earth. The system [...] Read more.
This paper presents a new Strap-down Inertial Navigation System/Spectrum Red-Shift/Star Sensor (SINS/SRS/SS) system integration methodology to improve the autonomy and reliability of spacecraft navigation using the spectrum red-shift information from natural celestial bodies such as the Sun, Jupiter and the Earth. The system models for SINS/SRS/SS integration are established. The information fusion of SINS/SRS/SS integration is designed as the structure of the federated Kalman filter to fuse the local estimations of SINS/SRS and SINS/SS integrated subsystems to generate the global state estimation for spacecraft navigation. A new robust adaptive unscented particle filter is also developed to obtain the local state estimations of SINS/SRS and SINS/SS integrated subsystems in a parallel manner. The simulation results demonstrate that the proposed methodology for SINS/SRS/SS integration can effectively calculate navigation solutions, leading to strong autonomy and high reliability for spacecraft navigation. Full article
(This article belongs to the Section Physical Sensors)
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23 pages, 6338 KiB  
Article
Rub-Impact Fault Diagnosis Using an Effective IMF Selection Technique in Ensemble Empirical Mode Decomposition and Hybrid Feature Models
by Alexander E. Prosvirin, Manjurul Islam, Jaeyoung Kim and Jong-Myon Kim
Sensors 2018, 18(7), 2040; https://doi.org/10.3390/s18072040 - 26 Jun 2018
Cited by 21 | Viewed by 5243
Abstract
The complex nature of rubbing faults makes it difficult to use traditional signal analysis methods for feature extraction. Various time-frequency analysis approaches based on signal decomposition, such as empirical mode decomposition (EMD) and ensemble EMD (EEMD), have been widely utilized recently to analyze [...] Read more.
The complex nature of rubbing faults makes it difficult to use traditional signal analysis methods for feature extraction. Various time-frequency analysis approaches based on signal decomposition, such as empirical mode decomposition (EMD) and ensemble EMD (EEMD), have been widely utilized recently to analyze rub-impact faults. However, traditional EMD suffers from “mode-mixing”, and in both EMD and EEMD the relevance of the extracted components to rubbing processes must be determined. In this paper, we introduce a new informative intrinsic mode function (IMF) selection method for EEMD and a hybrid feature model for diagnosing rub-impact faults of various intensities. Our method uses a novel selection procedure that combines the degree-of-presence ratio of rub impact and a Kullback–Leibler divergence-based similarity measure into an IMF quality metric with adaptive threshold-based selection to pick the meaningful signal-dominant modes. Signals reconstructed using the selected IMFs contained explicit information about the rubbing faults and are used for hybrid feature extraction. Experimental results demonstrated that the proposed approach effectively defines meaningful IMFs for rubbing processes, and the presented hybrid feature model allows for the classification of rub-impact faults of various intensities with good accuracy. Full article
(This article belongs to the Special Issue Sensors for Fault Detection)
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24 pages, 3051 KiB  
Article
Visual Information Fusion through Bayesian Inference for Adaptive Probability-Oriented Feature Matching
by David Valiente, Luis Payá, Luis M. Jiménez, Jose M. Sebastián and Óscar Reinoso
Sensors 2018, 18(7), 2041; https://doi.org/10.3390/s18072041 - 26 Jun 2018
Cited by 26 | Viewed by 4325
Abstract
This work presents a visual information fusion approach for robust probability-oriented feature matching. It is sustained by omnidirectional imaging, and it is tested in a visual localization framework, in mobile robotics. General visual localization methods have been extensively studied and optimized in terms [...] Read more.
This work presents a visual information fusion approach for robust probability-oriented feature matching. It is sustained by omnidirectional imaging, and it is tested in a visual localization framework, in mobile robotics. General visual localization methods have been extensively studied and optimized in terms of performance. However, one of the main threats that jeopardizes the final estimation is the presence of outliers. In this paper, we present several contributions to deal with that issue. First, 3D information data, associated with SURF (Speeded-Up Robust Feature) points detected on the images, is inferred under the Bayesian framework established by Gaussian processes (GPs). Such information represents a probability distribution for the feature points’ existence, which is successively fused and updated throughout the robot’s poses. Secondly, this distribution can be properly sampled and projected onto the next 2D image frame in t+1, by means of a filter-motion prediction. This strategy permits obtaining relevant areas in the image reference system, from which probable matches could be detected, in terms of the accumulated probability of feature existence. This approach entails an adaptive probability-oriented matching search, which accounts for significant areas of the image, but it also considers unseen parts of the scene, thanks to an internal modulation of the probability distribution domain, computed in terms of the current uncertainty of the system. The main outcomes confirm a robust feature matching, which permits producing consistent localization estimates, aided by the odometer’s prior to estimate the scale factor. Publicly available datasets have been used to validate the design and operation of the approach. Moreover, the proposal has been compared, firstly with a standard feature matching and secondly with a localization method, based on an inverse depth parametrization. The results confirm the validity of the approach in terms of feature matching, localization accuracy, and time consumption. Full article
(This article belongs to the Special Issue Visual Sensors)
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16 pages, 10866 KiB  
Article
Coumarin Probe for Selective Detection of Fluoride Ions in Aqueous Solution and Its Bioimaging in Live Cells
by Kantapat Chansaenpak, Anyanee Kamkaew, Oratai Weeranantanapan, Khomson Suttisintong and Gamolwan Tumcharern
Sensors 2018, 18(7), 2042; https://doi.org/10.3390/s18072042 - 26 Jun 2018
Cited by 23 | Viewed by 5873
Abstract
We have synthesized novel coumarin-based fluorescent chemosensors for detection of fluoride ions in aqueous solution. The detection mechanism relied on a fluoride-mediated desilylation triggering fluorogenic reaction and a strong interaction between fluoride and the silicon center. In this work, the hydroxyl-decorated coumarins containing [...] Read more.
We have synthesized novel coumarin-based fluorescent chemosensors for detection of fluoride ions in aqueous solution. The detection mechanism relied on a fluoride-mediated desilylation triggering fluorogenic reaction and a strong interaction between fluoride and the silicon center. In this work, the hydroxyl-decorated coumarins containing oxysilyl moiety have been synthesized through the aldehyde-functionalized coumarins. The optical responses toward fluoride, as well as aqueous stability studies of both aldehyde and hydroxyl functionalized coumarins, have been investigated. Due to the highest fluorescence enhancement upon the addition of fluoride and good stability in aqueous solution, the hydroxyl-decorated coumarin connected with the bulky tert-butyldiphenyloxysilyl group (-OSitBuPh2) has been selected for further investigation of its potential as a fluoride sensor. This hydroxyl-decorated coumarin can selectively sense fluoride ions in aqueous media (contain 0.8% MeCN) with desirable response times (40 min). The limit of detection of this compound was determined as 0.043 ppm, satisfying the standard fluoride level (0.7 ppm) in drinking water recommended by U.S. Department of Health and Human Services. The application of this silyl-capped coumarin derivative for fluoride analysis in collected water samples displayed satisfactory analytical accuracy (<5% error). Finally, this compound was successfully employed in fluorescence bioimaging of fluoride ions in human liver cancer cells, indicating its excellent cell permeability, ability to retain inside the living cells, and good stability under physiological conditions. Full article
(This article belongs to the Special Issue Colorimetric and Fluorescent Sensors 2018)
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28 pages, 1724 KiB  
Article
Multiple Access Control for Cognitive Radio-Based IEEE 802.11ah Networks
by Muhammad Shafiq, Maqbool Ahmad, Azeem Irshad, Moneeb Gohar, Muhammad Usman, Muhammad Khalil Afzal, Jin-Ghoo Choi and Heejung Yu
Sensors 2018, 18(7), 2043; https://doi.org/10.3390/s18072043 - 26 Jun 2018
Cited by 21 | Viewed by 5727
Abstract
The proliferation of Internet-of-Things (IoT) technology and its reliance on the license-free Industrial, Scientific, and Medical (ISM) bands have rendered radio spectrum scarce. The IoT can nevertheless obtain great advantage from Cognitive Radio (CR) technology for efficient use of a spectrum, to be [...] Read more.
The proliferation of Internet-of-Things (IoT) technology and its reliance on the license-free Industrial, Scientific, and Medical (ISM) bands have rendered radio spectrum scarce. The IoT can nevertheless obtain great advantage from Cognitive Radio (CR) technology for efficient use of a spectrum, to be implemented in IEEE 802.11af-based primary networks. However, such networks require a geolocation database and a centralized architecture to communicate white space information on channels. On the other hand, in spectrum sensing, CR presents various challenges such as the Hidden Primary Terminal (HPT) problem. To this end, we focus on the most recently released standard, i.e., IEEE 802.11ah, in which IoT stations can first be classified into multiple groups to reduce collisions and then they can periodically access the channel. Therein, both services are similarly supported by a centralized server that requires signaling overhead to control the groups of stations. In addition, more regroupings are required over time due to the frequent variations in the number of participating stations, which leads to more overhead. In this paper, we propose a new Multiple Access Control (MAC) protocol for CR-based IEEE 802.11ah systems, called Restricted Access with Collision and Interference Resolution (RACIR). We introduce a decentralized group split algorithm that distributes the participating stations into multiple groups based on a probabilistic estimation in order to resolve collisions. Furthermore, we propose a decentralized channel access procedure that avoids the HPT problem and resolves interference with the incumbent receiver. We analyze the performance of our proposed MAC protocol in terms of normalized throughput, packet delay and energy consumption with the Markov model and analytic expressions. The results are quite promising, which makes the RACIR protocol a strong candidate for the CR-based IoT environment. Full article
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13 pages, 2565 KiB  
Article
Vibration of a Rotating Micro-Ring under Electrical Field Based on Inextensible Approximation
by Tao Yu, Jiange Kou and Yuh-Chung Hu
Sensors 2018, 18(7), 2044; https://doi.org/10.3390/s18072044 - 26 Jun 2018
Cited by 5 | Viewed by 4332
Abstract
The problem of vibrations of rotating rings has been of interest for its wide applications in engineering, such as the vibratory ring gyroscopes. For the vibratory ring gyroscopes, the vibration of a micro ring is usually actuated and sensed by means of electrostatics. [...] Read more.
The problem of vibrations of rotating rings has been of interest for its wide applications in engineering, such as the vibratory ring gyroscopes. For the vibratory ring gyroscopes, the vibration of a micro ring is usually actuated and sensed by means of electrostatics. The analytical models of electrostatic microstructures are complicated due to their non-linear electromechanical coupling behavior. Therefore, this paper presents for the first time the free vibration of a rotating ring under uniform electrical field and the results will be helpful for extending our knowledge on the problem of vibrations of rotating rings, helping the design of vibratory ring gyroscopes, and inspiring the feasibilities of other engineering applications. An analytical model, based on thin-ring theory, is derived by means of energy method for a rotating ring under uniformly distributed electrical field. After that, the closed form solutions of the natural frequencies and modes are obtained by means of modal expansion method. Some valuable conclusions are made according to the results of the present analytical model. The electrical field causes not only an electrostatic force but also an equivalently negative electrical-stiffness. The equivalent negative electrical-stiffness will reduce either the natural frequencies or critical speeds of the rotating ring. It is known that the ring will buckle when its rotational speed equals its natural frequencies. The introduction of electrical field will further reduce the buckling speeds to a value less than the natural frequencies. The rotation effect will induce the so-called traveling modes, each one travels either in the same direction as the rotating ring or in the opposite direction with respect to stationary coordinate system. The electrical field will reduce the traveling velocities of the traveling modes. Full article
(This article belongs to the Collection Modeling, Testing and Reliability Issues in MEMS Engineering)
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30 pages, 9136 KiB  
Article
HyTexiLa: High Resolution Visible and Near Infrared Hyperspectral Texture Images
by Haris Ahmad Khan, Sofiane Mihoubi, Benjamin Mathon, Jean-Baptiste Thomas and Jon Yngve Hardeberg
Sensors 2018, 18(7), 2045; https://doi.org/10.3390/s18072045 - 26 Jun 2018
Cited by 35 | Viewed by 8967
Abstract
We present a dataset of close range hyperspectral images of materials that span the visible and near infrared spectrums: HyTexiLa (Hyperspectral Texture images acquired in Laboratory). The data is intended to provide high spectral and spatial resolution reflectance images of 112 materials to [...] Read more.
We present a dataset of close range hyperspectral images of materials that span the visible and near infrared spectrums: HyTexiLa (Hyperspectral Texture images acquired in Laboratory). The data is intended to provide high spectral and spatial resolution reflectance images of 112 materials to study spatial and spectral textures. In this paper we discuss the calibration of the data and the method for addressing the distortions during image acquisition. We provide a spectral analysis based on non-negative matrix factorization to quantify the spectral complexity of the samples and extend local binary pattern operators to the hyperspectral texture analysis. The results demonstrate that although the spectral complexity of each of the textures is generally low, increasing the number of bands permits better texture classification, with the opponent band local binary pattern feature giving the best performance. Full article
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18 pages, 13325 KiB  
Article
Online Model Updating and Dynamic Learning Rate-Based Robust Object Tracking
by Md Mojahidul Islam, Guoqing Hu and Qianbo Liu
Sensors 2018, 18(7), 2046; https://doi.org/10.3390/s18072046 - 26 Jun 2018
Cited by 10 | Viewed by 4259
Abstract
Robust visual tracking is a significant and challenging issue in computer vision-related research fields and has attracted an immense amount of attention from researchers. Due to various practical applications, many studies have been done that have introduced numerous algorithms. It is considered to [...] Read more.
Robust visual tracking is a significant and challenging issue in computer vision-related research fields and has attracted an immense amount of attention from researchers. Due to various practical applications, many studies have been done that have introduced numerous algorithms. It is considered to be a challenging problem due to the unpredictability of various real-time situations, such as illumination variations, occlusion, fast motion, deformation, and scale variation, even though we only know the initial target position. To address these matters, we used a kernelized-correlation-filter-based translation filter with the integration of multiple features such as histogram of oriented gradients (HOG) and color attributes. These powerful features are useful to differentiate the target from the surrounding background and are effective for motion blur and illumination variations. To minimize the scale variation problem, we designed a correlation-filter-based scale filter. The proposed adaptive model’s updating and dynamic learning rate strategies based on a peak-to-sidelobe ratio effectively reduce model-drifting problems by avoiding noisy appearance changes. The experiment results show that our method provides the best performance compared to other methods, with a distance precision score of 79.9%, overlap success score of 59.0%, and an average running speed of 74 frames per second on the object tracking benchmark (OTB-2015). Full article
(This article belongs to the Special Issue Artificial Intelligence and Machine Learning in Sensors Networks)
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9 pages, 3293 KiB  
Article
Quartz-Enhanced Photoacoustic Spectroscopy Sensor with a Small-Gap Quartz Tuning Fork
by Yu-Fei Ma, Yao Tong, Ying He, Jin-Hu Long and Xin Yu
Sensors 2018, 18(7), 2047; https://doi.org/10.3390/s18072047 - 27 Jun 2018
Cited by 16 | Viewed by 4579
Abstract
A highly sensitive quartz-enhanced photoacoustic spectroscopy (QEPAS) sensor based on a custom quartz tuning fork (QTF) with a small-gap of 200 μm was demonstrated. With the help of the finite element modeling (FEM) simulation software COMSOL, the change tendency of the QEPAS signal [...] Read more.
A highly sensitive quartz-enhanced photoacoustic spectroscopy (QEPAS) sensor based on a custom quartz tuning fork (QTF) with a small-gap of 200 μm was demonstrated. With the help of the finite element modeling (FEM) simulation software COMSOL, the change tendency of the QEPAS signal under the influence of the laser beam vertical position and the length of the micro-resonator (mR) were calculated theoretically. Water vapor (H2O) was selected as the target analyte. The experimental results agreed well with those of the simulation, which verified the correctness of the theoretical model. An 11-fold signal enhancement was achieved with the addition of an mR with an optimal length of 5 mm in comparison to the bare QTF. Finally, the H2O-QEPAS sensor, which was based on a small-gap QTF, achieved a minimum detection limit (MDL) of 1.3 ppm, indicating an improvement of the sensor performance when compared to the standard QTF that has a gap of 300 μm. Full article
(This article belongs to the Special Issue Optical Sensing and Imaging, from UV to THz Range)
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15 pages, 16528 KiB  
Article
Detection of Cattle Using Drones and Convolutional Neural Networks
by Alberto Rivas, Pablo Chamoso, Alfonso González-Briones and Juan Manuel Corchado
Sensors 2018, 18(7), 2048; https://doi.org/10.3390/s18072048 - 27 Jun 2018
Cited by 120 | Viewed by 10331
Abstract
Multirotor drones have been one of the most important technological advances of the last decade. Their mechanics are simple compared to other types of drones and their possibilities in flight are greater. For example, they can take-off vertically. Their capabilities have therefore brought [...] Read more.
Multirotor drones have been one of the most important technological advances of the last decade. Their mechanics are simple compared to other types of drones and their possibilities in flight are greater. For example, they can take-off vertically. Their capabilities have therefore brought progress to many professional activities. Moreover, advances in computing and telecommunications have also broadened the range of activities in which drones may be used. Currently, artificial intelligence and information analysis are the main areas of research in the field of computing. The case study presented in this article employed artificial intelligence techniques in the analysis of information captured by drones. More specifically, the camera installed in the drone took images which were later analyzed using Convolutional Neural Networks (CNNs) to identify the objects captured in the images. In this research, a CNN was trained to detect cattle, however the same training process could be followed to develop a CNN for the detection of any other object. This article describes the design of the platform for real-time analysis of information and its performance in the detection of cattle. Full article
(This article belongs to the Special Issue Smart Decision-Making)
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15 pages, 4398 KiB  
Article
3D Magnetic Field Reconstruction Methodology Based on a Scanning Magnetoresistive Probe
by Filipe Richheimer, Margaret Costa, Diana C. Leitao, João Gaspar, Susana Cardoso and Paulo P. Freitas
Sensors 2018, 18(7), 2049; https://doi.org/10.3390/s18072049 - 27 Jun 2018
Cited by 3 | Viewed by 5148
Abstract
The present work provides a detailed description on quantitative 3D magnetic field reconstruction using a scanning magnetoresistance microscopy setup incorporating a 19.5 μm × 2.5 μm magnetoresistive sensor. Therefore, making use of a rotation stage, 11 nm thick ferromagnetic CoFe elements [...] Read more.
The present work provides a detailed description on quantitative 3D magnetic field reconstruction using a scanning magnetoresistance microscopy setup incorporating a 19.5 μm × 2.5 μm magnetoresistive sensor. Therefore, making use of a rotation stage, 11 nm thick ferromagnetic CoFe elements with 20 μm × 5 μm planar size were measured along different sensor axes and converted into cartesian coordinate magnetic field components by use of the analytical coordinate transform equations. The reconstruction steps were followed and validated by numerical simulations based on a field averaging model caused by a non-negligible sensor volume. Detailed in-plane magnetic component reconstruction with ability to reconstruct sub-micrometer features is achieved. A discussion on the limiting factors for optimal resolution is presented. Full article
(This article belongs to the Section Physical Sensors)
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16 pages, 2643 KiB  
Article
Sensitive Spectroscopy of Acetone Using a Widely Tunable External-Cavity Quantum Cascade Laser
by Faisal Nadeem, Julien Mandon, Amir Khodabakhsh, Simona M. Cristescu and Frans J. M. Harren
Sensors 2018, 18(7), 2050; https://doi.org/10.3390/s18072050 - 27 Jun 2018
Cited by 29 | Viewed by 6944
Abstract
We employed a single-mode, widely tunable (~300 cm−1) external-cavity quantum cascade laser operating around 8 µm for broadband direct absorption spectroscopy and wavelength modulation spectroscopy where a modulation frequency of 50 kHz was employed with high modulation amplitudes of up to [...] Read more.
We employed a single-mode, widely tunable (~300 cm−1) external-cavity quantum cascade laser operating around 8 µm for broadband direct absorption spectroscopy and wavelength modulation spectroscopy where a modulation frequency of 50 kHz was employed with high modulation amplitudes of up to 10 GHz. Using a compact multipass cell, we measured the entire molecular absorption band of acetone at ~7.4 µm with a spectral resolution of ~1 cm−1. In addition, to demonstrate the high modulation dynamic range of the laser, we performed direct absorption (DAS) and second harmonic wavelength modulation spectroscopy (WMS-2f) of the Q-branch peak of acetone molecular absorption band (HWHM ~10 GHz) near 1365 cm−1. With WMS-2f, a minimum detection limit of 15 ppbv in less than 10 s is achieved, which yields a noise equivalent absorption sensitivity of 1.9 × 10−8 cm−1 Hz−1/2. Full article
(This article belongs to the Special Issue Spectroscopy Based Sensors)
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9 pages, 3996 KiB  
Article
Analysis and Improvement of a Dual-Core Photonic Crystal Fiber Sensor
by Pibin Bing, Shichao Huang, Jialei Sui, Hua Wang and Zhiyong Wang
Sensors 2018, 18(7), 2051; https://doi.org/10.3390/s18072051 - 27 Jun 2018
Cited by 36 | Viewed by 3827
Abstract
The characteristics of the dual-core photonic crystal fiber (PCF) sensor are studied using the finite element method (FEM), and the structure is improved according to the numerical simulation results. The results show that whether or not the four large air holes far away [...] Read more.
The characteristics of the dual-core photonic crystal fiber (PCF) sensor are studied using the finite element method (FEM), and the structure is improved according to the numerical simulation results. The results show that whether or not the four large air holes far away from the geometry center of the PCF are filled with analyte has no influence on the wavelength sensitivity of the sensor which means those holes can be replaced by small air holes. The wavelength sensitivity can be tuned by adjusting the sizes of the other large air holes which are as for liquid holes. The dynamic detection range of the refractive index (RI) is from 1.33 to 1.51. In particular, high linearity is obtained in the range of 1.44 to 1.51. The sensitivity is as high as 6021 nm/RIU when the liquid holes are the smallest. When liquid holes are tangential with the envelope of first layer air holes, the wavelength sensitivity is 4028 nm/RIU, and the coefficient of determination (R2) is 0.99822 when the RI of the analyte varies from 1.44 to 1.51 which shows that high sensitivity and good linearity are both obtained. Full article
(This article belongs to the Section Physical Sensors)
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40 pages, 10747 KiB  
Article
A Plug-and-Play Human-Centered Virtual TEDS Architecture for the Web of Things
by Dixys L. Hernández-Rojas, Tiago M. Fernández-Caramés, Paula Fraga-Lamas and Carlos J. Escudero
Sensors 2018, 18(7), 2052; https://doi.org/10.3390/s18072052 - 27 Jun 2018
Cited by 35 | Viewed by 7345
Abstract
This article presents a Virtual Transducer Electronic Data Sheet (VTEDS)-based framework for the development of intelligent sensor nodes with plug-and-play capabilities in order to contribute to the evolution of the Internet of Things (IoT) toward the Web of Things (WoT). It makes use [...] Read more.
This article presents a Virtual Transducer Electronic Data Sheet (VTEDS)-based framework for the development of intelligent sensor nodes with plug-and-play capabilities in order to contribute to the evolution of the Internet of Things (IoT) toward the Web of Things (WoT). It makes use of new lightweight protocols that allow sensors to self-describe, auto-calibrate, and auto-register. Such protocols enable the development of novel IoT solutions while guaranteeing low latency, low power consumption, and the required Quality of Service (QoS). Thanks to the developed human-centered tools, it is possible to configure and modify dynamically IoT device firmware, managing the active transducers and their communication protocols in an easy and intuitive way, without requiring any prior programming knowledge. In order to evaluate the performance of the system, it was tested when using Bluetooth Low Energy (BLE) and Ethernet-based smart sensors in different scenarios. Specifically, user experience was quantified empirically (i.e., how fast the system shows collected data to a user was measured). The obtained results show that the proposed VTED architecture is very fast, with some smart sensors (located in Europe) able to self-register and self-configure in a remote cloud (in South America) in less than 3 s and to display data to remote users in less than 2 s. Full article
(This article belongs to the Special Issue Internet of Things and Ubiquitous Sensing)
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18 pages, 5292 KiB  
Article
Sensitivity Analysis of Geometrical Parameters on the Aerodynamic Performance of Closed-Box Girder Bridges
by Yongxin Yang, Rui Zhou, Yaojun Ge, Yanliang Du and Lihai Zhang
Sensors 2018, 18(7), 2053; https://doi.org/10.3390/s18072053 - 27 Jun 2018
Cited by 10 | Viewed by 3848
Abstract
In this study, the influence of two critical geometrical parameters (i.e., angles of wind fairing, α; and lower inclined web, β) in the aerodynamic performance of closed-box girder bridges was systematically investigated through conducting a theoretical analysis and wind tunnel testing using laser [...] Read more.
In this study, the influence of two critical geometrical parameters (i.e., angles of wind fairing, α; and lower inclined web, β) in the aerodynamic performance of closed-box girder bridges was systematically investigated through conducting a theoretical analysis and wind tunnel testing using laser displacement sensors. The results show that, for a particular inclined web angle β, a closed-box girder with a sharper wind fairing angle of α = 50° has better flutter and vortex-induced vibration (VIV) performance than that with α = 60°, while an inclined web angle of β = 14° produces the best VIV performance. In addition, the results from particle image velocimetry (PIV) tests indicate that a wind fairing angle of α = 50° produces a better flutter performance by inducing a single vortex structure and a balanced distribution of the strength of vorticity in both upper and lower parts of the wake region. Furthermore, two-dimensional three-degrees-of-freedom (2D-3DOF) analysis results demonstrate that the absolute values of Part A (with a reference of flutter derivative A2*) and Part D (with a reference of A1*H3*) generally decrease with the increase of β, while the change of the participation level of heaving degrees of freedom (DOF) in torsion-dominated coupled flutter initially increases, reaches its peak, and then decreases with the increase of β. Full article
(This article belongs to the Special Issue Bridge Structural Health Monitoring and Damage Identification)
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13 pages, 1079 KiB  
Article
Shear Elasticity of Magnetic Gels with Internal Structures
by Dmitry Borin, Dmitri Chirikov and Andrey Zubarev
Sensors 2018, 18(7), 2054; https://doi.org/10.3390/s18072054 - 27 Jun 2018
Cited by 15 | Viewed by 3112
Abstract
We present the results of the theoretical modeling of the elastic shear properties of a magnetic gel, consisting of soft matrix and embedded, fine magnetizable particles, which are united in linear chain-like structures. We suppose that the composite is placed in a magnetic [...] Read more.
We present the results of the theoretical modeling of the elastic shear properties of a magnetic gel, consisting of soft matrix and embedded, fine magnetizable particles, which are united in linear chain-like structures. We suppose that the composite is placed in a magnetic field, perpendicular to the direction of the sample shear. Our results show that the field can significantly enhance the mechanical rigidity of the soft composite. Theoretical results are in quantitative agreement with the experiments. Full article
(This article belongs to the Special Issue Magnetic Materials Based Biosensors)
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10 pages, 2476 KiB  
Article
High Dynamic Micro Vibrator with Integrated Optical Displacement Detector for In-Situ Self-Calibration of MEMS Inertial Sensors
by Yi-Jia Du, Ting-Ting Yang, Dong-Dong Gong, Yi-Cheng Wang, Xiang-Yu Sun, Feng Qin and Gang Dai
Sensors 2018, 18(7), 2055; https://doi.org/10.3390/s18072055 - 27 Jun 2018
Cited by 6 | Viewed by 4408
Abstract
The scale factor drifts and other long-term instability drifts of Micro-Electro-Mechanical System (MEMS) inertial sensors are the main contributors of the position and orientation errors in high dynamic environments. In this paper, a novel high dynamic micro vibrator, which could provide high acceleration [...] Read more.
The scale factor drifts and other long-term instability drifts of Micro-Electro-Mechanical System (MEMS) inertial sensors are the main contributors of the position and orientation errors in high dynamic environments. In this paper, a novel high dynamic micro vibrator, which could provide high acceleration and high angular rate rotation with integrated optical displacement detector, is proposed. Commercial MEMS inertial sensors, including 3-axis accelerometer and 6-axis inertial measurement unit which is about 3 mm * 3 mm * 1 mm with 19 mg, could be bonded on the vibration platform of the micro vibrator to perform in-situ during the self-calibration procedure. The high dynamic micro vibrator is fabricated by a fully-integrated MEMS process, including lead zirconate titanate (PZT) film deposition, PZT and electrodes patterning, and structural ion etching. The optical displacement detector, using vertical-cavity surface-emitting laser (VCSEL) and photoelectric diodes (PD), is integrated on the top of the package to measure the 6-DOF vibrating displacement with the detecting resolution of 150 nm in the range of 500 μm. The maximum out-of-plane acceleration of the z-axis vibrating platform loaded with commercial 3-axis accelerometer (H3LIS331DL) achieves above 16 g and the maximum angular velocity achieves above 720°/s when the driving voltage is ±6 V. Full article
(This article belongs to the Special Issue Piezoelectric Micro- and Nano-Devices)
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10 pages, 2557 KiB  
Article
Sensitivity Enhancement in Surface Plasmon Resonance Biochemical Sensor Based on Transition Metal Dichalcogenides/Graphene Heterostructure
by Xiang Zhao, Tianye Huang, Perry Shum Ping, Xu Wu, Pan Huang, Jianxing Pan, Yiheng Wu and Zhuo Cheng
Sensors 2018, 18(7), 2056; https://doi.org/10.3390/s18072056 - 27 Jun 2018
Cited by 87 | Viewed by 4889
Abstract
In this work, a surface plasmon resonance (SPR) biosensor based on two-dimensional transition metal dichalcogenides (TMDCs) is proposed to improve the biosensor’s sensitivity. In this sensor, different kinds of two-dimensional TMDCs are coated on both surfaces of metal film. By optimizing the structural [...] Read more.
In this work, a surface plasmon resonance (SPR) biosensor based on two-dimensional transition metal dichalcogenides (TMDCs) is proposed to improve the biosensor’s sensitivity. In this sensor, different kinds of two-dimensional TMDCs are coated on both surfaces of metal film. By optimizing the structural parameters, the angular sensitivity can reach as high as 315.5 Deg/RIU with 7-layers WS2 and 36 nm Al thin film, which is 3.3 times of the conventional structure based on single Al thin film. We also obtain maximum phase sensitivity (3.85 × 106 Deg/RIU) with bilayer WS2 and 35 nm Al thin film. The phase sensitivity can be further improved by employing Ag and removing air layer. The proposed configuration is of great potential for biochemical sensing. Full article
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15 pages, 7001 KiB  
Article
Real-Time Curvature Detection of a Flexible Needle with a Bevel Tip
by Bo Zhang, Fangxin Chen, Miao Yang, Linxiang Huang, Zhijiang Du, Lining Sun and Wei Dong
Sensors 2018, 18(7), 2057; https://doi.org/10.3390/s18072057 - 27 Jun 2018
Cited by 11 | Viewed by 3495
Abstract
As one of the major methods for the diagnosis and treatment of cancers in their early stages, the percutaneous puncture technique has bright prospect in biopsy, ablation, proximity radiotherapy, and drug delivery. Recent years, researchers found the flexible needle cannot realize feedback control [...] Read more.
As one of the major methods for the diagnosis and treatment of cancers in their early stages, the percutaneous puncture technique has bright prospect in biopsy, ablation, proximity radiotherapy, and drug delivery. Recent years, researchers found the flexible needle cannot realize feedback control during the puncture surgeries only by path planning. To solve this problem, the flexible needle is tried to achieve real-time detection in this paper. Compared with previous methods, the strain gauges glued on the needle surface rather than the medical imaging techniques is used to collect the information to reconstruct the needle curve, which is benefit to integrate the whole system and obtain a more simple and accurate closed-loop control. This paper presented the math model of curve fitting and analyzed the causes of curve fitting errors. To verify the feasibility of this method, an experiment setup was built. Results from the experiments validated the solution in this paper to be effective. Full article
(This article belongs to the Special Issue Sensors for MEMS and Microsystems)
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17 pages, 3959 KiB  
Article
RES-Q-Trace: A Mobile CEAS-Based Demonstrator for Multi-Component Trace Gas Detection in the MIR
by Norbert Lang, Uwe Macherius, Henrik Zimmermann, Sven Glitsch, Mathias Wiese, Jürgen Röpcke and Jean-Pierre H. Van Helden
Sensors 2018, 18(7), 2058; https://doi.org/10.3390/s18072058 - 27 Jun 2018
Cited by 13 | Viewed by 4985
Abstract
Sensitive trace gas detection plays an important role in current challenges occurring in areas such as industrial process control and environmental monitoring. In particular, for medical breath analysis and for the detection of illegal substances, e.g., drugs and explosives, a selective and sensitive [...] Read more.
Sensitive trace gas detection plays an important role in current challenges occurring in areas such as industrial process control and environmental monitoring. In particular, for medical breath analysis and for the detection of illegal substances, e.g., drugs and explosives, a selective and sensitive detection of trace gases in real-time is required. We report on a compact and transportable multi-component system (RES-Q-Trace) for molecular trace gas detection based on cavity-enhanced techniques in the mid-infrared (MIR). The RES-Q-Trace system can operate four independent continuous wave quantum or interband cascade lasers each combined with an optical cavity. Twice the method of off-axis cavity-enhanced absorption spectroscopy (OA-CEAS) was used, twice the method of optical feedback cavity-enhanced absorption spectroscopy (OF-CEAS), respectively. Multi-functional software has been implemented (i) for the general system control; (ii) to drive the four different laser sources and (iii) to analyze the detector signals for concentration determination of several molecular species. For the validation of the versatility and the performance of the RES-Q-Trace instrument the species NO, N2O, CH4, C2H4 and C3H6O, with relevance in the fields of breath gas analysis and the detection of explosives have been monitored in the MIR with detection limits at atmospheric pressure in the ppb and ppt range. Full article
(This article belongs to the Special Issue Spectroscopy Based Sensors)
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17 pages, 4051 KiB  
Article
Wide-Band Color Imagery Restoration for RGB-NIR Single Sensor Images
by Xavier Soria, Angel D. Sappa and Riad I. Hammoud
Sensors 2018, 18(7), 2059; https://doi.org/10.3390/s18072059 - 27 Jun 2018
Cited by 20 | Viewed by 9274
Abstract
Multi-spectral RGB-NIR sensors have become ubiquitous in recent years. These sensors allow the visible and near-infrared spectral bands of a given scene to be captured at the same time. With such cameras, the acquired imagery has a compromised RGB color representation due to [...] Read more.
Multi-spectral RGB-NIR sensors have become ubiquitous in recent years. These sensors allow the visible and near-infrared spectral bands of a given scene to be captured at the same time. With such cameras, the acquired imagery has a compromised RGB color representation due to near-infrared bands (700–1100 nm) cross-talking with the visible bands (400–700 nm). This paper proposes two deep learning-based architectures to recover the full RGB color images, thus removing the NIR information from the visible bands. The proposed approaches directly restore the high-resolution RGB image by means of convolutional neural networks. They are evaluated with several outdoor images; both architectures reach a similar performance when evaluated in different scenarios and using different similarity metrics. Both of them improve the state of the art approaches. Full article
(This article belongs to the Special Issue Advances in Infrared Imaging: Sensing, Exploitation and Applications)
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28 pages, 432 KiB  
Review
Methods for the Real-World Evaluation of Fall Detection Technology: A Scoping Review
by Robert W. Broadley, Jochen Klenk, Sibylle B. Thies, Laurence P. J. Kenney and Malcolm H. Granat
Sensors 2018, 18(7), 2060; https://doi.org/10.3390/s18072060 - 27 Jun 2018
Cited by 49 | Viewed by 10524
Abstract
Falls in older adults present a major growing healthcare challenge and reliable detection of falls is crucial to minimise their consequences. The majority of development and testing has used laboratory simulations. As simulations do not cover the wide range of real-world scenarios performance [...] Read more.
Falls in older adults present a major growing healthcare challenge and reliable detection of falls is crucial to minimise their consequences. The majority of development and testing has used laboratory simulations. As simulations do not cover the wide range of real-world scenarios performance is poor when retested using real-world data. There has been a move from the use of simulated falls towards the use of real-world data. This review aims to assess the current methods for real-world evaluation of fall detection systems, identify their limitations and propose improved robust methods of evaluation. Twenty-two articles met the inclusion criteria and were assessed with regard to the composition of the datasets, data processing methods and the measures of performance. Real-world tests of fall detection technology are inherently challenging and it is clear the field is in its infancy. Most studies used small datasets and studies differed on how to quantify the ability to avoid false alarms and how to identify non-falls, a concept which is virtually impossible to define and standardise. To increase robustness and make results comparable, larger standardised datasets are needed containing data from a range of participant groups. Measures that depend on the definition and identification of non-falls should be avoided. Sensitivity, precision and F-measure emerged as the most suitable robust measures for evaluating the real-world performance of fall detection systems. Full article
(This article belongs to the Special Issue Data Analytics and Applications of the Wearable Sensors in Healthcare)
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16 pages, 3669 KiB  
Review
Probe of Alcohol Structures in the Gas and Liquid States Using C–H Stretching Raman Spectroscopy
by Yuanqin Yu, Wei Fan, Yuxi Wang, Xiaoguo Zhou, Jin Sun and Shilin Liu
Sensors 2018, 18(7), 2061; https://doi.org/10.3390/s18072061 - 28 Jun 2018
Cited by 8 | Viewed by 5205
Abstract
Vibrational spectroscopy is a powerful tool for probing molecular structures and dynamics since it offers a unique fingerprint that allows molecular identification. One of important aspects of applying vibrational spectroscopy is to develop the probes that can characterize the related properties of molecules [...] Read more.
Vibrational spectroscopy is a powerful tool for probing molecular structures and dynamics since it offers a unique fingerprint that allows molecular identification. One of important aspects of applying vibrational spectroscopy is to develop the probes that can characterize the related properties of molecules such as the conformation and intermolecular interaction. Many examples of vibrational probes have appeared in the literature, including the azide group (–N3), amide group (–CONH2), nitrile groups (–CN), hydroxyl group (–OH), –CH group and so on. Among these probes, the –CH group is an excellent one since it is ubiquitous in organic and biological molecules and the C–H stretching vibrational spectrum is extraordinarily sensitive to the local molecular environment. However, one challenge encountered in the application of C–H probes arises from the difficulty in the accurate assignment due to spectral congestion in the C–H stretching region. In this paper, recent advances in the complete assignment of C–H stretching spectra of aliphatic alcohols and the utility of C–H vibration as a probe of the conformation and weak intermolecular interaction are outlined. These results fully demonstrated the potential of the –CH chemical group as a molecular probe. Full article
(This article belongs to the Special Issue Spectroscopy Based Sensors)
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10 pages, 1630 KiB  
Article
Electrochemical Properties of Nitrate-Selective Electrodes: The Dependence of Resistance on the Solution Concentration
by Arina Ivanova and Konstantin Mikhelson
Sensors 2018, 18(7), 2062; https://doi.org/10.3390/s18072062 - 28 Jun 2018
Cited by 23 | Viewed by 5134
Abstract
The electrochemical properties of ion-exchanger-based solvent polymeric ion-selective electrodes (ISEs)—bulk and interfacial resistance, capacitance, and polarization under a galvanostatic current step—are studied, with a nitrate ISE based on tetradecylammonium nitrate (TDANO3) as a model system. The study is performed by chronopotentiometric [...] Read more.
The electrochemical properties of ion-exchanger-based solvent polymeric ion-selective electrodes (ISEs)—bulk and interfacial resistance, capacitance, and polarization under a galvanostatic current step—are studied, with a nitrate ISE based on tetradecylammonium nitrate (TDANO3) as a model system. The study is performed by chronopotentiometric and impedance measurements, and focuses on the dependence of the aforementioned properties on the concentration of NO3 anions in solution. The impacts from the bulk and the interfacial charge transfer to the overall membrane resistance are revealed. It is shown that the bulk resistance of the membranes decreases over an increase of NO3 concentration within the range of a Nernstian potentiometric response of the ISE. This fact, also reported earlier for K+- and Ca2+-selective ISEs, is not in line with current views of the mechanism of the ISE response, or of the role of ion exchange in particular. The origin of this effect is unclear. Estimates are made for the concentration of ionized species (NO3 and TDA+) and, respectively, for the TDANO3 association constant, as well as for the species diffusion coefficients in the membrane. Full article
(This article belongs to the Special Issue Potentiometric Chemical Sensors)
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18 pages, 3611 KiB  
Article
FluoSpec 2—An Automated Field Spectroscopy System to Monitor Canopy Solar-Induced Fluorescence
by Xi Yang, Hanyu Shi, Atticus Stovall, Kaiyu Guan, Guofang Miao, Yongguang Zhang, Yao Zhang, Xiangming Xiao, Youngryel Ryu and Jung-Eun Lee
Sensors 2018, 18(7), 2063; https://doi.org/10.3390/s18072063 - 28 Jun 2018
Cited by 88 | Viewed by 9422
Abstract
Accurate estimation of terrestrial photosynthesis has broad scientific and societal impacts. Measurements of photosynthesis can be used to assess plant health, quantify crop yield, and determine the largest CO2 flux in the carbon cycle. Long-term and continuous monitoring of vegetation optical properties [...] Read more.
Accurate estimation of terrestrial photosynthesis has broad scientific and societal impacts. Measurements of photosynthesis can be used to assess plant health, quantify crop yield, and determine the largest CO2 flux in the carbon cycle. Long-term and continuous monitoring of vegetation optical properties can provide valuable information about plant physiology. Recent developments of the remote sensing of solar-induced chlorophyll fluorescence (SIF) and vegetation spectroscopy have shown promising results in using this information to quantify plant photosynthetic activities and stresses at the ecosystem scale. However, there are few automated systems that allow for unattended observations over months to years. Here we present FluoSpec 2, an automated system for collecting irradiance and canopy radiance that has been deployed in various ecosystems in the past years. The instrument design, calibration, and tests are recorded in detail. We discuss the future directions of this field spectroscopy system. A network of SIF sensors, FluoNet, is established to measure the diurnal and seasonal variations of SIF in several ecosystems. Automated systems such as FluoSpec 2 can provide unique information on ecosystem functioning and provide important support to the satellite remote sensing of canopy photosynthesis. Full article
(This article belongs to the Special Issue Advanced Sensor Technologies for Crop Phenotyping Application)
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14 pages, 8307 KiB  
Article
A Promising Method of Typhoon Wave Retrieval from Gaofen-3 Synthetic Aperture Radar Image in VV-Polarization
by Qiyan Ji, Weizeng Shao, Yexin Sheng, Xinzhe Yuan, Jian Sun, Wei Zhou and Juncheng Zuo
Sensors 2018, 18(7), 2064; https://doi.org/10.3390/s18072064 - 28 Jun 2018
Cited by 13 | Viewed by 7159
Abstract
The motivation of this work is to explore the possibility of typhoon wave retrieval (the main parameter is significant wave height (SWH)) for C-band Gaofen (GF-3) synthetic aperture radar (SAR) with a wide swath coverage (>400 km). We aim to establish an analysis [...] Read more.
The motivation of this work is to explore the possibility of typhoon wave retrieval (the main parameter is significant wave height (SWH)) for C-band Gaofen (GF-3) synthetic aperture radar (SAR) with a wide swath coverage (>400 km). We aim to establish an analysis of a typhoon wave in the subresolution-scale (approximately 20 × 20 km2) on GF-3 SAR through SAR-measured parameters, including a normalized radar cross section (NRCS) and variance of the normalized SAR image (herein called cvar), which are the basic variables in an empirical wave retrieval algorithm and are independent of visible wave streaks. Several typhoons around the China Seas were captured by Chinese GF-3 SAR in 2017; e.g., Noru, Doksuri, Talim and Hato. The wave fields simulated from the third-generation numerical wave model WAVEWATCH-III (WW3) are collocated with these images. In general, the distribution patterns of the typhoon waves from the WW3 model are consistent with wave fields from the European Centre for Medium-Range Weather Forecasts (ECMWF) at 0.125° grids, indicating that the simulation results from the WW3 model are suitable for our study. In addition to winds retrieved from GF-3 SAR images in vertical-horizontal (VH) polarization, the characteristics of the typhoon wave on vertical-vertical (VV) polarization GF-3 SAR images are studied. It is found that SWH has a linear relationship with NRCS and cvar, however, SWH fluctuates with wind speed at all incidence angles. Based on the analyzed results, we simply tune two empirical wave retrieval algorithms for GF-3 SAR in typhoons. Although the correlation (COR) reaches 0.5 taking account into the NRCS term, a more accurate retrieval algorithm, including more related terms, is anticipated for further development for GF-3 SAR and validated through more typhoon images. Full article
(This article belongs to the Special Issue First Experiences with Chinese Gaofen-3 SAR Sensor)
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10 pages, 2683 KiB  
Article
Enhanced Hydrogen Detection Based on Mg-Doped InN Epilayer
by Shibo Wang, Xinqiang Wang, Zhaoying Chen, Ping Wang, Qi Qi, Xiantong Zheng, Bowen Sheng, Huapeng Liu, Tao Wang, Xin Rong, Mo Li, Jian Zhang, Xuelin Yang, Fujun Xu and Bo Shen
Sensors 2018, 18(7), 2065; https://doi.org/10.3390/s18072065 - 28 Jun 2018
Cited by 2 | Viewed by 4639
Abstract
It is a fact that surface electron accumulation layer with sheet electron density in the magnitude of ~1013 cm−2 on InN, either as-grown or Mg-doped, makes InN an excellent candidate for sensing application. In this paper, the response of hydrogen sensors [...] Read more.
It is a fact that surface electron accumulation layer with sheet electron density in the magnitude of ~1013 cm−2 on InN, either as-grown or Mg-doped, makes InN an excellent candidate for sensing application. In this paper, the response of hydrogen sensors based on Mg-doped InN films (InN:Mg) grown by molecular beam epitaxy has been investigated. The sensor exhibits a resistance variation ratio of 16.8% with response/recovery times of less than 2 min under exposure to 2000 ppm H2/air at 125 °C, which is 60% higher in the magnitude of response than the one based on the as-grown InN film. Hall-effect measurement shows that the InN:Mg with suitable Mg doping level exhibits larger sheet resistance, which accords with buried p-type conduction in the InN bulk. This work shows the advantage of InN:Mg and signifies its potential for sensing application. Full article
(This article belongs to the Special Issue Functional Materials for the Applications of Advanced Gas Sensors)
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20 pages, 7042 KiB  
Article
FaceLooks: A Smart Headband for Signaling Face-to-Face Behavior
by Taku Hachisu, Yadong Pan, Soichiro Matsuda, Baptiste Bourreau and Kenji Suzuki
Sensors 2018, 18(7), 2066; https://doi.org/10.3390/s18072066 - 28 Jun 2018
Cited by 13 | Viewed by 7090
Abstract
Eye-to-eye contact and facial expressions are key communicators, yet there has been little done to evaluate the basic properties of face-to-face; mutual head orientation behaviors. This may be because there is no practical device available to measure the behavior. This paper presents a [...] Read more.
Eye-to-eye contact and facial expressions are key communicators, yet there has been little done to evaluate the basic properties of face-to-face; mutual head orientation behaviors. This may be because there is no practical device available to measure the behavior. This paper presents a novel headband-type wearable device called FaceLooks, used for measuring the time of the face-to-face state with identity of the partner, using an infrared emitter and receiver. It can also be used for behavioral healthcare applications, such as for children with developmental disorders who exhibit difficulties with the behavior, by providing awareness through the visual feedback from the partner’s device. Two laboratory experiments showed the device’s detection range and response time, tested with a pair of dummy heads. Another laboratory experiment was done with human participants with gaze trackers and showed the device’s substantial agreement with a human observer. We then conducted two field studies involving children with intellectual disabilities and/or autism spectrum disorders. The first study showed that the devices could be used in the school setting, observing the children did not remove the devices. The second study showed that the durations of children’s face-to-face behavior could be increased under a visual feedback condition. The device shows its potential to be used in therapy and experimental fields because of its wearability and its ability to quantify and shape face-to-face behavior. Full article
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18 pages, 5022 KiB  
Article
Design and Evaluation of FBG-Based Tension Sensor in Laparoscope Surgical Robots
by Renfeng Xue, Bingyin Ren, Jiaqing Huang, Zhiyuan Yan and Zhijiang Du
Sensors 2018, 18(7), 2067; https://doi.org/10.3390/s18072067 - 28 Jun 2018
Cited by 44 | Viewed by 6310
Abstract
Due to the narrow space and a harsh chemical environment in the sterilization processes for the end-effector of surgical robots, it is difficult to install and integrate suitable sensors for the purpose of effective and precise force control. This paper presents an innovative [...] Read more.
Due to the narrow space and a harsh chemical environment in the sterilization processes for the end-effector of surgical robots, it is difficult to install and integrate suitable sensors for the purpose of effective and precise force control. This paper presents an innovative tension sensor for estimation of grasping force in our laparoscope surgical robot. The proposed sensor measures the tension of cable using fiber gratings (FBGs) which are pasted in the grooves on the inclined cantilevers of the sensor. By exploiting the stain measurement characteristics of FBGs, the small deformation of the inclined cantilevers caused by the cable tension can be measured. The working principle and the sensor model are analyzed. Based on the sensor model, the dimensions of the sensor are designed and optimized. A dedicated experimental setup is established to calibrate and test the sensor. The results of experiments for estimation the grasping force validate the sensor. Full article
(This article belongs to the Special Issue Tactile Sensors and Applications)
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12 pages, 1586 KiB  
Article
Threshold-Based Noise Detection and Reduction for Automatic Speech Recognition System in Human-Robot Interactions
by Sheng-Chieh Lee, Jhing-Fa Wang and Miao-Hia Chen
Sensors 2018, 18(7), 2068; https://doi.org/10.3390/s18072068 - 28 Jun 2018
Cited by 28 | Viewed by 5696
Abstract
This work develops a speech recognition system that uses two procedures of proposed noise detection and combined noise reduction. The system can be used in applications that require interactive robots to recognize the contents of speech that includes ambient noise. The system comprises [...] Read more.
This work develops a speech recognition system that uses two procedures of proposed noise detection and combined noise reduction. The system can be used in applications that require interactive robots to recognize the contents of speech that includes ambient noise. The system comprises two stages, which are the threshold-based noise detection and the noise reduction procedure. In the first stage, the proposed system automatically determines when to enhance the quality of speech based on the signal-to-noise ratio (SNR) values of the collected speech at all times. In the second stage, independent component analysis (ICA) and subspace speech enhancement (SSE) are employed for noise reduction. Experimental results reveal that the SNR values of the enhanced speech exceed those of the received noisy speech by approximately 20 dB to 25 dB. The noise reduction procedure improves the speech recognition rates by around 15% to 25%. The experimental results indicate that the proposed system can reduce the effect of noise in numerous noisy environments and improve the quality of speech for recognition purposes. Full article
(This article belongs to the Section Physical Sensors)
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19 pages, 2584 KiB  
Article
Square-Root Unscented Information Filter and Its Application in SINS/DVL Integrated Navigation
by Yan Guo, Meiping Wu, Kanghua Tang and Lu Zhang
Sensors 2018, 18(7), 2069; https://doi.org/10.3390/s18072069 - 28 Jun 2018
Cited by 17 | Viewed by 4282
Abstract
To address the problem of low accuracy for the regular filter algorithm in SINS/DVL integrated navigation, a square-root unscented information filter (SR-UIF) is presented in this paper. The proposed method: (1) adopts the state probability approximation instead of the Taylor model linearization in [...] Read more.
To address the problem of low accuracy for the regular filter algorithm in SINS/DVL integrated navigation, a square-root unscented information filter (SR-UIF) is presented in this paper. The proposed method: (1) adopts the state probability approximation instead of the Taylor model linearization in EKF algorithm to improve the accuracy of filtering estimation; (2) selects the most suitable parameter form at each filtering stage to simply the calculation complexity; (3) transforms the square root to ensure the symmetry and positive definiteness of the covariance matrix or information matrix, and then to enhance the stability of the filter. The simulation results indicate that the estimation accuracy of SR-UIF is higher than that of EKF, and similar to UKF; meanwhile the computational complexity of SR-UIF is lower than that of UKF. Full article
(This article belongs to the Collection Multi-Sensor Information Fusion)
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18 pages, 2095 KiB  
Article
On-Line Learning of Write Strategy for Ultra-Speed CD-RW Optical Recorder
by Leehter Yao and June-Kai Huang
Sensors 2018, 18(7), 2070; https://doi.org/10.3390/s18072070 - 28 Jun 2018
Cited by 1 | Viewed by 2629
Abstract
An on-line machine learning approach integrating the genetic algorithm (GA) and jitter measurements is proposed to learn the write strategy for the infrared diode of ultra-speed CD-RW recorders. The recording performance differs significantly for the CD-RW discs recorded for the first, second, or [...] Read more.
An on-line machine learning approach integrating the genetic algorithm (GA) and jitter measurements is proposed to learn the write strategy for the infrared diode of ultra-speed CD-RW recorders. The recording performance differs significantly for the CD-RW discs recorded for the first, second, or third time above. It is difficult to learn one set of write strategy parameters for the infrared diode of ultra-speed CD-RW recorder that satisfies the recording specifications for three different types of discs. The GA is applied to the on-line learning of write strategy. However, the convergence of GA stagnates at the final stage of the learning process due to the fact that the write strategy parameters learned by the GA need to satisfy the recording specifications for discs recorded for the first time, second time and third time within one recording trial. To overcome this difficulty, a scheme called dynamic parameter encoding is proposed. This scheme improves the GA convergence and explores the search space much better than the conventional GA. Full article
(This article belongs to the Section Intelligent Sensors)
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20 pages, 5986 KiB  
Article
UAV Visual and Laser Sensors Fusion for Detection and Positioning in Industrial Applications
by Edmundo Guerra, Rodrigo Munguía and Antoni Grau
Sensors 2018, 18(7), 2071; https://doi.org/10.3390/s18072071 - 28 Jun 2018
Cited by 15 | Viewed by 4890
Abstract
This work presents a solution to localize Unmanned Autonomous Vehicles with respect to pipes and other cylindrical elements found in inspection and maintenance tasks both in industrial and civilian infrastructures. The proposed system exploits the different features of vision and laser based sensors, [...] Read more.
This work presents a solution to localize Unmanned Autonomous Vehicles with respect to pipes and other cylindrical elements found in inspection and maintenance tasks both in industrial and civilian infrastructures. The proposed system exploits the different features of vision and laser based sensors, combining them to obtain accurate positioning of the robot with respect to the cylindrical structures. A probabilistic (RANSAC-based) procedure is used to segment possible cylinders found in the laser scans, and this is used as a seed to accurately determine the robot position through a computer vision system. The priors obtained from the laser scan registration help to solve the problem of determining the apparent contour of the cylinders. In turn this apparent contour is used in a degenerate quadratic conic estimation, enabling to visually estimate the pose of the cylinder. Full article
(This article belongs to the Special Issue I3S 2017 Selected Papers)
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25 pages, 4409 KiB  
Review
Ultraviolet Detectors Based on Wide Bandgap Semiconductor Nanowire: A Review
by Yanan Zou, Yue Zhang, Yongming Hu and Haoshuang Gu
Sensors 2018, 18(7), 2072; https://doi.org/10.3390/s18072072 - 28 Jun 2018
Cited by 289 | Viewed by 18319
Abstract
Ultraviolet (UV) detectors have attracted considerable attention in the past decade due to their extensive applications in the civil and military fields. Wide bandgap semiconductor-based UV detectors can detect UV light effectively, and nanowire structures can greatly improve the sensitivity of sensors with [...] Read more.
Ultraviolet (UV) detectors have attracted considerable attention in the past decade due to their extensive applications in the civil and military fields. Wide bandgap semiconductor-based UV detectors can detect UV light effectively, and nanowire structures can greatly improve the sensitivity of sensors with many quantum effects. This review summarizes recent developments in the classification and principles of UV detectors, i.e., photoconductive type, Schottky barrier type, metal-semiconductor-metal (MSM) type, p-n junction type and p-i-n junction type. The current state of the art in wide bandgap semiconductor materials suitable for producing nanowires for use in UV detectors, i.e., metallic oxide, III-nitride and SiC, during the last five years is also summarized. Finally, novel types of UV detectors such as hybrid nanostructure detectors, self-powered detectors and flexible detectors are introduced. Full article
(This article belongs to the Section Physical Sensors)
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18 pages, 6775 KiB  
Article
Application and Extension of Vertical Intensity Lower-Mode in Methods for Target Depth-Resolution with a Single-Vector Sensor
by Anbang Zhao, Xuejie Bi, Juan Hui, Caigao Zeng and Lin Ma
Sensors 2018, 18(7), 2073; https://doi.org/10.3390/s18072073 - 28 Jun 2018
Cited by 1 | Viewed by 2844
Abstract
In this paper, based on the reactive component of the vertical intensity, the method for target depth resolution has been improved. In the previous existing research results, using the reactive component of vertical intensity, the research objects for target depth resolution in shallow [...] Read more.
In this paper, based on the reactive component of the vertical intensity, the method for target depth resolution has been improved. In the previous existing research results, using the reactive component of vertical intensity, the research objects for target depth resolution in shallow water, can only be the targets whose frequencies can only excite the first two normal modes, and the depth of targets whose frequencies excite more than two normal modes cannot be correctly identified. The basic idea of the improved method is to classify targets on the foundation of the lower-mode correlation quantity of the vertical intensity. Based on the improved method, we can realize depth resolution of the targets whose frequency can excite the first three normal modes so as to effectively expand the working band useful for target depth resolution. Finally, we can realize the three-dimensional target depth resolution so as to distinguish the aerial, surface and underwater targets. The feasibility of the algorithm is verified by simulation and experimental data processing. Full article
(This article belongs to the Section Physical Sensors)
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41 pages, 8087 KiB  
Review
A Review of Emotion Recognition Using Physiological Signals
by Lin Shu, Jinyan Xie, Mingyue Yang, Ziyi Li, Zhenqi Li, Dan Liao, Xiangmin Xu and Xinyi Yang
Sensors 2018, 18(7), 2074; https://doi.org/10.3390/s18072074 - 28 Jun 2018
Cited by 702 | Viewed by 40433
Abstract
Emotion recognition based on physiological signals has been a hot topic and applied in many areas such as safe driving, health care and social security. In this paper, we present a comprehensive review on physiological signal-based emotion recognition, including emotion models, emotion elicitation [...] Read more.
Emotion recognition based on physiological signals has been a hot topic and applied in many areas such as safe driving, health care and social security. In this paper, we present a comprehensive review on physiological signal-based emotion recognition, including emotion models, emotion elicitation methods, the published emotional physiological datasets, features, classifiers, and the whole framework for emotion recognition based on the physiological signals. A summary and comparation among the recent studies has been conducted, which reveals the current existing problems and the future work has been discussed. Full article
(This article belongs to the Special Issue New Trends in Psychophysiology and Mental Health)
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23 pages, 5901 KiB  
Article
Enhancing Received Signal Strength-Based Localization through Coverage Hole Detection and Recovery
by Shuangjiao Zhai, Zhanyong Tang, Dajin Wang, Qingpei Li, Zhanglei Li, Xiaojiang Chen, Dingyi Fang, Feng Chen and Zheng Wang
Sensors 2018, 18(7), 2075; https://doi.org/10.3390/s18072075 - 28 Jun 2018
Cited by 11 | Viewed by 3882
Abstract
In wireless sensor networks (WSNs), Radio Signal Strength Indicator (RSSI)-based localization techniques have been widely used in various applications, such as intrusion detection, battlefield surveillance, and animal monitoring. One fundamental performance measure in those applications is the sensing coverage of WSNs. Insufficient coverage [...] Read more.
In wireless sensor networks (WSNs), Radio Signal Strength Indicator (RSSI)-based localization techniques have been widely used in various applications, such as intrusion detection, battlefield surveillance, and animal monitoring. One fundamental performance measure in those applications is the sensing coverage of WSNs. Insufficient coverage will significantly reduce the effectiveness of the applications. However, most existing studies on coverage assume that the sensing range of a sensor node is a disk, and the disk coverage model is too simplistic for many localization techniques. Moreover, there are some localization techniques of WSNs whose coverage model is non-disk, such as RSSI-based localization techniques. In this paper, we focus on detecting and recovering coverage holes of WSNs to enhance RSSI-based localization techniques whose coverage model is an ellipse. We propose an algorithm inspired by Voronoi tessellation and Delaunay triangulation to detect and recover coverage holes. Simulation results show that our algorithm can recover all holes and can reach any set coverage rate, up to 100% coverage. Full article
(This article belongs to the Section Sensor Networks)
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37 pages, 2886 KiB  
Review
Multifunction RF Systems for Naval Platforms
by Peter W. Moo and David J. DiFilippo
Sensors 2018, 18(7), 2076; https://doi.org/10.3390/s18072076 - 28 Jun 2018
Cited by 34 | Viewed by 12502
Abstract
The evolving role of modern navies has required increasingly higher levels of capability in the Radio Frequency (RF) shipboard systems that provide radar, communications, Electronic Attack (EA) and Electronic Support (ES) functions. The result has been a proliferation of topside antennas and associated [...] Read more.
The evolving role of modern navies has required increasingly higher levels of capability in the Radio Frequency (RF) shipboard systems that provide radar, communications, Electronic Attack (EA) and Electronic Support (ES) functions. The result has been a proliferation of topside antennas and associated hardware on naval vessels. The notion of MultiFunction RF (MFRF) systems has drawn considerable interest as an approach to reversing this trend. In a MFRF system, RF functions are consolidated within a shared set of electronics and antenna apertures that utilize Active Electronically Scanned Array (AESA) technology. This paper highlights a number of issues to be considered in the design and implementation of a naval MFRF system. Specifically, the key requirements of the RF functions of interest are first reviewed, and MFRF system design trade-offs resulting from costs and/or performance limitations in existing hardware technology are then discussed. It is found that limitations in hardware technology constrain the implementation of practical MFRF systems. MFRF system prototype development programs that have been conducted in other countries are described. MFRF resource allocation management is identified as an important future research topic. Full article
(This article belongs to the Section Physical Sensors)
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16 pages, 2123 KiB  
Article
Potential of Visible and Near-Infrared Hyperspectral Imaging for Detection of Diaphania pyloalis Larvae and Damage on Mulberry Leaves
by Lingxia Huang, Liang Yang, Liuwei Meng, Jingyu Wang, Shaojia Li, Xiaping Fu, Xiaoqiang Du and Di Wu
Sensors 2018, 18(7), 2077; https://doi.org/10.3390/s18072077 - 28 Jun 2018
Cited by 12 | Viewed by 3967
Abstract
Mulberry trees are an important crop for sericulture. Pests can affect the yield and quality of mulberry leaves. This study aims to develop a hyperspectral imaging system in visible and near-infrared (NIR) region (400–1700 nm) for the rapid identification of Diaphania pyloalis larvae [...] Read more.
Mulberry trees are an important crop for sericulture. Pests can affect the yield and quality of mulberry leaves. This study aims to develop a hyperspectral imaging system in visible and near-infrared (NIR) region (400–1700 nm) for the rapid identification of Diaphania pyloalis larvae and its damage. The extracted spectra of five region of interests (ROI), namely leaf vein, healthy mesophyll, slight damage, serious damage, and Diaphania pyloalis larva at 400–1000 nm (visible range) and 900–1700 nm (NIR range), were used to establish a partial least squares discriminant analysis (PLS-DA) and least-squares support vector machines (LS-SVM) models. Successive projections algorithm (SPA), uninformation variable elimination (UVE), UVE-SPA, and competitive adaptive reweighted sampling were used for variable selection. The best models in distinguishing between leaf vein, healthy mesophyll, slight damage and serious damage, leaf vein, healthy mesophyll, and larva, slight damage, serious damage, and larva were all the SPA-LS-SVM models, based on the NIR range data, and their correct rate of prediction (CRP) were all 100.00%. The best model for the identification of all five ROIs was the UVE-SPA-LS-SVM model, based on visible range data, which had the CRP value of 97.30%. In summary, visible and near infrared hyperspectral imaging could distinguish Diaphania pyloalis larvae and their damage from leaf vein and healthy mesophyll in a rapid and non-destructive way. Full article
(This article belongs to the Section Physical Sensors)
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24 pages, 5660 KiB  
Article
STVF: Spatial-Temporal Variational Filtering for Localization in Underwater Acoustic Sensor Networks
by Keyong Hu, Zhongwei Sun, Hanjiang Luo, Wei Zhou and Zhongwen Guo
Sensors 2018, 18(7), 2078; https://doi.org/10.3390/s18072078 - 28 Jun 2018
Cited by 9 | Viewed by 3206
Abstract
Localization is one of the critical services in Underwater Acoustic Sensor Networks (UASNs). Due to harsh underwater environments, the nodes often move with currents continuously. Consequently, the acoustic signals usually propagate with varying speeds in non-straight lines and the noise levels change frequently [...] Read more.
Localization is one of the critical services in Underwater Acoustic Sensor Networks (UASNs). Due to harsh underwater environments, the nodes often move with currents continuously. Consequently, the acoustic signals usually propagate with varying speeds in non-straight lines and the noise levels change frequently with the motion of the nodes. These limitations pose huge challenges for localization in UASNs. In this paper, we propose a novel localization method based on a variational filtering technique, in which the spatial correlation and temporal dependency information are utilized to improve localization performance. In the method, a state evolution model is employed to characterize the mobility pattern of the nodes and capture the uncertainty of the location transition. Then, a measurement model is used to reflect the relation between the measurements and the locations considering the dynamics of the acoustic speed and range noise. After that, a variational filtering scheme is adopted to determine the nodes’ locations, which consists of two phases: variational prediction and update. In the former phase, the coarse estimation of each node’ location is computed based on its previous location; in the latter phase, the coarse location is optimized by incorporating the measurements from the reference nodes as precisely as possible. At last, an iterative localization scheme is applied, in which a node labels itself as a reference node if the confidence of its location estimation is higher than the predefined threshold. We conducted extensive simulations under different parameter settings, and the results indicate that the proposed method has better localization accuracy compared to a typical SLMP algorithm while maintaining relatively high localization coverage. Moreover, spatial–temporal variational filtering (STVF) is more robust to the change of the parameter settings compared to SLMP. Full article
(This article belongs to the Section Sensor Networks)
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13 pages, 2538 KiB  
Technical Note
Design and Test of a New Inductive Force Sensor
by Robert Bram Giesberts, Victor IJzebrand Sluiter and Gijsbertus Jacob Verkerke
Sensors 2018, 18(7), 2079; https://doi.org/10.3390/s18072079 - 28 Jun 2018
Cited by 18 | Viewed by 4321
Abstract
The currently accepted interval of weekly cast changes in the treatment of clubfeet seems unsubstantiated. A force sensor is needed to determine the adaptation rate of a clubfoot to establish what cast change interval would be most effective and efficient. We developed a [...] Read more.
The currently accepted interval of weekly cast changes in the treatment of clubfeet seems unsubstantiated. A force sensor is needed to determine the adaptation rate of a clubfoot to establish what cast change interval would be most effective and efficient. We developed a force sensor based on the principle that the resonance frequency of an LC-tank changes when a metal target is brought in close proximity. A thin rubber ring between the LC-tank and the metal target transformed this proximity sensor into a force sensor. With a static load test and an incremental load test, the performance of the constructed force sensors was characterized. The custom-made sensor showed excellent sensitivity ((1.7±0.8×105) counts/N), resolution ((0.15±0.06) mN), and accuracy ((3.5±3.0) %) for the application. The observed drift was (2.1±0.7) %/log10(h), which is lower than other thin force sensors. Preliminary results of measurements in the treatment of Dupuytren fingers and clubfeet show good functioning for long-term force measurements. Full article
(This article belongs to the Section Physical Sensors)
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27 pages, 6021 KiB  
Article
Robust Face Recognition Using the Deep C2D-CNN Model Based on Decision-Level Fusion
by Jing Li, Tao Qiu, Chang Wen, Kai Xie and Fang-Qing Wen
Sensors 2018, 18(7), 2080; https://doi.org/10.3390/s18072080 - 28 Jun 2018
Cited by 66 | Viewed by 10205
Abstract
Given that facial features contain a wide range of identification information and cannot be completely represented by a single feature, the fusion of multiple features is particularly significant for achieving a robust face recognition performance, especially when there is a big difference between [...] Read more.
Given that facial features contain a wide range of identification information and cannot be completely represented by a single feature, the fusion of multiple features is particularly significant for achieving a robust face recognition performance, especially when there is a big difference between the test sets and the training sets. This has been proven in both traditional and deep learning approaches. In this work, we proposed a novel method named C2D-CNN (color 2-dimensional principal component analysis (2DPCA)-convolutional neural network). C2D-CNN combines the features learnt from the original pixels with the image representation learnt by CNN, and then makes decision-level fusion, which can significantly improve the performance of face recognition. Furthermore, a new CNN model is proposed: firstly, we introduce a normalization layer in CNN to speed up the network convergence and shorten the training time. Secondly, the layered activation function is introduced to make the activation function adaptive to the normalized data. Finally, probabilistic max-pooling is applied so that the feature information is preserved to the maximum extent while maintaining feature invariance. Experimental results show that compared with the state-of-the-art method, our method shows better performance and solves low recognition accuracy caused by the difference between test and training datasets. Full article
(This article belongs to the Special Issue Artificial Intelligence and Machine Learning in Sensors Networks)
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19 pages, 3421 KiB  
Article
An Optimization-Based Initial Alignment and Calibration Algorithm of Land-Vehicle SINS In-Motion
by Kang Gao, Shunqing Ren, Xijun Chen and Zhenhuan Wang
Sensors 2018, 18(7), 2081; https://doi.org/10.3390/s18072081 - 28 Jun 2018
Cited by 10 | Viewed by 3990
Abstract
For a running freely land-vehicle strapdown inertial navigation system (SINS), the problems of self-calibration and attitude alignment need to be solved simultaneously. This paper proposes a complete alignment algorithm for the land vehicle navigation using Inertial Measurement Units (IMUs) and an odometer. A [...] Read more.
For a running freely land-vehicle strapdown inertial navigation system (SINS), the problems of self-calibration and attitude alignment need to be solved simultaneously. This paper proposes a complete alignment algorithm for the land vehicle navigation using Inertial Measurement Units (IMUs) and an odometer. A self-calibration algorithm is proposed based on the global observability analysis to calibrate the odometer scale factor and IMU misalignment angle, and the initial alignment and calibration method based on optimal algorithm is established to estimate the attitude and other system parameters. This new algorithm has the capability of self-initialization and calibration without any prior attitude and sensor noise information. Computer simulation results show that the performance of the proposed algorithm is superior to the extended Kalman filter (EKF) method during the oscillating attitude motions, and the vehicle test validates its advantages. Full article
(This article belongs to the Special Issue Inertial Sensors and Systems 2018)
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24 pages, 6577 KiB  
Article
Recent Surface Water Extent of Lake Chad from Multispectral Sensors and GRACE
by Willibroad Gabila Buma, Sang-Il Lee and Jae Young Seo
Sensors 2018, 18(7), 2082; https://doi.org/10.3390/s18072082 - 28 Jun 2018
Cited by 59 | Viewed by 7663
Abstract
Consistent observations of lakes and reservoirs that comprise the majority of surface freshwater globally are limited, especially in Africa where water bodies are exposed to unfavorable climatic conditions and human interactions. Publicly available satellite imagery has increased the ability to monitor water bodies [...] Read more.
Consistent observations of lakes and reservoirs that comprise the majority of surface freshwater globally are limited, especially in Africa where water bodies are exposed to unfavorable climatic conditions and human interactions. Publicly available satellite imagery has increased the ability to monitor water bodies of various sizes without much financial hassle. Landsat 7 and 8 images were used in this study to estimate area changes around Lake Chad. The Automated Water Extraction Index (AWEI), Normalized Difference Water Index (NDWI), Modified Normalized Difference Water Index (MNDWI) and Normalized Difference Vegetation Index (NDVI) were compared for the remote sensing retrieval process of surface water. Otsu threshold method was used to separate water from non-water features. With an overall accuracy of ~96% and an inter-rater agreement (kappa coefficient) of 0.91, the MNDWI was a better indicator for mapping recent area changes in Lake Chad and was used to estimate the lake’s area changes from 2003–2016. Extracted monthly areas showed an increasing trend and ranged between ~1242 km2 and 2231 km2 indicating high variability within the 13-year period, 2003–2016. In addition, we combined Landsat measurements with Total Water Storage Anomaly (TWSA) data from the Gravity Recovery and Climate Experiment (GRACE) satellites. This combination is well matched with our estimated surface area trends. This work not only demonstrates the importance of remote sensing in sparsely gauged developing countries, it also suggests the use of freely available high-quality imagery data to address existing lake crisis. Full article
(This article belongs to the Special Issue Spatial Analysis and Remote Sensing)
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23 pages, 2012 KiB  
Review
Proximal Optical Sensors for Nitrogen Management of Vegetable Crops: A Review
by Francisco M. Padilla, Marisa Gallardo, M. Teresa Peña-Fleitas, Romina De Souza and Rodney B. Thompson
Sensors 2018, 18(7), 2083; https://doi.org/10.3390/s18072083 - 28 Jun 2018
Cited by 153 | Viewed by 11514
Abstract
Optimal nitrogen (N) management is essential for profitable vegetable crop production and to minimize N losses to the environment that are a consequence of an excessive N supply. Proximal optical sensors placed in contact with or close to the crop can provide a [...] Read more.
Optimal nitrogen (N) management is essential for profitable vegetable crop production and to minimize N losses to the environment that are a consequence of an excessive N supply. Proximal optical sensors placed in contact with or close to the crop can provide a rapid assessment of a crop N status. Three types of proximal optical sensors (chlorophyll meters, canopy reflectance sensors, and fluorescence-based flavonols meters) for monitoring the crop N status of vegetable crops are reviewed, addressing practical caveats and sampling considerations and evaluating the practical use of these sensors for crop N management. Research over recent decades has shown strong relationships between optical sensor measurements, and different measures of crop N status and of yield of vegetable species. However, the availability of both: (a) Sufficiency values to assess crop N status and (b) algorithms to translate sensor measurements into N fertilizer recommendations are limited for vegetable crops. Optical sensors have potential for N management of vegetable crops. However, research should go beyond merely diagnosing crop N status. Research should now focus on the determination of practical fertilization recommendations. It is envisaged that the increasing environmental and societal pressure on sustainable crop N management will stimulate progress in this area. Full article
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14 pages, 7678 KiB  
Article
An Innovative Diagnostic Film for Structural Health Monitoring of Metallic and Composite Structures
by Dimitrios G. Bekas, Zahra Sharif-Khodaei and M.H. Ferri Aliabadi
Sensors 2018, 18(7), 2084; https://doi.org/10.3390/s18072084 - 29 Jun 2018
Cited by 59 | Viewed by 6624
Abstract
A novel lightweight diagnostic film with sensors/actuators and a multiple-path wiring option using inkjet printing was developed. The diagnostic film allows for systematic, accurate, and repeatable sensor placement. Furthermore, the film is highly flexible and adaptable for placement on complex configurations. The film [...] Read more.
A novel lightweight diagnostic film with sensors/actuators and a multiple-path wiring option using inkjet printing was developed. The diagnostic film allows for systematic, accurate, and repeatable sensor placement. Furthermore, the film is highly flexible and adaptable for placement on complex configurations. The film can be attached to the surface of the structure through a uniform secondary boundary procedure or embedded within the composite layup during curing. The surface-mounted film can simply be peeled off for repair or replacement without scratching or damaging the part. The film offers significant weight reduction compared to other available technologies. A set of extreme temperature, altitude, and vibration environment test profiles were carried out following the Radio Technical Commission for Aeronautics (RTCA) DO-160 document to assess the durability and performance of the diagnostic film for onboard application. The diagnostic film was shown to be durable and reliable in withstanding the variable operational and harsh environmental conditions of tests representing the conditions of regional aircraft. Full article
(This article belongs to the Special Issue Piezoelectric Transducers: Advances in Structural Health Monitoring)
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22 pages, 586 KiB  
Article
An Enhanced Paradigm for Cognitive Cooperation Networks: Two-to-One Energy and Spectrum Dual-Cooperation
by Zhihui Liu, Wenjun Xu, Junyi Wang, Tao Dong and Hongbing Qiu
Sensors 2018, 18(7), 2085; https://doi.org/10.3390/s18072085 - 29 Jun 2018
Viewed by 3349
Abstract
In this paper, two-to-one energy and spectrum dual-cooperation (ESDC) is investigated for cognitive cooperation networks. Specifically, the energy and spectrum of two primary users (PUs) are both transferred or authorized to one multi-antenna secondary user (SU) in exchange for its aid in the [...] Read more.
In this paper, two-to-one energy and spectrum dual-cooperation (ESDC) is investigated for cognitive cooperation networks. Specifically, the energy and spectrum of two primary users (PUs) are both transferred or authorized to one multi-antenna secondary user (SU) in exchange for its aid in the signal relaying to guarantee the successful data transmission, whilst the SU, which originally owns no spectrum access privilege and limited energy storage, is also able to concurrently transmit its own data through spatial multiplexing. Moreover, network-coding is also adopted to further compress the data size and hence reduce the power consumption at SU. The formulated problem for the aforementioned two-to-one ESDC model is non-convex and intractable to solve directly. To solve the problem effectively, the Lagrangian dual methods plus fixed-point iteration methods and semidefinite relation methods are employed, and the optimal solution could be achieved through iterative optimization. Simulation results show that, compared with the traditional spectrum-only cooperation, the proposed two-to-one ESDC paradigms can greatly improve the successful transmission probability for PUs and achievable transmission rate for SU. Meanwhile, the proposed two-to-one dual-cooperation modes are significantly superior to the one-to-one cooperation mode, in terms of spectrum efficiency and energy efficiency. Full article
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16 pages, 779 KiB  
Article
Adaptive Noise Reduction Algorithm to Improve R Peak Detection in ECG Measured by Capacitive ECG Sensors
by Minseok Seo, Minho Choi, Jun Seong Lee and Sang Woo Kim
Sensors 2018, 18(7), 2086; https://doi.org/10.3390/s18072086 - 29 Jun 2018
Cited by 11 | Viewed by 5480
Abstract
Electrocardiograms (ECGs) can be conveniently obtained using capacitive ECG sensors. However, motion noise in measured ECGs can degrade R peak detection. To reduce noise, properties of reference signal and ECG measured by the sensors are analyzed and a new method of active noise [...] Read more.
Electrocardiograms (ECGs) can be conveniently obtained using capacitive ECG sensors. However, motion noise in measured ECGs can degrade R peak detection. To reduce noise, properties of reference signal and ECG measured by the sensors are analyzed and a new method of active noise cancellation (ANC) is proposed in this study. In the proposed algorithm, the original ECG signal at QRS interval is regarded as impulsive noise because the adaptive filter updates its weight as if impulsive noise is added. As the proposed algorithm does not affect impulsive noise, the original signal is not reduced during ANC. Therefore, the proposed algorithm can conserve the power of the original signal within the QRS interval and reduce only the power of noise at other intervals. The proposed algorithm was verified through comparisons with recent research using data from both indoor and outdoor experiments. The proposed algorithm will benefit a noise reduction of noisy biomedical signal measured from sensors. Full article
(This article belongs to the Special Issue Sensors for Biosignal Processing)
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12 pages, 1765 KiB  
Article
Error Sources and Distinctness of Materials Parameters Obtained by THz-Time Domain Spectroscopy Using an Example of Oxidized Engine Oil
by Mario Méndez Aller, Ali Mazin Abdul-Munaim, Dennis G. Watson and Sascha Preu
Sensors 2018, 18(7), 2087; https://doi.org/10.3390/s18072087 - 29 Jun 2018
Cited by 11 | Viewed by 5165
Abstract
Gasoline engine oil (SAE 5W-20) was subjected to thermal oxidization (TO) for four periods of time (0 h, 48 h, 96 h and 144 h) and exposed to THz-time domain spectroscopy (TDS) measurement. Error contributions from various error sources, such as repeatability errors, [...] Read more.
Gasoline engine oil (SAE 5W-20) was subjected to thermal oxidization (TO) for four periods of time (0 h, 48 h, 96 h and 144 h) and exposed to THz-time domain spectroscopy (TDS) measurement. Error contributions from various error sources, such as repeatability errors, assembly errors of the probe volume and errors caused by the TDS system were evaluated with respect to discernibility and significance of measurement results. The most significant error source was due to modifications of the TDS setup, causing errors in the range of 0.13% of the refractive index for samples with a refractive index around 1.467 and a probe volume length between 5 and 15 mm at 1 THz. The absorption coefficient error was in the range of 8.49% for an absorption around 0.6 cm−1. While the average of measurements taken with different setup configurations did not yield significant differences for different TO times, a single, fixed setup would be able to discern all investigated oil species across the entire frequency range of 0.5–2.5 THz. The absorption coefficient measurement showed greater discernibility than the measurement of the refractive index. Full article
(This article belongs to the Special Issue THz Imaging Systems and Sensors)
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16 pages, 4155 KiB  
Article
Response Time to a Vibrotactile Stimulus Presented on the Foot at Rest and During Walking on Different Surfaces
by Landry Delphin Chapwouo Tchakouté, Louis Tremblay and Bob-Antoine J. Menelas
Sensors 2018, 18(7), 2088; https://doi.org/10.3390/s18072088 - 29 Jun 2018
Cited by 4 | Viewed by 4182
Abstract
This study investigates the simple reaction time (SRT) and response time (RT) to a vibrotactile stimulus presented on two body locations at the lower extremity of the foot on different types of surface during walking. We determined RTs while walking on Concrete, Foam, [...] Read more.
This study investigates the simple reaction time (SRT) and response time (RT) to a vibrotactile stimulus presented on two body locations at the lower extremity of the foot on different types of surface during walking. We determined RTs while walking on Concrete, Foam, Sand, and gravel surface. Also, for RT, we evaluated two vibrotactile stimulus (VS) locations on the lower extremity: the ankle (AL) and under the foot plantar (FP). A total of 21 young adult participants (n = 21), aged mean 24 ± 2.9 years, took part in a two-session experiment with two main conditions (at rest and while walking on four types of surface). The control session included 2016 repeated measures, with one-way and two-way ANOVA analyses. The findings have consistently revealed slowness of RT to VS, in particular on sand and gravel surface. In addition, we found that body location has a significant effect on RT in certain surfaces. These results showed that RTs increased with environment changes during the performance of dual tasks. Full article
(This article belongs to the Section Physical Sensors)
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23 pages, 5391 KiB  
Article
A Novel Approach for Mapping Wheat Areas Using High Resolution Sentinel-2 Images
by Ali Nasrallah, Nicolas Baghdadi, Mario Mhawej, Ghaleb Faour, Talal Darwish, Hatem Belhouchette and Salem Darwich
Sensors 2018, 18(7), 2089; https://doi.org/10.3390/s18072089 - 29 Jun 2018
Cited by 58 | Viewed by 8626
Abstract
Global wheat production reached 754.8 million tons in 2017, according to the FAO database. While wheat is considered as a staple food for many populations across the globe, mapping wheat could be an effective tool to achieve the SDG2 sustainable development goal—End Hunger [...] Read more.
Global wheat production reached 754.8 million tons in 2017, according to the FAO database. While wheat is considered as a staple food for many populations across the globe, mapping wheat could be an effective tool to achieve the SDG2 sustainable development goal—End Hunger and Secure Food Security. In Lebanon, this crop is supported financially, and sometimes technically, by the Lebanese government. However, there is a lack of statistical databases, at both national and regional scales, as well as critical information much needed in the subsidy and compensation system. In this context, this study proposes an innovative approach, named Simple and Effective Wheat Mapping Approach (SEWMA), to map the winter wheat areas grown in the Bekaa plain, the primary wheat production area in Lebanon, in the years of 2016 and 2017. The proposed methodology is a tree-like approach relying on the Normalized Difference Vegetation Index (NDVI) values of four-month period that coincides with several phenological stages of wheat (i.e., tillering, stem extension, heading, flowering and ripening). The usage of the freely available Sentinel-2 imageries, with a high spatial (10 m) and temporal (5 days) resolutions, was necessary, particularly due to the small sized and overlapped plots encountered in the study area. Concerning the wheat areas, results show that there was a decrease from 11,063 ± 1309 ha in 2016 to 7605 ± 1184 in 2017. When SEWMA was applied using 2016 ground truth data, the overall accuracy reached 87.0% on 2017 data, whereas, when implemented using 2017 ground truth data, the overall accuracy was 82.6% on 2016 data. The novelty resides in executing early classification output (up to six weeks before harvest) as well as distinguishing wheat from other winter cereal crops with similar NDVI yearly profiles (i.e., barley and triticale). SEWMA offers a simple, yet effective and budget-saving approach providing early-season classification information, very crucial to decision support systems and the Lebanese government concerning, but not limited to, food production, trade, management and agricultural financial support. Full article
(This article belongs to the Special Issue Advanced Sensor Technologies for Crop Phenotyping Application)
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25 pages, 4152 KiB  
Article
Automated Method for Discrimination of Arrhythmias Using Time, Frequency, and Nonlinear Features of Electrocardiogram Signals
by Shirin Hajeb-Mohammadalipour, Mohsen Ahmadi, Reza Shahghadami and Ki H. Chon
Sensors 2018, 18(7), 2090; https://doi.org/10.3390/s18072090 - 29 Jun 2018
Cited by 27 | Viewed by 6533
Abstract
We developed an automated approach to differentiate between different types of arrhythmic episodes in electrocardiogram (ECG) signals, because, in real-life scenarios, a software application does not know in advance the type of arrhythmia a patient experiences. Our approach has four main stages: (1) [...] Read more.
We developed an automated approach to differentiate between different types of arrhythmic episodes in electrocardiogram (ECG) signals, because, in real-life scenarios, a software application does not know in advance the type of arrhythmia a patient experiences. Our approach has four main stages: (1) Classification of ventricular fibrillation (VF) versus non-VF segments—including atrial fibrillation (AF), ventricular tachycardia (VT), normal sinus rhythm (NSR), and sinus arrhythmias, such as bigeminy, trigeminy, quadrigeminy, couplet, triplet—using four image-based phase plot features, one frequency domain feature, and the Shannon entropy index. (2) Classification of AF versus non-AF segments. (3) Premature ventricular contraction (PVC) detection on every non-AF segment, using a time domain feature, a frequency domain feature, and two features that characterize the nonlinearity of the data. (4) Determination of the PVC patterns, if present, to categorize distinct types of sinus arrhythmias and NSR. We used the Massachusetts Institute of Technology-Beth Israel Hospital (MIT-BIH) arrhythmia database, Creighton University’s VT arrhythmia database, the MIT-BIH atrial fibrillation database, and the MIT-BIH malignant ventricular arrhythmia database to test our algorithm. Binary decision tree (BDT) and support vector machine (SVM) classifiers were used in both stage 1 and stage 3. We also compared our proposed algorithm’s performance to other published algorithms. Our VF detection algorithm was accurate, as in balanced datasets (and unbalanced, in parentheses) it provided an accuracy of 95.1% (97.1%), sensitivity of 94.5% (91.1%), and specificity of 94.2% (98.2%). The AF detection was accurate, as the sensitivity and specificity in balanced datasets (and unbalanced, in parentheses) were found to be 97.8% (98.6%) and 97.21% (97.1%), respectively. Our PVC detection algorithm was also robust, as the accuracy, sensitivity, and specificity were found to be 99% (98.1%), 98.0% (96.2%), and 98.4% (99.4%), respectively, for balanced and (unbalanced) datasets. Full article
(This article belongs to the Special Issue Sensors for Biosignal Processing)
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22 pages, 14030 KiB  
Article
Utilization of Multisensor Data Fusion for Magnetic Nondestructive Evaluation of Defects in Steel Elements under Various Operation Strategies
by Grzegorz Psuj
Sensors 2018, 18(7), 2091; https://doi.org/10.3390/s18072091 - 29 Jun 2018
Cited by 13 | Viewed by 3851
Abstract
Increasing the number of inspection sources creates an opportunity to combine information in order to properly set the operation of the entire system, not only in terms of such factors as reliability, confidence, or accuracy, but inspection time as well. In this paper, [...] Read more.
Increasing the number of inspection sources creates an opportunity to combine information in order to properly set the operation of the entire system, not only in terms of such factors as reliability, confidence, or accuracy, but inspection time as well. In this paper, a magnetic sensor-array-based nondestructive system was applied to inspect defects inside circular-shaped steel elements. The experiments were carried out for various sensor network strategies, followed by the fusion of multisensor data for each case. In order to combine the measurements, first data registration and then four algorithms based on spatial and transformed representations of sensor signals were applied. In the case of spatial representation, the data were combined using an algorithm operating directly on input signals, allowing pooling of information. To build the transformed representation, a multiresolution analysis based on the Laplacian pyramid was used. Finally, the quality of the obtained results was assessed. The details of algorithms are given and the results are presented and discussed. It is shown that the application of data fusion rules for magnetic multisensor inspection systems can result in the growth of reliability of proper identification and classification of defects in steel elements depending on the utilized configuration of the sensor network. Full article
(This article belongs to the Section Physical Sensors)
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15 pages, 14200 KiB  
Article
Smart Sensing of Pavement Temperature Based on Low-Cost Sensors and V2I Communications
by Jorge Godoy, Rodolfo Haber, Juan Jesús Muñoz, Fernando Matía and Álvaro García
Sensors 2018, 18(7), 2092; https://doi.org/10.3390/s18072092 - 29 Jun 2018
Cited by 16 | Viewed by 6861
Abstract
Nowadays, the preservation, maintenance, rehabilitation, and improvement of road networks are key issues. Pavement condition is highly affected by environmental factors such as temperature and humidity, hence the importance of building databases enriched with real-time information from monitoring systems that enable the analysis [...] Read more.
Nowadays, the preservation, maintenance, rehabilitation, and improvement of road networks are key issues. Pavement condition is highly affected by environmental factors such as temperature and humidity, hence the importance of building databases enriched with real-time information from monitoring systems that enable the analysis and modeling of the road properties. Information and communication technologies, and specifically wireless sensor networks and computational intelligence methods, are enabling the design of new monitoring systems. The main goal of this work is the design of a pavement monitoring system for measuring temperature at internal layers. The proposed solution is based on low-cost and robust temperature sensors, vehicle-to-infrastructure communications, allowing one to transmit information directly from probes to a moving auscultation vehicle, and a neural network-based model for prediction pavement temperature. User requirements drive probes’ design to a modular device, with easy installation, low cost, and reduced energy consumption. Results of the test and validation experiments show both the benefits and viability of the proposed system, which reflect in an accuracy improvement and reduction in routine test duration. Finally, data collected over a year is applied to assess the performance of BELLS3 models and the suggested neural network for predicting pavement temperature. The dynamic behavior of the predicted temperature and the mean absolute error of the neural network-based model are better than the BELL3 model, demonstrating the suitability of the proposed pavement monitoring system. Full article
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24 pages, 11528 KiB  
Article
Passive Location Resource Scheduling Based on an Improved Genetic Algorithm
by Jianjun Jiang, Jing Zhang, Lijia Zhang, Xiaomin Ran and Yanqun Tang
Sensors 2018, 18(7), 2093; https://doi.org/10.3390/s18072093 - 29 Jun 2018
Cited by 14 | Viewed by 4577
Abstract
With the development of science and technology, modern communication scenarios have put forward higher requirements for passive location technology. However, current location systems still use manual scheduling methods and cannot meet the current mission-intensive and widely-distributed scenarios, resulting in inefficient task completion. To [...] Read more.
With the development of science and technology, modern communication scenarios have put forward higher requirements for passive location technology. However, current location systems still use manual scheduling methods and cannot meet the current mission-intensive and widely-distributed scenarios, resulting in inefficient task completion. To address this issue, this paper proposes a method called multi-objective, multi-constraint and improved genetic algorithm-based scheduling (MMIGAS), contributing a centralized combinatorial optimization model with multiple objectives and multiple constraints and conceiving an improved genetic algorithm. First, we establish a basic mathematical framework based on the structure of a passive location system. Furthermore, to balance performance with respect to multiple measures and avoid low efficiency, we propose a multi-objective optimal function including location accuracy, completion rate and resource utilization. Moreover, to enhance its practicability, we formulate multiple constraints for frequency, resource capability and task cooperation. For model solving, we propose an improved genetic algorithm with better convergence speed and global optimization ability, by introducing constraint-proof initialization, a penalty function and a modified genetic operator. Simulations indicate the good astringency, steady time complexity and satisfactory location accuracy of MMIGAS. Moreover, compared with manual scheduling, MMIGAS can improve the efficiency while maintaining high location precision. Full article
(This article belongs to the Collection Positioning and Navigation)
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18 pages, 7302 KiB  
Article
Debonding Detection in Hidden Frame Supported Glass Curtain Walls Using the Nonlinear Ultrasonic Modulation Method with Piezoceramic Transducers
by Xiaobin Hong, Yuan Liu, Yonghong Liufu and Peisong Lin
Sensors 2018, 18(7), 2094; https://doi.org/10.3390/s18072094 - 29 Jun 2018
Cited by 33 | Viewed by 5012
Abstract
Debonding defects are common and they are the main reason for the failure of hidden frame supported glass curtain walls, which are widely used as an external enclosure and decorative structure. In this paper, a debonding detection method for hidden frame supported glass [...] Read more.
Debonding defects are common and they are the main reason for the failure of hidden frame supported glass curtain walls, which are widely used as an external enclosure and decorative structure. In this paper, a debonding detection method for hidden frame supported glass curtain walls is developed based on nonlinear ultrasonic modulation and piezoceramic transducers. First, the excitation frequency was determined according to the response characteristics. Then, empirical mode decomposition (EMD) was applied to extract the feature components. After discrete Fourier transform (DFT), the nonlinear coefficients were calculated to evaluate the debonding defect. Finally, the experimental setup was established and a series of experiments were carried out to verify the feasibility and effectiveness of the nonlinear ultrasonic modulation method. The nonlinear harmonics detection method was also investigated and it was compared with the nonlinear ultrasonic modulation method. The detection effect at different temperatures and impact were studied. The results showed that the nonlinear coefficient increases with the debonding length. The mean squared error (MSE) of the nonlinear ultrasonic modulation method was improved by 41% compared with the nonlinear harmonics method. The nonlinear ultrasonic modulation method can successfully detect debonding defects in hidden frame supported glass curtain walls at different temperatures and impact. Full article
(This article belongs to the Special Issue Recent Advances of Piezoelectric Transducers and Applications)
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12 pages, 3822 KiB  
Article
An Accurate Bioimpedance Measurement System for Blood Pressure Monitoring
by Toan Huu Huynh, Roozbeh Jafari and Wan-Young Chung
Sensors 2018, 18(7), 2095; https://doi.org/10.3390/s18072095 - 29 Jun 2018
Cited by 64 | Viewed by 11664
Abstract
One potential method to estimate noninvasive cuffless blood pressure (BP) is through measurement of pulse wave velocity (PWV), which can be characterized by measuring the distance and the transit time of the pulse between two arterial sites. To obtain the pulse waveform, bioimpedance [...] Read more.
One potential method to estimate noninvasive cuffless blood pressure (BP) is through measurement of pulse wave velocity (PWV), which can be characterized by measuring the distance and the transit time of the pulse between two arterial sites. To obtain the pulse waveform, bioimpedance (BI) measurement is a promising approach because it continuously reflects the change in BP through the change in the arterial cross-sectional area. Several studies have investigated BI channels in a vertical direction with electrodes located along the wrist and the finger to calculate PWV and convert to BP; however, the measurement systems were relatively large in size. In order to reduce the total device size for use in a PWV-based BP smartwatch, this study proposes and examines a horizontal BI structure. The BI device is also designed to apply in a very small body area. Our proposed structure is based on two sets of four-electrode BI interface attached around the wrist. The effectiveness of our system and approach is evaluated on 15 human subjects; the PWV values are obtained with various distances between two BI channels to assess the efficacy. The results show that our BI system can monitor pulse rate efficiently in only a 0.5 × 1.75 cm2 area of the body. The correlation of pulse rate from the proposed design against the reference is 0.98 ± 0.07 (p < 0.001). Our structure yields higher detection ratios for PWV measurements of 99.0 ± 2.2%, 99.0 ± 2.1%, and 94.8 ± 3.7% at 1, 2, and 3 cm between two BI channels, respectively. The measured PWVs correlate well with the BP standard device at 0.81 ± 0.08 and 0.84 ± 0.07 with low root-mean-squared-errors at 7.47 ± 2.15 mmHg and 5.17 ± 1.81 mmHg for SBP and DBP, respectively. Our results inform future designs of smart watches capable of measuring blood pressure. Full article
(This article belongs to the Special Issue Selected Papers from IEEE ICASI 2018)
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27 pages, 12541 KiB  
Article
A Computational Model of Watermark Algorithmic Robustness Capable of Resisting Image Cropping for Remote Sensing Images
by Deyu Tong, Na Ren, Wenzhong Shi and Changqing Zhu
Sensors 2018, 18(7), 2096; https://doi.org/10.3390/s18072096 - 29 Jun 2018
Cited by 4 | Viewed by 3841
Abstract
Various watermarking algorithms have been studied to better enable the copyright protection of remote sensing images. The robustness of such algorithms against image cropping attacks has subsequently been verified mainly by various experiments. However, to date, the experimental results are subject to the [...] Read more.
Various watermarking algorithms have been studied to better enable the copyright protection of remote sensing images. The robustness of such algorithms against image cropping attacks has subsequently been verified mainly by various experiments. However, to date, the experimental results are subject to the differences in experimental factors and computational resource costs. Hence, the study presented in this paper proposes a robustness computation model of watermarking remote sensing images in terms of the image cropping attack. The robustness computation model consists of three parts: analysis principles, an evaluation index, and a computation method. The robustness analysis principles are provided based on the salient features of watermarking remote sensing images and attacking properties. A probability-based evaluation index is then defined to more comprehensively measure the robustness of different algorithms. The computation method developed in this study is based on permutations and the inclusion-exclusion principle to theoretically calculate robustness. The experiments conducted to verify the effectiveness of the computation model, revealed true closeness between both the calculated and experimental results. Finally, the relationships between the robustness and the different parameters used in the watermarking algorithms are investigated by using the proposed computation model. Full article
(This article belongs to the Special Issue Sensor Signal and Information Processing)
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17 pages, 3047 KiB  
Article
A Semi-Supervised Approach to Bearing Fault Diagnosis under Variable Conditions towards Imbalanced Unlabeled Data
by Xinan Chen, Zhipeng Wang, Zhe Zhang, Limin Jia and Yong Qin
Sensors 2018, 18(7), 2097; https://doi.org/10.3390/s18072097 - 29 Jun 2018
Cited by 37 | Viewed by 5222
Abstract
Fault diagnosis of rolling element bearings is an effective technology to ensure the steadiness of rotating machineries. Most of the existing fault diagnosis algorithms are supervised methods and generally require sufficient labeled data for training. However, the acquisition of labeled samples is often [...] Read more.
Fault diagnosis of rolling element bearings is an effective technology to ensure the steadiness of rotating machineries. Most of the existing fault diagnosis algorithms are supervised methods and generally require sufficient labeled data for training. However, the acquisition of labeled samples is often laborious and costly in practice, whereas there are abundant unlabeled samples which also imply health information of bearings. Thus, it is worthwhile to develop semi-supervised methods of fault diagnosis to make effective use of the plentiful unlabeled samples. Nevertheless, considering the normal data are much more than the faulty ones, the problem of imbalanced data exists among unlabeled samples for fault diagnosis. Besides, in practice, bearings often work under uncertain and variable operation conditions, which would also have negative influence on fault diagnosis. To solve these issues, a novel hybrid method for bearing fault diagnosis is proposed in this paper: (1) Inspired by visibility graph, a novel fault feature extraction method named visibility graph feature (VGF) is proposed. The obtained features by VGF are natively insensitive to variable conditions, which has been validated by a simulation experiment in this paper; (2) On basis of VGF, to deal with imbalanced unlabeled data, graph-based rebalance semi-supervised learning (GRSSL) for fault diagnosis is proposed. In GRSSL, a graph based on a weighted sparse adjacency matrix is constructed by the k-nearest neighbors and Gaussian Kernel weighting algorithm by means of the samples. Then, a bivariate cost function over classification and normalized label variable is built up to rebalance the importance of labels. Finally, the proposed VGF-GRSSL method was verified by data collected from Case Western Reserve University Bearing Data Center. The experiment results show that the proposed method of bearing fault diagnosis performs effectively to deal with the imbalanced unlabeled data under variable conditions. Full article
(This article belongs to the Special Issue Sensors for Fault Detection)
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8 pages, 2114 KiB  
Article
Improving the Performance of an SPR Biosensor Using Long-Range Surface Plasmon of Ga-Doped Zinc Oxide
by Banxian Ruan, Qi You, Jiaqi Zhu, Leiming Wu, Jun Guo, Xiaoyu Dai and Yuanjiang Xiang
Sensors 2018, 18(7), 2098; https://doi.org/10.3390/s18072098 - 30 Jun 2018
Cited by 37 | Viewed by 6292
Abstract
Transparent conducting oxides (TCOs) have appeared in the past few years as potential plasmonic materials for the development of optical devices in the near infrared regime (NIR). However, the performance of biosensors with TCOs has been limited in sensitivity and figure of merit [...] Read more.
Transparent conducting oxides (TCOs) have appeared in the past few years as potential plasmonic materials for the development of optical devices in the near infrared regime (NIR). However, the performance of biosensors with TCOs has been limited in sensitivity and figure of merit (FOM). To improve the performance of the biosensors with TCOs, a biosensor based on long-range surface plasmon with Ga-doped zinc oxide (GZO) is proposed. It is shown that a larger FOM with a 2~7 times enhancement compared to the traditional surface plasmon polaritons (SPPs) sensor and higher detection accuracy (DA) can be realized in our proposed sensor compared with the surface plasmon resonance (SPR) sensor with GZO. Therefore, this sensor can be used to detect biological activity or chemical reactions in the near infrared region. Full article
(This article belongs to the Special Issue Novel Sensors Based on Metal Oxide Films and Structures)
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25 pages, 23285 KiB  
Article
Multimed: An Integrated, Multi-Application Platform for the Real-Time Recording and Sub-Millisecond Processing of Biosignals
by Antoine Pirog, Yannick Bornat, Romain Perrier, Matthieu Raoux, Manon Jaffredo, Adam Quotb, Jochen Lang, Noëlle Lewis and Sylvie Renaud
Sensors 2018, 18(7), 2099; https://doi.org/10.3390/s18072099 - 30 Jun 2018
Cited by 8 | Viewed by 5097
Abstract
Enhanced understanding and control of electrophysiology mechanisms are increasingly being hailed as key knowledge in the fields of modern biology and medicine. As more and more excitable cell mechanics are being investigated and exploited, the need for flexible electrophysiology setups becomes apparent. With [...] Read more.
Enhanced understanding and control of electrophysiology mechanisms are increasingly being hailed as key knowledge in the fields of modern biology and medicine. As more and more excitable cell mechanics are being investigated and exploited, the need for flexible electrophysiology setups becomes apparent. With that aim, we designed Multimed, which is a versatile hardware platform for the real-time recording and processing of biosignals. Digital processing in Multimed is an arrangement of generic processing units from a custom library. These can freely be rearranged to match the needs of the application. Embedded onto a Field Programmable Gate Array (FPGA), these modules utilize full-hardware signal processing to lower processing latency. It achieves constant latency, and sub-millisecond processing and decision-making on 64 channels. The FPGA core processing unit makes Multimed suitable as either a reconfigurable electrophysiology system or a prototyping platform for VLSI implantable medical devices. It is specifically designed for open- and closed-loop experiments and provides consistent feedback rules, well within biological microseconds timeframes. This paper presents the specifications and architecture of the Multimed system, then details the biosignal processing algorithms and their digital implementation. Finally, three applications utilizing Multimed in neuroscience and diabetes research are described. They demonstrate the system’s configurability, its multi-channel, real-time processing, and its feedback control capabilities. Full article
(This article belongs to the Section Biosensors)
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19 pages, 3799 KiB  
Article
A Data Model for Using OpenStreetMap to Integrate Indoor and Outdoor Route Planning
by Zhiyong Wang and Lei Niu
Sensors 2018, 18(7), 2100; https://doi.org/10.3390/s18072100 - 30 Jun 2018
Cited by 35 | Viewed by 6922
Abstract
With a rapidly-growing volume of volunteered geographic information (VGI), there is an increasing trend towards using VGI to provide location-based services. In this study, we investigate using OpenStreetMap data to integrate indoor and outdoor route planning for pedestrians. To support indoor and outdoor [...] Read more.
With a rapidly-growing volume of volunteered geographic information (VGI), there is an increasing trend towards using VGI to provide location-based services. In this study, we investigate using OpenStreetMap data to integrate indoor and outdoor route planning for pedestrians. To support indoor and outdoor route planning, in this paper, we focus on the connections inside buildings and propose a data model, which uses OSM primitives (nodes, ways and relations) and tags to capture horizontal and vertical indoor components, as well as the connection between indoor and outdoor environments. A set of new approaches is developed to support indoor modeling and mapping. Based on the proposed data model, we present a workflow that enables automatic generation of a routing graph and provide an algorithm to calculate integrated indoor-outdoor routes. We applied our data model to a set of test cases. The application results demonstrate the capability of our data model in modeling built environments and its feasibility for the integration of indoor and outdoor navigation. Full article
(This article belongs to the Special Issue Crowd-Sensing and Remote Sensing Technologies for Smart Cities)
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9 pages, 2814 KiB  
Article
Smart Optical Catheters for Epidurals
by Benito Carotenuto, Armando Ricciardi, Alberto Micco, Ezio Amorizzo, Marco Mercieri, Antonello Cutolo and Andrea Cusano
Sensors 2018, 18(7), 2101; https://doi.org/10.3390/s18072101 - 30 Jun 2018
Cited by 28 | Viewed by 9920
Abstract
Placing the needle inside the epidural space for locoregional anesthesia is a challenging procedure, which even today is left to the expertise of the operator. Recently, we have demonstrated that the use of optically sensorized needles significantly improves the effectiveness of this procedure. [...] Read more.
Placing the needle inside the epidural space for locoregional anesthesia is a challenging procedure, which even today is left to the expertise of the operator. Recently, we have demonstrated that the use of optically sensorized needles significantly improves the effectiveness of this procedure. Here, we propose an optimized configuration, where the optical fiber strain sensor is directly integrated inside the epidural catheter. The new design allows the solving of the biocompatibility issues and increases the versatility of the former configuration. Through an in vivo study carried out on a porcine model, we confirm the reliability of our approach, which also opens the way to catheter monitoring during insertion inside biological spaces. Full article
(This article belongs to the Special Issue Fiber Optic Sensors for Smart Catheters)
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15 pages, 8210 KiB  
Article
A Conformal Driving Class IV Flextensional Transducer
by Tianfang Zhou, Yu Lan, Qicheng Zhang, Jingwen Yuan, Shichang Li and Wei Lu
Sensors 2018, 18(7), 2102; https://doi.org/10.3390/s18072102 - 30 Jun 2018
Cited by 25 | Viewed by 5418
Abstract
Class IV Flextensional Transducers (FTs) are the most popular among various FTs used as low-frequency and high power underwater acoustic sources. However, an undeniable fact exists in Class IV FTs is that the resonance frequency of breathing mode regulator used is fairly raised [...] Read more.
Class IV Flextensional Transducers (FTs) are the most popular among various FTs used as low-frequency and high power underwater acoustic sources. However, an undeniable fact exists in Class IV FTs is that the resonance frequency of breathing mode regulator used is fairly raised by its longitudinal driver stacks. In this research, a conformal driving Class IV FT in which the driver stacks are kept conformal with its oval shell was proposed aiming at the limitations of conventional driving Class IV FTs described above. The device exhibits competitive Transmitting Voltage Responses (TVRs) but much lower operation frequencies with respect to conventional driving Class IV FTs, through the designs of conformal and segmentally controlled driver stacks. Geometric parameters analysis was carried out extensively by Finite Element (FE) simulations for the design optimizations and then a conformal driving Class IV FT resonating at 510 Hz (45% approximately lower than that of conventional driving Class IV FT with the same shell geometry) was finalized. Subsequently the conformal driving Class IV was fabricated and tested in the anechoic tank experimentally. Good agreements of both FE predictions and experimental results demonstrate its low-frequency and small-size acoustic performance. Full article
(This article belongs to the Special Issue Underwater Sensing, Communication, Networking and Systems)
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7 pages, 3809 KiB  
Article
An Antenna Proximity Sensor for Mobile Terminals Using Reflection Coefficient
by Wonsub Lim, Dongil Yang and Youngoo Yang
Sensors 2018, 18(7), 2103; https://doi.org/10.3390/s18072103 - 30 Jun 2018
Cited by 7 | Viewed by 5350
Abstract
This paper presents a new antenna proximity sensor for mobile terminals based on the measured reflection coefficient using a bidirectional coupler which is positioned between the main antenna and the front-end module. Using the coupled forward and reverse long-term evolution signals by the [...] Read more.
This paper presents a new antenna proximity sensor for mobile terminals based on the measured reflection coefficient using a bidirectional coupler which is positioned between the main antenna and the front-end module. Using the coupled forward and reverse long-term evolution signals by the bidirectional coupler, the reflection coefficient looking into the antenna was calculated in the base-band processor. The measured reflection coefficients showed clear differences for both the types of objects, and the distances between the terminal and the objects. The proposed antenna proximity sensor showed a recognition distance that was approximately 5 mm longer than that of a conventional capacitive proximity sensor. Full article
(This article belongs to the Special Issue RF Technology for Sensor Applications)
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23 pages, 664 KiB  
Article
Energy Consumption Model for Sensor Nodes Based on LoRa and LoRaWAN
by Taoufik Bouguera, Jean-François Diouris, Jean-Jacques Chaillout, Randa Jaouadi and Guillaume Andrieux
Sensors 2018, 18(7), 2104; https://doi.org/10.3390/s18072104 - 30 Jun 2018
Cited by 316 | Viewed by 28202
Abstract
Energy efficiency is the key requirement to maximize sensor node lifetime. Sensor nodes are typically powered by a battery source that has finite lifetime. Most Internet of Thing (IoT) applications require sensor nodes to operate reliably for an extended period of time. To [...] Read more.
Energy efficiency is the key requirement to maximize sensor node lifetime. Sensor nodes are typically powered by a battery source that has finite lifetime. Most Internet of Thing (IoT) applications require sensor nodes to operate reliably for an extended period of time. To design an autonomous sensor node, it is important to model its energy consumption for different tasks. Each task consumes a power consumption amount for a period of time. To optimize the consumed energy of the sensor node and have long communication range, Low Power Wide Area Network technology is considered. This paper describes an energy consumption model based on LoRa and LoRaWAN, which allows estimating the consumed power of each sensor node element. The definition of the different node units is first introduced. Then, a full energy model for communicating sensors is proposed. This model can be used to compare different LoRaWAN modes to find the best sensor node design to achieve its energy autonomy. Full article
(This article belongs to the Section Sensor Networks)
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18 pages, 1265 KiB  
Article
Smooth 3D Dubins Curves Based Mobile Data Gathering in Sparse Underwater Sensor Networks
by Wenyu Cai and Meiyan Zhang
Sensors 2018, 18(7), 2105; https://doi.org/10.3390/s18072105 - 30 Jun 2018
Cited by 12 | Viewed by 4779
Abstract
Sensory data collection is one of the most important concerns in underwater sensor networks (USNs). Because full connectivity cannot be guaranteed, mobile data gathering with autonomous underwater vehicles (AUVs) is widely used in sparse three-dimensional (3D) USNs to solve energy-imbalance problems between different [...] Read more.
Sensory data collection is one of the most important concerns in underwater sensor networks (USNs). Because full connectivity cannot be guaranteed, mobile data gathering with autonomous underwater vehicles (AUVs) is widely used in sparse three-dimensional (3D) USNs to solve energy-imbalance problems between different sensor nodes. AUVs with relatively abundant energy and storage can collect sensory data from one sensor node to transmit to another node, so as to avoid energy-intensive multi-hop transmission. As a result, movement control strategy and data collecting path planning for AUVs are very crucial for the performance of data acquisition. This paper proposes a smooth 3D Dubins curves based mobile data gathering mechanism to overcome the kinematic nonholonomic constraints of AUVs. The objective of our proposed method is to collect sensory data along smooth 3D Dubins paths, which are interpolated by continuous Bezier curves in the Z-axis from 2D Dubins curves. Extensive simulation results verify that the proposed method has a more efficient performance in terms of path smoothness and energy consumption; thus it is very suitable for mobile data collection in 3D underwater sensor networks. Full article
(This article belongs to the Section Sensor Networks)
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22 pages, 10061 KiB  
Article
Pipeline Damage Detection Using Piezoceramic Transducers: Numerical Analyses with Experimental Validation
by Shi Yan, Ying Li, Shuai Zhang, Gangbing Song and Putian Zhao
Sensors 2018, 18(7), 2106; https://doi.org/10.3390/s18072106 - 30 Jun 2018
Cited by 31 | Viewed by 5111
Abstract
This paper aims to set up a finite element model using piezoelectric elements to realize pipeline structure damage identification analysis. Ultrasonic guided wave propagation characteristics and damage identification of pipeline structures are analyzed by the ABAQUS software. The pulse-echo method using an L(0, [...] Read more.
This paper aims to set up a finite element model using piezoelectric elements to realize pipeline structure damage identification analysis. Ultrasonic guided wave propagation characteristics and damage identification of pipeline structures are analyzed by the ABAQUS software. The pulse-echo method using an L(0, 2) mode impulse guided wave with a central frequency of 70 kHz is applied to evaluate different size circumferential cracks. An experiment was performed for the validation of the numerical analysis results. Both of the results show that the proposed FEM model with piezoelectric elements can efficiently reveal the dynamic behaviors, which can be used in much more precise numerical simulations than the equivalent dynamic displacement loading method. Full article
(This article belongs to the Section Intelligent Sensors)
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15 pages, 2918 KiB  
Article
Access Control Model Based on Time Synchronization Trust in Wireless Sensor Networks
by Zhaobin Liu, Qiang Ma, Wenzhi Liu, Victor S. Sheng, Liang Zhang and Gang Liu
Sensors 2018, 18(7), 2107; https://doi.org/10.3390/s18072107 - 30 Jun 2018
Cited by 5 | Viewed by 3933
Abstract
Internal reliability and external safety of Wireless Sensor Networks (WSN) data transmission have become increasingly outstanding issues with the wide applications of WSN. This paper proposes a new method for access control and mitigation of interfering noise in time synchronization environments. First, a [...] Read more.
Internal reliability and external safety of Wireless Sensor Networks (WSN) data transmission have become increasingly outstanding issues with the wide applications of WSN. This paper proposes a new method for access control and mitigation of interfering noise in time synchronization environments. First, a formal definition is given regarding the impact interference noise has on the clock skew and clock offset of each node. The degree of node interference behavior is estimated dynamically from the perspective of time-stamp changes caused by the interference noise. Secondly, a general access control model is proposed to resist invasion of noise interference. A prediction model is constructed using the Bayesian method for calculating the reliability of neighbor node behavior in the proposed model. Interference noise, which attacks the time synchronization, is regarded as the key factor for probability estimation of the reliability. The result of the calculations determines whether it is necessary to initiate synchronization filtering. Finally, a division of trust levels with bilinear definition is employed to lower interference noise and improve the quality of interference detection. Experimental results show that this model has advantages in system overhead, energy consumption and testing errors, compared to its counterparts. When the disturbance intensity of a WSN increases, the proposed optimized algorithm converges faster with a lower network communication load. Full article
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19 pages, 5505 KiB  
Article
A Novel Eddy Current Testing Error Compensation Technique Based on Mamdani-Type Fuzzy Coupled Differential and Absolute Probes
by Ahmed N. Abdalla, Kharudin Ali, Johnny K. S. Paw, Damhuji Rifai and Moneer A. Faraj
Sensors 2018, 18(7), 2108; https://doi.org/10.3390/s18072108 - 30 Jun 2018
Cited by 23 | Viewed by 4381
Abstract
Eddy current testing (ECT) is an accurate, widely used and well-understood inspection technique, particularly in the aircraft and nuclear industries. The coating thickness or lift-off will influence the measurement of defect depth on pipes or plates. It will be an uncertain decision condition [...] Read more.
Eddy current testing (ECT) is an accurate, widely used and well-understood inspection technique, particularly in the aircraft and nuclear industries. The coating thickness or lift-off will influence the measurement of defect depth on pipes or plates. It will be an uncertain decision condition whether the defects on a workpiece are cracks or scratches. This problem can lead to the occurrence of pipe leakages, besides causing the degradation of a company’s productivity and most importantly risking the safety of workers. In this paper, a novel eddy current testing error compensation technique based on Mamdani-type fuzzy coupled differential and absolute probes was proposed. The general descriptions of the proposed ECT technique include details of the system design, intelligent fuzzy logic design and Simulink block development design. The detailed description of the proposed probe selection, design and instrumentation of the error compensation of eddy current testing (ECECT) along with the absolute probe and differential probe relevant to the present research work are presented. The ECECT simulation and hardware design are proposed, using the fuzzy logic technique for the development of the new methodology. The depths of the defect coefficients of the probe’s lift-off caused by the coating thickness were measured by using a designed setup. In this result, the ECECT gives an optimum correction for the lift-off, in which the reduction of error is only within 0.1% of its all-out value. Finally, the ECECT is used to measure lift-off in a range of approximately 1 mm to 5 mm, and the performance of the proposed method in non-linear cracks is assessed. Full article
(This article belongs to the Section Physical Sensors)
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17 pages, 9454 KiB  
Article
Real Time Precise Relative Positioning with Moving Multiple Reference Receivers
by Hui Li, Shuang Gao, Liang Li, Chun Jia and Lin Zhao
Sensors 2018, 18(7), 2109; https://doi.org/10.3390/s18072109 - 30 Jun 2018
Cited by 6 | Viewed by 3899
Abstract
The stationary reference receiver with precisely known coordinates is difficult to establish in some special real-time relative positioning applications. To improve the relative position estimation accuracy and the reliability simultaneously for the RTK without a precisely known reference receiver, multiple receivers mounted on [...] Read more.
The stationary reference receiver with precisely known coordinates is difficult to establish in some special real-time relative positioning applications. To improve the relative position estimation accuracy and the reliability simultaneously for the RTK without a precisely known reference receiver, multiple receivers mounted on a moving platform are used as the base station. A code and phase measurement fusion model is proposed to reduce the communication burden and generate measurements at any virtual position where it is inconvenient to install the GPS receiver. To keep the integer property of the ambiguity of fused phase measurements, the RTK method with the moving reference receivers is proposed by implementing the integer ambiguity transformation and error absorption strategy based on the known geometry of multiple receivers. Static and kinematic experiments were carried out to evaluate the performance of the proposed relative positioning method. When compared with the single-receiver solution, static results have shown that the proposed method can improve position accuracy by 15.9% and 15.7% for the horizontal and the vertical component, respectively. The kinematic results have shown that the proposed method can achieve position accuracy enhancement by 26.9% for the vertical component. Full article
(This article belongs to the Section Remote Sensors)
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15 pages, 2418 KiB  
Article
LiReD: A Light-Weight Real-Time Fault Detection System for Edge Computing Using LSTM Recurrent Neural Networks
by Donghyun Park, Seulgi Kim, Yelin An and Jae-Yoon Jung
Sensors 2018, 18(7), 2110; https://doi.org/10.3390/s18072110 - 30 Jun 2018
Cited by 129 | Viewed by 12203
Abstract
Monitoring the status of the facilities and detecting any faults are considered an important technology in a smart factory. Although the faults of machine can be analyzed in real time using collected data, it requires a large amount of computing resources to handle [...] Read more.
Monitoring the status of the facilities and detecting any faults are considered an important technology in a smart factory. Although the faults of machine can be analyzed in real time using collected data, it requires a large amount of computing resources to handle the massive data. A cloud server can be used to analyze the collected data, but it is more efficient to adopt the edge computing concept that employs edge devices located close to the facilities. Edge devices can improve data processing and analysis speed and reduce network costs. In this paper, an edge device capable of collecting, processing, storing and analyzing data is constructed by using a single-board computer and a sensor. And, a fault detection model for machine is developed based on the long short-term memory (LSTM) recurrent neural networks. The proposed system called LiReD was implemented for an industrial robot manipulator and the LSTM-based fault detection model showed the best performance among six fault detection models. Full article
(This article belongs to the Special Issue Sensors for Fault Detection)
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22 pages, 16732 KiB  
Article
Experiments on MEMS Integration in 0.25 μm CMOS Process
by Piotr Michalik, Daniel Fernández, Matthias Wietstruck, Mehmet Kaynak and Jordi Madrenas
Sensors 2018, 18(7), 2111; https://doi.org/10.3390/s18072111 - 30 Jun 2018
Cited by 16 | Viewed by 7143
Abstract
In this paper, we share our practical experience gained during the development of CMOS-MEMS (Complementary Metal-Oxide Semiconductor Micro Electro Mechanical Systems) devices in IHP SG25 technology. The experimental prototyping process is illustrated with examples of three CMOS-MEMS chips and starts from rough process [...] Read more.
In this paper, we share our practical experience gained during the development of CMOS-MEMS (Complementary Metal-Oxide Semiconductor Micro Electro Mechanical Systems) devices in IHP SG25 technology. The experimental prototyping process is illustrated with examples of three CMOS-MEMS chips and starts from rough process exploration and characterization, followed by the definition of the useful MEMS design space to finally reach CMOS-MEMS devices with inertial mass up to 4.3 μg and resonance frequency down to 4.35 kHz. Furthermore, the presented design techniques help to avoid several structural and reliability issues such as layer delamination, device stiction, passivation fracture or device cracking due to stress. Full article
(This article belongs to the Special Issue Integrated MEMS Sensors for the IoT Era)
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18 pages, 772 KiB  
Article
Self-Controllable Secure Location Sharing for Trajectory-Based Message Delivery on Cloud-Assisted VANETs
by Youngho Park, Chul Sur, Si-Wan Noh and Kyung-Hyune Rhee
Sensors 2018, 18(7), 2112; https://doi.org/10.3390/s18072112 - 1 Jul 2018
Cited by 5 | Viewed by 4087
Abstract
In vehicular ad hoc networks, trajectory-based message delivery is a message forwarding strategy that utilizes the vehicle’s preferred driving routes information to deliver messages to the moving vehicles with the help of roadside units. For the purpose of supporting trajectory-based message delivery to [...] Read more.
In vehicular ad hoc networks, trajectory-based message delivery is a message forwarding strategy that utilizes the vehicle’s preferred driving routes information to deliver messages to the moving vehicles with the help of roadside units. For the purpose of supporting trajectory-based message delivery to a moving vehicle, the driving locations of the vehicle need to be shared with message senders. However, from a security perspective, vehicle users do not want their driving locations to be exposed to others except their desired senders for location privacy preservation. Therefore, in this paper, we propose a secure location-sharing system to allow a vehicle user (or driver) to share his/her driving trajectory information with roadside units authorized by the user. To design the proposed system, we put a central service manager which maintains vehicle trajectory data and acts as a broker between vehicles and roadside units to share the trajectory data on the cloud. Nevertheless, we make the trajectory data be hidden from not only unauthorized entities but also the service manager by taking advantage of a proxy re-encryption scheme. Hence, a vehicle can control that only the roadside units designated by the vehicle can access the trajectory data of the vehicle. Full article
(This article belongs to the Special Issue Security, Trust and Privacy for Sensor Networks)
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17 pages, 5604 KiB  
Article
A Semantic Labeling Approach for Accurate Weed Mapping of High Resolution UAV Imagery
by Huasheng Huang, Yubin Lan, Jizhong Deng, Aqing Yang, Xiaoling Deng, Lei Zhang and Sheng Wen
Sensors 2018, 18(7), 2113; https://doi.org/10.3390/s18072113 - 1 Jul 2018
Cited by 53 | Viewed by 5659
Abstract
Weed control is necessary in rice cultivation, but the excessive use of herbicide treatments has led to serious agronomic and environmental problems. Suitable site-specific weed management (SSWM) is a solution to address this problem while maintaining the rice production quality and quantity. In [...] Read more.
Weed control is necessary in rice cultivation, but the excessive use of herbicide treatments has led to serious agronomic and environmental problems. Suitable site-specific weed management (SSWM) is a solution to address this problem while maintaining the rice production quality and quantity. In the context of SSWM, an accurate weed distribution map is needed to provide decision support information for herbicide treatment. UAV remote sensing offers an efficient and effective platform to monitor weeds thanks to its high spatial resolution. In this work, UAV imagery was captured in a rice field located in South China. A semantic labeling approach was adopted to generate the weed distribution maps of the UAV imagery. An ImageNet pre-trained CNN with residual framework was adapted in a fully convolutional form, and transferred to our dataset by fine-tuning. Atrous convolution was applied to extend the field of view of convolutional filters; the performance of multi-scale processing was evaluated; and a fully connected conditional random field (CRF) was applied after the CNN to further refine the spatial details. Finally, our approach was compared with the pixel-based-SVM and the classical FCN-8s. Experimental results demonstrated that our approach achieved the best performance in terms of accuracy. Especially for the detection of small weed patches in the imagery, our approach significantly outperformed other methods. The mean intersection over union (mean IU), overall accuracy, and Kappa coefficient of our method were 0.7751, 0.9445, and 0.9128, respectively. The experiments showed that our approach has high potential in accurate weed mapping of UAV imagery. Full article
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19 pages, 7978 KiB  
Article
A Low-Cost INS-Integratable GNSS Ultra-Short Baseline Attitude Determination System
by Wenyi Li, Peirong Fan, Xiaowei Cui, Sihao Zhao, Tianyi Ma and Mingquan Lu
Sensors 2018, 18(7), 2114; https://doi.org/10.3390/s18072114 - 1 Jul 2018
Cited by 13 | Viewed by 5406
Abstract
Traditional attitude determination using global navigation satellite system (GNSS) carrier phases is mostly applied on geodetic-grade receivers with sufficient baseline length. However, for some special applications such as mobile communication base station smart antenna attitude determination, only low-cost receivers with ultra-short baselines can [...] Read more.
Traditional attitude determination using global navigation satellite system (GNSS) carrier phases is mostly applied on geodetic-grade receivers with sufficient baseline length. However, for some special applications such as mobile communication base station smart antenna attitude determination, only low-cost receivers with ultra-short baselines can be employed, and the environments are more challenging. When solving the ambiguity resolution (AR) problem with low-cost receivers, it is hard for the traditional methods in ambiguity domain to estimate float ambiguities accurately due to the large code pseudorange noises; thus, such systems fail to determine the correct ambiguities. Aiming at improving the AR success rate for ultra-short baselines attitude determination with low-cost receivers, we provide an objective function named Mean Square Residual (MSR) based on the geometrical relationship among the position spherical search space, the fractional carrier phases, and the possible ambiguities. The method can be calculated without code pseudoranges, and thus, can provide a higher AR success rate when using low-cost receivers. The corresponding analysis and acceptance test method are discussed in this contribution, and further, as an extension for more complicated urban dynamic applications, a GNSS/Inertial Navigation System (INS) integrated system is introduced. Several experiments have been conducted to verify performance. Full article
(This article belongs to the Collection Positioning and Navigation)
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13 pages, 5521 KiB  
Article
A Simplified Analysis Method for the Piezo Jet Dispenser with a Diamond Amplifier
by Guiling Deng, Na Wang, Can Zhou and Junhui Li
Sensors 2018, 18(7), 2115; https://doi.org/10.3390/s18072115 - 2 Jul 2018
Cited by 26 | Viewed by 4584
Abstract
Diamond amplifiers have been widely applied in Nano actuators and Robots. In order to study the dynamic characteristics of the diamond amplifier system which is used in the piezo jet dispenser, it is simplified as a spring-mass-damper system. The dynamic characteristics of the [...] Read more.
Diamond amplifiers have been widely applied in Nano actuators and Robots. In order to study the dynamic characteristics of the diamond amplifier system which is used in the piezo jet dispenser, it is simplified as a spring-mass-damper system. The dynamic characteristics of the jet dispenser system are analyzed with the simplified method. The characteristics are also tested. The results agree with the simulation, which proves the method is feasible. It will provide a simplified and intuitive representation of the movement of the amplifier, and also provide reliable simulation and experimental platforms for jet dispensing analysis. Full article
(This article belongs to the Special Issue Piezoelectric Micro- and Nano-Devices)
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15 pages, 4453 KiB  
Article
A Visual Cortex-Inspired Imaging-Sensor Architecture and Its Application in Real-Time Processing
by Hui Wei and Luping Wang
Sensors 2018, 18(7), 2116; https://doi.org/10.3390/s18072116 - 2 Jul 2018
Cited by 4 | Viewed by 3030
Abstract
For robots equipped with an advanced computer vision-based system, object recognition has stringent real-time requirements. When the environment becomes complicated and keeps changing, existing works (e.g., template-matching strategy and machine-learning strategy) are computationally expensive, compromising object recognition performance and even stability. In order [...] Read more.
For robots equipped with an advanced computer vision-based system, object recognition has stringent real-time requirements. When the environment becomes complicated and keeps changing, existing works (e.g., template-matching strategy and machine-learning strategy) are computationally expensive, compromising object recognition performance and even stability. In order to detect objects accurately, it is necessary to build an efficient imaging sensor architecture as the neural architecture. Inspired by the neural mechanism of primary visual cortex, this paper presents an efficient three-layer architecture and proposes an approach of constraint propagation examination to efficiently extract and process information (linear contour). Through applying this architecture in the preprocessing phase to extract lines, the running time of object detection is decreased dramatically because not only are all lines represented as very simple vectors, but also the number of lines is very limited. In terms of the second measure of improving efficiency, we apply a shape-based recognition method because it does not need any high-dimensional feature descriptor, long-term training, or time-expensive preprocessing. The final results perform well. It is proved that detection performance is good. The brain is the result of natural optimization, so we conclude that a visual cortex-inspired imaging sensor architecture can greatly improve the efficiency of information processing. Full article
(This article belongs to the Special Issue Bio-Inspiring Sensing)
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21 pages, 3445 KiB  
Article
Using Stigmergy to Distinguish Event-Specific Topics in Social Discussions
by Mario G. C. A. Cimino, Alessandro Lazzeri, Witold Pedrycz and Gigliola Vaglini
Sensors 2018, 18(7), 2117; https://doi.org/10.3390/s18072117 - 2 Jul 2018
Cited by 3 | Viewed by 3304
Abstract
In settings wherein discussion topics are not statically assigned, such as in microblogs, a need exists for identifying and separating topics of a given event. We approach the problem by using a novel type of similarity, calculated between the major terms used in [...] Read more.
In settings wherein discussion topics are not statically assigned, such as in microblogs, a need exists for identifying and separating topics of a given event. We approach the problem by using a novel type of similarity, calculated between the major terms used in posts. The occurrences of such terms are periodically sampled from the posts stream. The generated temporal series are processed by using marker-based stigmergy, i.e., a biologically-inspired mechanism performing scalar and temporal information aggregation. More precisely, each sample of the series generates a functional structure, called mark, associated with some concentration. The concentrations disperse in a scalar space and evaporate over time. Multiple deposits, when samples are close in terms of instants of time and values, aggregate in a trail and then persist longer than an isolated mark. To measure similarity between time series, the Jaccard’s similarity coefficient between trails is calculated. Discussion topics are generated by such similarity measure in a clustering process using Self-Organizing Maps, and are represented via a colored term cloud. Structural parameters are correctly tuned via an adaptation mechanism based on Differential Evolution. Experiments are completed for a real-world scenario, and the resulting similarity is compared with Dynamic Time Warping (DTW) similarity. Full article
(This article belongs to the Special Issue Social Sensing)
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12 pages, 3217 KiB  
Article
Dense RGB-D SLAM with Multiple Cameras
by Xinrui Meng, Wei Gao and Zhanyi Hu
Sensors 2018, 18(7), 2118; https://doi.org/10.3390/s18072118 - 2 Jul 2018
Cited by 18 | Viewed by 4953
Abstract
A multi-camera dense RGB-D SLAM (simultaneous localization and mapping) system has the potential both to speed up scene reconstruction and to improve localization accuracy, thanks to multiple mounted sensors and an enlarged effective field of view. To effectively tap the potential of the [...] Read more.
A multi-camera dense RGB-D SLAM (simultaneous localization and mapping) system has the potential both to speed up scene reconstruction and to improve localization accuracy, thanks to multiple mounted sensors and an enlarged effective field of view. To effectively tap the potential of the system, two issues must be understood: first, how to calibrate the system where sensors usually shares small or no common field of view to maximally increase the effective field of view; second, how to fuse the location information from different sensors. In this work, a three-Kinect system is reported. For system calibration, two kinds of calibration methods are proposed, one is suitable for system with inertial measurement unit (IMU) using an improved hand–eye calibration method, the other for pure visual SLAM without any other auxiliary sensors. In the RGB-D SLAM stage, we extend and improve a state-of-art single RGB-D SLAM method to multi-camera system. We track the multiple cameras’ poses independently and select the one with the pose minimal-error as the reference pose at each moment to correct other cameras’ poses. To optimize the initial estimated pose, we improve the deformation graph by adding an attribute of device number to distinguish surfels built by different cameras and do deformations according to the device number. We verify the accuracy of our extrinsic calibration methods in the experiment section and show the satisfactory reconstructed models by our multi-camera dense RGB-D SLAM. The RMSE (root-mean-square error) of the lengths measured in our reconstructed mode is 1.55 cm (similar to the state-of-art single camera RGB-D SLAM systems). Full article
(This article belongs to the Special Issue Sensors Signal Processing and Visual Computing)
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21 pages, 7359 KiB  
Article
A Kind of Joint Routing and Resource Allocation Scheme Based on Prioritized Memories-Deep Q Network for Cognitive Radio Ad Hoc Networks
by Yihang Du, Fan Zhang and Lei Xue
Sensors 2018, 18(7), 2119; https://doi.org/10.3390/s18072119 - 2 Jul 2018
Cited by 25 | Viewed by 3118
Abstract
Cognitive Radio (CR) is a promising technology to overcome spectrum scarcity, which currently faces lots of unsolved problems. One of the critical challenges for setting up such systems is how to coordinate multiple protocol layers such as routing and spectrum access in a [...] Read more.
Cognitive Radio (CR) is a promising technology to overcome spectrum scarcity, which currently faces lots of unsolved problems. One of the critical challenges for setting up such systems is how to coordinate multiple protocol layers such as routing and spectrum access in a partially observable environment. In this paper, a deep reinforcement learning approach is adopted for solving above problem. Firstly, for the purpose of compressing huge action space in the cross-layer design problem, a novel concept named responsibility rating is introduced to help decide the transmission power of every Secondary User (SU). In order to deal with problem of dimension curse while reducing replay memory, the Prioritized Memories Deep Q-Network (PM-DQN) is proposed. Furthermore, PM-DQN is applied to solve the joint routing and resource allocation problem in cognitive radio ad hoc network for minimizing the transmission delay and power consumption. Simulation results illustrates that our proposed algorithm can reduce the end-to-end delay, packet loss ratio and estimation error while achieving higher energy efficiency compared with traditional algorithm. Full article
(This article belongs to the Section Sensor Networks)
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51 pages, 15280 KiB  
Review
A Comparative Study of Four Kinds of Adaptive Decomposition Algorithms and Their Applications
by Tao Liu, Zhijun Luo, Jiahong Huang and Shaoze Yan
Sensors 2018, 18(7), 2120; https://doi.org/10.3390/s18072120 - 2 Jul 2018
Cited by 97 | Viewed by 7869
Abstract
The adaptive decomposition algorithm is a powerful tool for signal analysis, because it can decompose signals into several narrow-band components, which is advantageous to quantitatively evaluate signal characteristics. In this paper, we present a comparative study of four kinds of adaptive decomposition algorithms, [...] Read more.
The adaptive decomposition algorithm is a powerful tool for signal analysis, because it can decompose signals into several narrow-band components, which is advantageous to quantitatively evaluate signal characteristics. In this paper, we present a comparative study of four kinds of adaptive decomposition algorithms, including some algorithms deriving from empirical mode decomposition (EMD), empirical wavelet transform (EWT), variational mode decomposition (VMD) and Vold–Kalman filter order tracking (VKF_OT). Their principles, advantages and disadvantages, and improvements and applications to signal analyses in dynamic analysis of mechanical system and machinery fault diagnosis are showed. Examples are provided to illustrate important influence performance factors and improvements of these algorithms. Finally, we summarize applicable scopes, inapplicable scopes and some further works of these methods in respect of precise filters and rough filters. It is hoped that the paper can provide a valuable reference for application and improvement of these methods in signal processing. Full article
(This article belongs to the Section Physical Sensors)
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11 pages, 3663 KiB  
Article
Geometric Accuracy Evaluation of High-Resolution Satellite Images Based on Xianning Test Field
by Xiongwei Zheng, Qi Huang, Jingjing Wang, Taoyang Wang and Guo Zhang
Sensors 2018, 18(7), 2121; https://doi.org/10.3390/s18072121 - 2 Jul 2018
Cited by 10 | Viewed by 3925
Abstract
The evaluation of geometric accuracy of high-resolution satellite images (HRSIs) has been increasingly recognized in recent years. The traditional approach is to verify each satellite individually. It is difficult to directly compare the difference in their accuracy. In order to evaluate geometric accuracy [...] Read more.
The evaluation of geometric accuracy of high-resolution satellite images (HRSIs) has been increasingly recognized in recent years. The traditional approach is to verify each satellite individually. It is difficult to directly compare the difference in their accuracy. In order to evaluate geometric accuracy for multiple satellite images based on the same ground control benchmark, a reliable test field in Xianning (China) was utilized for geometric accuracy validation of HRSIs. Our research team has obtained multiple HRSIs in the Xianning test field, such as SPOT-6, Pleaides, ALOS, ZY-3 and TH-1. In addition, ground control points (GCPs) were acquired with GPS by field surveying, which were used to select the significant feature area on the images. We assess the orientation accuracy of the HRSIs with the single image and stereo models. Within this study, the geometrical performance of multiple HRSIs was analyzed in detail, and the results of orientation are shown and discussed. As a result, it is feasible and necessary to establish such a geometric verification field to evaluate the geometric quality of multiple HRSIs. Full article
(This article belongs to the Section Remote Sensors)
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13 pages, 4112 KiB  
Article
Characterization of the Use of Low Frequency Ultrasonic Guided Waves to Detect Fouling Deposition in Pipelines
by Habiba Lais, Premesh S. Lowe, Tat-Hean Gan, Luiz C. Wrobel and Jamil Kanfoud
Sensors 2018, 18(7), 2122; https://doi.org/10.3390/s18072122 - 2 Jul 2018
Cited by 23 | Viewed by 5721
Abstract
The accumulation of fouling within a structure is a well-known and costly problem across many industries. The build-up is dependent on the environmental conditions surrounding the fouled structure. Many attempts have been made to detect fouling accumulation in critical engineering structures and to [...] Read more.
The accumulation of fouling within a structure is a well-known and costly problem across many industries. The build-up is dependent on the environmental conditions surrounding the fouled structure. Many attempts have been made to detect fouling accumulation in critical engineering structures and to optimize the application of power ultrasonic fouling removal procedures, i.e., flow monitoring, ultrasonic guided waves and thermal imaging. In recent years, the use of ultrasonic guided waves has been identified as a promising technology to detect fouling deposition/growth. This technology also has the capability to assess structural health; an added value to the industry. The use of ultrasonic guided waves for structural health monitoring is established but fouling detection using ultrasonic guided waves is still in its infancy. The present study focuses on the characterization of fouling detection using ultrasonic guided waves. A 6.2-m long 6-inch schedule 40 carbon steel pipe has been used to study the effect of (Calcite) fouling on ultrasonic guided wave propagation within the structure. Parameters considered include frequency selection, number of cycles and dispersion at incremental fouling thickness. According to the studied conditions, a 0.5 dB/m drop in signal amplitude occurs for a fouling deposition of 1 mm. The findings demonstrate the potential to detect fouling build-up in lengthy pipes and to quantify its thickness by the reduction in amplitude found from further numerical investigation. This variable can be exploited to optimize the power ultrasonic fouling removal procedure. Full article
(This article belongs to the Special Issue Ultrasonic Sensors 2018)
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21 pages, 4202 KiB  
Article
Initial Alignment Algorithm Based on the DMCS Method in Single-Axis RSINS with Large Azimuth Misalignment Angles for Submarines
by Xiu-Wei Xia and Qian Sun
Sensors 2018, 18(7), 2123; https://doi.org/10.3390/s18072123 - 2 Jul 2018
Cited by 4 | Viewed by 2926
Abstract
Since the inertial sensor error has been modulated effectively by the Rotation Modulation Technique (RMT), the Rotation Strapdown Inertial Navigation System (RSINS) has been widely used for submarines in order to satisfy the requirement of high-accuracy and long working duration. The performance of [...] Read more.
Since the inertial sensor error has been modulated effectively by the Rotation Modulation Technique (RMT), the Rotation Strapdown Inertial Navigation System (RSINS) has been widely used for submarines in order to satisfy the requirement of high-accuracy and long working duration. The performance of the initial alignment is main factor affecting the accuracy of the Strapdown Inertial Navigation System (SINS). The traditional initial alignment algorithm based on the compass method has bad performance when the misalignment angle is large, which will make the submarine SINS fail to launch properly in a complex operating environment. Since the RSINS uses the mathematical platform to calculate the navigation information, it allows multiple algorithms to run simultaneously, and different algorithms do not interact with each other. Thus, to improve the alignment accuracy, an initial alignment algorithm based on the Dual Mathematical Calculation System (DMCS) is proposed; moreover, to solve the problem of large azimuth misalignment angle, an improved DMCS-based alignment algorithm is also presented in this paper. Both simulations and experiments showed that the novel algorithm can effectively improve the initial alignment performance under the large misalignment angle environment, enhancing the environmental suitability of the RSINS. Full article
(This article belongs to the Section Physical Sensors)
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21 pages, 31714 KiB  
Article
Low-Cost Electronic Tagging System for Bee Monitoring
by Paulo De Souza, Peter Marendy, Karien Barbosa, Setia Budi, Pascal Hirsch, Nasiha Nikolic, Tom Gunthorpe, Gustavo Pessin and Andrew Davie
Sensors 2018, 18(7), 2124; https://doi.org/10.3390/s18072124 - 2 Jul 2018
Cited by 41 | Viewed by 9034
Abstract
This paper introduces both a hardware and a software system designed to allow low-cost electronic monitoring of social insects using RFID tags. Data formats for individual insect identification and their associated experiment are proposed to facilitate data sharing from experiments conducted with this [...] Read more.
This paper introduces both a hardware and a software system designed to allow low-cost electronic monitoring of social insects using RFID tags. Data formats for individual insect identification and their associated experiment are proposed to facilitate data sharing from experiments conducted with this system. The antennas’ configuration and their duty cycle ensure a high degree of detection rates. Other advantages and limitations of this system are discussed in detail in the paper. Full article
(This article belongs to the Special Issue RFID-Based Sensors for IoT Applications)
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19 pages, 4384 KiB  
Article
Managing Pervasive Sensing Campaigns via an Experimentation-as-a-Service Platform for Smart Cities
by Dimitrios Amaxilatis, Georgios Mylonas, Luis Diez, Evangelos Theodoridis, Verónica Gutiérrez and Luis Muñoz
Sensors 2018, 18(7), 2125; https://doi.org/10.3390/s18072125 - 2 Jul 2018
Cited by 15 | Viewed by 4132
Abstract
The adoption of technologies like the IoT in urban environments, together with the intensive use of smartphones, is driving transformation towards smart cities. Under this perspective, Experimentation-as-a-Service within OrganiCity aims to create an experimental facility with technologies, services, and applications that simplify innovation [...] Read more.
The adoption of technologies like the IoT in urban environments, together with the intensive use of smartphones, is driving transformation towards smart cities. Under this perspective, Experimentation-as-a-Service within OrganiCity aims to create an experimental facility with technologies, services, and applications that simplify innovation within urban ecosystems. We discuss here tools that facilitate experimentation, implementing ways to organize, execute, and administer experimentation campaigns in a smart city context. We discuss the benefits of our framework, presenting some preliminary results. This is the first time such tools are paired with large-scale smart city infrastructures, enabling both city-scale experimentation and cross-site experimentation. Full article
(This article belongs to the Special Issue Smart Cities)
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19 pages, 6441 KiB  
Article
Spatio-Temporal Optimization of Perishable Goods’ Shelf Life by a Pro-Active WSN-Based Architecture
by Daniela De Venuto and Giovanni Mezzina
Sensors 2018, 18(7), 2126; https://doi.org/10.3390/s18072126 - 2 Jul 2018
Cited by 36 | Viewed by 6069
Abstract
The waste in the perishable goods supply-chain has prompted many global organizations (e.g., FAO and WHO), to develop the Hazard Analysis and Critical Control Points (HACCP) protocol that ensures a high degree of food quality, minimizing the losses in all the stages of [...] Read more.
The waste in the perishable goods supply-chain has prompted many global organizations (e.g., FAO and WHO), to develop the Hazard Analysis and Critical Control Points (HACCP) protocol that ensures a high degree of food quality, minimizing the losses in all the stages of the farm-to-fork chain. It has been proven that good warehouse management practices improve the average life of perishable goods. The advances in wireless sensors network (WSN) technology offers the possibility of a “smart” storage organization. In this paper, a low cost reprogrammable WSN-based architecture for functional warehouse management is proposed. The management is based on the continuous monitoring of environmental parameters (i.e., temperature, light exposure and relative humidity), and on their combination to extract a spatial real-time prediction of the product shelf life. For each product, the quality decay is computed by using a 1st order kinetic Arrhenius model to the whole storage site area. It strives to identify, in a way compatible with the other products’ shelf lives, the position within the warehouse that maximizes the food expiration date. The shelf life computing and the “first-expired first-out” logistic problem are entrusted to a Raspberry Pi-based central unit, which manages a set of automated pallet transporters for the displacement of products, according to the computed shelf lives. The management unit supports several commercial light/temperature/humidity sensor solutions, implementing ZigBee, Bluetooth and HTTP-request interfaces. A proof of concept of the presented pro-active WSN-based architecture is also shown. Comparing the proposed monitoring system for the storage of e.g., agricultural products, with a typical one, the experimental results show an improvement of the expected expiration date of about 1.2 ± 0.5 days, for each pallet, when placed in a non-refrigerated environment. In order to stress the versatility of the WSN solution, a section is dedicated to the implemented system user interfaces that highlight detecting critical situations and allow timely automatic or human interventions, minimizing the latter. Full article
(This article belongs to the Special Issue Sensor Networks for Environmental Observations)
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20 pages, 5232 KiB  
Article
Effect of Helmert Transformation Parameters and Weight Matrix on Seasonal Signals in GNSS Coordinate Time Series
by Guo Chen, Qile Zhao, Na Wei and Min Li
Sensors 2018, 18(7), 2127; https://doi.org/10.3390/s18072127 - 3 Jul 2018
Cited by 4 | Viewed by 3838
Abstract
Seasonal signals caused by the Earth’s surface mass redistribution can be detected by Global Navigation Satellite Systems (GNSS). The authors analyze the effect of Helmert transformation parameters and weight matrices, as well as the additional draconic signals on seasonal signals, in the GNSS [...] Read more.
Seasonal signals caused by the Earth’s surface mass redistribution can be detected by Global Navigation Satellite Systems (GNSS). The authors analyze the effect of Helmert transformation parameters and weight matrices, as well as the additional draconic signals on seasonal signals, in the GNSS coordinate time series. Moreover, the contribution of environmental loading models to the GNSS position series is assessed. Position time series of 647 global stations, with spans of 2–21 years are collected to generate six cumulative solutions using different parameters estimated in a deterministic model, as well as weight matrices. Comparison among the different solutions indicates that Helmert transformation parameters and weight matrices can result in a root mean square of 0.1 mm and 0.3 mm for seasonal signals, respectively. Compared to the displacements obtained from environmental loading models, seasonal signals estimated with the Helmert parameters and full weight matrices considered seems to have the best agreement with the results of the loading model. Meanwhile, the additional draconic signals are not effective to be parameterized in the deterministic model with an observation time span less than 15 years, marginally. There are 62%, 72% and 90% of 647 stations with weight root mean squares (WRMS) reduced by removing the loading-model-induced changes from the GNSS residual series for the east, north and vertical components, respectively. Finally, to obtain a velocity estimation with a bias of less than 0.1 mm/yr induced by seasonal signals, the position series with a time span greater than seven years is suggested. Full article
(This article belongs to the Section Remote Sensors)
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12 pages, 3396 KiB  
Article
Measurement of Urinary Bladder Pressure: A Comparison of Methods
by Ingelin Clausen, Lars Geir W. Tvedt and Thomas Glott
Sensors 2018, 18(7), 2128; https://doi.org/10.3390/s18072128 - 3 Jul 2018
Cited by 17 | Viewed by 12410
Abstract
Pressure is an essential parameter for the normal function of almost all organs in the human body. Measurement of pressure is therefore highly important in clinical practice and medical research. In clinical practice, pressures are often measured indirectly through a fluid line where [...] Read more.
Pressure is an essential parameter for the normal function of almost all organs in the human body. Measurement of pressure is therefore highly important in clinical practice and medical research. In clinical practice, pressures are often measured indirectly through a fluid line where the pressure is transmitted from the organ of interest to a remote, externally localized transducer. This method has several limitations and is prone to artefacts from movements. Results from an in vitro bench study comparing the characteristics of two different sensor systems for bladder assessment are presented; a new cystometry system using a MEMS-based in-target organ sensor was compared with a conventional system using water-filled lines connected to external transducers. Robustness to measurement errors due to patient movement was investigated through response to forced vibrations. While the new cystometry system detected real changes in applied pressure for excitation frequencies ranging from 5 Hz to 25 Hz, such small and high-frequency stimuli were not transmitted through the water-filled line connected to the external transducer. The new sensor system worked well after a resilient test at frequencies up to 70 Hz. The in-target organ sensor system will offer new possibilities for long-term monitoring of in vivo pressure in general. This opens up the possibility for future personalized medical treatment and renders possible new health services and, thereby, an increased patient empowerment and quality of life. Full article
(This article belongs to the Special Issue Implantable Sensors 2018)
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13 pages, 8873 KiB  
Article
An Optical Fiber Refractive Index Sensor Based on the Hybrid Mode of Tamm and Surface Plasmon Polaritons
by Xian Zhang, Xiao-Song Zhu and Yi-Wei Shi
Sensors 2018, 18(7), 2129; https://doi.org/10.3390/s18072129 - 3 Jul 2018
Cited by 34 | Viewed by 5035
Abstract
A novel high performance optical fiber refractive index (RI) sensor based on the hybrid transverse magnetic (TM) mode of Tamm plasmon polariton (TPP) and surface plasmon polariton (SPP) is proposed. The structure of the sensor is a multi-mode optical fiber with a one [...] Read more.
A novel high performance optical fiber refractive index (RI) sensor based on the hybrid transverse magnetic (TM) mode of Tamm plasmon polariton (TPP) and surface plasmon polariton (SPP) is proposed. The structure of the sensor is a multi-mode optical fiber with a one dimensional photonic crystal (1 DPC)/metal multi-films outer coated on its fiber core. A simulation study of the proposed sensor is carried out with the geometrical optical model to investigate the performance of the designed sensor with respect to the center wavelength, bilayer period and the thickness of silver layer. Because the lights transmitted in the fiber sensor have much larger incident angles than those in the prism based sensors, the center wavelength of the 1 DPC should shift to longer wavelength. When the coupling between TM-TPP and SPP is stronger, the sensor exhibits better performance because the electromagnetic field of the TPP-SPP hybrid mode is enhanced more in the analyte. Compared to most conventional fiber surface plasmon resonance sensors, the figure of merit of the proposed sensor is much higher while the sensitivity is comparable. The idea of utilizing TPP-SPP hybrid mode for RI sensing in the solid-core optical fiber structure presented in this paper could contribute to the study of the fiber RI sensor based on TPP. Full article
(This article belongs to the Special Issue Resonant Sensors)
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11 pages, 3347 KiB  
Article
Wireless Passive Ultra High Frequency RFID Antenna Sensor for Surface Crack Monitoring and Quantitative Analysis
by Jun Zhang, Bei Huang, Gary Zhang and Gui Yun Tian
Sensors 2018, 18(7), 2130; https://doi.org/10.3390/s18072130 - 3 Jul 2018
Cited by 52 | Viewed by 7298
Abstract
An exponential increase in large-scale infrastructure facilitates the development of wireless passive sensors for permanent installation and in-service health monitoring. Due to their wireless, passive and cost-effective characteristics, ultra-high frequency (UHF) radio frequency identification (RFID) tag antenna based sensors are receiving increasing attention [...] Read more.
An exponential increase in large-scale infrastructure facilitates the development of wireless passive sensors for permanent installation and in-service health monitoring. Due to their wireless, passive and cost-effective characteristics, ultra-high frequency (UHF) radio frequency identification (RFID) tag antenna based sensors are receiving increasing attention for structural health monitoring (SHM). This paper uses a circular patch antenna sensor with an open rectangular window for crack monitoring. The sensing mechanism is quantitatively studied in conjunction with a mode analysis, which can uncover the intrinsic principle for turning an antenna into a crack sensor. The robustness of the feature is examined when the variation of crack position associated with an aluminum sample and the antenna sensor is considered. The experimental results demonstrate a reasonable sensitivity and resolution for crack characterization. Full article
(This article belongs to the Special Issue Passive Electromagnetic Sensors for Autonomous Wireless Networks)
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10 pages, 3129 KiB  
Article
A 10-Bit 300 kS/s Reference-Voltage Regulator Free SAR ADC for Wireless-Powered Implantable Medical Devices
by Yongkui Yang, Jun Zhou, Xin Liu and Wang Ling Goh
Sensors 2018, 18(7), 2131; https://doi.org/10.3390/s18072131 - 3 Jul 2018
Cited by 2 | Viewed by 3999
Abstract
This paper presents a reference-voltage regulator free successive-approximation-register analog-to-digital converters (SAR ADC) with self-timed pre-charging for wireless-powered implantable medical devices. Assisted by a self-timed pre-charging technique, the proposed SAR ADC eliminates the need for a power-hungry reference-voltage regulator and area-consuming decoupling capacitor while [...] Read more.
This paper presents a reference-voltage regulator free successive-approximation-register analog-to-digital converters (SAR ADC) with self-timed pre-charging for wireless-powered implantable medical devices. Assisted by a self-timed pre-charging technique, the proposed SAR ADC eliminates the need for a power-hungry reference-voltage regulator and area-consuming decoupling capacitor while maintaining insensitivity to the supply voltage fluctuation. Fabricated with a 0.18-µm complementary metal–oxide–semiconductor (CMOS) technology, the proposed SAR ADC achieves a Signal To Noise And Distortion Ratio (SNDR) of 53.32 dB operating at 0.8 V with a supply voltage fluctuation of 50 mVpp and consumes a total power of 2.72 µW at a sampling rate of 300 kS/s. Including the self-timed pre-charging circuits, the total figure-of-merit (FOM) is 23.9 fJ/conversion-step and the total area occupied is 0.105 mm2. Full article
(This article belongs to the Special Issue Wearable and Implantable Sensors and Electronics Circuits)
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28 pages, 4439 KiB  
Article
Optimal Polygon Decomposition for UAV Survey Coverage Path Planning in Wind
by Matthew Coombes, Tom Fletcher, Wen-Hua Chen and Cunjia Liu
Sensors 2018, 18(7), 2132; https://doi.org/10.3390/s18072132 - 3 Jul 2018
Cited by 62 | Viewed by 13405
Abstract
In this paper, a new method for planning coverage paths for fixed-wing Unmanned Aerial Vehicle (UAV) aerial surveys is proposed. Instead of the more generic coverage path planning techniques presented in previous literature, this method specifically concentrates on decreasing flight time of fixed-wing [...] Read more.
In this paper, a new method for planning coverage paths for fixed-wing Unmanned Aerial Vehicle (UAV) aerial surveys is proposed. Instead of the more generic coverage path planning techniques presented in previous literature, this method specifically concentrates on decreasing flight time of fixed-wing aircraft surveys. This is achieved threefold: by the addition of wind to the survey flight time model, accounting for the fact fixed-wing aircraft are not constrained to flight within the polygon of the region of interest, and an intelligent method for decomposing the region into convex polygons conducive to quick flight times. It is shown that wind can make a huge difference to survey time, and that flying perpendicular can confer a flight time advantage. Small UAVs, which have very slow airspeeds, can very easily be flying in wind, which is 50% of their airspeed. This is why the technique is shown to be so effective, due to the fact that ignoring wind for small, slow, fixed-wing aircraft is a considerable oversight. Comparing this method to previous techniques using a Monte Carlo simulation on randomised polygons shows a significant reduction in flight time. Full article
(This article belongs to the Special Issue Sensors in Agriculture 2018)
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28 pages, 12652 KiB  
Article
Deterministic Propagation Modeling for Intelligent Vehicle Communication in Smart Cities
by Fausto Granda, Leyre Azpilicueta, Cesar Vargas-Rosales, Mikel Celaya-Echarri, Peio Lopez-Iturri, Erik Aguirre, Jose Javier Astrain, Pablo Medrano, Jesus Villandangos and Francisco Falcone
Sensors 2018, 18(7), 2133; https://doi.org/10.3390/s18072133 - 3 Jul 2018
Cited by 15 | Viewed by 4618
Abstract
Vehicular Ad Hoc Networks (VANETs) are envisaged to be a critical building block of Smart Cities and Intelligent Transportation System (ITS) where applications for pollution, congestion reduction, vehicle mobility improvement, accident prevention and safer roads are some of the VANETs expected benefits towards [...] Read more.
Vehicular Ad Hoc Networks (VANETs) are envisaged to be a critical building block of Smart Cities and Intelligent Transportation System (ITS) where applications for pollution, congestion reduction, vehicle mobility improvement, accident prevention and safer roads are some of the VANETs expected benefits towards Intelligent Vehicle Communications. Although there is a significant research effort in Vehicle-to-Infrastructure (V2I) and Vehicle-to-Vehicle (V2V) communication radio channel characterization, the use of a deterministic approach as a complement of theoretical and empirical models is required to understand more accurately the propagation phenomena in urban environments. In this work, a deterministic computational tool based on an in-house 3D Ray-Launching algorithm is used to represent and analyze large-scale and small-scale urban radio propagation phenomena, including vehicle movement effects on each of the multipath components. In addition, network parameters such as throughput, packet loss and jitter, have been obtained by means of a set of experimental measurements for different V2I and V2V links. Results show the impact of factors such as distance, frequency, location of antenna transmitters (TX), obstacles and vehicle speed. These results are useful for radio-planning Wireless Sensor Networks (WSNs) designers and deployment of urban Road Side Units (RSUs). Full article
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16 pages, 2369 KiB  
Article
Automatic Annotation of Unlabeled Data from Smartphone-Based Motion and Location Sensors
by Nsikak Pius Owoh, Manmeet Mahinderjit Singh and Zarul Fitri Zaaba
Sensors 2018, 18(7), 2134; https://doi.org/10.3390/s18072134 - 3 Jul 2018
Cited by 14 | Viewed by 4419
Abstract
Automatic data annotation eliminates most of the challenges we faced due to the manual methods of annotating sensor data. It significantly improves users’ experience during sensing activities since their active involvement in the labeling process is reduced. An unsupervised learning technique such as [...] Read more.
Automatic data annotation eliminates most of the challenges we faced due to the manual methods of annotating sensor data. It significantly improves users’ experience during sensing activities since their active involvement in the labeling process is reduced. An unsupervised learning technique such as clustering can be used to automatically annotate sensor data. However, the lingering issue with clustering is the validation of generated clusters. In this paper, we adopted the k-means clustering algorithm for annotating unlabeled sensor data for the purpose of detecting sensitive location information of mobile crowd sensing users. Furthermore, we proposed a cluster validation index for the k-means algorithm, which is based on Multiple Pair-Frequency. Thereafter, we trained three classifiers (Support Vector Machine, K-Nearest Neighbor, and Naïve Bayes) using cluster labels generated from the k-means clustering algorithm. The accuracy, precision, and recall of these classifiers were evaluated during the classification of “non-sensitive” and “sensitive” data from motion and location sensors. Very high accuracy scores were recorded from Support Vector Machine and K-Nearest Neighbor classifiers while a fairly high accuracy score was recorded from the Naïve Bayes classifier. With the hybridized machine learning (unsupervised and supervised) technique presented in this paper, unlabeled sensor data was automatically annotated and then classified. Full article
(This article belongs to the Special Issue Annotation of User Data for Sensor-Based Systems)
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22 pages, 907 KiB  
Article
Design and Implementation of a Central-Controllable and Secure Multicast System Based on Universal Identifier Network
by Jianfeng Guan, Xuan Liu, Su Yao and Zhongbai Jiang
Sensors 2018, 18(7), 2135; https://doi.org/10.3390/s18072135 - 3 Jul 2018
Cited by 6 | Viewed by 3997
Abstract
With the rapid increase of network users and services, the breadth and depth of Internet have greatly changed. The mismatch between current network requirements and original network architecture design has spurred the evolution or revolution of Internet to remedy this gap. Lots of [...] Read more.
With the rapid increase of network users and services, the breadth and depth of Internet have greatly changed. The mismatch between current network requirements and original network architecture design has spurred the evolution or revolution of Internet to remedy this gap. Lots of research projects on future network architecture have been launched, in which Universal Identifier Network (UIN) architecture that is based on the identifier/location separation, access/core separation and control/forwarding separation can provide better mobility, security and reliability. On the other hand, the demand of group communication has increased due to the fine-grained network services and successive booming of new applications such as IoT (Internet of Things). Most of current multicast schemes are based on the open group model with open group membership (multicast only care the multicast group state, not the group member) and open access to send/receive multicast data, which are beneficial to multicast routing for its simplification. However, the open group membership makes the group member management difficult to be realized, and open access may result in lots of security vulnerabilities such as Denial of service (DoS), eavesdropping and masquerading, which make deployment more difficult. Therefore, in this paper we propose a Central-Controllable and Secure Multicast (CCSM) system based on the UIN architecture, and redesign the multicast service procedures including registration, join/leave, multicast routing construction and update with objective to achieve better mobility support, security, scalability and controllable. More specifically, we design a new group management scheme to perform the multicast members join/leave with authentication and a central-controllable multicast routing scheme to provide a secure way to set up multicast entries on routers. The CCSM inherits the characteristics of UIN in terms of mobility and security, and it can provide the centralized multicast routing computation and distributes the multicast routing into forwarders. We compare CCSM with Protocol Independent Multicast-Sparse Mode (PIM-SM), and the results show that CCSM reduces the multicast join delay, and performs better than PIM-SM in term of reconstruction cost under low multicast density. Full article
(This article belongs to the Special Issue Security, Trust and Privacy for Sensor Networks)
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32 pages, 11367 KiB  
Article
Differential Ultra-Wideband Microwave Imaging: Principle Application Challenges
by Jürgen Sachs, Sebastian Ley, Thomas Just, Somayyeh Chamaani and Marko Helbig
Sensors 2018, 18(7), 2136; https://doi.org/10.3390/s18072136 - 3 Jul 2018
Cited by 26 | Viewed by 7014
Abstract
Wideband microwave imaging is of interest wherever optical opaque scenarios need to be analyzed, as these waves can penetrate biological tissues, many building materials, or industrial materials. One of the challenges of microwave imaging is the computation of the image from the measurement [...] Read more.
Wideband microwave imaging is of interest wherever optical opaque scenarios need to be analyzed, as these waves can penetrate biological tissues, many building materials, or industrial materials. One of the challenges of microwave imaging is the computation of the image from the measurement data because of the need to solve extensive inverse scattering problems due to the sometimes complicated wave propagation. The inversion problem simplifies if only spatially limited objects—point objects, in the simplest case—with temporally variable scattering properties are of interest. Differential imaging uses this time variance by observing the scenario under test over a certain time interval. Such problems exist in medical diagnostics, in the search for surviving earthquake victims, monitoring of the vitality of persons, detection of wood pests, control of industrial processes, and much more. This paper gives an overview of imaging methods for point-like targets and discusses the impact of target variations onto the radar data. Because the target variations are very weak in many applications, a major issue of differential imaging concerns the suppression of random effects by appropriate data processing and concepts of radar hardware. The paper introduces related methods and approaches, and some applications illustrate their performance. Full article
(This article belongs to the Special Issue Sensors for Microwave Imaging and Detection)
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16 pages, 28257 KiB  
Article
A Compact Low-Power LoRa IoT Sensor Node with Extended Dynamic Range for Channel Measurements
by Thomas Ameloot, Patrick Van Torre and Hendrik Rogier
Sensors 2018, 18(7), 2137; https://doi.org/10.3390/s18072137 - 3 Jul 2018
Cited by 32 | Viewed by 6606
Abstract
As sub-GHz wireless Internet of Things (IoT) sensor networks set the stage for long-range, low-data-rate communication, wireless technologies such as LoRa and SigFox receive a lot of attention. They aim to offer a reliable means of communication for an extensive amount of monitoring [...] Read more.
As sub-GHz wireless Internet of Things (IoT) sensor networks set the stage for long-range, low-data-rate communication, wireless technologies such as LoRa and SigFox receive a lot of attention. They aim to offer a reliable means of communication for an extensive amount of monitoring and management applications. Recently, several studies have been conducted on their performance, but none of these feature a high dynamic range in terms of channel measurement. In this contribution an autonomous, low-power, LoRa-compatible wireless sensor node is presented. The main uses for this node are situated in LoRa channel characterization and link performance analysis. By applying stepped attenuators controlled by a dynamic attenuation adjustment algorithm, this node provides a dynamic range that is significantly larger than what is provided by commercially available LoRa modules. The node was calibrated in order to obtain accurate measurements of the received signal power in dBm. In this paper, both the hardware design as well as some verification measurements are discussed, unveiling various LoRa-related research applications and opportunities. Full article
(This article belongs to the Section Internet of Things)
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19 pages, 5218 KiB  
Article
Forecasting of Cereal Yields in a Semi-arid Area Using the Simple Algorithm for Yield Estimation (SAFY) Agro-Meteorological Model Combined with Optical SPOT/HRV Images
by Aicha Chahbi Bellakanji, Mehrez Zribi, Zohra Lili-Chabaane and Bernard Mougenot
Sensors 2018, 18(7), 2138; https://doi.org/10.3390/s18072138 - 3 Jul 2018
Cited by 21 | Viewed by 4535
Abstract
In semi-arid areas characterized by frequent drought events, there is often a strong need for an operational grain yield forecasting system, to help decision-makers with the planning of annual imports. However, monitoring the crop canopy and production capacity of plants, especially for cereals, [...] Read more.
In semi-arid areas characterized by frequent drought events, there is often a strong need for an operational grain yield forecasting system, to help decision-makers with the planning of annual imports. However, monitoring the crop canopy and production capacity of plants, especially for cereals, can be challenging. In this paper, a new approach to yield estimation by combining data from the Simple Algorithm for Yield estimation (SAFY) agro-meteorological model with optical SPOT/ High Visible Resolution (HRV) satellite data is proposed. Grain yields are then statistically estimated as a function of Leaf Area Index (LAI) during the maximum growth period between 25 March and 5 April. The LAI is retrieved from the SAFY model, and calibrated using SPOT/HRV data. This study is based on the analysis of a rich database, which was acquired over a period of two years (2010–2011, 2012–2013) at the Merguellil site in central Tunisia (North Africa) from more than 60 test fields and 20 optical satellite SPOT/HRV images. The validation and calibration of this methodology is presented, on the basis of two subsets of observations derived from the experimental database. Finally, an inversion technique is applied to estimate the overall yield of the entire studied site. Full article
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22 pages, 16616 KiB  
Article
Accurate Calibration of Multi-LiDAR-Multi-Camera Systems
by Zoltán Pusztai, Iván Eichhardt and Levente Hajder
Sensors 2018, 18(7), 2139; https://doi.org/10.3390/s18072139 - 3 Jul 2018
Cited by 76 | Viewed by 12584
Abstract
As autonomous driving attracts more and more attention these days, the algorithms and sensors used for machine perception become popular in research, as well. This paper investigates the extrinsic calibration of two frequently-applied sensors: the camera and Light Detection and Ranging (LiDAR). The [...] Read more.
As autonomous driving attracts more and more attention these days, the algorithms and sensors used for machine perception become popular in research, as well. This paper investigates the extrinsic calibration of two frequently-applied sensors: the camera and Light Detection and Ranging (LiDAR). The calibration can be done with the help of ordinary boxes. It contains an iterative refinement step, which is proven to converge to the box in the LiDAR point cloud, and can be used for system calibration containing multiple LiDARs and cameras. For that purpose, a bundle adjustment-like minimization is also presented. The accuracy of the method is evaluated on both synthetic and real-world data, outperforming the state-of-the-art techniques. The method is general in the sense that it is both LiDAR and camera-type independent, and only the intrinsic camera parameters have to be known. Finally, a method for determining the 2D bounding box of the car chassis from LiDAR point clouds is also presented in order to determine the car body border with respect to the calibrated sensors. Full article
(This article belongs to the Special Issue Depth Sensors and 3D Vision)
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17 pages, 5960 KiB  
Article
Development of a Modular Board for EEG Signal Acquisition
by Tomas Uktveris and Vacius Jusas
Sensors 2018, 18(7), 2140; https://doi.org/10.3390/s18072140 - 3 Jul 2018
Cited by 42 | Viewed by 9495
Abstract
The increased popularity of brain-computer interfaces (BCIs) has created a new demand for miniaturized and low-cost electroencephalogram (EEG) acquisition devices for entertainment, rehabilitation, and scientific needs. The lack of scientific analysis for such system design, modularity, and unified validation tends to suppress progress [...] Read more.
The increased popularity of brain-computer interfaces (BCIs) has created a new demand for miniaturized and low-cost electroencephalogram (EEG) acquisition devices for entertainment, rehabilitation, and scientific needs. The lack of scientific analysis for such system design, modularity, and unified validation tends to suppress progress in this field and limit supply for new low-cost device availability. To eliminate this problem, this paper presents the design and evaluation of a compact, modular, battery powered, conventional EEG signal acquisition board based on an ADS1298 analog front-end chip. The introduction of this novel, vertically stackable board allows the EEG scaling problem to be solved by effectively reconfiguring hardware for small or more demanding applications. The ability to capture 16 to 64 EEG channels at sample rates from 250 Hz to 1000 Hz and to transfer raw EEG signal over a Bluetooth or Wi-Fi interface was implemented. Furthermore, simple but effective assessment techniques were used for system evaluation. While conducted tests confirm the validity of the system against official datasheet specifications and for real-world applications, the proposed quality verification methods can be further employed for analyzing other similar EEG devices in the future. With 6.59 microvolts peak-to-peak input referred noise and a −97 dB common mode rejection ratio in 0–70 Hz band, the proposed design can be qualified as a low-cost precision cEEG research device. Full article
(This article belongs to the Special Issue EEG Electrodes)
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13 pages, 3512 KiB  
Article
Fluorinated Metal Phthalocyanines: Interplay between Fluorination Degree, Films Orientation, and Ammonia Sensing Properties
by Darya Klyamer, Aleksandr Sukhikh, Sergey Gromilov, Pavel Krasnov and Tamara Basova
Sensors 2018, 18(7), 2141; https://doi.org/10.3390/s18072141 - 3 Jul 2018
Cited by 58 | Viewed by 4859
Abstract
In this work, the sensor response of MPcFx (M = Cu, Co, Zn; x = 0, 4, 16) films toward gaseous NH3 (10–50 ppm) was studied by a chemiresistive method and compared to that of unsubstituted MPc films to reveal the [...] Read more.
In this work, the sensor response of MPcFx (M = Cu, Co, Zn; x = 0, 4, 16) films toward gaseous NH3 (10–50 ppm) was studied by a chemiresistive method and compared to that of unsubstituted MPc films to reveal the effects of central metals and F-substituents on the sensing properties. A combination of atomic force microscopy and X-ray diffraction techniques have been used to elucidate the structural features of thin MPcFx films deposited by organic molecular beam deposition. It has been shown that the sensor response of MPcF4 films to ammonia is noticeably higher than that of MPc films, which is in good correlation with the values of binding energy between the metal phthalocyanine and NH3 molecules, as calculated by the density functional theory (DFT) method. At the same time, in contrast to the DFT calculations, MPcF16 demonstrated the lesser sensor response compared with MPcF4, which appeared to be connected with the different structure and morphology of their films. The ZnPcF4 films were shown to exhibit a sensitivity to ammonia up to concentrations as low as 0.1 ppm, and can be used for the selective detection of ammonia in the presence of some reducing gases and volatile organic compounds. Moreover, the ZnPcF4 films can be used for the detection of NH3 in the gas mixture simulating exhaled air (N2 76%, O2 16%, H2O 5%, and CO2 3%). Full article
(This article belongs to the Special Issue Supramolecular Chemistry for Sensors Application)
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22 pages, 3882 KiB  
Article
Light-Weight Integration and Interoperation of Localization Systems in IoT
by Abdulkadir Karaagac, Pieter Suanet, Wout Joseph, Ingrid Moerman and Jeroen Hoebeke
Sensors 2018, 18(7), 2142; https://doi.org/10.3390/s18072142 - 3 Jul 2018
Cited by 4 | Viewed by 5706
Abstract
As the ideas and technologies behind the Internet of Things (IoT) take root, a vast array of new possibilities and applications is emerging with the significantly increased number of devices connected to the Internet. Moreover, we are also witnessing the fast emergence of [...] Read more.
As the ideas and technologies behind the Internet of Things (IoT) take root, a vast array of new possibilities and applications is emerging with the significantly increased number of devices connected to the Internet. Moreover, we are also witnessing the fast emergence of location-based services with an abundant number of localization technologies and solutions with varying capabilities and limitations. We believe that, at this moment in time, the successful integration of these two diverse technologies is mutually beneficial and even essential for both fields. IoT is one of the major fields that can benefit from localization services, and so, the integration of localization systems in the IoT ecosystem would enable numerous new IoT applications. Further, the use of standardized IoT architectures, interaction and information models will permit multiple localization systems to communicate and interoperate with each other in order to obtain better context information and resolve positioning errors or conflicts. Therefore, in this work, we investigate the semantic interoperation and integration of positioning systems in order to obtain the full potential of the localization ecosystem in the context of IoT. Additionally, we also validate the proposed design by means of an industrial case study, which targets fully-automated warehouses utilizing location-aware and interconnected IoT products and systems. Full article
(This article belongs to the Special Issue Sensor Fusion and Novel Technologies in Positioning and Navigation)
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17 pages, 19593 KiB  
Article
Multi-Focus Image Fusion Method for Vision Sensor Systems via Dictionary Learning with Guided Filter
by Qilei Li, Xiaomin Yang, Wei Wu, Kai Liu and Gwanggil Jeon
Sensors 2018, 18(7), 2143; https://doi.org/10.3390/s18072143 - 3 Jul 2018
Cited by 25 | Viewed by 5886
Abstract
Vision sensor systems (VSS) are widely deployed in surveillance, traffic and industrial contexts. A large number of images can be obtained via VSS. Because of the limitations of vision sensors, it is difficult to obtain an all-focused image. This causes difficulties in analyzing [...] Read more.
Vision sensor systems (VSS) are widely deployed in surveillance, traffic and industrial contexts. A large number of images can be obtained via VSS. Because of the limitations of vision sensors, it is difficult to obtain an all-focused image. This causes difficulties in analyzing and understanding the image. In this paper, a novel multi-focus image fusion method (SRGF) is proposed. The proposed method uses sparse coding to classify the focused regions and defocused regions to obtain the focus feature maps. Then, a guided filter (GF) is used to calculate the score maps. An initial decision map can be obtained by comparing the score maps. After that, consistency verification is performed, and the initial decision map is further refined by the guided filter to obtain the final decision map. By performing experiments, our method can obtain satisfying fusion results. This demonstrates that the proposed method is competitive with the existing state-of-the-art fusion methods. Full article
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24 pages, 4308 KiB  
Article
Smart Vest for Respiratory Rate Monitoring of COPD Patients Based on Non-Contact Capacitive Sensing
by David Naranjo-Hernández, Alejandro Talaminos-Barroso, Javier Reina-Tosina, Laura M. Roa, Gerardo Barbarov-Rostan, Pilar Cejudo-Ramos, Eduardo Márquez-Martín and Francisco Ortega-Ruiz
Sensors 2018, 18(7), 2144; https://doi.org/10.3390/s18072144 - 3 Jul 2018
Cited by 71 | Viewed by 11343
Abstract
In this paper, a first approach to the design of a portable device for non-contact monitoring of respiratory rate by capacitive sensing is presented. The sensing system is integrated into a smart vest for an untethered, low-cost and comfortable breathing monitoring of Chronic [...] Read more.
In this paper, a first approach to the design of a portable device for non-contact monitoring of respiratory rate by capacitive sensing is presented. The sensing system is integrated into a smart vest for an untethered, low-cost and comfortable breathing monitoring of Chronic Obstructive Pulmonary Disease (COPD) patients during the rest period between respiratory rehabilitation exercises at home. To provide an extensible solution to the remote monitoring using this sensor and other devices, the design and preliminary development of an e-Health platform based on the Internet of Medical Things (IoMT) paradigm is also presented. In order to validate the proposed solution, two quasi-experimental studies have been developed, comparing the estimations with respect to the golden standard. In a first study with healthy subjects, the mean value of the respiratory rate error, the standard deviation of the error and the correlation coefficient were 0.01 breaths per minute (bpm), 0.97 bpm and 0.995 (p < 0.00001), respectively. In a second study with COPD patients, the values were −0.14 bpm, 0.28 bpm and 0.9988 (p < 0.0000001), respectively. The results for the rest period show the technical and functional feasibility of the prototype and serve as a preliminary validation of the device for respiratory rate monitoring of patients with COPD. Full article
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11 pages, 4232 KiB  
Article
Simultaneous Measurement of Curvature, Strain and Temperature Using a Twin-Core Photonic Crystal Fiber-Based Sensor
by Tongtong Zhao, Shuqin Lou, Xin Wang, Wan Zhang and Yulei Wang
Sensors 2018, 18(7), 2145; https://doi.org/10.3390/s18072145 - 3 Jul 2018
Cited by 36 | Viewed by 4743
Abstract
A novel twin-core photonic crystal fiber-based sensor for simultaneous measurement of curvature, strain and temperature is proposed. The fiber sensor is constructed by splicing the homemade twin-core photonic crystal fiber between two segments of single mode fiber. Affected by the coupling between two [...] Read more.
A novel twin-core photonic crystal fiber-based sensor for simultaneous measurement of curvature, strain and temperature is proposed. The fiber sensor is constructed by splicing the homemade twin-core photonic crystal fiber between two segments of single mode fiber. Affected by the coupling between two cores, the transmission spectrum of the fiber sensor has different wavelength responses to curvature, strain, and temperature. The maximal sensitivities to curvature, strain and temperature are 10.89 nm/m−1, 1.24 pm/με and 73.9 pm/°C, respectively. Simultaneous measurement of curvature, strain and temperature can be achieved by monitoring the wavelength shifts of selected valleys in the transmission spectrum. Contrast experiment based on traditional twin-core fiber is carried out. Experimental results demonstrate that twin-core photonic crystal fiber-based sensor has higher sensitivity and better linearity than traditional twin-core fiber-based sensor. Full article
(This article belongs to the Special Issue Optical Sensors Using Microstructured and Photonics Crystal Fibers)
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13 pages, 2700 KiB  
Article
Comparison of Data Preprocessing Approaches for Applying Deep Learning to Human Activity Recognition in the Context of Industry 4.0
by Xiaochen Zheng, Meiqing Wang and Joaquín Ordieres-Meré
Sensors 2018, 18(7), 2146; https://doi.org/10.3390/s18072146 - 3 Jul 2018
Cited by 129 | Viewed by 11461
Abstract
According to the Industry 4.0 paradigm, all objects in a factory, including people, are equipped with communication capabilities and integrated into cyber-physical systems (CPS). Human activity recognition (HAR) based on wearable sensors provides a method to connect people to CPS. Deep learning has [...] Read more.
According to the Industry 4.0 paradigm, all objects in a factory, including people, are equipped with communication capabilities and integrated into cyber-physical systems (CPS). Human activity recognition (HAR) based on wearable sensors provides a method to connect people to CPS. Deep learning has shown surpassing performance in HAR. Data preprocessing is an important part of deep learning projects and takes up a large part of the whole analytical pipeline. Data segmentation and data transformation are two critical steps of data preprocessing. This study analyzes the impact of segmentation methods on deep learning model performance, and compares four data transformation approaches. An experiment with HAR based on acceleration data from multiple wearable devices was conducted. The multichannel method, which treats the data for the three axes as three overlapped color channels, produced the best performance. The highest overall recognition accuracy achieved was 97.20% for eight daily activities, based on the data from seven wearable sensors, which outperformed most of the other machine learning techniques. Moreover, the multichannel approach was applied to three public datasets and produced satisfying results for multi-source acceleration data. The proposed method can help better analyze workers’ activities and help to integrate people into CPS. Full article
(This article belongs to the Collection Multi-Sensor Information Fusion)
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32 pages, 3444 KiB  
Review
Review of Chirped Fiber Bragg Grating (CFBG) Fiber-Optic Sensors and Their Applications
by Daniele Tosi
Sensors 2018, 18(7), 2147; https://doi.org/10.3390/s18072147 - 4 Jul 2018
Cited by 150 | Viewed by 20793
Abstract
Fiber Bragg Gratings (FBGs) are one of the most popular technology within fiber-optic sensors, and they allow the measurement of mechanical, thermal, and physical parameters. In recent years, a strong emphasis has been placed on the fabrication and application of chirped FBGs (CFBGs), [...] Read more.
Fiber Bragg Gratings (FBGs) are one of the most popular technology within fiber-optic sensors, and they allow the measurement of mechanical, thermal, and physical parameters. In recent years, a strong emphasis has been placed on the fabrication and application of chirped FBGs (CFBGs), which are characterized by a non-uniform modulation of the refractive index within the core of an optical fiber. A CFBG behaves as a cascade of FBGs, each one reflecting a narrow spectrum that depends on temperature and/or strain. The key characteristic of CFBGs is that their reflection spectrum depends on the strain/temperature observed in each section of the grating; thus, they enable a short-length distributed sensing, whereas it is possible to detect spatially resolved variations of temperature or strain with resolution on the order of a millimeter over the grating length. Based on this premise, CFBGs have found important applications in healthcare, mechanical engineering, and shock waves analysis, among others. This work reviews the present and emerging trends in CFBG sensors, focusing on all aspects of the sensing element and outlining the application case scenarios for which CFBG sensors have been demonstrated. Full article
(This article belongs to the Special Issue Recent Advances in Fiber Bragg Grating Based Sensors)
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12 pages, 2610 KiB  
Article
Millimeter Wave High Resolution Radar Accuracy in Fog Conditions—Theory and Experimental Verification
by Yosef Golovachev, Ariel Etinger, Gad A. Pinhasi and Yosef Pinhasi
Sensors 2018, 18(7), 2148; https://doi.org/10.3390/s18072148 - 4 Jul 2018
Cited by 43 | Viewed by 4933
Abstract
Attenuation and group delay effects on millimeter wave (MMW) propagation in clouds and fog are studied theoretically and verified experimentally using high resolution radar in an indoor space filled with artificial fog. In the theoretical analysis, the frequency-dependent attenuation and group delay were [...] Read more.
Attenuation and group delay effects on millimeter wave (MMW) propagation in clouds and fog are studied theoretically and verified experimentally using high resolution radar in an indoor space filled with artificial fog. In the theoretical analysis, the frequency-dependent attenuation and group delay were derived via the permittivity of the medium. The results are applied to modify the millimeter-wave propagation model (MPM) and employed to study the effect of fog and cloud on the accuracy of the Frequency-Modulated Continuous-Wave (FMCW) radar operating in millimeter wavelengths. Artificial fog was generated in the experimental study to demonstrate ultra-low visibility in a confined space. The resulted attenuation and group delay were measured using FMCW radar operating at 320–330 GHz. It was found that apart from the attenuation, the incremental group delay caused by the fog also played a role in the accuracy of the radar. The results were compared to the analytical model. It was shown that although the artificial fog has slight different characteristics compare to the natural fog and clouds, in particle composition, size, and density, the model predictions were good, pointing out that the dispersive effects should be considered in the design of remote sensing radars operating in millimeter and sub-millimeter wavelengths. Full article
(This article belongs to the Section Remote Sensors)
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11 pages, 3188 KiB  
Article
Acoustic Parametric Signal Generation for Underwater Communication
by María Campo-Valera, Miguel Ardid, Dídac D. Tortosa, Ivan Felis, Juan A. Martínez-Mora, Carlos D. Llorens and Pablo Cervantes
Sensors 2018, 18(7), 2149; https://doi.org/10.3390/s18072149 - 4 Jul 2018
Cited by 6 | Viewed by 4197
Abstract
This paper presents a study of different types of parametric signals with application to underwater acoustic communications. In all the signals, the carrier frequency is 200 kHz, which corresponds to the resonance frequency of the transducer under study and different modulations are presented [...] Read more.
This paper presents a study of different types of parametric signals with application to underwater acoustic communications. In all the signals, the carrier frequency is 200 kHz, which corresponds to the resonance frequency of the transducer under study and different modulations are presented and compared. In this sense, we study modulations with parametric sine sweeps (4 to 40 kHz) that represent binary codes (zeros and ones), getting closer to the application in acoustic communications. The different properties of the transmitting signals in terms of bit rate reconstruction, directivity, efficiency, and power needed are discussed as well. Full article
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22 pages, 13168 KiB  
Article
Second Iteration of Photogrammetric Processing to Refine Image Orientation with Improved Tie-Points
by Nguyen Truong Giang, Jean-Michaël Muller, Ewelina Rupnik, Christian Thom and Marc Pierrot-Deseilligny
Sensors 2018, 18(7), 2150; https://doi.org/10.3390/s18072150 - 4 Jul 2018
Cited by 10 | Viewed by 4129
Abstract
Photogrammetric processing is available in various software solutions and can easily deliver 3D pointclouds as accurate as 1 pixel. Certain applications, e.g., very accurate shape reconstruction in industrial metrology or change detection for deformation studies in geosciences, require results of enhanced accuracy. The [...] Read more.
Photogrammetric processing is available in various software solutions and can easily deliver 3D pointclouds as accurate as 1 pixel. Certain applications, e.g., very accurate shape reconstruction in industrial metrology or change detection for deformation studies in geosciences, require results of enhanced accuracy. The tie-point extraction step is the opening in the photogrammetric processing chain and therefore plays a key role in the quality of the subsequent image orientation, camera calibration and 3D reconstruction. Improving its precision will have an impact on the obtained 3D. In this research work we describe a method which aims at enhancing the accuracy of image orientation by adding a second iteration photogrammetric processing. The result from the classical processing is used as a priori information to guide the extraction of refined tie-points of better photogrammetric quality. Evaluated on indoor and UAV acquisitions, the proposed methodology shows a significant improvement on the obtained 3D point accuracy. Full article
(This article belongs to the Section Remote Sensors)
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12 pages, 1898 KiB  
Article
Simultaneous Detection of Adenosine Triphosphate and Glucose Based on the Cu-Fenton Reaction
by Fei Qu, Jingwen Li, Wenli Han, Lian Xia and Jinmao You
Sensors 2018, 18(7), 2151; https://doi.org/10.3390/s18072151 - 4 Jul 2018
Cited by 8 | Viewed by 4643
Abstract
Both adenosine triphosphate (ATP) and glucose are important to human health, and their abnormal levels are closely related to angiocardiopathy and hypoglycaemia. Therefore, the simultaneous determination of ATP and glucose with a single test mode is highly desirable for disease diagnostics and early [...] Read more.
Both adenosine triphosphate (ATP) and glucose are important to human health, and their abnormal levels are closely related to angiocardiopathy and hypoglycaemia. Therefore, the simultaneous determination of ATP and glucose with a single test mode is highly desirable for disease diagnostics and early recognition. Herein, a new fluorescence on/off switch sensing platform is developed by carbon nanodots (CNDs) to detect ATP and glucose simultaneously. The fluorescence of CNDs can be quenched by Cu2+ and hydrogen peroxide (H2O2), due to the formation of hydroxyl radicals (·OH) produced in the Cu-Fenton reaction. Based on the high affinity of Cu2+ with ATP, the fluorescence of CNDs will recover effectively after adding ATP. Additionally, glucose can be efficiently catalyzed by glucose oxidase (GOx) to generate H2O2, so the platform can also be utilized to analyze glucose. Under optimum conditions, this sensing platform displays excellent sensitivity and the linear ranges are from 0.1 to 7 μM for ATP with a limit of detection (LOD) of 30.2 nM, and from 0.1 to 7 mM for glucose with a LOD 39.8 μM, respectively. Benefiting from the high sensitivity and selectivity, this sensing platform is successfully applied for simultaneous detection of ATP and glucose in human serum samples with satisfactory recoveries. Full article
(This article belongs to the Special Issue Colorimetric and Fluorescent Sensors 2018)
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17 pages, 10484 KiB  
Article
InSAR Baseline Estimation for Gaofen-3 Real-Time DEM Generation
by Huan Lu, Zhiyong Suo, Zhenfang Li, Jinwei Xie, Jiwei Zhao and Qingjun Zhang
Sensors 2018, 18(7), 2152; https://doi.org/10.3390/s18072152 - 4 Jul 2018
Cited by 8 | Viewed by 5353
Abstract
For Interferometry Synthetic Aperture Radar (InSAR), the normal baseline is one of the main factors that affects the accuracy of the ground elevation. For Gaofen-3 (GF-3) InSAR processing, the poor accuracy of the real-time orbit determination results in a large baseline error, leads [...] Read more.
For Interferometry Synthetic Aperture Radar (InSAR), the normal baseline is one of the main factors that affects the accuracy of the ground elevation. For Gaofen-3 (GF-3) InSAR processing, the poor accuracy of the real-time orbit determination results in a large baseline error, leads to a modulation error in azimuth and a slope error in the range for timely Digital Elevation Model (DEM) generation. In order to address this problem, a novel baseline estimation approach based on Shuttle Radar Topography Mission (SRTM) DEM is proposed in this paper. Firstly, the orbit fitting is executed to remove the non-linear error factor, which is different from traditional methods. Secondly, the height errors are obtained in a slant-range plane between SRTM DEM and the GF-3 generated DEM, which can be used to estimate the baseline error with a linear variation. Then, the real-time orbit can be calibrated by the baseline error. Finally, the DEM generation is performed by using the modified baseline and orbit. This approach has the merit of spatial and precise orbital free ability. Based on the results of GF-3 interferometric SAR data for Hebei, the effectiveness of the proposed algorithm is verified and the accuracy of GF-3 real-time DEM products can be improved extensively. Full article
(This article belongs to the Special Issue First Experiences with Chinese Gaofen-3 SAR Sensor)
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17 pages, 4560 KiB  
Article
Multiple Fusion Based on the CCD and MEMS Accelerometer for the Low-Cost Multi-Loop Optoelectronic System Control
by Yong Luo, Yao Mao, Wei Ren, Yongmei Huang, Chao Deng and Xi Zhou
Sensors 2018, 18(7), 2153; https://doi.org/10.3390/s18072153 - 4 Jul 2018
Cited by 14 | Viewed by 3996
Abstract
In the charge-coupled device (CCD) and micro-electro-mechanical system (MEMS) accelerometer based low-cost multi-loop optoelectronic control system (OCS), due to accelerometers’ drift and noise in low frequency, the disturbance suppression (DS) is insufficient. Previously, based on the acceleration and position dual-loop control (ADLC), researchers [...] Read more.
In the charge-coupled device (CCD) and micro-electro-mechanical system (MEMS) accelerometer based low-cost multi-loop optoelectronic control system (OCS), due to accelerometers’ drift and noise in low frequency, the disturbance suppression (DS) is insufficient. Previously, based on the acceleration and position dual-loop control (ADLC), researchers combined a disturbance observer (DOB) with a virtual velocity loop to make some medium-frequency DS exchange for low-frequency performance. However, it is not optimal because the classic DOB based on accelerometers’ inaccurate signals cannot observe accurate disturbance in low frequency and the velocity based on a CCD and accelerometer time-domain fusion carried the CCD’s delay, resulting in the drop of medium-frequency DS. In this paper, considering the CCD’s advantage in low frequency and the accelerometer’s strength in high frequency, we propose to fuse their signals twice with a modified complementary filter method to respectively acquire an acceleration and velocity. The new acceleration with no drift and less noise but lower bandwidth creates a new acceleration model and is only used in fusion DOB (FDOB), while the velocity with little delay is to build an additional velocity loop. Compared with the traditional DOB enhanced by the time-domain fusion velocity loop, experiments verify that the proposed multiple fusion would apparently enhance the system’s DS, especially in low and medium frequency. Full article
(This article belongs to the Special Issue Inertial Sensors and Systems 2018)
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18 pages, 7333 KiB  
Article
Designing Interactive Experiences for Children with Cochlear Implant
by Sandra Cano, Leandro Flórez-Aristizábal, César A. Collazos, Habib M. Fardaoun and Daniyal M. Alghazzawi
Sensors 2018, 18(7), 2154; https://doi.org/10.3390/s18072154 - 4 Jul 2018
Cited by 8 | Viewed by 4507
Abstract
Information and Communication Technologies (ICTs) have grown exponentially in the education context and the use of digital products by children is increasing. As a result, teachers are taking advantage of ICTs to include mobile devices such as Tablets or Smartphones inside the classroom [...] Read more.
Information and Communication Technologies (ICTs) have grown exponentially in the education context and the use of digital products by children is increasing. As a result, teachers are taking advantage of ICTs to include mobile devices such as Tablets or Smartphones inside the classroom as playful support material to motivate children during their learning. Designing an interactive experience for a child with a special need such as a hearing impairment is a great challenge. In this article, two interactive systems are depicted, using a non-traditional interaction, by the following stages: analysis, design and implementation, with the participation of children with cochlear implant in the Institute of Blind and Deaf Children of Valle del Cauca, Colombia and the ASPAS Institute, Mallorca, Spain, who evaluated both interactive systems, PHONOMAGIC and CASETO. Positive results were obtained, showing that the use of real objects can greatly influence the environment in which children interact with the game, allowing them to explore and manipulate the objects supporting their teaching-learning processes. Full article
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10 pages, 3829 KiB  
Article
High-Performance Limiting Current Oxygen Sensor Comprised of Highly Active La0.75Sr0.25Cr0.5Mn0.5O3 Electrode
by Jie Zou, Qian Lin, Chu Cheng, Xin Zhang, Qinghui Jin, Han Jin, Jinxia Wang and Jiawen Jian
Sensors 2018, 18(7), 2155; https://doi.org/10.3390/s18072155 - 4 Jul 2018
Cited by 5 | Viewed by 4659
Abstract
Zirconia-based limiting current oxygen sensor gains considerable attention, due to its high-performance in improving the combustion efficiency of fossil fuels and reducing the emission of exhaust gases. Nevertheless, the Pt electrode is frequently used in the oxygen sensor, therefore, it restrains the broader [...] Read more.
Zirconia-based limiting current oxygen sensor gains considerable attention, due to its high-performance in improving the combustion efficiency of fossil fuels and reducing the emission of exhaust gases. Nevertheless, the Pt electrode is frequently used in the oxygen sensor, therefore, it restrains the broader application due to the high cost. Quite recently, La0.75Sr0.25Cr0.5Mn0.5O3 (LSCM) has been reported to be highly active to catalyze oxygen reduction. Herein, with the intention of replacing the frequently used Pt, we studied the practicability of adapting the LSCM to zirconia-based limiting current oxygen sensor. Through comparing the electrocatalytic activity of LSCM and Pt, it is confirmed that LSCM gave analogous oxygen reactivity with that of the Pt. Then, limiting the current oxygen sensors comprised of LSCM or Pt are fabricated and their sensing behavior to oxygen in the range of 2–25% is evaluated. Conclusively, quick response/recovery rate (within 7s), linear relationship, and high selectivity (against 5% CO2 and H2O) in sensing oxygen are observed for the sensors, regardless of the sensing materials (LSCM or Pt) that are used in the sensor. Particularly, identical sensing characteristics are observed for the sensors consisting of LSCM or Pt, indicating the practicability of replacing the Pt electrode by adapting the LSCM electrode to future zirconia-based oxygen sensors. Full article
(This article belongs to the Special Issue Functional Materials for the Applications of Advanced Gas Sensors)
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17 pages, 978 KiB  
Article
Integrating Cyber-Physical Systems in a Component-Based Approach for Smart Homes
by Javier Criado, José Andrés Asensio, Nicolás Padilla and Luis Iribarne
Sensors 2018, 18(7), 2156; https://doi.org/10.3390/s18072156 - 4 Jul 2018
Cited by 20 | Viewed by 4875
Abstract
Integration of different cyber-physical systems involves a development process that takes into account some solutions for intercommunicating and interoperating heterogeneous devices. Each device can be managed as a thing within the Internet-of-Things concept by using web technologies. In addition, a “thing” can be [...] Read more.
Integration of different cyber-physical systems involves a development process that takes into account some solutions for intercommunicating and interoperating heterogeneous devices. Each device can be managed as a thing within the Internet-of-Things concept by using web technologies. In addition, a “thing” can be managed as an encapsulated component by applying component-based software engineering principles. Based on this context, we propose a solution for integrating heterogeneous systems using a specific component-based technology. Specifically, we focus on enabling the connection of different types of subsystems present in smart home solutions. This technology enables interoperability by applying a homogeneous component representation that provides communication features through web sockets, and by implementing gateways in proprietary network connections. Furthermore, our solution eases the extension of these systems by means of abstract representations of the architectures and devices that form part of them. The approach is validated through an example scenario with different subsystems of a smart home solution. Full article
(This article belongs to the Special Issue Smart Homes)
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15 pages, 6344 KiB  
Article
Analysis of Frequency Stability and Thermoelastic Effects for Slotted Tuning Fork MEMS Resonators
by Valentina Zega, Attilio Frangi, Andrea Guercilena and Gabriele Gattere
Sensors 2018, 18(7), 2157; https://doi.org/10.3390/s18072157 - 4 Jul 2018
Cited by 25 | Viewed by 4068
Abstract
MicroElectroMechanical Systems (MEMS) resonators are attracting increasing interest because of their smaller size and better integrability as opposed to their quartz counterparts. However, thermal drift of the natural frequency of silicon structures is one of the main issues that has hindered the development [...] Read more.
MicroElectroMechanical Systems (MEMS) resonators are attracting increasing interest because of their smaller size and better integrability as opposed to their quartz counterparts. However, thermal drift of the natural frequency of silicon structures is one of the main issues that has hindered the development of MEMS resonators. Extensive investigations have addressed both the fabrication process (e.g., introducing heavy doping of the silicon) and the mechanical design (e.g., exploiting proper orientation of the device, slots, nonlinearities). In this work, starting from experimental data published in the literature, we show that a careful design can help reduce the thermal drift even when slots are inserted in the devices in order to decrease thermoelastic losses. A custom numerical code able to predict the dynamic behavior of MEMS resonators for different materials, orientations and doping levels is coupled with an evolutionary optimization algorithm and the possibility to find an optimal mechanical design is demonstrated on a tuning-fork resonator. Full article
(This article belongs to the Special Issue State-of-the-Art Sensors Technology in Italy 2017)
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17 pages, 561 KiB  
Article
Hidden Policy Attribute-Based Data Sharing with Direct Revocation and Keyword Search in Cloud Computing
by Axin Wu, Dong Zheng, Yinghui Zhang and Menglei Yang
Sensors 2018, 18(7), 2158; https://doi.org/10.3390/s18072158 - 4 Jul 2018
Cited by 41 | Viewed by 4073
Abstract
Attribute-based encryption can be used to realize fine-grained data sharing in open networks. However, in practical applications, we have to address further challenging issues, such as attribute revocation and data search. How do data users search for the data they need in massive [...] Read more.
Attribute-based encryption can be used to realize fine-grained data sharing in open networks. However, in practical applications, we have to address further challenging issues, such as attribute revocation and data search. How do data users search for the data they need in massive amounts of data? When users leave the system, they lose the right to decrypt the shared data. In this case, how do we ensure that revoked users cannot decrypt shared data? In this paper, we successfully address these issues by proposing a hidden policy attribute-based data sharing scheme with direct revocation and keyword search. In the proposed scheme, the direct revocation of attributes does not need to update the private key of non-revoked users during revocation. In addition, a keyword search is realized in our scheme, and the search time is constant with the increase in attributes. In particular, the policy is hidden in our scheme, and hence, users’ privacy is protected. Our security and performance analyses show that the proposed scheme can tackle the security and efficiency concerns in cloud computing. Full article
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21 pages, 1688 KiB  
Article
An Analytical Temperature-Dependent Design Model for Contour-Mode MEMS Resonators and Oscillators Verified by Measurements
by Johannes Stegner, Sebastian Gropp, Dmitry Podoskin, Uwe Stehr, Martin Hoffmann and Matthias A. Hein
Sensors 2018, 18(7), 2159; https://doi.org/10.3390/s18072159 - 4 Jul 2018
Cited by 8 | Viewed by 4404
Abstract
The importance of micro-electromechanical systems (MEMS) for radio-frequency (RF) applications is rapidly growing. In RF mobile-communication systems, MEMS-based circuits enable a compact implementation, low power consumption and high RF performance, e.g., bulk-acoustic wave filters with low insertion loss and low noise or fast [...] Read more.
The importance of micro-electromechanical systems (MEMS) for radio-frequency (RF) applications is rapidly growing. In RF mobile-communication systems, MEMS-based circuits enable a compact implementation, low power consumption and high RF performance, e.g., bulk-acoustic wave filters with low insertion loss and low noise or fast and reliable MEMS switches. However, the cross-hierarchical modelling of micro-electronic and micro-electromechanical constituents together in one multi-physical design process is still not as established as the design of integrated micro-electronic circuits, such as operational amplifiers. To close the gap between micro-electronics and micro-electromechanics, this paper presents an analytical approach towards the linear top-down design of MEMS resonators, based on their electrical specification, by the solution of the mechanical wave equation. In view of the central importance of thermal effects for the performance and stability of MEMS-based RF circuits, the temperature dependence was included in the model; the aim was to study the variations of the RF parameters of the resonators and to enable a temperature dependent MEMS oscillator simulation. The variations of the resonator parameters with respect to the ambient temperature were then verified by RF measurements in a vacuum chamber at temperatures between −35 C and 85 C. The systematic body of data revealed temperature coefficients of the resonant frequency between −26 ppm/K and −20 ppm/K, which are in good agreement with other data from the literature. Based on the MEMS resonator model derived, a MEMS oscillator was designed, simulated, and measured in a vacuum chamber yielding a measured temperature coefficient of the oscillation frequency of −26.3 ppm/K. The difference of the temperature coefficients of frequency of oscillator and resonator turned out to be mainly influenced by the limited Q-factor of the MEMS device. In both studies, the analytical model and the measurement showed very good agreement in terms of temperature dependence and the prediction of fabrication results of the resonators designed. This analytical modelling approach serves therefore as an important step towards the design and simulation of micro-electronics and micro-electromechanics in one uniform design process. Furthermore, temperature dependences of MEMS oscillators can now be studied by simulations instead of time-consuming and complex measurements. Full article
(This article belongs to the Special Issue MEMS Resonators)
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23 pages, 11204 KiB  
Article
A Tightly Coupled RTK/INS Algorithm with Ambiguity Resolution in the Position Domain for Ground Vehicles in Harsh Urban Environments
by Wei Li, Wenyi Li, Xiaowei Cui, Sihao Zhao and Mingquan Lu
Sensors 2018, 18(7), 2160; https://doi.org/10.3390/s18072160 - 4 Jul 2018
Cited by 25 | Viewed by 7114
Abstract
Vehicles driving in urban canyons are always confronted with a degraded Global Navigation Satellite System (GNSS) signal environment. The surrounding obstacles may cause signal reflections or blockages, which lead to large multipath noises and intermittent GNSS reception. Under these circumstances, it is not [...] Read more.
Vehicles driving in urban canyons are always confronted with a degraded Global Navigation Satellite System (GNSS) signal environment. The surrounding obstacles may cause signal reflections or blockages, which lead to large multipath noises and intermittent GNSS reception. Under these circumstances, it is not feasible to use conventional real-time kinematic (RTK) algorithms to maintain high-precision performance for positioning. In order to meet the special requirements of safety-critical applications under non-ideal observation conditions, a novel tightly coupled RTK/Inertial Navigation System (INS) algorithm is proposed in this paper, which can provide accurate and reliable positioning results continuously. Our integrated RTK/INS algorithm has three features. Firstly, INS measurements are used to help search for integer ambiguities in the position domain. INS solutions can provide a more accurate initial location and a more efficient search region. Secondly, the criterion for determining whether a candidate position is the correct solution is only related to the fractional value of the carrier-phase measurement. Thus, the new algorithm is immune to cycle slips as well as large pseudorange noises. Thirdly, our algorithm can provide more accurate ranging information than the pseudorange, even though it may not necessarily be fixed successfully, because it selects the weighted ambiguity solution as the result rather than the candidate point with maximum probability. The proposed algorithm is demonstrated on both simulated and real datasets. Compared with single epoch RTK and conventional tightly coupled RTK/INS integrations that search integer ambiguities in the ambiguity domain, our method attains better accuracy and stability in a simulated environment. Moreover, the real experimental results are presented to validate the performance of the new integrated navigation algorithm. Full article
(This article belongs to the Collection Positioning and Navigation)
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12 pages, 24029 KiB  
Article
In-Line Inspection Tool with Eddy Current Instrumentation for Fatigue Crack Detection
by Cesar Camerini, João Marcos Alcoforado Rebello, Lucas Braga, Rafael Santos, Tomasz Chady, Grzegorz Psuj and Gabriela Pereira
Sensors 2018, 18(7), 2161; https://doi.org/10.3390/s18072161 - 5 Jul 2018
Cited by 21 | Viewed by 6463
Abstract
Eddy current transducer with sensing coils placed orthogonally and connected in differential mode was introduced to evaluate fatigue cracks in clad pipeline circumferential welds. A dedicated embedded electronic hardware was developed to drive the transducer and measure the electrical complex impedance of the [...] Read more.
Eddy current transducer with sensing coils placed orthogonally and connected in differential mode was introduced to evaluate fatigue cracks in clad pipeline circumferential welds. A dedicated embedded electronic hardware was developed to drive the transducer and measure the electrical complex impedance of the coils, and was specifically designed for operation under autonomous in-line inspection tool. In the laboratory experiments, an automated inspection was performed with the goal to evaluate transducer’s detectability, and different scanning speed was tested to reproduce in service situation. The results have confirmed that the introduced eddy current transducer is a potential solution for fatigue crack detection in clad circumferential weld root, while the hardware developed presented a reasonable SNR reaching the data rate required to be incorporated in an autonomous in-line inspection tool. Full article
(This article belongs to the Special Issue Magnetic Sensors)
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14 pages, 5201 KiB  
Article
SoEasy: A Software Framework for Easy Hardware Control Programming for Diverse IoT Platforms
by Junyoung Lee, Gwang-il Park, Jong-ha Shin, Jin-hae Lee, Cormac J. Sreenan and Seong-eun Yoo
Sensors 2018, 18(7), 2162; https://doi.org/10.3390/s18072162 - 5 Jul 2018
Cited by 11 | Viewed by 6644
Abstract
Many Internet of Things (IoT) applications are emerging and evolving rapidly thanks to widespread open-source hardware platforms. Most of the high-end open-source IoT platforms include built-in peripherals, such as the universal asynchronous receiver and transmitter (UART), pulse width modulation (PWM), general purpose input [...] Read more.
Many Internet of Things (IoT) applications are emerging and evolving rapidly thanks to widespread open-source hardware platforms. Most of the high-end open-source IoT platforms include built-in peripherals, such as the universal asynchronous receiver and transmitter (UART), pulse width modulation (PWM), general purpose input output (GPIO) ports and timers, and have enough computation power to run embedded operating systems such as Linux. However, each IoT platform has its own way of configuring peripherals, and it is difficult for programmers or users to configure the same peripheral on a different platform. Although diverse open-source IoT platforms are widespread, the difficulty in programming those platforms hinders the growth of IoT applications. Therefore, we propose an easy and convenient way to program and configure the operation of each peripheral using a user-friendly Web-based software framework. Through the implementation of the software framework and the real mobile robot application development along with it, we show the feasibility of the proposed software framework, named SoEasy. Full article
(This article belongs to the Special Issue Future Research Trends in Internet of Things and Sensor Networks)
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9 pages, 1227 KiB  
Article
Nonlinear Flow Sensor Calibration with an Accurate Syringe
by Paolo Jose Cesare Biselli, Raquel Siqueira Nóbrega and Francisco Garcia Soriano
Sensors 2018, 18(7), 2163; https://doi.org/10.3390/s18072163 - 5 Jul 2018
Cited by 9 | Viewed by 5419
Abstract
Flow sensors are required for monitoring patients on mechanical ventilation and in respiratory research. Proper calibration is important for ensuring accuracy and can be done with a precision syringe. This procedure, however, becomes complex for nonlinear flow sensors, which are commonly used. The [...] Read more.
Flow sensors are required for monitoring patients on mechanical ventilation and in respiratory research. Proper calibration is important for ensuring accuracy and can be done with a precision syringe. This procedure, however, becomes complex for nonlinear flow sensors, which are commonly used. The objective of the present work was to develop an algorithm to allow the calibration of nonlinear flow sensors using an accurate syringe. We first noticed that a power law equation could properly fit the pressure-flow relationship of nonlinear flow sensors. We then developed a software code to estimate the parameters for this equation using a 3 L syringe (calibration syringe). Finally, we tested the performance of a calibrated flow sensor using a different 3 L syringe (testing syringe) and a commercially available spirometer. After calibration, the sensor had a bias ranging from −1.7% to 3.0% and precision from 0.012 L to 0.039 L for volumes measured with the 3 L testing syringe. Calibrated sensor performance was at least as good as the commercial sensor. This calibration procedure can be done at the bedside for both clinical and research purposes, therefore improving the accuracy of nonlinear flow sensors. Full article
(This article belongs to the Special Issue Point of Care Sensors)
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10 pages, 1818 KiB  
Article
Targeting FRET-Based Reporters for cAMP and PKA Activity Using AKAP79
by Nshunge Musheshe, Miguel J. Lobo, Martina Schmidt and Manuela Zaccolo
Sensors 2018, 18(7), 2164; https://doi.org/10.3390/s18072164 - 5 Jul 2018
Cited by 11 | Viewed by 5200
Abstract
Fluorescence resonance energy transfer (FRET)-based sensors for 3′–5′cyclic adenosine monophosphate (cAMP) and protein kinase A (PKA) allow real-time imaging of cAMP levels and kinase activity in intact cells with high spatiotemporal resolution. The development of FRET-based sensors has made it possible to directly [...] Read more.
Fluorescence resonance energy transfer (FRET)-based sensors for 3′–5′cyclic adenosine monophosphate (cAMP) and protein kinase A (PKA) allow real-time imaging of cAMP levels and kinase activity in intact cells with high spatiotemporal resolution. The development of FRET-based sensors has made it possible to directly demonstrate that cAMP and PKA signals are compartmentalized. These sensors are currently widely used to dissect the organization and physiological function of local cAMP/PKA signaling events in a variety of cell systems. Fusion to targeting domains has been used to direct the sensors to a specific subcellular nanodomain and to monitor cAMP and PKA activity at specific subcellular sites. Here, we investigate the effects of using the A-kinase anchoring protein 79 (AKAP79) as a targeting domain for cAMP and PKA FRET-based reporters. As AKAP79 interacts with PKA itself, when used as a targeting domain, it can potentially impact on the amplitude and kinetics of the signals recorded locally. By using as the targeting domain wild type AKAP79 or a mutant that cannot interact with PKA, we establish that AKAP79 does not affect the amplitude and kinetics of cAMP changes or the level of PKA activity detected by the sensor. Full article
(This article belongs to the Special Issue Luminescence and Chemiluminescence Sensors)
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12 pages, 8899 KiB  
Article
A High-Precision CMOS Temperature Sensor with Thermistor Linear Calibration in the (−5 °C, 120 °C) Temperature Range
by Chua-Chin Wang, Zong-You Hou and Jhih-Cheng You
Sensors 2018, 18(7), 2165; https://doi.org/10.3390/s18072165 - 5 Jul 2018
Cited by 11 | Viewed by 7057
Abstract
A high-precision Complementary Metal-Oxide-Semiconductor (CMOS) temperature sensor for (−5 °C, 120 °C) temperature range is designed and analyzed in this investigation. The proposed design is featured with a temperature range selection circuit so that the thermistor linear circuit automatically switches to a corresponding [...] Read more.
A high-precision Complementary Metal-Oxide-Semiconductor (CMOS) temperature sensor for (−5 °C, 120 °C) temperature range is designed and analyzed in this investigation. The proposed design is featured with a temperature range selection circuit so that the thermistor linear circuit automatically switches to a corresponding calibration loop in light of the temperature range besides the analysis of the calibration method. It resolves the problem that the temperature range of a single thermistor temperature sensor is too small. Notably, the output of the proposed design also attains a high linearity. The measurement results in a thermal chamber justifying that the output voltage is 1.96 V to 4.15 V, the maximum linearity error ≤1.4%, and the worst temperature error ≤1.1 °C in the temperature range of −5 °C to 120 °C. Full article
(This article belongs to the Special Issue CMOS Smart Temperature Sensors)
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15 pages, 6298 KiB  
Article
A Blade Defect Diagnosis Method by Fusing Blade Tip Timing and Tip Clearance Information
by Ji-wang Zhang, Lai-bin Zhang and Li-xiang Duan
Sensors 2018, 18(7), 2166; https://doi.org/10.3390/s18072166 - 5 Jul 2018
Cited by 18 | Viewed by 3873
Abstract
Blade tip timing (BTT) technology is considered the most promising method for blade vibration measurements due to the advantages of its simplicity and non-contact measurement capacity. Nevertheless, BTT technology still suffers from two problems, which are (1) the requirements of domain expertise and [...] Read more.
Blade tip timing (BTT) technology is considered the most promising method for blade vibration measurements due to the advantages of its simplicity and non-contact measurement capacity. Nevertheless, BTT technology still suffers from two problems, which are (1) the requirements of domain expertise and prior knowledge of BTT signals analysis due to severe under-sampling; and (2) that the traditional BTT method can only judge whether there is a defect in the blade but it cannot judge the severity and the location of the defect. Thus, how to overcome the above drawbacks has become a big challenge. Aiming at under-sampled BTT signals, a feature learning method using a convolutional neural network (CNN) is introduced. In this way, some new fault-sensitive features can be adaptively learned from raw under-sampled data and it is therefore no longer necessary to rely on prior knowledge. At the same time, research has found that tip clearance (TC) is also very sensitive to the blade state, especially regarding defect severity and location. A novel analysis method fusing TC and BTT signals is proposed in this paper. The goal of this approach is to integrate tip clearance information with tip timing information for blade fault detection. The method consists of four key steps: First, we extract the TC and BTT signals from raw pulse data; second, TC statistical features and BTT deep learning features will be extracted and fused using the kernel principal component analysis (KPCA) method; then, model training and selection are carried out; and finally, 16 sets of experiments are carried out to validate the feasibility of the proposed method and the classification accuracy achieves 95%, which is far higher than the traditional diagnostic method. Full article
(This article belongs to the Section Physical Sensors)
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11 pages, 1654 KiB  
Article
The Accuracy of the Detection of Body Postures and Movements Using a Physical Activity Monitor in People after a Stroke
by Malou H. J. Fanchamps, Herwin L. D. Horemans, Gerard M. Ribbers, Henk J. Stam and Johannes B. J. Bussmann
Sensors 2018, 18(7), 2167; https://doi.org/10.3390/s18072167 - 5 Jul 2018
Cited by 50 | Viewed by 4737
Abstract
Background: In stroke rehabilitation not only are the levels of physical activity important, but body postures and movements performed during one’s daily-life are also important. This information is provided by a new one-sensor accelerometer that is commercially available, low-cost, and user-friendly. The present [...] Read more.
Background: In stroke rehabilitation not only are the levels of physical activity important, but body postures and movements performed during one’s daily-life are also important. This information is provided by a new one-sensor accelerometer that is commercially available, low-cost, and user-friendly. The present study examines the accuracy of this activity monitor (Activ8) in detecting several classes of body postures and movements in people after a stroke. Methods: Twenty-five people after a stroke participated in an activity protocol with either basic activities or daily-life activities performed in a laboratory and/or at home. Participants wore an Activ8 on their less-affected thigh. The primary outcome was the difference in registered time for the merged class “upright position” (standing/walking/running) between the Activ8 and the video recording (the reference method). Secondary analyses focused on classes other than “upright position”. Results: The Activ8 underestimated the merged class “upright position” by 3.8% (775 s). The secondary analyses showed an overestimation of “lying/sitting” (4.5% (569 s)) and of “cycling” (6.5% (206 s)). The differences were lowest for basic activities in the laboratory and highest for daily-life activities at home. Conclusions: The Activ8 is sufficiently accurate in detecting different classes of body postures and movements of people after a stroke during basic activities and daily-life activities in a laboratory and/or at home. Full article
(This article belongs to the Special Issue Wearable Smart Devices)
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11 pages, 4529 KiB  
Article
Sensitive Detection of Escherichia coli O157:H7 in Food Products by Impedimetric Immunosensors
by Francesca Malvano, Roberto Pilloton and Donatella Albanese
Sensors 2018, 18(7), 2168; https://doi.org/10.3390/s18072168 - 5 Jul 2018
Cited by 40 | Viewed by 4522
Abstract
In this work, the development of an impedimetric label-free immunosensor for the detection of Escherichia coli O157:H7 is reported. Different immobilization techniques of monoclonal anti-E. coli were tested, in order to reach the very low limit of detections. The comparison between the [...] Read more.
In this work, the development of an impedimetric label-free immunosensor for the detection of Escherichia coli O157:H7 is reported. Different immobilization techniques of monoclonal anti-E. coli were tested, in order to reach the very low limit of detections. The comparison between the immobilization procedures underlined the advantages of the oriented procedure and the use of a dendrimer, which allowed for immobilizing a higher number of antibody units, reaching a very high sensitivity. However, the use of activated ferrocene as electron-transferring mediator, which improved the electrical properties of the system, resulted in a very low limit of detection equal to 3 cfu/mL. This immunosensor was used to analyze milk and meat samples obtaining a good agreement with the results of the ELISA methods. Full article
(This article belongs to the Special Issue Smart Biosensing at BBMEC 12, Rome)
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15 pages, 3094 KiB  
Article
Thermal Imaging Metrology with a Smartphone Sensor
by Leigh Russell Stanger, Thomas Charles Wilkes, Nicholas Andrew Boone, Andrew John Samuel McGonigle and Jon Raffe Willmott
Sensors 2018, 18(7), 2169; https://doi.org/10.3390/s18072169 - 6 Jul 2018
Cited by 10 | Viewed by 7006
Abstract
Thermal imaging cameras are expensive, particularly those designed for measuring high temperature objects with low measurement uncertainty. A wide range of research and industrial applications would benefit from lower cost temperature imaging sensors with improved metrology. To address this problem, we present the [...] Read more.
Thermal imaging cameras are expensive, particularly those designed for measuring high temperature objects with low measurement uncertainty. A wide range of research and industrial applications would benefit from lower cost temperature imaging sensors with improved metrology. To address this problem, we present the first ever quantification methodology for the temperature measurement performance of an ultra-low cost thermal imaging system based on a smartphone sensor. The camera was formed from a back illuminated silicon Complementary Metal Oxide Semiconductor (CMOS) sensor, developed for the smartphone camera market. It was packaged for use with a Raspberry Pi computer. We designed and fitted a custom-made triplet lens assembly. The system performance was characterised with a range of state-of-the-art techniques and metrics: establishing a temperature resolution of below 10 °C in the range 600–1000 °C. Furthermore, the scene dependent aspects of combined uncertainty were considered. The minimum angular subtense for which an accurate thermal measurement could be made was determined to be 1.35°, which corresponds to a 23 mm bar at a distance of 1 m, or 45:1 field-of-view in radiation thermometer nomenclature. Full article
(This article belongs to the Special Issue Advances in Infrared Imaging: Sensing, Exploitation and Applications)
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19 pages, 3379 KiB  
Article
Systematic Experimental Assessment of a 2D-Motion Sensor to Detect Relative Movement between Residual Limb and Prosthetic Socket
by Veronika Noll, Stephan Rinderknecht and Philipp Beckerle
Sensors 2018, 18(7), 2170; https://doi.org/10.3390/s18072170 - 6 Jul 2018
Cited by 5 | Viewed by 4574
Abstract
A sensor system for measuring the relative movement between prosthetic socket and residual limb based on a 2D-motion sensor is introduced and thoroughly tested experimentally. The quantitative analysis of test rig evaluation is used to identify advantageous sensor settings and liner configurations. Considering [...] Read more.
A sensor system for measuring the relative movement between prosthetic socket and residual limb based on a 2D-motion sensor is introduced and thoroughly tested experimentally. The quantitative analysis of test rig evaluation is used to identify advantageous sensor settings and liner configurations. Considering these favorable settings, sensor functionality is quantified to errrel=0.52±1.78%. Advancing to convex measurement surfaces, the sensor shows absolute errors of errabs1 mm in an observable measurement scenario. The feasibility of measuring gait-induced relative movement with the proposed 2D-motion sensor is shown via a biomechanical plausibility study. Overall, the findings suggest that the proposed sensor system is suitable for investigating the relative movement between residual limb and prosthetic socket in dynamic gait situations. Full article
(This article belongs to the Section Physical Sensors)
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22 pages, 7422 KiB  
Article
Damage Detection of L-Shaped Concrete Filled Steel Tube (L-CFST) Columns under Cyclic Loading Using Embedded Piezoceramic Transducers
by Juan Zhang, Yong Li, Guofeng Du and Gangbing Song
Sensors 2018, 18(7), 2171; https://doi.org/10.3390/s18072171 - 6 Jul 2018
Cited by 52 | Viewed by 8105
Abstract
L-shaped concrete filled steel tube (L-CFST) columns are used frequently in civil engineering, and the concrete damage inside the L-CFST column is difficult to monitor. This research aims to develop a new method to monitor the internal concrete damage in the L-CFST column [...] Read more.
L-shaped concrete filled steel tube (L-CFST) columns are used frequently in civil engineering, and the concrete damage inside the L-CFST column is difficult to monitor. This research aims to develop a new method to monitor the internal concrete damage in the L-CFST column by using embedded piezoceramic smart aggregates (SAs) under low frequency cyclic loading. The SA enabled active method is used to monitor the concrete damages near the bottom of the L-CFST columns, and the wavelet packet analysis is used to establish a damage index, which is used to analyze the acquired data. During the experiment, three L-CFST columns with different wall thickness of the steel tube were tested. The experimental results find that the structural damage indices under the low-frequency cyclic loading are basically consistent with the results of the hysteretic curves and the skeleton curve of the specimens, and are in good agreement with the experimental phenomena. We conclude that the use of smart aggregate can directly and clearly reflect the damage process of the concrete core, demonstrating the feasibility of using piezoceramic smart aggregates to monitor the internal concrete damage of the L-CFST column. Full article
(This article belongs to the Special Issue Piezoelectric Transducers: Advances in Structural Health Monitoring)
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15 pages, 39582 KiB  
Article
A New Vegetation Index Based on Multitemporal Sentinel-2 Images for Discriminating Heavy Metal Stress Levels in Rice
by Zhijiang Zhang, Meiling Liu, Xiangnan Liu and Gaoxiang Zhou
Sensors 2018, 18(7), 2172; https://doi.org/10.3390/s18072172 - 6 Jul 2018
Cited by 51 | Viewed by 6071
Abstract
Heavy metal stress in crops is a worldwide problem that requires accurate and timely monitoring. This study aimed to improve the accuracy of monitoring heavy metal stress levels in rice by using multiple Sentinel-2 images. The selected study areas are in Zhuzhou City, [...] Read more.
Heavy metal stress in crops is a worldwide problem that requires accurate and timely monitoring. This study aimed to improve the accuracy of monitoring heavy metal stress levels in rice by using multiple Sentinel-2 images. The selected study areas are in Zhuzhou City, Hunan Province, China. Six Sentinel-2 images were acquired in 2017, and heavy metal concentrations in soil were measured. A novel vegetation index called heavy metal stress sensitive index (HMSSI) was proposed. HMSSI is the ratio between two red-edge spectral indices, namely the red-edge chlorophyll index (CIred-edge) and the plant senescence reflectance index (PSRI). To demonstrate the capability of HMSSI, the performances of CIred-edge and PSRI in discriminating heavy metal stress levels were compared with that of HMSSI at different growth stages. Random forest (RF) was used to establish a multitemporal monitoring model to detect heavy metal stress levels in rice based on HMSSI at different growth stages. Results show that HMSSI is more sensitive to heavy metal stress than CIred-edge and PSRI at different growth stages. The performance of a multitemporal monitoring model combining the whole growth stage images was better than any other single growth stage in distinguishing heavy metal stress levels. Therefore, HMSSI can be regarded as an indicator for monitoring heavy metal stress levels with a multitemporal monitoring model. Full article
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14 pages, 4826 KiB  
Article
Inverse Finite Element Method for Reconstruction of Deformation in the Gantry Structure of Heavy-Duty Machine Tool Using FBG Sensors
by Mingyao Liu, Xiong Zhang, Han Song, Shiguang Zhou, Zude Zhou and Weijian Zhou
Sensors 2018, 18(7), 2173; https://doi.org/10.3390/s18072173 - 6 Jul 2018
Cited by 31 | Viewed by 3162
Abstract
The deformation of the gantry structure in heavy-duty machine tools is an important factor that affects machining accuracy. In order to realize real-time monitoring of the deformation of the gantry structure, which is statically indeterminate and complex in shape, the reconstruction algorithm based [...] Read more.
The deformation of the gantry structure in heavy-duty machine tools is an important factor that affects machining accuracy. In order to realize real-time monitoring of the deformation of the gantry structure, which is statically indeterminate and complex in shape, the reconstruction algorithm based on inverse Finite Element Method (iFEM) is proposed and fiber Bragg grating (FBG) sensors are used to measure strain data. The elements of the gantry structure are divided and the displacement functions of each element are determined. The shape function is obtained by substituting degree of freedoms (DOF) of element nodes into displacement functions. Through a differential method, the relation between strain and DOF of element nodes is established by the strain matrices. Subsequently, the DOF of element nodes are obtained by minimizing an error functional defined as the least-squares error between the analytic strain data and the corresponding experimental strains. Considering coordinate transformation and problem-specific displacement boundary conditions, the total deformation of the gantry structure is obtained. Following this, the experiment was carried out. The deformation simulated by ANSYS was used to replace the experimentally measured deformation and then compared with the deformation reconstructed by iFEM under the same loading condition. The accuracy of iFEM for reconstructing deformation of the gantry structure in heavy-duty machine tools is verified. It provides a new view for improving the machining precision of heavy-duty machine tools. Full article
(This article belongs to the Section Physical Sensors)
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22 pages, 831 KiB  
Article
Cost–Benefit Optimization of Structural Health Monitoring Sensor Networks
by Giovanni Capellari, Eleni Chatzi and Stefano Mariani
Sensors 2018, 18(7), 2174; https://doi.org/10.3390/s18072174 - 6 Jul 2018
Cited by 50 | Viewed by 6236
Abstract
Structural health monitoring (SHM) allows the acquisition of information on the structural integrity of any mechanical system by processing data, measured through a set of sensors, in order to estimate relevant mechanical parameters and indicators of performance. Herein we present a method to [...] Read more.
Structural health monitoring (SHM) allows the acquisition of information on the structural integrity of any mechanical system by processing data, measured through a set of sensors, in order to estimate relevant mechanical parameters and indicators of performance. Herein we present a method to perform the cost–benefit optimization of a sensor network by defining the density, type, and positioning of the sensors to be deployed. The effectiveness (benefit) of an SHM system may be quantified by means of information theory, namely through the expected Shannon information gain provided by the measured data, which allows the inherent uncertainties of the experimental process (i.e., those associated with the prediction error and the parameters to be estimated) to be accounted for. In order to evaluate the computationally expensive Monte Carlo estimator of the objective function, a framework comprising surrogate models (polynomial chaos expansion), model order reduction methods (principal component analysis), and stochastic optimization methods is introduced. Two optimization strategies are proposed: the maximization of the information provided by the measured data, given the technological, identifiability, and budgetary constraints; and the maximization of the information–cost ratio. The application of the framework to a large-scale structural problem, the Pirelli tower in Milan, is presented, and the two comprehensive optimization methods are compared. Full article
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15 pages, 5168 KiB  
Article
UV-Vis Spectroscopy: A New Approach for Assessing the Color Index of Transformer Insulating Oil
by Yang Sing Leong, Pin Jern Ker, M. Z. Jamaludin, Saifuddin M. Nomanbhay, Aiman Ismail, Fairuz Abdullah, Hui Mun Looe and Chin Kim Lo
Sensors 2018, 18(7), 2175; https://doi.org/10.3390/s18072175 - 6 Jul 2018
Cited by 50 | Viewed by 12616
Abstract
Monitoring the condition of transformer oil is considered to be one of the preventive maintenance measures and it is very critical in ensuring the safety as well as optimal performance of the equipment. Various oil properties and contents in oil can be monitored [...] Read more.
Monitoring the condition of transformer oil is considered to be one of the preventive maintenance measures and it is very critical in ensuring the safety as well as optimal performance of the equipment. Various oil properties and contents in oil can be monitored such as acidity, furanic compounds and color. The current method is used to determine the color index (CI) of transformer oil produces an error of 0.5 in measurement, has high risk of human handling error, additional expense such as sampling and transportations, and limited samples can be measured per day due to safety and health reasons. Therefore, this work proposes the determination of CI of transformer oil using ultraviolet-to-visible (UV-Vis) spectroscopy. Results show a good correlation between the CI of transformer oil and the absorbance spectral responses of oils from 300 nm to 700 nm. Modeled equations were developed to relate the CI of the oil with the cutoff wavelength and absorbance, and with the area under the curve from 360 nm to 600 nm. These equations were verified with another set of oil samples. The equation that describes the relationship between cutoff wavelength, absorbance and CI of the oil shows higher accuracy with root mean square error (RMSE) of 0.1961. Full article
(This article belongs to the Special Issue Sensors for Fault Detection)
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12 pages, 3137 KiB  
Article
Temperature Compensation of Elasto-Magneto-Electric (EME) Sensors in Cable Force Monitoring Using BP Neural Network
by Ru Zhang, Yuanfeng Duan, Yang Zhao and Xuan He
Sensors 2018, 18(7), 2176; https://doi.org/10.3390/s18072176 - 6 Jul 2018
Cited by 58 | Viewed by 4453
Abstract
Techniques based on the elasto-magnetic (EM) effect have been receiving increasing attention for their significant advantages in cable stress/force monitoring of in-service structures. Variations in ambient temperature affect the magnetic behaviors of steel components, causing errors in the sensor and measurement system results. [...] Read more.
Techniques based on the elasto-magnetic (EM) effect have been receiving increasing attention for their significant advantages in cable stress/force monitoring of in-service structures. Variations in ambient temperature affect the magnetic behaviors of steel components, causing errors in the sensor and measurement system results. Therefore, temperature compensation is essential. In this paper, the effect of temperature on the force monitoring of steel cables using smart elasto-magneto-electric (EME) sensors was investigated experimentally. A back propagation (BP) neural network method is proposed to obtain a direct readout of the applied force in the engineering environment, involving less computational complexity. On the basis of the data measured in the experiment, an improved BP neural network model was established. The test result shows that, over a temperature range of approximately −10 °C to 60 °C, the maximum relative error in the force measurement is within ±0.9%. A polynomial fitting method was also implemented for comparison. It is concluded that the method based on a BP neural network can be more reliable, effective and robust, and can be extended to temperature compensation of other similar sensors. Full article
(This article belongs to the Special Issue Magnetic Sensors)
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17 pages, 4514 KiB  
Article
Indoor Motion Detection Using Wi-Fi Channel State Information in Flat Floor Environments Versus in Staircase Environments
by Zehua Dong, Fangmin Li, Julang Ying and Kaveh Pahlavan
Sensors 2018, 18(7), 2177; https://doi.org/10.3390/s18072177 - 6 Jul 2018
Cited by 24 | Viewed by 4376
Abstract
Recently, Wi-Fi channel state information (CSI) motion detection systems have been widely researched for applications in human health care and security in flat floor environments. However, these systems disregard the indoor context, which is often complex and consists of unique features, such as [...] Read more.
Recently, Wi-Fi channel state information (CSI) motion detection systems have been widely researched for applications in human health care and security in flat floor environments. However, these systems disregard the indoor context, which is often complex and consists of unique features, such as staircases. Motion detection on a staircase is also meaningful and important for various applications, such as fall detection and intruder detection. In this paper, we present the difference in CSI motion detection in flat floor and staircase environments through analysing the radio propagation model and experiments in real settings. For comparison in the two environments, an indoor CSI motion detection system is proposed with several novel methods including correlation-based fusion, moving variance segmentation (MVS), Doppler spread spectrum to improve the system performance, and a correlation check to reduce the implementation cost. Compared with existing systems, our system is validated to have a better performance in both flat floor and staircase environments, and further utilized to verify the superior CSI motion detection performance in staircase environments versus flat floor environments. Full article
(This article belongs to the Section Remote Sensors)
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10 pages, 1858 KiB  
Article
Role of Carboxyl and Amine Termination on a Boron-Doped Diamond Solution Gate Field Effect Transistor (SGFET) for pH Sensing
by Shaili Falina, Sora Kawai, Nobutaka Oi, Hayate Yamano, Taisuke Kageura, Evi Suaebah, Masafumi Inaba, Yukihiro Shintani, Mohd Syamsul and Hiroshi Kawarada
Sensors 2018, 18(7), 2178; https://doi.org/10.3390/s18072178 - 6 Jul 2018
Cited by 15 | Viewed by 5266
Abstract
In this paper, we report on the effect of carboxyl- and amine terminations on a boron-doped diamond surface (BDD) in relation to pH sensitivity. Carboxyl termination was achieved by anodization oxidation in Carmody buffer solution (pH 7). The carboxyl-terminated diamond surface was exposed [...] Read more.
In this paper, we report on the effect of carboxyl- and amine terminations on a boron-doped diamond surface (BDD) in relation to pH sensitivity. Carboxyl termination was achieved by anodization oxidation in Carmody buffer solution (pH 7). The carboxyl-terminated diamond surface was exposed to nitrogen radicals to generate an amine-terminated surface. The pH sensitivity of the carboxyl- and amine-terminated surfaces was measured from pH 2 to pH 12. The pH sensitivities of the carboxyl-terminated surface at low and high pH are 45 and 3 mV/pH, respectively. The pH sensitivity after amine termination is significantly higher—the pH sensitivities at low and high pH are 65 and 24 mV/pH, respectively. We find that the negatively-charged surface properties of the carboxyl-terminated surface due to ionization of –COOH causes very low pH detection in the high pH region (pH 7–12). In the case of the amine-terminated surface, the surface properties are interchangeable in both acidic and basic solutions; therefore, we observed pH detection at both low and high pH regions. The results presented here may provide molecular-level understanding of surface properties with charged ions in pH solutions. The understanding of these surface terminations on BDD substrate may be useful to design diamond-based biosensors. Full article
(This article belongs to the Section Biosensors)
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13 pages, 3175 KiB  
Article
A Non-Label and Enzyme-Free Sensitive Detection Method for Thrombin Based on Simulation-Assisted DNA Assembly
by Yingying Zhang, Luhui Wang, Yanan Wang and Yafei Dong
Sensors 2018, 18(7), 2179; https://doi.org/10.3390/s18072179 - 6 Jul 2018
Cited by 8 | Viewed by 4346
Abstract
Taking advantage of the high selectivity of aptamers and enzyme-free catalyzed hairpin assembly (CHA) amplification strategy, we herein describe a label-free and enzyme-free sensitive fluorescent and colorimetric strategy for thrombin detection in this paper. In the presence of target, the corresponding aptamer of [...] Read more.
Taking advantage of the high selectivity of aptamers and enzyme-free catalyzed hairpin assembly (CHA) amplification strategy, we herein describe a label-free and enzyme-free sensitive fluorescent and colorimetric strategy for thrombin detection in this paper. In the presence of target, the corresponding aptamer of the partial dsDNA probes will bind to the target and liberate the initiation strand, which is artfully designed as the “on” switch for hairpin assembly. Moreover, the displaced initiation strand partakes in a multi-cycle process and produces numerous G-quadruplexes, which have a remarkable enhancement in fluorescent/colorimetric signal from NMM (N-methyl-mesoporphyrin IX) and TMB (3,3′,5,5′-tetramethylbenzidine), respectively. The proposed amplification strategy for thrombin detection is of high sensitivity, down to 2.4 pM, and also achieves colorimetric signals that are able to be distinguished by naked eye. More importantly, the thermodynamics of interacting DNA strands used in our work, and the process of toehold strand displacement-driven assembly are simulated before biological testing, verifying the feasibility theoretically, and simplifying the subsequent actual experiments. Therefore, our approach and simulation have a certain potential application in biomarker detection and quantitatively monitor for disease diagnosis. Full article
(This article belongs to the Special Issue Label-Free Biosensors)
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11 pages, 2018 KiB  
Article
An Electronic Nose Based Method for the Discrimination of Weathered Petroleum-Derived Products
by María José Aliaño-González, Marta Ferreiro-González, Gerardo F. Barbero, Jesús Ayuso, José A. Álvarez, Miguel Palma and Carmelo G. Barroso
Sensors 2018, 18(7), 2180; https://doi.org/10.3390/s18072180 - 6 Jul 2018
Cited by 19 | Viewed by 3662
Abstract
In recent years pollution due to hydrocarbon spills has increased markedly as a result of the numerous advances in technologies and industrial processes. Anthropogenic activities (accidental or illegal) are responsible for most of these incidents. In some cases, the spills are not detected [...] Read more.
In recent years pollution due to hydrocarbon spills has increased markedly as a result of the numerous advances in technologies and industrial processes. Anthropogenic activities (accidental or illegal) are responsible for most of these incidents. In some cases, the spills are not detected at the moment they occur and the contaminants are subjected to different degradation phenomena that may change the chemical composition of the hydrocarbon over time. An incorrect or ineffective identification of the spill could lead to significant consequences, bearing in mind that most spills are hazardous to the environment. In the present work the capacity of the analytical technique based on the Electronic Nose (eNose) combined with chemometrics in the identification and discrimination of different weathered petroleum-derived products (PDPs) was studied. Different volumes (40 μL and 80 μL) of PDPs (gasoline, diesel, and paraffin) were poured onto different supports (wood, cork, paper, and cotton sheet) and subjected to a natural weathering process by evaporation for one month. The porosity of the support was also studied. The application of linear discriminant analysis allowed the full discrimination of the samples according to the presence/absence of PDP and a 97.7% of correct discrimination of the different PDPs regardless of the weathering time, support or volume used. The results show that the system is capable of detecting and discriminating the presence of petroleum-derived products in any of the situations studied. Full article
(This article belongs to the Section Chemical Sensors)
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10 pages, 1711 KiB  
Article
Spectral Imaging Analysis for Ultrasensitive Biomolecular Detection Using Gold-Capped Nanowire Arrays
by Yi-Hsin Tai, Po-Han Fu, Kuang-Li Lee and Pei-Kuen Wei
Sensors 2018, 18(7), 2181; https://doi.org/10.3390/s18072181 - 6 Jul 2018
Cited by 7 | Viewed by 4314
Abstract
A spectral integration combined with a threshold method for the analysis of spectral scanning surface plasmon resonance (SPR) images can significantly increase signal recognition at low concentration of antibody solution. The 12-well SPR sensing plates consisted of gold-capped nanowire arrays with 500-nm period, [...] Read more.
A spectral integration combined with a threshold method for the analysis of spectral scanning surface plasmon resonance (SPR) images can significantly increase signal recognition at low concentration of antibody solution. The 12-well SPR sensing plates consisted of gold-capped nanowire arrays with 500-nm period, 80-nm linewidth and 50-nm gold thickness which were used for generating multiple SPR images. A threshold method is introduced to eliminate background noises in spectral scanning images. Combining spectral integration and the threshold method, the detection limit of antibody concentration was 1.23 ng/mL. Using multiple-well SPR sensing plates and the proposed analytical method, multiple kinetic responses with spectral and spatial information on different sensing areas can be sensitively measured. Full article
(This article belongs to the Special Issue Label-free Optical Nanobiosensors)
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13 pages, 5690 KiB  
Article
Dynamic Deflection of a Railroad Sleeper from the Coupled Measurements of Acceleration and Strain
by Sung-Ho Joh, Katherine Magno and Sung Ho Hwang
Sensors 2018, 18(7), 2182; https://doi.org/10.3390/s18072182 - 6 Jul 2018
Cited by 13 | Viewed by 5551
Abstract
Dynamic deflection of a railroad sleeper works as an indicator of ballast stiffness, reflecting the health conditions of a ballast track. However, difficulty exists in measuring dynamic deflection of a railroad sleeper by conventional deflection transducers such as a linear variable differential transformer [...] Read more.
Dynamic deflection of a railroad sleeper works as an indicator of ballast stiffness, reflecting the health conditions of a ballast track. However, difficulty exists in measuring dynamic deflection of a railroad sleeper by conventional deflection transducers such as a linear variable differential transformer (LVDT) or a potentiometer. This is because a fixed reference point is unattainable due to ground vibrations during train passage. In this paper, a patented signal processing technique for evaluation of pseudo-deflection is presented to recover dynamic deflection of a railroad sleeper using a coupled measurement of acceleration and strain at the concrete sleeper. The presented technique combines high-frequency deflections calculated from double integration of acceleration and low-frequency deflections determined from strains. Validity of the combined deflections was shown by the deflections measured with a camera target on a concrete sleeper, captured by a high-resolution DSLR camera with superb video capturing features and processed by computer vision techniques, such as Canny edge detection and Blob analysis. Full article
(This article belongs to the Section Physical Sensors)
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25 pages, 2858 KiB  
Article
A Personalized Healthcare Monitoring System for Diabetic Patients by Utilizing BLE-Based Sensors and Real-Time Data Processing
by Ganjar Alfian, Muhammad Syafrudin, Muhammad Fazal Ijaz, M. Alex Syaekhoni, Norma Latif Fitriyani and Jongtae Rhee
Sensors 2018, 18(7), 2183; https://doi.org/10.3390/s18072183 - 6 Jul 2018
Cited by 209 | Viewed by 17956
Abstract
Current technology provides an efficient way of monitoring the personal health of individuals. Bluetooth Low Energy (BLE)-based sensors can be considered as a solution for monitoring personal vital signs data. In this study, we propose a personalized healthcare monitoring system by utilizing a [...] Read more.
Current technology provides an efficient way of monitoring the personal health of individuals. Bluetooth Low Energy (BLE)-based sensors can be considered as a solution for monitoring personal vital signs data. In this study, we propose a personalized healthcare monitoring system by utilizing a BLE-based sensor device, real-time data processing, and machine learning-based algorithms to help diabetic patients to better self-manage their chronic condition. BLEs were used to gather users’ vital signs data such as blood pressure, heart rate, weight, and blood glucose (BG) from sensor nodes to smartphones, while real-time data processing was utilized to manage the large amount of continuously generated sensor data. The proposed real-time data processing utilized Apache Kafka as a streaming platform and MongoDB to store the sensor data from the patient. The results show that commercial versions of the BLE-based sensors and the proposed real-time data processing are sufficiently efficient to monitor the vital signs data of diabetic patients. Furthermore, machine learning–based classification methods were tested on a diabetes dataset and showed that a Multilayer Perceptron can provide early prediction of diabetes given the user’s sensor data as input. The results also reveal that Long Short-Term Memory can accurately predict the future BG level based on the current sensor data. In addition, the proposed diabetes classification and BG prediction could be combined with personalized diet and physical activity suggestions in order to improve the health quality of patients and to avoid critical conditions in the future. Full article
(This article belongs to the Special Issue Wireless Body Area Networks and Connected Health)
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25 pages, 2968 KiB  
Article
Internet-Of-Things in Motion: A UAV Coalition Model for Remote Sensing in Smart Cities
by Adiel Ismail, Bigomokero Antoine Bagula and Emmanuel Tuyishimire
Sensors 2018, 18(7), 2184; https://doi.org/10.3390/s18072184 - 6 Jul 2018
Cited by 43 | Viewed by 4933
Abstract
Unmanned aerial vehicles (UAVs) or drones are increasingly used in cities to provide service tasks that are too dangerous, expensive or difficult for human beings. Drones are also used in cases where a task can be performed more economically and or more efficiently [...] Read more.
Unmanned aerial vehicles (UAVs) or drones are increasingly used in cities to provide service tasks that are too dangerous, expensive or difficult for human beings. Drones are also used in cases where a task can be performed more economically and or more efficiently than if done by humans. These include remote sensing tasks where drones can be required to form coalitions by pooling their resources to meet the service requirements at different locations of interest in a city. During such coalition formation, finding the shortest path from a source to a location of interest is key to efficient service delivery. For fixed-wing UAVs, Dubins curves can be applied to find the shortest flight path. When a UAV flies to a location of interest, the angle or orientation of the UAV upon its arrival is often not important. In such a case, a simplified version of the Dubins curve consisting of two instead of three parts can be used. This paper proposes a novel model for UAV coalition and an algorithm derived from basic geometry that generates a path derived from the original Dubins curve for application in remote sensing missions of fixed-wing UAVs. The algorithm is tested by incorporating it into three cooperative coalition formation algorithms. The performance of the model is evaluated by varying the number of types of resources and the sensor ranges of the UAVs to reveal the relevance and practicality of the proposed model. Full article
(This article belongs to the Special Issue Unmanned Aerial Vehicle Networks, Systems and Applications)
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29 pages, 2291 KiB  
Article
Toward a More Complete, Flexible, and Safer Speed Planning for Autonomous Driving via Convex Optimization
by Yu Zhang, Huiyan Chen, Steven L. Waslander, Tian Yang, Sheng Zhang, Guangming Xiong and Kai Liu
Sensors 2018, 18(7), 2185; https://doi.org/10.3390/s18072185 - 6 Jul 2018
Cited by 36 | Viewed by 25641
Abstract
In this paper, we present a complete, flexible and safe convex-optimization-based method to solve speed planning problems over a fixed path for autonomous driving in both static and dynamic environments. Our contributions are five fold. First, we summarize the most common constraints raised [...] Read more.
In this paper, we present a complete, flexible and safe convex-optimization-based method to solve speed planning problems over a fixed path for autonomous driving in both static and dynamic environments. Our contributions are five fold. First, we summarize the most common constraints raised in various autonomous driving scenarios as the requirements for speed planner developments and metrics to measure the capacity of existing speed planners roughly for autonomous driving. Second, we introduce a more general, flexible and complete speed planning mathematical model including all the summarized constraints compared to the state-of-the-art speed planners, which addresses limitations of existing methods and is able to provide smooth, safety-guaranteed, dynamic-feasible, and time-efficient speed profiles. Third, we emphasize comfort while guaranteeing fundamental motion safety without sacrificing the mobility of cars by treating the comfort box constraint as a semi-hard constraint in optimization via slack variables and penalty functions, which distinguishes our method from existing ones. Fourth, we demonstrate that our problem preserves convexity with the added constraints, thus global optimality of solutions is guaranteed. Fifth, we showcase how our formulation can be used in various autonomous driving scenarios by providing several challenging case studies in both static and dynamic environments. A range of numerical experiments and challenging realistic speed planning case studies have depicted that the proposed method outperforms existing speed planners for autonomous driving in terms of constraint type covered, optimality, safety, mobility and flexibility. Full article
(This article belongs to the Special Issue Advances on Vehicular Networks: From Sensing to Autonomous Driving)
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17 pages, 5311 KiB  
Article
An Outlier Detection Method Based on Mahalanobis Distance for Source Localization
by Qingli Yan, Jianfeng Chen and Lieven De Strycker
Sensors 2018, 18(7), 2186; https://doi.org/10.3390/s18072186 - 7 Jul 2018
Cited by 19 | Viewed by 5951
Abstract
This paper addresses the problem of localization accuracy degradation caused by outliers of the angle of arrival (AOA). The problem of outlier detection of the AOA is converted into the detection of the estimated source position sets, which are obtained by the proposed [...] Read more.
This paper addresses the problem of localization accuracy degradation caused by outliers of the angle of arrival (AOA). The problem of outlier detection of the AOA is converted into the detection of the estimated source position sets, which are obtained by the proposed division and greedy replacement method. The Mahalanobis distance based on robust mean and covariance matrix estimation method is then introduced to identify the outliers from the position sets. Finally, the weighted least squares method based on the reliable probabilities and distances is proposed for source localization. The simulation and experimental results show that the proposed method outperforms representative methods when unreliable AOAs are present. Full article
(This article belongs to the Special Issue Applications of Wireless Sensors in Localization and Tracking)
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15 pages, 6837 KiB  
Article
Determination of Intensity-Based Stochastic Models for Terrestrial Laser Scanners Utilising 3D-Point Clouds
by Daniel Wujanz, Mathias Burger, Felix Tschirschwitz, Tassilo Nietzschmann, Frank Neitzel and Thomas P. Kersten
Sensors 2018, 18(7), 2187; https://doi.org/10.3390/s18072187 - 7 Jul 2018
Cited by 36 | Viewed by 6465
Abstract
Recent advances in stochastic modelling of reflectorless rangefinders revealed an inherent relationship among raw intensity values and the corresponding precision of observed distances. In order to derive the stochastic properties of a terrestrial laser scanner’s (TLS) rangefinder, distances have to be observed repeatedly. [...] Read more.
Recent advances in stochastic modelling of reflectorless rangefinders revealed an inherent relationship among raw intensity values and the corresponding precision of observed distances. In order to derive the stochastic properties of a terrestrial laser scanner’s (TLS) rangefinder, distances have to be observed repeatedly. For this, the TLS of interest has to be operated in the so-called 1D-mode—a functionality which is offered only by a few manufacturers due to laser safety regulations. The article at hand proposes two methodologies to compute intensity-based stochastic models based on capturing geometric primitives in form of planar shapes utilising 3D-point clouds. At first the procedures are applied to a phase-based Zoller + Fröhlich IMAGER 5006h. The generated results are then evaluated by comparing the outcome to the parameters of a stochastic model which has been derived by means of measurements captured in 1D-mode. Another open research question is if intensity-based stochastic models are applicable for other rangefinder types. Therefore, one of the suggested procedures is applied to a Riegl VZ-400i impulse scanner, as well as a Leica ScanStation P40 TLS that deploys a hybrid rangefinder technology. The generated results successfully demonstrate alternative methods for the computation of intensity-based stochastic models as well as their transferability to other rangefinder technologies. Full article
(This article belongs to the Section Remote Sensors)
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21 pages, 7274 KiB  
Article
Real-Time Vehicle Roll Angle Estimation Based on Neural Networks in IoT Low-Cost Devices
by Javier García Guzmán, Lisardo Prieto González, Jonatan Pajares Redondo, Mat Max Montalvo Martínez and María Jesús L. Boada
Sensors 2018, 18(7), 2188; https://doi.org/10.3390/s18072188 - 7 Jul 2018
Cited by 30 | Viewed by 6095
Abstract
The high rate of vehicle-crash victims has a fatal economic and social impact in today’s societies. In particular, road crashes where heavy vehicles are involved cause more severe damage because they are prone to rollover. For this reason, many researches are focused on [...] Read more.
The high rate of vehicle-crash victims has a fatal economic and social impact in today’s societies. In particular, road crashes where heavy vehicles are involved cause more severe damage because they are prone to rollover. For this reason, many researches are focused on developing RSC Roll Stability Control (RSC) systems. Concerning the design of RSC systems with an adequate performance, it is mandatory to know the dynamics of the vehicle. The main problem arises from the lack of ability to directly capture several required dynamic vehicle variables, such as roll angle, from low-cost sensors. Previous studies demonstrate that low-cost sensors can provide data in real-time with the required precision and reliability. Even more, other research works indicate that neural networks are efficient mechanisms to estimate roll angle. Nevertheless, it is necessary to assess that the fusion of data coming from low-cost devices and estimations provided by neural networks can fulfill hard real-time processing constraints, achieving high level of accuracy during circulation of a vehicle in real situations. In order to address this issue, this study has two main goals: (1) Design and develop an IoT based architecture, integrating ANN in low cost kits with different hardware architectures in order to estimate under real-time constraints the vehicle roll angle. This architecture is able to work under high dynamic conditions, by following specific best practices and considerations during its design; (2) assess that the IoT architecture deployed in low-cost experimental kits achieve the hard real-time performance constraints estimating the roll angle with the required calculation accuracy. To fulfil these objectives, an experimental environment was set up, composed of a van with two set of low-cost kits, one including a Raspberry Pi 3 Model Band the other having an Intel Edison System on Chip linked to a SparkFun 9 Degrees of Freedom module. This experimental environment be tested in different maneuvers for comparison purposes. Neural networks embedded in low-cost sensor kits provide roll angle estimations highly approximated to real values. Even more, Intel Edison and Raspberry Pi 3 Model B have enough computing capabilities to successfully run roll angle estimation based on neural networks to determine rollover risk situations, fulfilling real-time operation restrictions stated for this problem. Full article
(This article belongs to the Special Issue Sensor Signal and Information Processing)
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18 pages, 2707 KiB  
Article
Benefits and Limitations of the Record and Replay Approach for GNSS Receiver Performance Assessment in Harsh Scenarios
by Calogero Cristodaro, Laura Ruotsalainen and Fabio Dovis
Sensors 2018, 18(7), 2189; https://doi.org/10.3390/s18072189 - 7 Jul 2018
Cited by 18 | Viewed by 6504
Abstract
Global navigation satellite systems play a significant role in the development of intelligent transport systems, where the estimation of the vehicle’s position is a key element. However, in strongly constrained environments such as city centers, the definition of quality metrics and the assessment [...] Read more.
Global navigation satellite systems play a significant role in the development of intelligent transport systems, where the estimation of the vehicle’s position is a key element. However, in strongly constrained environments such as city centers, the definition of quality metrics and the assessment of positioning performances are challenges to be addressed. Due to the variability of different urban scenarios, the modeling of the dynamics as well as the architecture of the positioning platform, which might embed other sensors and aiding means to the GNSS unit, make it hard to define unambiguous positioning metrics. Performance assessment through analytical models and simulators can be ineffective in terms of cost, complexity, and general validity and scalability of the results. This paper shows how a record and replay approach can be an efficient solution to grant fidelity to a realistic scenario. This work discusses advantages and disadvantages with emphasis on the case study of harsh scenarios. Such an approach requires proper data collections that allow the replay phase to test the GNSS-based positioning terminals. This paper presents the results obtained on a set of field tests related to different scenarios, selected as representative for the key performance indicators assessment. Full article
(This article belongs to the Collection Positioning and Navigation)
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13 pages, 431 KiB  
Article
A Dynamic Estimation of Service Level Based on Fuzzy Logic for Robustness in the Internet of Things
by Bing Jia, Lifei Hao, Chuxuan Zhang and Dong Chen
Sensors 2018, 18(7), 2190; https://doi.org/10.3390/s18072190 - 7 Jul 2018
Cited by 9 | Viewed by 3635
Abstract
The Internet of things (IoT) technology is developing rapidly, and the IoT services are penetrating broadly into every aspect of people’s lives. As the large amount of services grows dramatically, how to discover and select the best services dynamically to satisfy the actual [...] Read more.
The Internet of things (IoT) technology is developing rapidly, and the IoT services are penetrating broadly into every aspect of people’s lives. As the large amount of services grows dramatically, how to discover and select the best services dynamically to satisfy the actual needs of users in the IoT service set, the elements of which have the same function, is an unavoidable issue. Therefore, for the robustness of the IoT system, evaluating the quality level of the IoT service to provide a reference for the users choosing the most appropriate service has become a hot topic. Most of the current methods just use some static data to evaluate the quality of the service and ignore the dynamic changing trend of the service performance. In this paper, an estimation mechanism for the quality level of the IoT service based on fuzzy logic is conducted to grade the quality of the service. Specifically, the comprehensive factors are taken into account according to the defined level changing rules and the effect of the service in the previous execution process, so that it can provide users with an effective reference. Experiments are carried out by using a simulated service set. It is shown that the proposed algorithm can estimate the quality level of the service more comprehensively and reasonably, which is evidently superior to the other two common methods, i.e., the estimating method by a Randomization Test (RT) and the estimating method by a Single Test in Steps (STS). Full article
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10 pages, 4135 KiB  
Article
Research on a Fast-Response Thermal Conductivity Sensor Based on Carbon Nanotube Modification
by Hongquan Zhang, Bin Shen, Wenbin Hu and Xinlei Liu
Sensors 2018, 18(7), 2191; https://doi.org/10.3390/s18072191 - 7 Jul 2018
Cited by 15 | Viewed by 5073
Abstract
Aiming at solving the slow-response problem of traditional bead-type thermal conductivity gas sensors, a fast-response thermal conductivity gas sensor can be made by using multiwalled carbon nanotubes (MWNTs), combined with the technology of carrier modification, to modify the performance of the sensor carrier. [...] Read more.
Aiming at solving the slow-response problem of traditional bead-type thermal conductivity gas sensors, a fast-response thermal conductivity gas sensor can be made by using multiwalled carbon nanotubes (MWNTs), combined with the technology of carrier modification, to modify the performance of the sensor carrier. The carrier material, granular nanoscale γ-Al2O3/ZrO2, was synthesized by chemical precipitation, and its particle size was found to be 50–70 nm through SEM. After the carrier material was wet-incorporated into carbon nanotubes, the composite carrier γ-Al2O3/ZrO2/MWNTs was obtained. The results show that the designed thermal conductivity sensor has a fast response to methane gas, with a 90% response time of 7 s and a recovery time of 16 s. There is a good linear relationship between the sensor output and CH4 gas concentration, with an average sensitivity of 1.15 mV/1% CH4. Thus, the response speed of a thermal conductivity sensor can be enhanced by doping carbon nanotubes into γ-Al2O3/ZrO2. Full article
(This article belongs to the Special Issue Functional Materials for the Applications of Advanced Gas Sensors)
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10 pages, 6640 KiB  
Article
Investigation of A Slow-Light Enhanced Near-Infrared Absorption Spectroscopic Gas Sensor, Based on Hollow-Core Photonic Band-Gap Fiber
by Zhi-Fa Wu, Chuan-Tao Zheng, Zhi-Wei Liu, Dan Yao, Wen-Xue Zheng, Yi-Ding Wang, Fei Wang and Da-Ming Zhang
Sensors 2018, 18(7), 2192; https://doi.org/10.3390/s18072192 - 7 Jul 2018
Cited by 13 | Viewed by 3808
Abstract
Generic modeling and analysis of a slow-light enhanced absorption spectroscopic gas sensor was proposed, using a mode-tuned, hollow-core, photonic band-gap fiber (HC-PBF) as an absorption gas cell. Mode characteristics of the un-infiltrated and infiltrated HC-PBF and gas absorption enhancement of the infiltrated HC-PBF [...] Read more.
Generic modeling and analysis of a slow-light enhanced absorption spectroscopic gas sensor was proposed, using a mode-tuned, hollow-core, photonic band-gap fiber (HC-PBF) as an absorption gas cell. Mode characteristics of the un-infiltrated and infiltrated HC-PBF and gas absorption enhancement of the infiltrated HC-PBF were analyzed. A general rule of microfluidic parameters for targeting different gas species in the near-infrared was obtained. Ammonia (NH3) was used as an example to explore the effects of slow light on gas detection. The second harmonic (2f) signal and Allan deviation were theoretically investigated based on the derived formulations. Full article
(This article belongs to the Section Physical Sensors)
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18 pages, 744 KiB  
Article
Integration of Low-Cost GNSS and Monocular Cameras for Simultaneous Localization and Mapping
by Xiao Chen, Weidong Hu, Lefeng Zhang, Zhiguang Shi and Maisi Li
Sensors 2018, 18(7), 2193; https://doi.org/10.3390/s18072193 - 7 Jul 2018
Cited by 32 | Viewed by 5682
Abstract
Low-cost Global Navigation Satellite System (GNSS) receivers and monocular cameras are widely used in daily activities. The complementary nature of these two devices is ideal for outdoor navigation. In this paper, we investigate the integration of GNSS and monocular camera measurements in a [...] Read more.
Low-cost Global Navigation Satellite System (GNSS) receivers and monocular cameras are widely used in daily activities. The complementary nature of these two devices is ideal for outdoor navigation. In this paper, we investigate the integration of GNSS and monocular camera measurements in a simultaneous localization and mapping system. The proposed system first aligns the coordinates between two sensors. Subsequently, the measurements are fused by an optimization-based scheme. Our system can function in real-time and obtain the absolute position, scale, and attitude of the vehicle. It achieves a high accuracy without a preset map and also has the capability to work with a preset map. The system can easily be extended to create other forms of maps or for other types of cameras. Experimental results on a popular public dataset are presented to validate the performance of the proposed system. Full article
(This article belongs to the Special Issue Sensor Fusion and Novel Technologies in Positioning and Navigation)
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39 pages, 3767 KiB  
Review
Review of Three-Dimensional Human-Computer Interaction with Focus on the Leap Motion Controller
by Daniel Bachmann, Frank Weichert and Gerhard Rinkenauer
Sensors 2018, 18(7), 2194; https://doi.org/10.3390/s18072194 - 7 Jul 2018
Cited by 126 | Viewed by 25981
Abstract
Modern hardware and software development has led to an evolution of user interfaces from command-line to natural user interfaces for virtual immersive environments. Gestures imitating real-world interaction tasks increasingly replace classical two-dimensional interfaces based on Windows/Icons/Menus/Pointers (WIMP) or touch metaphors. Thus, the purpose [...] Read more.
Modern hardware and software development has led to an evolution of user interfaces from command-line to natural user interfaces for virtual immersive environments. Gestures imitating real-world interaction tasks increasingly replace classical two-dimensional interfaces based on Windows/Icons/Menus/Pointers (WIMP) or touch metaphors. Thus, the purpose of this paper is to survey the state-of-the-art Human-Computer Interaction (HCI) techniques with a focus on the special field of three-dimensional interaction. This includes an overview of currently available interaction devices, their applications of usage and underlying methods for gesture design and recognition. Focus is on interfaces based on the Leap Motion Controller (LMC) and corresponding methods of gesture design and recognition. Further, a review of evaluation methods for the proposed natural user interfaces is given. Full article
(This article belongs to the Section Physical Sensors)
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14 pages, 6570 KiB  
Article
A Compact Impact Rotary Motor Based on a Piezoelectric Tube Actuator with Helical Interdigitated Electrodes
by Liling Han, Huining Zhao, Haojie Xia, Chengliang Pan, Yizhou Jiang, Weishi Li and Liandong Yu
Sensors 2018, 18(7), 2195; https://doi.org/10.3390/s18072195 - 7 Jul 2018
Cited by 14 | Viewed by 3417
Abstract
This paper presents a novel impact rotary motor based on a piezoelectric tube actuator with helical interdigitated electrodes which has a compact structure and high resolution. The assembled prototype motor has a maximum diameter of 15 mm and a length of 65 mm [...] Read more.
This paper presents a novel impact rotary motor based on a piezoelectric tube actuator with helical interdigitated electrodes which has a compact structure and high resolution. The assembled prototype motor has a maximum diameter of 15 mm and a length of 65 mm and works under a saw-shaped driving voltage. The LuGre friction model is adopted to analyze the rotary motion process of the motor in the dynamic simulations. From the experimental tests, the first torsional resonant frequency of the piezoelectric tube is 59.289 kHz with a free boundary condition. A series of experiments about the stepping characteristics of different driving voltages, duty cycles, and working frequencies are carried out by a laser Doppler vibrometer based on a fabricated prototype motor. The experimental results show that the prototype rotary motor can produce a maximum torsional angle of about 0.03° using a driving voltage of 480 Vp-p (peak-to-peak driving voltage) with a duty ratio of 0% under a small friction force of about 0.1 N. The motor can produce a maximum average angle of about 2.55 rad/s and a stall torque of 0.4 mN∙m at 8 kHz using a driving voltage of 640 Vp-p with a duty ratio of 0% under a large friction force of about 3.6 N. The prototype can be driven in forward and backward motion and is working in stick-slip mode at low frequencies and slip-slip mode at high frequencies. Full article
(This article belongs to the Section Physical Sensors)
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10 pages, 1980 KiB  
Article
Selective Monitoring of Oxyanion Mixtures by a Flow System with Raman Detection
by Félix Zapata, Fernando Ortega-Ojeda, Carmen García-Ruiz and Miguel González-Herráez
Sensors 2018, 18(7), 2196; https://doi.org/10.3390/s18072196 - 8 Jul 2018
Cited by 10 | Viewed by 4916
Abstract
Raman spectroscopy is a selective detection system scarcely applied for the flow analysis of solutions with the aim of detecting several compounds at once without a previous separation step. This work explores the potential of a portable Raman system in a flow system [...] Read more.
Raman spectroscopy is a selective detection system scarcely applied for the flow analysis of solutions with the aim of detecting several compounds at once without a previous separation step. This work explores the potential of a portable Raman system in a flow system for the selective detection of a mixture of seven oxyanions (carbonate, sulphate, nitrate, phosphate, chlorate, perchlorate, and thiosulphate). The specific bands of these compounds (symmetric stretching Raman active vibrations of carbonate at 1068 cm−1, nitrate at 1049 cm−1, thiosulphate at 998 cm−1, phosphate at 989 cm−1, sulphate at 982 cm−1, perchlorate at 935 cm−1, and chlorate at 932 cm−1) enabled their simultaneous detection in mixtures. Although the oxyanions’ limit of detection (LOD) was rather poor (in the millimolar range), this extremely simple system is very useful for the single-measurement detection of most of the oxyanions in mixtures, without requiring a previous separation step. In addition, quantitative determination of the desired oxyanion can be performed by means of the corresponding calibration line. These are important advantages for controlling in-line processes in industries like those manufacturing fertilizers, pharmaceuticals, chemicals, or food, among others. Full article
(This article belongs to the Special Issue Optical Biochemical Sensor Systems and Applications)
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11 pages, 2642 KiB  
Article
Decimeter-Level Geolocation Accuracy Updated by a Parametric Tropospheric Model with GF-3
by Wentao Wang, Jiayin Liu and Xiaolan Qiu
Sensors 2018, 18(7), 2197; https://doi.org/10.3390/s18072197 - 8 Jul 2018
Cited by 8 | Viewed by 4264
Abstract
GaoFen-3 (GF-3) is a multi-polarization C-band synthetic aperture radar (SAR) satellite in China with a resolution of up to 1 m. Up to now, the geolocation accuracy of GF-3 could be improved to 3 m. According to the current study, there still exist [...] Read more.
GaoFen-3 (GF-3) is a multi-polarization C-band synthetic aperture radar (SAR) satellite in China with a resolution of up to 1 m. Up to now, the geolocation accuracy of GF-3 could be improved to 3 m. According to the current study, there still exist meter-level geolocation residuals caused by atmospheric path delay after compensating with a static tropospheric model. In this paper, we compensate the residuals with the sophisticated tropospheric model based on real meteorological data. The experimental results show that the tropospheric model has an accuracy on the millimeter level, which can increase GF-3’s geolocation accuracy to several decimeters compared with the static tropospheric model. Full article
(This article belongs to the Special Issue First Experiences with Chinese Gaofen-3 SAR Sensor)
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23 pages, 8939 KiB  
Article
A Cost-Effective IoT System for Monitoring Indoor Radon Gas Concentration
by Oscar Blanco-Novoa, Tiago M. Fernández-Caramés, Paula Fraga-Lamas and Luis Castedo
Sensors 2018, 18(7), 2198; https://doi.org/10.3390/s18072198 - 8 Jul 2018
Cited by 68 | Viewed by 11238
Abstract
Radon is a noble gas originating from the radioactive decay chain of uranium or thorium. Most radon emanates naturally from the soil and from some building materials, so it can be found in many places around the world, in particular in regions with [...] Read more.
Radon is a noble gas originating from the radioactive decay chain of uranium or thorium. Most radon emanates naturally from the soil and from some building materials, so it can be found in many places around the world, in particular in regions with soils containing granite or slate. It is almost impossible for a person to detect radon gas without proper tools, since it is invisible, odorless, tasteless and colorless. The problem is that a correlation has been established between the presence of high radon gas concentrations and the incidence of lung cancer. In fact, the World Health Organization (WHO) has stated that the exposure to radon is the second most common cause of lung cancer after smoking, and it is the primary cause of lung cancer among people who have never smoked. Although there are commercial radon detectors, most of them are either expensive or provide very limited monitoring capabilities. To tackle such an issue, this article presents a cost-effective IoT radon gas remote monitoring system able to obtain accurate concentration measurements. It can also trigger events to prevent dangerous situations and to warn users about them. Moreover, the proposed solution can activate mitigation devices (e.g., forced ventilation) to decrease radon gas concentration. In order to show its performance, the system was evaluated in three different scenarios corresponding to representative buildings in Galicia (Spain), a region where high radon gas concentrations are common due to the composition of the soil. In addition, the influence of using external hardware (i.e., WiFi transceivers and an embedded System-on-Chip (SoC)) next to the radon gas sensor is studied, concluding that, in the tested scenarios, they do not interfere with the measurements. Full article
(This article belongs to the Special Issue Intelligent Sensor Systems for Environmental Monitoring)
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17 pages, 4479 KiB  
Article
A Novel Damage Indicator Based on the Electromechanical Impedance Principle for Structural Damage Identification
by Pin Zhou, Dansheng Wang and Hongping Zhu
Sensors 2018, 18(7), 2199; https://doi.org/10.3390/s18072199 - 8 Jul 2018
Cited by 19 | Viewed by 3366
Abstract
This paper presents a novel structural damage detection indicator, i.e., fourth-order voltage statistical moment (FVSM) based on the electromechanical impedance (EMI) principle, and then proposes a two-step damage detection method based on the novel indicator and a differential evolution algorithm (DEA). In this [...] Read more.
This paper presents a novel structural damage detection indicator, i.e., fourth-order voltage statistical moment (FVSM) based on the electromechanical impedance (EMI) principle, and then proposes a two-step damage detection method based on the novel indicator and a differential evolution algorithm (DEA). In this study, several lead zirconate titanate (PZT) sensors bonded to an experimental steel beam were utilized to acquire the time-domain voltage responses. On this basis, the fourth-order voltage statistical moments (FVSMs) of the voltage responses are computed to locate the damage element in the detected structure, and the proposed damage detection method is utilized to quantify the damage. In addition, theoretical PZT voltage responses are also calculated based on the piezoelectric theory and the spectral element method (SEM). Experimental results verify the accuracy of the theoretical voltage values and the effectiveness of the proposed damage indicator. Results indicate that the FVSM is effective in locating the damage element. Integrated with DEA, the proposed technique is capable of quantifying damage. Full article
(This article belongs to the Section Physical Sensors)
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17 pages, 18893 KiB  
Article
CMOS Capacitive Fingerprint Sensor Based on Differential Sensing Circuit with Noise Cancellation
by Hossam Hassan and Hyung-Won Kim
Sensors 2018, 18(7), 2200; https://doi.org/10.3390/s18072200 - 8 Jul 2018
Cited by 19 | Viewed by 10556
Abstract
In this paper, we introduce a differential sensing technique for CMOS capacitive fingerprint detection. It employs a new capacitive-sensing cell structure with charge sharing detection and readout circuit. The proposed technique also can eliminate the effect of parasitic capacitances by employing parasitic insensitive [...] Read more.
In this paper, we introduce a differential sensing technique for CMOS capacitive fingerprint detection. It employs a new capacitive-sensing cell structure with charge sharing detection and readout circuit. The proposed technique also can eliminate the effect of parasitic capacitances by employing parasitic insensitive switched-capacitor structure and so increases the sensitivity even under severe noisy conditions. It can also overcome the performance degradation caused by various conditions of finger surface by using a differential integrator and adjusting its number of integrations. In addition, the proposed architecture allows parallel detection of all sensing channels. It can, therefore, substantially speed up the detection process compared with conventional architectures. We implemented a prototype fingerprint sensor chip with an array of 20 × 16 sensor cells using a 130 nm CMOS process. Simulation experiments demonstrated that the proposed architecture provided an SNR gain of 54 dB, whereas a conventional single line sensing gives an SNR gain of only 13 dB. Full article
(This article belongs to the Section Physical Sensors)
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18 pages, 3770 KiB  
Article
Cholesterol-Bearing Fluorescent G-Quadruplex Potassium Probes for Anchoring at the Langmuir Monolayer and Cell Membrane
by Angelika Świtalska, Anna Dembska, Agnieszka Fedoruk-Wyszomirska and Bernard Juskowiak
Sensors 2018, 18(7), 2201; https://doi.org/10.3390/s18072201 - 9 Jul 2018
Cited by 8 | Viewed by 4796
Abstract
The purpose of the present work was to design, synthesize and spectrally characterize cholesterol-anchored fluorescent oligonucleotide probes (Ch(F-TBA-T), Ch(py-TBA-py)), based on G-quadruplexes, which were able to incorporate into a lipid structure (Langmuir monolayer, living cell membrane). The probes, based on the thrombin-binding aptamer [...] Read more.
The purpose of the present work was to design, synthesize and spectrally characterize cholesterol-anchored fluorescent oligonucleotide probes (Ch(F-TBA-T), Ch(py-TBA-py)), based on G-quadruplexes, which were able to incorporate into a lipid structure (Langmuir monolayer, living cell membrane). The probes, based on the thrombin-binding aptamer (TBA) sequence, were labeled with fluorescent dyes which enabled simultaneous monitoring of the formation of G-quadruplex structures and visualization of probe incorporation into the cellular membrane. The combinations of fluorophores used included fluorescence resonance energy transfer (FRET) and excimer emission approaches. The structural changes of the probes upon binding with K+ or Na+ ions were monitored with fluorescence techniques. These systems showed a very high binding preference for K+ over Na+ ions. The use of confocal fluorescence microscopy indicated successful anchoring of the cholesterol-bearing fluorescent probes to the living cell membrane. These structurally simple cholesterol-based fluorescent probes have good potential for opening up new and exciting opportunities in the field of biosensors; e.g., in vivo detection of K+ ions. Full article
(This article belongs to the Special Issue Spectroscopy Based Sensors)
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14 pages, 1000 KiB  
Article
On-Device Learning of Indoor Location for WiFi Fingerprint Approach
by Marco Aurelio Nuño-Maganda, Hiram Herrera-Rivas, Cesar Torres-Huitzil, Heidy Marisol Marín-Castro and Yuriria Coronado-Pérez
Sensors 2018, 18(7), 2202; https://doi.org/10.3390/s18072202 - 9 Jul 2018
Cited by 21 | Viewed by 4061
Abstract
Indoor positioning is a recent technology that has gained interest in industry and academia thanks to the promising results of locating objects, people or robots accurately in indoor environments. One of the utilized technologies is based on algorithms that process the Received Signal [...] Read more.
Indoor positioning is a recent technology that has gained interest in industry and academia thanks to the promising results of locating objects, people or robots accurately in indoor environments. One of the utilized technologies is based on algorithms that process the Received Signal Strength Indicator (RSSI) in order to infer location information without previous knowledge of the distribution of the Access Points (APs) in the area of interest. This paper presents the design and implementation of an indoor positioning mobile application, which allows users to capture and build their own RSSI maps by off-line training of a set of selected classifiers and using the models generated to obtain the current indoor location of the target device. In an early experimental and design stage, 59 classifiers were evaluated, using data from proposed indoor scenarios. Then, from the tested classifiers in the early stage, only the top-five classifiers were integrated with the proposed mobile indoor positioning, based on the accuracy obtained for the test scenarios. The proposed indoor application achieves high classification rates, above 89%, for at least 10 different locations in indoor environments, where each location has a minimum separation of 0.5 m. Full article
(This article belongs to the Section Sensor Networks)
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20 pages, 1299 KiB  
Article
Automatic Annotation for Human Activity Recognition in Free Living Using a Smartphone
by Federico Cruciani, Ian Cleland, Chris Nugent, Paul McCullagh, Kåre Synnes and Josef Hallberg
Sensors 2018, 18(7), 2203; https://doi.org/10.3390/s18072203 - 9 Jul 2018
Cited by 53 | Viewed by 7890
Abstract
Data annotation is a time-consuming process posing major limitations to the development of Human Activity Recognition (HAR) systems. The availability of a large amount of labeled data is required for supervised Machine Learning (ML) approaches, especially in the case of online and personalized [...] Read more.
Data annotation is a time-consuming process posing major limitations to the development of Human Activity Recognition (HAR) systems. The availability of a large amount of labeled data is required for supervised Machine Learning (ML) approaches, especially in the case of online and personalized approaches requiring user specific datasets to be labeled. The availability of such datasets has the potential to help address common problems of smartphone-based HAR, such as inter-person variability. In this work, we present (i) an automatic labeling method facilitating the collection of labeled datasets in free-living conditions using the smartphone, and (ii) we investigate the robustness of common supervised classification approaches under instances of noisy data. We evaluated the results with a dataset consisting of 38 days of manually labeled data collected in free living. The comparison between the manually and the automatically labeled ground truth demonstrated that it was possible to obtain labels automatically with an 80–85% average precision rate. Results obtained also show how a supervised approach trained using automatically generated labels achieved an 84% f-score (using Neural Networks and Random Forests); however, results also demonstrated how the presence of label noise could lower the f-score up to 64–74% depending on the classification approach (Nearest Centroid and Multi-Class Support Vector Machine). Full article
(This article belongs to the Special Issue Annotation of User Data for Sensor-Based Systems)
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35 pages, 3758 KiB  
Article
Reset Controller Design Based on Error Minimization for a Lane Change Maneuver
by Miguel Cerdeira, Pablo Falcón, Emma Delgado and Antonio Barreiro
Sensors 2018, 18(7), 2204; https://doi.org/10.3390/s18072204 - 9 Jul 2018
Cited by 4 | Viewed by 4036
Abstract
An intelligent vehicle must face a wide variety of situations ranging from safe and comfortable to more aggressive ones. Smooth maneuvers are adequately addressed by means of linear control, whereas more aggressive maneuvers are tackled by nonlinear techniques. Likewise, there exist intermediate scenarios [...] Read more.
An intelligent vehicle must face a wide variety of situations ranging from safe and comfortable to more aggressive ones. Smooth maneuvers are adequately addressed by means of linear control, whereas more aggressive maneuvers are tackled by nonlinear techniques. Likewise, there exist intermediate scenarios where the required responses are smooth but constrained in some way (rise time, settling time, overshoot). Due to the existence of the fundamental linear limitations, which impose restrictions on the attainable time-domain and frequency-domain performance, linear systems cannot provide smoothness while operating in compliance with the previous restrictions. For this reason, this article aims to explore the effects of reset control on the alleviation of these limitations for a lane change maneuver under a set of demanding design conditions to guarantee a suitable ride quality and a swift response. To this end, several reset strategies are considered, determining the best reset condition to apply as well as the magnitude thereto. Concerning the reset condition that triggers the reset action, three strategies are considered: zero crossing of the controller input, fixed reset band and variable reset band. As far as the magnitude of the reset action is concerned, a full-reset technique is compared to a Lyapunov-based error minimization method to calculate the optimal reset percentage. The base linear controller subject to the reset action is searched via genetic algorithms. The proposed controllers are validated by means of CarSim. Full article
(This article belongs to the Section Intelligent Sensors)
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15 pages, 582 KiB  
Article
Energy-Efficient Multicast Service Delivery Exploiting Single Frequency Device-To-Device Communications in 5G New Radio Systems
by Sara Pizzi, Federica Rinaldi, Antonella Molinaro, Antonio Iera and Giuseppe Araniti
Sensors 2018, 18(7), 2205; https://doi.org/10.3390/s18072205 - 9 Jul 2018
Cited by 6 | Viewed by 4905
Abstract
The forthcoming fifth generation (5G) networks are claimed to deliver the large amount of traffic generated by the huge number of heterogeneous devices that constitute the Internet of Things (IoT). This unprecedented volume of both human- and machine-generated traffic to be managed imposes [...] Read more.
The forthcoming fifth generation (5G) networks are claimed to deliver the large amount of traffic generated by the huge number of heterogeneous devices that constitute the Internet of Things (IoT). This unprecedented volume of both human- and machine-generated traffic to be managed imposes 5G network operators to move the focus from throughput-optimized to energy-efficiency-optimized resource allocation solutions. Device-to-device (D2D) communications are recognized as an effective offloading technique that the 5G network can exploit to boost the capacity and energy efficiency of future 5G networks. In this paper, we design a technique to efficiently deliver multicast traffic in a 5G New Radio (NR) network by exploiting the benefits of D2D communication and single-frequency operation in order to improve the overall network energy efficiency. In the designed solution, the subset of devices in better channel conditions are served through a conventional multicast transmission, while cell-edge devices receive the multicast service from relay nodes that simultaneously transmit in D2D mode the same content. The dimension of the multicast serving area and the set of D2D connections to establish are chosen in order to maximize the overall network energy efficiency. Performed simulation results show the effectiveness of the proposed solution under varying frame configurations and number of multicast devices. Full article
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17 pages, 1053 KiB  
Article
Consensual Negotiation-Based Decision Making for Connected Appliances in Smart Home Management Systems
by Khac-Hoai Nam Bui, Jason J. Jung and David Camacho
Sensors 2018, 18(7), 2206; https://doi.org/10.3390/s18072206 - 9 Jul 2018
Cited by 20 | Viewed by 6114
Abstract
Recently, the concept of Internet of Agent has been introduced as a potential technology that pushes intelligence, data processing, analytics and communication capabilities down to the point where the data originates. In this paper, we introduce a novel approach for a Decentralized Home [...] Read more.
Recently, the concept of Internet of Agent has been introduced as a potential technology that pushes intelligence, data processing, analytics and communication capabilities down to the point where the data originates. In this paper, we introduce a novel approach for a Decentralized Home Energy Management System by applying the Internet of Agent concept. In particular, we first present an Internet of Agent framework in terms of sensing, communicating and collaborating among connected appliances. Then, the decentralized management based on consensual negotiation mechanism with several intelligent techniques are proposed for dynamic scheduling connected appliance. Specifically, by applying the Internet of Agent framework, connected appliances are regarded as smart agents that are able to make individual decisions by reaching agreement over the exchange of operations on competitive resources. Furthermore, in this study, the load balancing problem in which load shifting is able to reduce the electricity demand during peak hours is taken into account in order to emphasize the effectiveness of our approach. For the experiment, we develop a simulation of smart home environment to evaluate our approach using NetLogo, a tool which provides real-time analysis in the modeling and simulation domain of complex systems. Full article
(This article belongs to the Special Issue Smart Decision-Making)
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18 pages, 404 KiB  
Article
A Survey on the Roadmap to Mandate on Board Connectivity and Enable V2V-Based Vehicular Sensor Networks
by Barbara M. Masini, Alessandro Bazzi and Alberto Zanella
Sensors 2018, 18(7), 2207; https://doi.org/10.3390/s18072207 - 9 Jul 2018
Cited by 97 | Viewed by 7749
Abstract
Vehicles will soon be connected and will be interacting directly with each other and with the road infrastructure, bringing substantial benefits in terms of safety and traffic efficiency. The past decade has seen the development of different wireless access technologies for vehicle-to-everything (V2X) [...] Read more.
Vehicles will soon be connected and will be interacting directly with each other and with the road infrastructure, bringing substantial benefits in terms of safety and traffic efficiency. The past decade has seen the development of different wireless access technologies for vehicle-to-everything (V2X) communications and an extensive set of related use cases have been drafted, each with its own requirements. In this paper, focusing on short-range communications, we analyze the technical and economic motivations that are driving the development of new road users’ connectivity, discussing the international intentions to mandate on board devices for V2X communication. We also go in depth with the enabling wireless access technologies, from IEEE 802.11p to short-range Cellular-V2X and other complementary technologies, such as visible light communication (VLC) and millimeterWaves, up to hybrid communication and 5G. We conclude our survey with some performance comparison in urban realistic scenarios, underlying that the choice of the future enabling technology is not so easy to predict and mostly depends on mandatory laws at the international level. Full article
(This article belongs to the Special Issue Sensor Networks for Smart Roads)
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44 pages, 11729 KiB  
Review
A Review on Systems-Based Sensory Gloves for Sign Language Recognition State of the Art between 2007 and 2017
by Mohamed Aktham Ahmed, Bilal Bahaa Zaidan, Aws Alaa Zaidan, Mahmood Maher Salih and Muhammad Modi bin Lakulu
Sensors 2018, 18(7), 2208; https://doi.org/10.3390/s18072208 - 9 Jul 2018
Cited by 212 | Viewed by 21709
Abstract
Loss of the ability to speak or hear exerts psychological and social impacts on the affected persons due to the lack of proper communication. Multiple and systematic scholarly interventions that vary according to context have been implemented to overcome disability-related difficulties. Sign language [...] Read more.
Loss of the ability to speak or hear exerts psychological and social impacts on the affected persons due to the lack of proper communication. Multiple and systematic scholarly interventions that vary according to context have been implemented to overcome disability-related difficulties. Sign language recognition (SLR) systems based on sensory gloves are significant innovations that aim to procure data on the shape or movement of the human hand. Innovative technology for this matter is mainly restricted and dispersed. The available trends and gaps should be explored in this research approach to provide valuable insights into technological environments. Thus, a review is conducted to create a coherent taxonomy to describe the latest research divided into four main categories: development, framework, other hand gesture recognition, and reviews and surveys. Then, we conduct analyses of the glove systems for SLR device characteristics, develop a roadmap for technology evolution, discuss its limitations, and provide valuable insights into technological environments. This will help researchers to understand the current options and gaps in this area, thus contributing to this line of research. Full article
(This article belongs to the Section Physical Sensors)
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20 pages, 8101 KiB  
Article
Assessment of Retrieved N2O, NO2, and HF Profiles from the Atmospheric Infrared Ultraspectral Sounder Based on Simulated Spectra
by Hongmei Wang, Xiaoying Li, Jian Xu, Xingying Zhang, Shule Ge, Liangfu Chen, Yapeng Wang, Songyan Zhu, Jing Miao and Yidan Si
Sensors 2018, 18(7), 2209; https://doi.org/10.3390/s18072209 - 9 Jul 2018
Cited by 10 | Viewed by 4717
Abstract
The Atmospheric Infrared Ultraspectral Sounder (AIUS), the first high-resolution (0.02 cm−1) solar occultation sounder, aboard GF5, was launched in May 2018 from China. However, relevant studies about vertical profiles of atmospheric constituents based on its operational data were not conducted until [...] Read more.
The Atmospheric Infrared Ultraspectral Sounder (AIUS), the first high-resolution (0.02 cm−1) solar occultation sounder, aboard GF5, was launched in May 2018 from China. However, relevant studies about vertical profiles of atmospheric constituents based on its operational data were not conducted until half a year later. Due to an urgent need for Hin-orbit tests, the real spectra (called reference spectra hereafter) were substituted with simulated spectra calculated from the reference forward model (RFM) plus different random noises at different altitudes. In the generation process of the reference spectra for N2O, NO2, and HF species, ACE-FTS (Atmospheric Chemistry Experiment–Fourier Transform Spectrometer instrument on the SCISAT satellite) level 2 products replace corresponding profiles included in the atmospheric background profiles. The optimal estimation method is employed to extract N2O, NO2, and HF profiles in this study. Comparing the retrieved results with ACE-FTS level 2 products, the relative deviations for these three species are calculated. For N2O, the average relative deviation is less than 6% at altitudes below 25 km, while larger deviations are observed in the range of 25–45 km, with the maximum being at ~25%. Additionally, the difference for NO2 is less than 5% in the 20–45 km range, with a larger discrepancy found below 20 km and above 45 km; the maximum deviation reaches ±40%. For HF, the relative deviation is less than 6% for all tangent heights, implying satisfactory retrieval. The vertical resolution, averaging kernel, and number of degrees of freedom are used to assess the retrieval algorithm, which indicate that the retrieved information content is much more attributable to the reference spectra contribution than to the a priori profile. Finally, a large number of retrieval tests are performed for N2O, NO2, and HF in selected areas covering the Arctic region, northern middle latitude, tropics, southern middle latitude, and Antarctic region, and reliable results are obtained. Thus, to a great extent, the algorithm adopted in the AIUS system can process retrievals reliably and precisely. Full article
(This article belongs to the Section Remote Sensors)
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14 pages, 3647 KiB  
Article
Continuous and Real-Time Detection of Drinking-Water Pathogens with a Low-Cost Fluorescent Optofluidic Sensor
by João Simões and Tao Dong
Sensors 2018, 18(7), 2210; https://doi.org/10.3390/s18072210 - 10 Jul 2018
Cited by 36 | Viewed by 6275
Abstract
Growing access to tap water and consequent expansion of water distribution systems has created numerous challenges to maintaining water quality between the treatment node and final consumer. Despite all efforts to develop sustainable monitoring systems, there is still a lack of low cost, [...] Read more.
Growing access to tap water and consequent expansion of water distribution systems has created numerous challenges to maintaining water quality between the treatment node and final consumer. Despite all efforts to develop sustainable monitoring systems, there is still a lack of low cost, continuous and real time devices that demonstrate potential for large-scale implementation in wide water distribution networks. The following work presents a study of a low-cost, optofluidic sensor, based on Trypthopan Intrinsic Fluorescence. The fluorospectrometry analysis performed (before sensor development) supports the existence of a measurable fluorescence output signal originating from the tryptophan contained within pathogenic bacteria. The sensor was mounted using a rapid prototyping technique (3D printing), and the integrated optical system was achieved with low-cost optical components. The sensor performance was evaluated with spiked laboratory samples containing E. coli and Legionella, in both continuous and non-continuous flow situations. Results have shown a linear relationship between the signal measured and pathogen concentration, with limits of detection at 1.4 × 103 CFU/mL. The time delay between contamination and detection of the bacteria was practically null. Therefore, this study supports the potential application of tryptophan for monitoring drinking water against water pathogens. Full article
(This article belongs to the Special Issue Micro-Nano Systems Technology and Micro-Nano Intelligent Manufacture)
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12 pages, 7315 KiB  
Article
Highly Sensitive Acetone Gas Sensor Based on g-C3N4 Decorated MgFe2O4 Porous Microspheres Composites
by Run Zhang, Yan Wang, Zhanying Zhang and Jianliang Cao
Sensors 2018, 18(7), 2211; https://doi.org/10.3390/s18072211 - 10 Jul 2018
Cited by 64 | Viewed by 6760
Abstract
The g-C3N4 decorated magnesium ferrite (MgFe2O4) porous microspheres composites were successfully obtained via a one-step solvothermal method. The structure and morphology of the as-prepared MgFe2O4/g-C3N4 composites were characterized by [...] Read more.
The g-C3N4 decorated magnesium ferrite (MgFe2O4) porous microspheres composites were successfully obtained via a one-step solvothermal method. The structure and morphology of the as-prepared MgFe2O4/g-C3N4 composites were characterized by the techniques of X-ray diffraction (XRD), field-emission scanning electron microscopy (FESEM), transmission electron microscopy (TEM), thermal gravity and differential scanning calorimeter (TG–DSC) and N2-sorption. The gas sensing properties of the samples were measured and compared with a pure MgFe2O4-based sensor. The maximum response of the sensor based on MgFe2O4/g-C3N4 composites with 10 wt % g-C3N4 content to acetone is improved by about 145 times, while the optimum temperature was lowered by 60 °C. Moreover, the sensing mechanism and the reason for improving gas sensing performance were also discussed. Full article
(This article belongs to the Special Issue Advanced Nanomaterials based Gas Sensors)
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9 pages, 372 KiB  
Article
Hopf Bifurcation and Vibration Control for a Thrust Magnetic Bearing with Variable Load Mass
by Lingling Zhang
Sensors 2018, 18(7), 2212; https://doi.org/10.3390/s18072212 - 10 Jul 2018
Cited by 7 | Viewed by 3161
Abstract
In the working process, the load mass of the thrust magnetic bearing has a significant change. If the load mass changes greatly, the original fixed control parameters cannot ensure that the system is in the optimal stable suspension state, and the performance of [...] Read more.
In the working process, the load mass of the thrust magnetic bearing has a significant change. If the load mass changes greatly, the original fixed control parameters cannot ensure that the system is in the optimal stable suspension state, and the performance of the system will become worse or even self-excited. Firstly, a single freedom degree of the suspension control system model is established, and the critical condition of the system is analyzed when a self-excited oscillation occurs. Then, a linear adaptive control law is proposed for the system with variable parameters, which can tolerate the wide range of load mass. The simulation results show that the adaptive control law can keep the stability of the system when the load mass varies in a large range and avoid the self-excited vibration. Full article
(This article belongs to the Section Physical Sensors)
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8 pages, 3428 KiB  
Article
A Fiber Bragg Grating-Based Anemometer
by Chuan-Ying Huang, Pei-Wen Chan, Hung-Ying Chang and Wen-Fung Liu
Sensors 2018, 18(7), 2213; https://doi.org/10.3390/s18072213 - 10 Jul 2018
Cited by 9 | Viewed by 4096
Abstract
A novel fiber anemometer based on two pairs of fiber gratings is experimentally demonstrated and can simultaneously detect wind speed and wind direction. One pair of gratings, which are separated by 90° in space, is fixed on a small stainless steel pipe driven [...] Read more.
A novel fiber anemometer based on two pairs of fiber gratings is experimentally demonstrated and can simultaneously detect wind speed and wind direction. One pair of gratings, which are separated by 90° in space, is fixed on a small stainless steel pipe driven by a rotating disc for measuring the wind-direction angle. The other pair is composed of a sensing and a matched grating. The frequency of the spectrum-shifted of the sensing grating to overlap with that of the matched grating is employed for determining the wind speed. The errors in the wind-speed and wind-angle measurements are experimentally demonstrated to be less than 1%. The proposed fiber anemometer with a simple and durable structure can be applied in wind-powered electricity generators. Full article
(This article belongs to the Section Physical Sensors)
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9 pages, 5249 KiB  
Article
Direct Detection of Candida albicans with a Membrane Based Electrochemical Impedance Spectroscopy Sensor
by Dorota Kwasny, Sheida Esmail Tehrani, Catarina Almeida, Ida Schjødt, Maria Dimaki and Winnie E. Svendsen
Sensors 2018, 18(7), 2214; https://doi.org/10.3390/s18072214 - 10 Jul 2018
Cited by 22 | Viewed by 5628
Abstract
Candidemia and invasive candidiasis is a cause of high mortality and morbidity rates among hospitalized patients worldwide. The occurrence of the infections increases due to the complexity of the patients and overuse of the antifungal therapy. The current Candida detection method includes blood [...] Read more.
Candidemia and invasive candidiasis is a cause of high mortality and morbidity rates among hospitalized patients worldwide. The occurrence of the infections increases due to the complexity of the patients and overuse of the antifungal therapy. The current Candida detection method includes blood culturing which is a lengthy procedure and thus delays the administration of the antifungal therapy. Even though the results are available after 48 h it is still the gold standard in pathogen detection in a hospital setting. In this work we present an electrochemical impedance sensor that is capable of detecting Candida albicans yeast. The yeast cells are captured on electrodes specifically functionalized with anti-Candida antibodies and detection is achieved by electrochemical impedance spectroscopy. The sensor allows for detection of the yeast cells at clinically relevant concentrations in less than 1 h. Full article
(This article belongs to the Section Biosensors)
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21 pages, 8849 KiB  
Article
An Adaptive Nonlocal Mean Filter for PolSAR Data with Shape-Adaptive Patches Matching
by Peng Shen, Changcheng Wang, Han Gao and Jianjun Zhu
Sensors 2018, 18(7), 2215; https://doi.org/10.3390/s18072215 - 10 Jul 2018
Cited by 20 | Viewed by 3854
Abstract
The traditional nonlocal filters for polarimetric synthetic aperture radar (PolSAR) images are based on square patches matching to obtain homogeneous pixels in a large search window. However, it is still difficult for the regular patches to work well in the complex textured areas, [...] Read more.
The traditional nonlocal filters for polarimetric synthetic aperture radar (PolSAR) images are based on square patches matching to obtain homogeneous pixels in a large search window. However, it is still difficult for the regular patches to work well in the complex textured areas, even when the patch size has a small enough setting (e.g., 3 × 3 windows). Therefore, this paper proposes an adaptive nonlocal mean filter with shape-adaptive patches matching (ANLM) for PolSAR images. Mainly, the shape-adaptive (SA) matching patches are constructed by combining the polarimetric likelihood ratio test for coherency matrices (PolLRT-CM) and the region growing (RG), which is called PolLRT-CMRG. It is used to distinguish the homogeneous and heterogeneous pixels in textured areas effectively. Then, to enhance the filtering effect, it is necessary to take the adaptive threshold selection of similarity test (Simi-Test) into consideration. The simulated, low spatial resolution SAR580-Convair and high spatial resolution ESAR PolSAR image datasets are selected for experiments. We make a detailed quantitative and qualitative analysis for the filtered results. The experimental results have demonstrated that the proposed ANLM filter has better performance in speckle suppression and detail preservation than that of the traditional local and nonlocal filters. Full article
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18 pages, 3172 KiB  
Article
3D Analysis of Upper Limbs Motion during Rehabilitation Exercises Using the KinectTM Sensor: Development, Laboratory Validation and Clinical Application
by Bruno Bonnechère, Victor Sholukha, Lubos Omelina, Serge Van Sint Jan and Bart Jansen
Sensors 2018, 18(7), 2216; https://doi.org/10.3390/s18072216 - 10 Jul 2018
Cited by 23 | Viewed by 5061
Abstract
Optoelectronic devices are the gold standard for 3D evaluation in clinics, but due to the complexity of this kind of hardware and the lack of access for patients, affordable, transportable, and easy-to-use systems must be developed to be largely used in daily clinics. [...] Read more.
Optoelectronic devices are the gold standard for 3D evaluation in clinics, but due to the complexity of this kind of hardware and the lack of access for patients, affordable, transportable, and easy-to-use systems must be developed to be largely used in daily clinics. The KinectTM sensor has various advantages compared to optoelectronic devices, such as its price and transportability. However, it also has some limitations: (in)accuracy of the skeleton detection and tracking as well as the limited amount of available points, which makes 3D evaluation impossible. To overcome these limitations, a novel method has been developed to perform 3D evaluation of the upper limbs. This system is coupled to rehabilitation exercises, allowing functional evaluation while performing physical rehabilitation. To validate this new approach, a two-step method was used. The first step was a laboratory validation where the results obtained with the KinectTM were compared with the results obtained with an optoelectronic device; 40 healthy young adults participated in this first part. The second step was to determine the clinical relevance of this kind of measurement. Results of the healthy subjects were compared with a group of 22 elderly adults and a group of 10 chronic stroke patients to determine if different patterns could be observed. The new methodology and the different steps of the validations are presented in this paper. Full article
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26 pages, 2664 KiB  
Article
Huber’s Non-Linearity for GNSS Interference Mitigation
by Daniele Borio, Haoqing Li and Pau Closas
Sensors 2018, 18(7), 2217; https://doi.org/10.3390/s18072217 - 10 Jul 2018
Cited by 35 | Viewed by 5213
Abstract
Satellite-based navigation is prevalent in both commercial applications and critical infrastructures, providing precise position and time referencing. As a consequence, interference to such systems can have repercussions on a plethora of fields. Additionally, Privacy Preserving Devices (PPD)—jamming devices—are relatively inexpensive and easy to [...] Read more.
Satellite-based navigation is prevalent in both commercial applications and critical infrastructures, providing precise position and time referencing. As a consequence, interference to such systems can have repercussions on a plethora of fields. Additionally, Privacy Preserving Devices (PPD)—jamming devices—are relatively inexpensive and easy to obtain, potentially denying the service in a wide geographical area. Current jamming mitigation technology is based on interference cancellation approaches, requiring the detection and estimation of the interference waveform. Recently, the Robust Interference Mitigation (RIM) framework was proposed, which leverages results in robust statistics by treating the jamming signal as an outlier. It has the advantage of rejecting jamming signals without detecting or estimating its waveform. In this paper, we extend the framework to situations where the jammer is sparse in some transformed domain other than the time domain. Additionally, we analyse the use of Huber’s non-linearity within RIM and derive its loss of efficiency. We compare its performance to state-of-the-art techniques and to other RIM solutions, with both synthetic and real signals, showing remarkable results. Full article
(This article belongs to the Special Issue GNSS and Fusion with Other Sensors)
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27 pages, 17106 KiB  
Article
Impact Monitoring for Aircraft Smart Composite Skins Based on a Lightweight Sensor Network and Characteristic Digital Sequences
by Lei Qiu, Xiaolei Deng, Shenfang Yuan, YongAn Huang and Yuanqiang Ren
Sensors 2018, 18(7), 2218; https://doi.org/10.3390/s18072218 - 10 Jul 2018
Cited by 53 | Viewed by 6985
Abstract
Due to the growing use of composite materials in aircraft structures, Aircraft Smart Composite Skins (ASCSs) which have the capability of impact monitoring for large-scale composite structures need to be developed. However, the impact of an aircraft composite structure is a random transient [...] Read more.
Due to the growing use of composite materials in aircraft structures, Aircraft Smart Composite Skins (ASCSs) which have the capability of impact monitoring for large-scale composite structures need to be developed. However, the impact of an aircraft composite structure is a random transient event that needs to be monitored on-line continuously. Therefore, the sensor network of an ASCS and the corresponding impact monitoring system which needs to be installed on the aircraft as an on-board device must meet the requirements of light weight, low power consumption and high reliability. To achieve this point, an Impact Region Monitor (IRM) based on piezoelectric sensors and guided wave has been proposed and developed. It converts the impact response signals output from piezoelectric sensors into Characteristic Digital Sequences (CDSs), and then uses a simple but efficient impact region localization algorithm to achieve impact monitoring with light weight and low power consumption. However, due to the large number of sensors of ASCS, the realization of lightweight sensor network is still a key problem to realize an applicable ASCS for on-line and continuous impact monitoring. In this paper, three kinds of lightweight piezoelectric sensor networks including continuous series sensor network, continuous parallel sensor network and continuous heterogeneous sensor network are proposed. They can greatly reduce the lead wires of the piezoelectric sensors of ASCS and they can also greatly reduce the monitoring channels of the IRM. Furthermore, the impact region localization methods, which are based on the CDSs and the lightweight sensor networks, are proposed as well so that the lightweight sensor networks can be applied to on-line and continuous impact monitoring of ASCS with a large number of piezoelectric sensors. The lightweight piezoelectric sensor networks and the corresponding impact region localization methods are validated on the composite wing box of an unmanned aerial vehicle. The accuracy rate of impact region localization is higher than 92%. Full article
(This article belongs to the Special Issue Smart Sensors and Smart Structures)
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11 pages, 14226 KiB  
Article
Substituted 2-Aminobenzothiazoles Salicylidenes Synthesis and Characterization as Cyanide Sensors in Aqueous Medium
by Anas G. Elsafy, Hala Sultan Al-Easa and Yousef M. Hijji
Sensors 2018, 18(7), 2219; https://doi.org/10.3390/s18072219 - 10 Jul 2018
Cited by 10 | Viewed by 4131
Abstract
(E)-2-((benzo[d]thiazol-2-ylimino)methyl)-4-nitrophenol 1 and (E)-2-(((6-methoxybenzo[d]thiazol-2-yl)imino)methyl)-4-nitrophenol 2 were synthesized efficiently under microwave conditions. The structures were confirmed using IR, 1H NMR, and 13C NMR. UV-vis. Fluorescence investigations demonstrated that 1 and 2 are sensitive and selective sensors for detection [...] Read more.
(E)-2-((benzo[d]thiazol-2-ylimino)methyl)-4-nitrophenol 1 and (E)-2-(((6-methoxybenzo[d]thiazol-2-yl)imino)methyl)-4-nitrophenol 2 were synthesized efficiently under microwave conditions. The structures were confirmed using IR, 1H NMR, and 13C NMR. UV-vis. Fluorescence investigations demonstrated that 1 and 2 are sensitive and selective sensors for detection of cyanide over all other anions SCN, AcO, N3, H2PO4, H2AsO4, F, Cl, Br, and I in aqueous media. Cyanide induces colorimetric change from pale yellow to dark yellow and from transparent to pale yellow for 1 and 2, respectively. It enhances the absorption at wavelengths 385 nm and 425 nm of 1 and 385 nm and 435 nm of 2. Acidic anions H2PO4 and H2AsO4 displayed significant interference with the interaction of cyanide and sensors 1 and 2. Sensor 1 has lower detection limit (LDL) 1 × 10−6 M, while 2 has LDL 1.35 × 10−6 M. Full article
(This article belongs to the Section Chemical Sensors)
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22 pages, 12742 KiB  
Article
A Deep CNN-LSTM Model for Particulate Matter (PM2.5) Forecasting in Smart Cities
by Chiou-Jye Huang and Ping-Huan Kuo
Sensors 2018, 18(7), 2220; https://doi.org/10.3390/s18072220 - 10 Jul 2018
Cited by 586 | Viewed by 24930
Abstract
In modern society, air pollution is an important topic as this pollution exerts a critically bad influence on human health and the environment. Among air pollutants, Particulate Matter (PM2.5) consists of suspended particles with a diameter equal to or less than [...] Read more.
In modern society, air pollution is an important topic as this pollution exerts a critically bad influence on human health and the environment. Among air pollutants, Particulate Matter (PM2.5) consists of suspended particles with a diameter equal to or less than 2.5 μm. Sources of PM2.5 can be coal-fired power generation, smoke, or dusts. These suspended particles in the air can damage the respiratory and cardiovascular systems of the human body, which may further lead to other diseases such as asthma, lung cancer, or cardiovascular diseases. To monitor and estimate the PM2.5 concentration, Convolutional Neural Network (CNN) and Long Short-Term Memory (LSTM) are combined and applied to the PM2.5 forecasting system. To compare the overall performance of each algorithm, four measurement indexes, Mean Absolute Error (MAE), Root Mean Square Error (RMSE) Pearson correlation coefficient and Index of Agreement (IA) are applied to the experiments in this paper. Compared with other machine learning methods, the experimental results showed that the forecasting accuracy of the proposed CNN-LSTM model (APNet) is verified to be the highest in this paper. For the CNN-LSTM model, its feasibility and practicability to forecast the PM2.5 concentration are also verified in this paper. The main contribution of this paper is to develop a deep neural network model that integrates the CNN and LSTM architectures, and through historical data such as cumulated hours of rain, cumulated wind speed and PM2.5 concentration. In the future, this study can also be applied to the prevention and control of PM2.5. Full article
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25 pages, 4537 KiB  
Article
Thermal Response of Jointed Rock Masses Inferred from Infrared Thermographic Surveying (Acuto Test-Site, Italy)
by Matteo Fiorucci, Gian Marco Marmoni, Salvatore Martino and Paolo Mazzanti
Sensors 2018, 18(7), 2221; https://doi.org/10.3390/s18072221 - 10 Jul 2018
Cited by 45 | Viewed by 5336
Abstract
The Mediterranean region is affected by considerable daily and seasonal temperature variations due to intense solar radiation. In mid-seasons, thermal excursions can exceed tens of degrees thus influencing the long-term behaviour of jointed rock masses acting as a preparatory factor for rock slope [...] Read more.
The Mediterranean region is affected by considerable daily and seasonal temperature variations due to intense solar radiation. In mid-seasons, thermal excursions can exceed tens of degrees thus influencing the long-term behaviour of jointed rock masses acting as a preparatory factor for rock slope instabilities. In order to evaluate the thermal response of a densely jointed rock-block, monitoring has been in operation since 2016 by direct and remote sensing techniques in an abandoned quarry in Acuto (central Italy). Monthly InfraRed Thermographic (IRT) surveys were carried out on its exposed faces and along sections of interest across monitored main joints. The results highlight the daily and seasonal cyclical behaviour, constraining amplitudes and rates of heating and cooling phases. The temperature time-series revealed the effect of sun radiation and exposure on thermal response of the rock-block, which mainly depends on the seasonal conditions. The influence of opened joints in the heat propagation is revealed by the differential heating experienced across it, which was verified under 1D and 2D analysis. IRT has proved to be a valid monitoring technique in supporting traditional approaches, for the definition of the surficial temperature distribution on rock masses or stone building materials. Full article
(This article belongs to the Special Issue Advances in Infrared Imaging: Sensing, Exploitation and Applications)
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20 pages, 1770 KiB  
Article
Wideband Spectrum Sensing Based on Single-Channel Sub-Nyquist Sampling for Cognitive Radio
by Changjian Liu, Houjun Wang, Jie Zhang and Zongmiao He
Sensors 2018, 18(7), 2222; https://doi.org/10.3390/s18072222 - 10 Jul 2018
Cited by 17 | Viewed by 3810
Abstract
Spectrum sensing is an important task in cognitive radio. However, currently available Analog-to-Digital Converters (ADC) can hardly satisfy the sampling rate requirement for wideband signals. Even with such an ADC, the cost is extremely high in terms of price and power consumption. In [...] Read more.
Spectrum sensing is an important task in cognitive radio. However, currently available Analog-to-Digital Converters (ADC) can hardly satisfy the sampling rate requirement for wideband signals. Even with such an ADC, the cost is extremely high in terms of price and power consumption. In this paper, we propose a spectrum-sensing method based on single-channel sub-Nyquist sampling. Firstly, a serial Multi-Coset Sampling (MCS) structure is designed to avoid mismatches among sub-ADCs in the traditional parallel MCS. Clocks of the sample/hold and ADC are provided by two non-uniform sampling clocks. The cooperation between these two non-uniform sampling clocks shifts the high sampling rate burden from the ADC to the sample/hold. Secondly, a power spectrum estimation method using sub-Nyquist samples is introduced, and an efficient spectrum-sensing algorithm is proposed. By exploiting the frequency-smoothing property, the proposed efficient spectrum-sensing algorithm only needs to estimate power spectrum at partial frequency bins to conduct spectrum sensing, which will save a large amount of computational cost. Finally, the sampling pattern design of the proposed serial MCS is given, and it is proved to be a minimal circular sparse ruler with an additional constraint. Simulations show that mismatches in traditional parallel MCS have a serious impact on spectrum-sensing performance, while the proposed serial MCS combined with the efficient spectrum-sensing algorithm exhibits outstanding spectrum-sensing performance at much lower computational cost. Full article
(This article belongs to the Section Sensor Networks)
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17 pages, 2980 KiB  
Article
Recharging Schedule for Mitigating Data Loss in Wireless Rechargeable Sensor Network
by Haolin Liu, Qingyong Deng, Shujuan Tian, Xin Peng and Tingrui Pei
Sensors 2018, 18(7), 2223; https://doi.org/10.3390/s18072223 - 10 Jul 2018
Cited by 15 | Viewed by 3787
Abstract
Wireless Power Transfer (WPT) technology is considered as a promising approach to make Wireless Rechargeable Sensor Network (WRSN) work perpetually. In WRSN, a vehicle exists, termed a mobile charger, which can move close to sensor nodes and charge them wirelessly. Due to the [...] Read more.
Wireless Power Transfer (WPT) technology is considered as a promising approach to make Wireless Rechargeable Sensor Network (WRSN) work perpetually. In WRSN, a vehicle exists, termed a mobile charger, which can move close to sensor nodes and charge them wirelessly. Due to the mobile charger’s limited traveling distance and speed, not every node that needs to be charged may be serviced in time. Thus, in such scenario, how to make a route plan for the mobile charger to determine which nodes should be charged first is a critical issue related to the network’s Quality of Service (QoS). In this paper, we propose a mobile charger’s scheduling algorithm to mitigate the data loss of network by considering the node’s criticality in connectivity and energy. First, we introduce a novel metric named criticality index to measure node’s connectivity contribution, which is computed as a summation of node’s neighbor dissimilarity. Furthermore, to reflect the node’s charging demand, an indicator called energy criticality is adopted to weight the criticality index, which is a normalized ratio of the node’s consumed energy to its total energy. Then, we formulate an optimization problem with the objective of maximizing total weighted criticality indexes of nodes to construct a charging tour, subject to the mobile charger’s traveling distance constraint. Due to the NP-hardness of the problem, a heuristic algorithm is proposed to solve it. The heuristic algorithm includes three steps, which is spanning tree growing, tour construction and tour improvement. Finally, we compare the proposed algorithm to the state-of-art scheduling algorithms. The obtained results demonstrate that the proposed algorithm is a promising one. Full article
(This article belongs to the Special Issue QoS in Wireless Sensor Networks)
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16 pages, 6912 KiB  
Article
IoT Hierarchical Topology Strategy and Intelligentize Evaluation System of Diesel Engine in Complexity Environment
by Jiangshan Liu, Ming Chen, Tangfeng Yang and Jie Wu
Sensors 2018, 18(7), 2224; https://doi.org/10.3390/s18072224 - 10 Jul 2018
Cited by 10 | Viewed by 9322
Abstract
In complex discrete manufacturing environment, there used to be a poor network and an isolated information island in production line, which led to slow information feedback and low utilization ratio, hindering the construction of enterprise intelligence. To solve these problems, uncertain factors in [...] Read more.
In complex discrete manufacturing environment, there used to be a poor network and an isolated information island in production line, which led to slow information feedback and low utilization ratio, hindering the construction of enterprise intelligence. To solve these problems, uncertain factors in the production process and demands of sensor network were analyzed; hierarchical topology design method and the deployment strategy of the complexity industrial internet of things were proposed; and a big data analysis model and a system security protection system based on the network were established. The weight of each evaluation index was calculated using analytic hierarchy process, which established the intelligentized evaluation system and model. An actual production scene was also selected to validate the feasibility of the method. A diesel engine production workshop and the enterprise MES were used as an example to establish a network topology. The intelligence level based on both subjective and objective factors were evaluated and analyzed considering both quantitative and qualitative aspects. Analysis results show that the network topology design method and the intelligentize evaluation system were feasible, could improve the intelligence level effectively, and the network framework was expansible. Full article
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12 pages, 2412 KiB  
Article
Practical Methods for Vehicle Speed Estimation Using a Microprocessor-Embedded System with AMR Sensors
by Vytautas Markevicius, Dangirutis Navikas, Adam Idzkowski, Darius Andriukaitis, Algimantas Valinevicius and Mindaugas Zilys
Sensors 2018, 18(7), 2225; https://doi.org/10.3390/s18072225 - 10 Jul 2018
Cited by 19 | Viewed by 5253
Abstract
The proper operation of computing resources in a microprocessor-embedded system plays a key role in reducing computing time. Processing the variable amount of collected data in real-time improves the performance of a microprocessor-embedded system. In this regard, a vehicle’s speed measurement system is [...] Read more.
The proper operation of computing resources in a microprocessor-embedded system plays a key role in reducing computing time. Processing the variable amount of collected data in real-time improves the performance of a microprocessor-embedded system. In this regard, a vehicle’s speed measurement system is no exception. The computing time for evaluating any speed value is expected to be reduced as much as possible. Four computational methods, including cross-correlation, are discussed. An exemplary pair of recorded signals presenting the change in magnetic field magnitude is analyzed. The sample delay values are compared. The results of the evaluated speed and the execution time of the program code are presented for each method based on a dataset of 200 randomly driven vehicles. The results of the performed tests confirm that the cross-correlation-based methods are not always reliable in situations when the sample size is small, i.e., it is a segment of the impulse response caused by a driving vehicle. Full article
(This article belongs to the Special Issue Sensor Networks for Smart Roads)
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18 pages, 2685 KiB  
Article
Industrial Data Space Architecture Implementation Using FIWARE
by Álvaro Alonso, Alejandro Pozo, José Manuel Cantera, Francisco De la Vega and Juan José Hierro
Sensors 2018, 18(7), 2226; https://doi.org/10.3390/s18072226 - 11 Jul 2018
Cited by 70 | Viewed by 7954
Abstract
We are in front of a new digital revolution that will transform the way we understand and use services and infrastructures. One of the key factors of this revolution is related to the evolution of the Internet of Things (IoT). Connected sensors will [...] Read more.
We are in front of a new digital revolution that will transform the way we understand and use services and infrastructures. One of the key factors of this revolution is related to the evolution of the Internet of Things (IoT). Connected sensors will be installed in cities and homes affecting the daily life of people and providing them new ways of performing their daily activities. However, this revolution will also affect business and industry bringing the IoT to the production processes in what is called Industry 4.0. Sensor-enabled manufacturing equipment will allow real time communication, smart diagnosis and autonomous decision making. In this scope, the Industrial Data Spaces (IDS) Association has created a Reference Architecture model that aims to provide a common frame for designing and deploying Industry IoT infrastructures. In this paper, we present an implementation of such Reference Architecture based on FIWARE open source software components (Generic Enablers). We validate the proposed architecture by deploying and testing it in a real industry use case that tries to improve the maintenance and operation of milling machines. We conclude that the FIWARE-based IDS implementation fits the requirements of the IDS Reference Architecture providing open source software suitable to any Industry 4.0 environment. Full article
(This article belongs to the Special Issue Sensor Networks and Systems to Enable Industry 4.0 Environments)
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12 pages, 6175 KiB  
Article
Expert System for Monitoring the Malaxing State of the Olive Paste Based on Computer Vision
by Diego M. Martínez Gila, Pablo Cano Marchal, Juan Gómez Ortega and Javier Gámez García
Sensors 2018, 18(7), 2227; https://doi.org/10.3390/s18072227 - 11 Jul 2018
Cited by 2 | Viewed by 2973
Abstract
The malaxing of olive paste is one of the most important sub-processes in the virgin olive oil production process. The master continuously supervises the olive paste inside the themomixer to assess the preparation state of the olive paste and he acts manually over [...] Read more.
The malaxing of olive paste is one of the most important sub-processes in the virgin olive oil production process. The master continuously supervises the olive paste inside the themomixer to assess the preparation state of the olive paste and he acts manually over the process variables. The viscosity, granularity, and the presence of olive oil over the paste are the main indicators of the olive paste state. Furthermore, the temperature, time, coadjuvant addition and the shovel speeds are the process variables in the thermomixer. In this work, different image-processing parameters have been proposed to automatically assess the aforementioned indicators and they have been used as inputs in the designed fuzzy controller. Also, the outputs of this controller have been evaluated according to a sequence of images obtained inside the thermomixer and during the malaxing process in a real olive mill. Full article
(This article belongs to the Section Intelligent Sensors)
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14 pages, 2313 KiB  
Article
GNSS/INS Fusion with Virtual Lever-Arm Measurements
by Aviram Borko, Itzik Klein and Gilad Even-Tzur
Sensors 2018, 18(7), 2228; https://doi.org/10.3390/s18072228 - 11 Jul 2018
Cited by 24 | Viewed by 6104
Abstract
The navigation subsystem in most platforms is based on an inertial navigation system (INS). Regardless of the INS grade, its navigation solution drifts in time. To avoid such a drift, the INS is fused with external sensor measurements such as a global navigation [...] Read more.
The navigation subsystem in most platforms is based on an inertial navigation system (INS). Regardless of the INS grade, its navigation solution drifts in time. To avoid such a drift, the INS is fused with external sensor measurements such as a global navigation satellite system (GNSS). Recent publications showed that the lever-arm, defined as the relative position between the INS and aiding sensor, has a strong influence on navigation accuracy. Most research in this field is focused on INS/GNSS fusion with GNSS position or velocity updates while considering various maneuvers types. In this paper, we propose to employ virtual lever-arm (VLA) measurements to improve the accuracy and time to convergence of the observable INS error-states. In particular, we show that VLA measurements improve performance even in stationary conditions. In situations when maneuvering helps to improve state observability, VLA measurements manage to gain additional improvement in accuracy. These results are supported by simulation and field experiments with a vehicle mounted with a GNSS and an INS. Full article
(This article belongs to the Special Issue GNSS and Fusion with Other Sensors)
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17 pages, 7016 KiB  
Article
An Indoor Positioning System Based on Static Objects in Large Indoor Scenes by Using Smartphone Cameras
by Aoran Xiao, Ruizhi Chen, Deren Li, Yujin Chen and Dewen Wu
Sensors 2018, 18(7), 2229; https://doi.org/10.3390/s18072229 - 11 Jul 2018
Cited by 58 | Viewed by 7469
Abstract
The demand for location-based services (LBS) in large indoor spaces, such as airports, shopping malls, museums and libraries, has been increasing in recent years. However, there is still no fully applicable solution for indoor positioning and navigation like Global Navigation Satellite System (GNSS) [...] Read more.
The demand for location-based services (LBS) in large indoor spaces, such as airports, shopping malls, museums and libraries, has been increasing in recent years. However, there is still no fully applicable solution for indoor positioning and navigation like Global Navigation Satellite System (GNSS) solutions in outdoor environments. Positioning in indoor scenes by using smartphone cameras has its own advantages: no additional needed infrastructure, low cost and a large potential market due to the popularity of smartphones, etc. However, existing methods or systems based on smartphone cameras and visual algorithms have their own limitations when implemented in relatively large indoor spaces. To deal with this problem, we designed an indoor positioning system to locate users in large indoor scenes. The system uses common static objects as references, e.g., doors and windows, to locate users. By using smartphone cameras, our proposed system is able to detect static objects in large indoor spaces and then calculate the smartphones’ position to locate users. The system integrates algorithms of deep learning and computer vision. Its cost is low because it does not require additional infrastructure. Experiments in an art museum with a complicated visual environment suggest that this method is able to achieve positioning accuracy within 1 m. Full article
(This article belongs to the Special Issue Selected Papers from UPINLBS 2018)
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19 pages, 4949 KiB  
Article
Desertification Sensitivity Analysis Using MEDALUS Model and GIS: A Case Study of the Oases of Middle Draa Valley, Morocco
by Atman Ait Lamqadem, Biswajeet Pradhan, Hafid Saber and Abdelmejid Rahimi
Sensors 2018, 18(7), 2230; https://doi.org/10.3390/s18072230 - 11 Jul 2018
Cited by 66 | Viewed by 10033
Abstract
Oases can play a significant role in the sustainable economic development of arid and Saharan regions. The aim of this study was to map the desertification-sensitive areas in the Middle Draa Valley (MDV), which is in the southeast of Morocco. A total of [...] Read more.
Oases can play a significant role in the sustainable economic development of arid and Saharan regions. The aim of this study was to map the desertification-sensitive areas in the Middle Draa Valley (MDV), which is in the southeast of Morocco. A total of 13 indices that affect desertification processes were identified and analyzed using a geographic information system. The Mediterranean desertification and land use approach; which has been widely used in the Mediterranean regions due to its simplicity; flexibility and rapid implementation strategy; was applied. All the indices were grouped into four main quality indices; i.e., soil quality; climate quality; vegetation quality and management quality indices. Each quality index was constructed by the combination of several sub-indicators. In turn; the geometric mean of the four quality index maps was used to construct a map of desertification-sensitive areas; which were classified into four classes (i.e., low; moderate; high and very high sensitivity). Results indicated that only 16.63% of the sites in the study were classified as least sensitive to desertification; and 50.34% were classified as highly and very highly sensitive areas. Findings also showed that climate and human pressure factors are the most important indicators affecting desertification sensitivity in the MDV. The framework used in this research provides suitable results and can be easily implemented in similar oasis arid areas. Full article
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11 pages, 4763 KiB  
Article
High Accuracy Open-Type Current Sensor with a Differential Planar Hall Resistive Sensor
by Sungho Lee, Sungmin Hong, Wonki Park, Wonhyo Kim, Jaehoon Lee, Kwangho Shin, Cheol-Gi Kim and Daesung Lee
Sensors 2018, 18(7), 2231; https://doi.org/10.3390/s18072231 - 12 Jul 2018
Cited by 16 | Viewed by 6176
Abstract
In this paper, we propose a high accuracy open-type current sensor with a differential Planar Hall Resistive (PHR) sensor. Conventional open-type current sensors with magnetic sensors are usually vulnerable to interference from an external magnetic field. To reduce the effect of an unintended [...] Read more.
In this paper, we propose a high accuracy open-type current sensor with a differential Planar Hall Resistive (PHR) sensor. Conventional open-type current sensors with magnetic sensors are usually vulnerable to interference from an external magnetic field. To reduce the effect of an unintended magnetic field, the proposed design uses a differential structure with PHR. The differential structure provides robust performance to unwanted magnetic flux and increased magnetic sensitivity. In addition, instead of conventional Hall sensors with a magnetic concentrator, a newly developed PHR with high sensitivity is employed to sense horizontal magnetic fields. The PHR sensor and read-out integrated circuit (IC) are integrated through a post-Complementary metal-oxide-semiconductor (CMOS) process using multi-chip packaging. The current sensor is designed to measure a 1 A current level. The measured performance of the designed current sensor has a 16 kHz bandwidth and a current nonlinearity of under ±0.5%. Full article
(This article belongs to the Section Physical Sensors)
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17 pages, 4729 KiB  
Article
Non-GNSS Smartphone Pedestrian Navigation Using Barometric Elevation and Digital Map-Matching
by Daniel Broyles, Kyle Kauffman, John Raquet and Piotr Smagowski
Sensors 2018, 18(7), 2232; https://doi.org/10.3390/s18072232 - 11 Jul 2018
Cited by 5 | Viewed by 4725
Abstract
Pedestrian navigation in outdoor environments where global navigation satellite systems (GNSS) are unavailable is a challenging problem. Existing technologies that have attempted to address this problemoften require external reference signals or specialized hardware, the extra size,weight, power, and cost of which are unsuitable [...] Read more.
Pedestrian navigation in outdoor environments where global navigation satellite systems (GNSS) are unavailable is a challenging problem. Existing technologies that have attempted to address this problemoften require external reference signals or specialized hardware, the extra size,weight, power, and cost of which are unsuitable for many applications. This article presents a real-time, self-contained outdoor navigation application that uses only the existing sensors on a smartphone in conjunction with a preloaded digital elevation map. The core algorithm implements a particle filter, which fuses sensor data with a stochastic pedestrian motion model to predict the user’s position. The smartphone’s barometric elevation is then compared with the elevation map to constrain the position estimate. The system developed for this research was deployed on Android smartphones and tested in several terrains using a variety of elevation data sources. The results fromthese experiments showthe systemachieves positioning accuracies in the tens of meters that do not grow as a function of time Full article
(This article belongs to the Special Issue GNSS and Fusion with Other Sensors)
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23 pages, 1255 KiB  
Article
Context-Aware Gossip-Based Protocol for Internet of Things Applications
by Lina Altoaimy, Arwa Alromih, Shiroq Al-Megren, Ghada Al-Hudhud, Heba Kurdi and Kamal Youcef-Toumi
Sensors 2018, 18(7), 2233; https://doi.org/10.3390/s18072233 - 11 Jul 2018
Cited by 4 | Viewed by 5107
Abstract
This paper proposes a gossip-based protocol that utilises a multi-factor weighting function (MFWF) that takes several parameters into account: residual energy, Chebyshev distances to neighbouring nodes and the sink node, node density, and message priority. The effects of these parameters were examined to [...] Read more.
This paper proposes a gossip-based protocol that utilises a multi-factor weighting function (MFWF) that takes several parameters into account: residual energy, Chebyshev distances to neighbouring nodes and the sink node, node density, and message priority. The effects of these parameters were examined to guide the customization of the weight function to effectively disseminate data to three types of IoT applications: critical, bandwidth-intensive, and energy-efficient applications. The performances of the three resulting MFWFs were assessed in comparison with the performances of the traditional gossiping protocol and the Fair Efficient Location-based Gossiping (FELGossiping) protocol in terms of end-to-end delay, network lifetime, rebroadcast nodes, and saved rebroadcasts. The experimental results demonstrated the proposed protocol’s ability to achieve a much shorter delay for critical IoT applications. For bandwidth-intensive IoT application, the proposed protocol was able to achieve a smaller percentage of rebroadcast nodes and an increased percentage of saved rebroadcasts, i.e., better bandwidth utilisation. The adapted MFWF for energy-efficient IoT application was able to improve the network lifetime compared to that of gossiping and FELGossiping. These results demonstrate the high level of flexibility of the proposed protocol with respect to network context and message priority. Full article
(This article belongs to the Special Issue Future Research Trends in Internet of Things and Sensor Networks)
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17 pages, 12918 KiB  
Article
Capacitive Phase Shift Detection for Measuring Water Holdup in Horizontal Oil–Water Two-Phase Flow
by Hongxin Zhang, Lusheng Zhai, Cong Yan, Hongmei Wang and Ningde Jin
Sensors 2018, 18(7), 2234; https://doi.org/10.3390/s18072234 - 11 Jul 2018
Cited by 13 | Viewed by 4257
Abstract
In this paper, a phase shift detection system of flow impedance is designed based on a concave capacitance sensor (CCS). The flow impedance of oil–water stratified flow is investigated by establishing an equivalent circuit model and a finite element model. The influence of [...] Read more.
In this paper, a phase shift detection system of flow impedance is designed based on a concave capacitance sensor (CCS). The flow impedance of oil–water stratified flow is investigated by establishing an equivalent circuit model and a finite element model. The influence of exciting frequency and sensor geometric parameters on the phase shift output of the CCS is studied to access an optimal phase shift measurement system. An experiment of horizontal oil–water two-phase flows was conducted during which four flow patterns are observed, i.e., stratified flow (ST), stratified wavy flow (SW), dual continuous flow (DC), and dispersed oil-in-water and water flow (DO/W&W). The phase shift responses of the CCS to the water holdup variation are collected. The results indicate that the phase shift response of the CCS presents satisfied sensitivity for ST and SW flow patterns, which is consistent with the predictions of the equivalent circuit model and the finite element model. Although the flow structures of DC and DO/W&W flows are extremely nonuniform, the phase shift response of the CCS still shows better linearity and sensitivity to the water holdup variation. In general, the capacitive phase shift detection technology exhibits advantages for water holdup measurement in horizontal oil–water two-phase flow with nonuniform phase distributions and conductive water. Full article
(This article belongs to the Section Physical Sensors)
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22 pages, 7193 KiB  
Article
An Effective Singular Value Selection and Bearing Fault Signal Filtering Diagnosis Method Based on False Nearest Neighbors and Statistical Information Criteria
by Zhiqiang Liao, Liuyang Song, Peng Chen, Zhaoyi Guan, Ziye Fang and Ke Li
Sensors 2018, 18(7), 2235; https://doi.org/10.3390/s18072235 - 11 Jul 2018
Cited by 18 | Viewed by 5143
Abstract
Singular value decomposition (SVD) is an effective method used in bearing fault diagnosis. Ideally two important problems should be solved in any diagnosis: one is how to decide the dimension embedding of the trajectory matrix (TM); the other is how to select the [...] Read more.
Singular value decomposition (SVD) is an effective method used in bearing fault diagnosis. Ideally two important problems should be solved in any diagnosis: one is how to decide the dimension embedding of the trajectory matrix (TM); the other is how to select the singular value (SV) representing the intrinsic information of the bearing condition. In order to solve such problems, this study proposed an effective method to find the optimal TM and SV and perform fault signal filtering based on false nearest neighbors (FNN) and statistical information criteria. First of all, the embedded dimension of the trajectory matrix is determined with the FNN according to the chaos theory. Then the trajectory matrix is subjected to SVD, which is helpful to acquire all the combinations of SV and decomposed signals. According to the similarities of the signal changed back and signal in normal state based on statistical information criteria, the SV representing fault signal can be obtained. The spectrum envelope demodulation method can be used to perform effective analysis on the fault. The effectiveness of the proposed method is verified with simulation signals and low-speed bearing fault signals, and compared with the published SVD-based method and Fast Kurtogram diagnosis method. Full article
(This article belongs to the Special Issue Sensors for Fault Detection)
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10 pages, 4937 KiB  
Article
Radiation-Resistant Er3+-Doped Superfluorescent Fiber Sources
by Chengxiang Liu, Xu Wu, Jianhui Zhu, Nie He, Zhuoyan Li, Gongshen Zhang, Li Zhang and Shuangchen Ruan
Sensors 2018, 18(7), 2236; https://doi.org/10.3390/s18072236 - 11 Jul 2018
Cited by 9 | Viewed by 3640
Abstract
The radiation effects of three Er3+-doped superfluorescent fiber sources (SFSs), which are based on three segments of Er-doped fibers with different lengths, are studied experimentally. We observed that the radiation-induced attenuation of the signal light of the 1530 nm band for [...] Read more.
The radiation effects of three Er3+-doped superfluorescent fiber sources (SFSs), which are based on three segments of Er-doped fibers with different lengths, are studied experimentally. We observed that the radiation-induced attenuation of the signal light of the 1530 nm band for an SFS is less than that of the 1560 nm band. Thus, the trimming technique of the Gauss-like spectra is investigated to reduce the mean wavelength drift. A filter was customized and used in superfluorescent fiber sources. To further reduce output power loss, the method with feedback control of pump power was adopted in the SFS. Then, the trimming spectral SFS with pump feedback control was tested under irradiation environment at the dose rate of 2.988 Gy/h. The experimental results demonstrate that the mean wavelength drift is <40 ppm and the loss of output power is <0.2 dB under a total dose higher than 1000 Gy. These findings confirm the significance of the method in improving radiation-resistant capabilities of fiber sources under irradiation environments. Full article
(This article belongs to the Special Issue Sensors and Materials for Harsh Environments)
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17 pages, 11487 KiB  
Article
Mapping Oil Spills from Dual-Polarized SAR Images Using an Artificial Neural Network: Application to Oil Spill in the Kerch Strait in November 2007
by Daeseong Kim and Hyung-Sup Jung
Sensors 2018, 18(7), 2237; https://doi.org/10.3390/s18072237 - 11 Jul 2018
Cited by 25 | Viewed by 4406
Abstract
Synthetic aperture radar (SAR) has been widely used to detect oil-spill areas through the backscattering intensity difference between oil and background pixels. However, since the signal is similar to that produced by other phenomena, positive identification can be challenging. In this study we [...] Read more.
Synthetic aperture radar (SAR) has been widely used to detect oil-spill areas through the backscattering intensity difference between oil and background pixels. However, since the signal is similar to that produced by other phenomena, positive identification can be challenging. In this study we developed an algorithm to effectively analyze large-scale oil spill areas in SAR images by focusing on optimizing the input layer to artificial neural network (ANN) through removal the factor of lowering the accuracy. An ANN algorithm was used to generate probability maps of oil spills. Highly accurate pixel-based data processing was conducted through false or un-detection element reduction by normalizing the image or applying a non-local (NL) means filter and median filter to the input neurons for ANN. In addition, the standard deviation of co-polarized phase difference (CPD) was used to reduce false detection from the look-alike with weak damping effect. The algorithm was validated using TerraSAR-X images of an oil spill caused by stranded oil tanker Volganefti-139 in the Kerch Strait in 2007. According to the validation results of the receiver operating characteristic (ROC) curve, the oil spill was detected with an accuracy of about 95.19% and un-detection or false detection by look-alike and speckle noise was greatly reduced. Full article
(This article belongs to the Section Remote Sensors)
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15 pages, 4859 KiB  
Article
A SEMG-Force Estimation Framework Based on a Fast Orthogonal Search Method Coupled with Factorization Algorithms
by Xiang Chen, Yuan Yuan, Shuai Cao, Xu Zhang and Xun Chen
Sensors 2018, 18(7), 2238; https://doi.org/10.3390/s18072238 - 11 Jul 2018
Cited by 15 | Viewed by 3451
Abstract
A novel framework based on the fast orthogonal search (FOS) method coupled with factorization algorithms was proposed and implemented to realize high-accuracy muscle force estimation via surface electromyogram (SEMG). During static isometric elbow flexion, high-density SEMG (HD-SEMG) signals were recorded from upper arm [...] Read more.
A novel framework based on the fast orthogonal search (FOS) method coupled with factorization algorithms was proposed and implemented to realize high-accuracy muscle force estimation via surface electromyogram (SEMG). During static isometric elbow flexion, high-density SEMG (HD-SEMG) signals were recorded from upper arm muscles, and the generated elbow force was measured at the wrist. HD-SEMG signals were decomposed into time-invariant activation patterns and time-varying activation curves using three typical factorization algorithms including principal component analysis (PCA), independent component analysis (ICA), and nonnegative matrix factorization (NMF). The activation signal of the target muscle was obtained by summing the activation curves, and the FOS algorithm was used to create basis functions with activation signals and establish the force estimation model. Static isometric elbow flexion experiments at three target levels were performed on seven male subjects, and the force estimation performances were compared among three typical factorization algorithms as well as a conventional method for extracting the average signal envelope of all HD-SEMG channels (AVG-ENVLP method). The overall root mean square difference (RMSD) values between the measured forces and the estimated forces obtained by different methods were 11.79 ± 4.29% for AVG-ENVLP, 9.74 ± 3.77% for PCA, 9.59 ± 3.81% for ICA, and 9.51 ± 4.82% for NMF. The results demonstrated that, compared to the conventional AVG-ENVLP method, factorization algorithms could substantially improve the performance of force estimation. The FOS method coupled with factorization algorithms provides an effective way to estimate the combined force of multiple muscles and has potential value in the fields of sports biomechanics, gait analysis, prosthesis control strategy, and exoskeleton devices for assisted rehabilitation. Full article
(This article belongs to the Section Physical Sensors)
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28 pages, 15797 KiB  
Article
Novel Adaptive Laser Scanning Method for Point Clouds of Free-Form Objects
by Yufu Zang, Bisheng Yang, Fuxun Liang and Xiongwu Xiao
Sensors 2018, 18(7), 2239; https://doi.org/10.3390/s18072239 - 11 Jul 2018
Cited by 16 | Viewed by 3626
Abstract
Laser scanners are widely used to collect coordinates, also known as point-clouds, of three-dimensional free-form objects. For creating a solid model from a given point-cloud and transferring the data from the model, features-based optimization of the point-cloud to minimize the number if points [...] Read more.
Laser scanners are widely used to collect coordinates, also known as point-clouds, of three-dimensional free-form objects. For creating a solid model from a given point-cloud and transferring the data from the model, features-based optimization of the point-cloud to minimize the number if points in the cloud is required. To solve this problem, existing methods mainly extract significant points based on local surface variation of a predefined level. However, comprehensively describing an object’s geometric information using a predefined level is difficult since an object usually has multiple levels of details. Therefore, we propose a simplification method based on a multi-level strategy that adaptively determines the optimal level of points. For each level, significant points are extracted from the point cloud based on point importance measured by both local surface variation and the distribution of neighboring significant points. Furthermore, the degradation of perceptual quality for each level is evaluated by the adjusted mesh structural distortion measurement to select the optimal level. Experiments are performed to evaluate the effectiveness and applicability of the proposed method, demonstrating a reliable solution to optimize the adaptive laser scanning of point clouds for free-forms objects. Full article
(This article belongs to the Section Remote Sensors)
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18 pages, 3276 KiB  
Article
Improved ABC Algorithm Optimizing the Bridge Sensor Placement
by Jianhui Yang and Zhenrui Peng
Sensors 2018, 18(7), 2240; https://doi.org/10.3390/s18072240 - 11 Jul 2018
Cited by 13 | Viewed by 4537
Abstract
Inspired by sensor coverage density and matching & preserving strategy, this paper proposes an Improved Artificial Bee Colony (IABC) algorithm which is designed to optimize bridge sensor placement. We use dynamic random coverage coding method to initialize colony to ensure the diversity and [...] Read more.
Inspired by sensor coverage density and matching & preserving strategy, this paper proposes an Improved Artificial Bee Colony (IABC) algorithm which is designed to optimize bridge sensor placement. We use dynamic random coverage coding method to initialize colony to ensure the diversity and effectiveness. In addition, we randomly select the factors with lower trust value to search and evolve after food source being matched in order that the relatively high trust point factor is retained in the exploitation of food sources, which reduces the blindness of searching and improves the efficiency of convergence and the accuracy of the algorithm. According to the analysis of the modal data of the Ha-Qi long span railway bridge, the results show that IABC algorithm has faster convergence rate and better global search ability when solving the optimal placement problem of bridge sensor. The final analysis results also indicate that the IABC’s solution accuracy is 76.45% higher than that of the ABC algorithm, and the solution stability is improved by 86.23%. The final sensor placement mostly covers the sensitive monitoring points of the bridge structure and, in this way, the IABC algorithm is suitable for solving the optimal placement problem of large bridge and other structures. Full article
(This article belongs to the Special Issue Bridge Structural Health Monitoring and Damage Identification)
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13 pages, 2121 KiB  
Article
Radar Detection of Fluctuating Targets under Heavy-Tailed Clutter Using Track-Before-Detect
by Jie Gao, Jinsong Du and Wei Wang
Sensors 2018, 18(7), 2241; https://doi.org/10.3390/s18072241 - 12 Jul 2018
Cited by 21 | Viewed by 5030
Abstract
This paper considers the detection of fluctuating targets in heavy-tailed clutter through the use of dynamic programming based on track-before-detect (DP–TBD) in radar systems. The clutter is modeled in terms of K-distribution, which can be widely used to describe non-Gaussian clutter received from [...] Read more.
This paper considers the detection of fluctuating targets in heavy-tailed clutter through the use of dynamic programming based on track-before-detect (DP–TBD) in radar systems. The clutter is modeled in terms of K-distribution, which can be widely used to describe non-Gaussian clutter received from high-resolution radars and radars working at small grazing angles. Swerling type 1 is considered to describe the target fluctuation between scans. Conventional TBD techniques suffer from significant performance loss in heavy-tailed environments due to the more frequent occurrences of target-like outliers. In this paper, we resort to a DP–TBD algorithm based on prior information, which can enhance the detection performance by using the environment and target fluctuating information during the integration process of TBD. Under non-Gaussian background, the expressions of the likelihood ratio merit function for Swerling type 1 targets are derived first. However, the closed-form of the merit function is difficult to obtain. In order to reduce the complexity of evaluating the merit function and the computational load, an efficient approximation method as well as a two-stage detection approach is proposed and used in the integration process. Finally, several numerical simulations of the new strategy and the comparisons are presented to verify that the proposed algorithm can improve the detection performance, especially for fluctuating targets in heavy-tailed clutter. Full article
(This article belongs to the Section Remote Sensors)
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10 pages, 996 KiB  
Article
Graphene-Based Raman Spectroscopy for pH Sensing of X-rays Exposed and Unexposed Culture Media and Cells
by Carlo Camerlingo, Alessandro Verde, Lorenzo Manti, Roberta Meschini, Ines Delfino and Maria Lepore
Sensors 2018, 18(7), 2242; https://doi.org/10.3390/s18072242 - 12 Jul 2018
Cited by 14 | Viewed by 4396
Abstract
Graphene provides a unique way of sensing the local pH level of substances on the micrometric scale, with important implications for the monitoring of cellular metabolic activities where proton excretion could occur. Accordingly, an innovative biosensing approach for the quantification of the pH [...] Read more.
Graphene provides a unique way of sensing the local pH level of substances on the micrometric scale, with important implications for the monitoring of cellular metabolic activities where proton excretion could occur. Accordingly, an innovative biosensing approach for the quantification of the pH value of biological fluids, to be used also with small amounts of fluids, was realized and tested. It is based on the use of micro-Raman spectroscopy to detect the modifications of the graphene doping level induced by the contact of the graphene with the selected fluids. The approach was preliminarily tested on aqueous solutions of known pH values. It was then used to quantify the pH values of cell culture media directly exposed to different doses of X-ray radiation and to media exposed to X-ray-irradiated cells. The Raman response of cells placed on graphene layers was also examined. Full article
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21 pages, 7087 KiB  
Article
A Miniature Binocular Endoscope with Local Feature Matching and Stereo Matching for 3D Measurement and 3D Reconstruction
by Di Wang, Hua Liu and Xiang Cheng
Sensors 2018, 18(7), 2243; https://doi.org/10.3390/s18072243 - 12 Jul 2018
Cited by 26 | Viewed by 5072
Abstract
As the traditional single camera endoscope can only provide clear images without 3D measurement and 3D reconstruction, a miniature binocular endoscope based on the principle of binocular stereoscopic vision to implement 3D measurement and 3D reconstruction in tight and restricted spaces is presented. [...] Read more.
As the traditional single camera endoscope can only provide clear images without 3D measurement and 3D reconstruction, a miniature binocular endoscope based on the principle of binocular stereoscopic vision to implement 3D measurement and 3D reconstruction in tight and restricted spaces is presented. In order to realize the exact matching of points of interest in the left and right images, a novel construction method of the weighted orthogonal-symmetric local binary pattern (WOS-LBP) descriptor is presented. Then a stereo matching algorithm based on Gaussian-weighted AD-Census transform and improved cross-based adaptive regions is studied to realize 3D reconstruction for real scenes. In the algorithm, we adjust determination criterions of adaptive regions for edge and discontinuous areas in particular and as well extract mismatched pixels caused by occlusion through image entropy and region-growing algorithm. This paper develops a binocular endoscope with an external diameter of 3.17 mm and the above algorithms are applied in it. The endoscope contains two CMOS cameras and four fiber optics for illumination. Three conclusions are drawn from experiments: (1) the proposed descriptor has good rotation invariance, distinctiveness and robustness to light change as well as noises; (2) the proposed stereo matching algorithm has a mean relative error of 8.48% for Middlebury standard pairs of images and compared with several classical stereo matching algorithms, our algorithm performs better in edge and discontinuous areas; (3) the mean relative error of length measurement is 3.22%, and the endoscope can be utilized to measure and reconstruct real scenes effectively. Full article
(This article belongs to the Special Issue Depth Sensors and 3D Vision)
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33 pages, 15199 KiB  
Article
Using Deep Learning and Low-Cost RGB and Thermal Cameras to Detect Pedestrians in Aerial Images Captured by Multirotor UAV
by Diulhio Candido De Oliveira and Marco Aurelio Wehrmeister
Sensors 2018, 18(7), 2244; https://doi.org/10.3390/s18072244 - 12 Jul 2018
Cited by 61 | Viewed by 7939
Abstract
The use of Unmanned Aerial Vehicles (UAV) has been increasing over the last few years in many sorts of applications due mainly to the decreasing cost of this technology. One can see the use of the UAV in several civilian applications such as [...] Read more.
The use of Unmanned Aerial Vehicles (UAV) has been increasing over the last few years in many sorts of applications due mainly to the decreasing cost of this technology. One can see the use of the UAV in several civilian applications such as surveillance and search and rescue. Automatic detection of pedestrians in aerial images is a challenging task. The computing vision system must deal with many sources of variability in the aerial images captured with the UAV, e.g., low-resolution images of pedestrians, images captured at distinct angles due to the degrees of freedom that a UAV can move, the camera platform possibly experiencing some instability while the UAV flies, among others. In this work, we created and evaluated different implementations of Pattern Recognition Systems (PRS) aiming at the automatic detection of pedestrians in aerial images captured with multirotor UAV. The main goal is to assess the feasibility and suitability of distinct PRS implementations running on top of low-cost computing platforms, e.g., single-board computers such as the Raspberry Pi or regular laptops without a GPU. For that, we used four machine learning techniques in the feature extraction and classification steps, namely Haar cascade, LBP cascade, HOG + SVM and Convolutional Neural Networks (CNN). In order to improve the system performance (especially the processing time) and also to decrease the rate of false alarms, we applied the Saliency Map (SM) and Thermal Image Processing (TIP) within the segmentation and detection steps of the PRS. The classification results show the CNN to be the best technique with 99.7% accuracy, followed by HOG + SVM with 92.3%. In situations of partial occlusion, the CNN showed 71.1% sensitivity, which can be considered a good result in comparison with the current state-of-the-art, since part of the original image data is missing. As demonstrated in the experiments, by combining TIP with CNN, the PRS can process more than two frames per second (fps), whereas the PRS that combines TIP with HOG + SVM was able to process 100 fps. It is important to mention that our experiments show that a trade-off analysis must be performed during the design of a pedestrian detection PRS. The faster implementations lead to a decrease in the PRS accuracy. For instance, by using HOG + SVM with TIP, the PRS presented the best performance results, but the obtained accuracy was 35 percentage points lower than the CNN. The obtained results indicate that the best detection technique (i.e., the CNN) requires more computational resources to decrease the PRS computation time. Therefore, this work shows and discusses the pros/cons of each technique and trade-off situations, and hence, one can use such an analysis to improve and tailor the design of a PRS to detect pedestrians in aerial images. Full article
(This article belongs to the Section Remote Sensors)
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13 pages, 4018 KiB  
Article
Mapping Forest Structure Using UAS inside Flight Capabilities
by Karel Kuželka and Peter Surový
Sensors 2018, 18(7), 2245; https://doi.org/10.3390/s18072245 - 12 Jul 2018
Cited by 39 | Viewed by 4614
Abstract
We evaluated two unmanned aerial systems (UASs), namely the DJI Phantom 4 Pro and DJI Mavic Pro, for 3D forest structure mapping of the forest stand interior with the use of close-range photogrammetry techniques. Assisted flights were performed within two research plots established [...] Read more.
We evaluated two unmanned aerial systems (UASs), namely the DJI Phantom 4 Pro and DJI Mavic Pro, for 3D forest structure mapping of the forest stand interior with the use of close-range photogrammetry techniques. Assisted flights were performed within two research plots established in mature pure Norway spruce (Picea abies (L.) H. Karst.) and European beech (Fagus sylvatica L.) forest stands. Geotagged images were used to produce georeferenced 3D point clouds representing tree stem surfaces. With a flight height of 8 m above the ground, the stems were precisely modeled up to a height of 10 m, which represents a considerably larger portion of the stem when compared with terrestrial close-range photogrammetry. Accuracy of the point clouds was evaluated by comparing field-measured tree diameters at breast height (DBH) with diameter estimates derived from the point cloud using four different fitting methods, including the bounding circle, convex hull, least squares circle, and least squares ellipse methods. The accuracy of DBH estimation varied with the UAS model and the diameter fitting method utilized. With the Phantom 4 Pro and the least squares ellipse method to estimate diameter, the mean error of diameter estimates was −1.17 cm (−3.14%) and 0.27 cm (0.69%) for spruce and beech stands, respectively. Full article
(This article belongs to the Section Remote Sensors)
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9 pages, 2168 KiB  
Communication
Slight pH Fluctuations in the Gold Nanoparticle Synthesis Process Influence the Performance of the Citrate Reduction Method
by Braulio Contreras-Trigo, Víctor Díaz-García, Enrique Guzmán-Gutierrez, Ignacio Sanhueza, Pablo Coelho, Sebastián E. Godoy, Sergio Torres and Patricio Oyarzún
Sensors 2018, 18(7), 2246; https://doi.org/10.3390/s18072246 - 12 Jul 2018
Cited by 46 | Viewed by 6998
Abstract
Gold nanoparticles (AuNPs) are currently under intense investigation for biomedical and biotechnology applications, thanks to their ease in preparation, stability, biocompatibility, multiple surface functionalities, and size-dependent optical properties. The most commonly used method for AuNP synthesis in aqueous solution is the reduction of [...] Read more.
Gold nanoparticles (AuNPs) are currently under intense investigation for biomedical and biotechnology applications, thanks to their ease in preparation, stability, biocompatibility, multiple surface functionalities, and size-dependent optical properties. The most commonly used method for AuNP synthesis in aqueous solution is the reduction of tetrachloroauric acid (HAuCl4) with trisodium citrate. We have observed variations in the pH and in the concentration of the gold colloidal suspension synthesized under standard conditions, verifying a reduction in the reaction yield by around 46% from pH 5.3 (2.4 nM) to pH 4.7 (1.29 nM). Citrate-capped AuNPs were characterized by UV-visible spectroscopy, TEM, EDS, and zeta-potential measurements, revealing a linear correlation between pH and the concentration of the generated AuNPs. This result can be attributed to the adverse effect of protons both on citrate oxidation and on citrate adsorption onto the gold surface, which is required to form the stabilization layer. Overall, this study provides insight into the effect of the pH over the synthesis performance of the method, which would be of particular interest from the point of view of large-scale manufacturing processes. Full article
(This article belongs to the Section Biosensors)
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24 pages, 895 KiB  
Article
A Software-Defined Networking Framework to Provide Dynamic QoS Management in IEEE 802.11 Networks
by Pilar Manzanares-Lopez, Josemaria Malgosa-Sanahuja and Juan Pedro Muñoz-Gea
Sensors 2018, 18(7), 2247; https://doi.org/10.3390/s18072247 - 12 Jul 2018
Cited by 9 | Viewed by 3691
Abstract
In this paper, the concept of SDN (Software Defined Networking) is extended to be applied to wireless networks. Traditionally, in a wired SDN environment, the OpenFlow protocol is the communication protocol used to configure the flow table of forwarding elements (i.e., [...] Read more.
In this paper, the concept of SDN (Software Defined Networking) is extended to be applied to wireless networks. Traditionally, in a wired SDN environment, the OpenFlow protocol is the communication protocol used to configure the flow table of forwarding elements (i.e., switches and Access Points). However, although in IEEE 802.11 networks there is no concept of forwarding, the SDN paradigm could also be applied to set up the wireless network dynamically, in order to improve the performance. In this case, not only the network elements, that is the Access Points, but also the mobile elements should configure their link and physical layers parameters following the guidelines of a centralized SDN controller. In particular, we propose a mechanism called DEDCA (Dynamic Enhanced Distributed Channel Access) to manage the channel access in wireless networks, and a framework that enables its implementation in 802.11-based wireless networks using SDN technology. The key aspect of this alternative solution is the control over the contention window size of the wireless terminals. Thus, an adequate response to dynamic and short-term Quality of Service (QoS) requirements can be offered to services running on these networks. DEDCA mechanism relies upon the use of a scalar parameter called gain. The mathematical model which has allowed us to obtain this parameter is presented and evaluated in this paper. Finally, the usefulness of the proposed solutions have been evaluated by means of their implementation in an example case. Full article
(This article belongs to the Special Issue Software-Defined Networking Based Mobile Networks)
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23 pages, 5642 KiB  
Article
Smart Environmental Monitoring and Assessment Technologies (SEMAT)—A New Paradigm for Low-Cost, Remote Aquatic Environmental Monitoring
by Jarrod Trevathan and Ron Johnstone
Sensors 2018, 18(7), 2248; https://doi.org/10.3390/s18072248 - 12 Jul 2018
Cited by 41 | Viewed by 12190
Abstract
Expense and the logistical difficulties with deploying scientific monitoring equipment are the biggest limitations to undertaking large scale monitoring of aquatic environments. The Smart Environmental Monitoring and Assessment Technologies (SEMAT) project is aimed at addressing this problem by creating an open standard for [...] Read more.
Expense and the logistical difficulties with deploying scientific monitoring equipment are the biggest limitations to undertaking large scale monitoring of aquatic environments. The Smart Environmental Monitoring and Assessment Technologies (SEMAT) project is aimed at addressing this problem by creating an open standard for low-cost, near real-time, remote aquatic environmental monitoring systems. This paper presents the latest refinement of the SEMAT system in-line with the evolution of existing technologies, inexpensive sensors and environmental monitoring expectations. We provide a systems analysis and design of the SEMAT remote monitoring units and the back-end data management system. The system’s value is augmented through a unique e-waste recycling and repurposing model which engages/educates the community in the production of the SEMAT units using social enterprise. SEMAT serves as an open standard for the community to innovate around to further the state of play with low-cost environmental monitoring. The latest SEMAT units have been trialled in a peri-urban lake setting and the results demonstrate the system’s capabilities to provide ongoing data in near real-time to validate an environmental model of the study site. Full article
(This article belongs to the Section Internet of Things)
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20 pages, 14107 KiB  
Article
Consistent Semantic Annotation of Outdoor Datasets via 2D/3D Label Transfer
by Radim Tylecek and Robert B. Fisher
Sensors 2018, 18(7), 2249; https://doi.org/10.3390/s18072249 - 12 Jul 2018
Cited by 9 | Viewed by 5660
Abstract
The advance of scene understanding methods based on machine learning relies on the availability of large ground truth datasets, which are essential for their training and evaluation. Construction of such datasets with imagery from real sensor data however typically requires much manual annotation [...] Read more.
The advance of scene understanding methods based on machine learning relies on the availability of large ground truth datasets, which are essential for their training and evaluation. Construction of such datasets with imagery from real sensor data however typically requires much manual annotation of semantic regions in the data, delivered by substantial human labour. To speed up this process, we propose a framework for semantic annotation of scenes captured by moving camera(s), e.g., mounted on a vehicle or robot. It makes use of an available 3D model of the traversed scene to project segmented 3D objects into each camera frame to obtain an initial annotation of the associated 2D image, which is followed by manual refinement by the user. The refined annotation can be transferred to the next consecutive frame using optical flow estimation. We have evaluated the efficiency of the proposed framework during the production of a labelled outdoor dataset. The analysis of annotation times shows that up to 43% less effort is required on average, and the consistency of the labelling is also improved. Full article
(This article belongs to the Special Issue Annotation of User Data for Sensor-Based Systems)
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14 pages, 7975 KiB  
Article
Biosensing System for Concentration Quantification of Magnetically Labeled E. coli in Water Samples
by Anna Malec, Georgios Kokkinis, Christoph Haiden and Ioanna Giouroudi
Sensors 2018, 18(7), 2250; https://doi.org/10.3390/s18072250 - 12 Jul 2018
Cited by 8 | Viewed by 3759
Abstract
Bacterial contamination of water sources (e.g., lakes, rivers and springs) from waterborne bacteria is a crucial water safety issue and its prevention is of the utmost significance since it threatens the health and well-being of wildlife, livestock, and human populations and can lead [...] Read more.
Bacterial contamination of water sources (e.g., lakes, rivers and springs) from waterborne bacteria is a crucial water safety issue and its prevention is of the utmost significance since it threatens the health and well-being of wildlife, livestock, and human populations and can lead to serious illness and even death. Rapid and multiplexed measurement of such waterborne pathogens is vital and the challenge is to instantly detect in these liquid samples different types of pathogens with high sensitivity and specificity. In this work, we propose a biosensing system in which the bacteria are labelled with streptavidin coated magnetic markers (MPs—magnetic particles) forming compounds (MLBs—magnetically labelled bacteria). Video microscopy in combination with a particle tracking software are used for their detection and quantification. When the liquid containing the MLBs is introduced into the developed, microfluidic platform, the MLBs are accelerated towards the outlet by means of a magnetic field gradient generated by integrated microconductors, which are sequentially switched ON and OFF by a microcontroller. The velocities of the MLBs and that of reference MPs, suspended in the same liquid in a parallel reference microfluidic channel, are calculated and compared in real time by a digital camera mounted on a conventional optical microscope in combination with a particle trajectory tracking software. The MLBs will be slower than the reference MPs due to the enhanced Stokes’ drag force exerted on them, resulting from their greater volume and altered hydrodynamic shape. The results of the investigation showed that the parameters obtained from this method emerged as reliable predictors for E. coli concentrations. Full article
(This article belongs to the Special Issue Magnetic Materials Based Biosensors)
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21 pages, 3212 KiB  
Review
A Review of PZT Patches Applications in Submerged Systems
by Alexandre Presas, Yongyao Luo, Zhengwei Wang, David Valentin and Mònica Egusquiza
Sensors 2018, 18(7), 2251; https://doi.org/10.3390/s18072251 - 12 Jul 2018
Cited by 45 | Viewed by 7634
Abstract
Submerged systems are found in many engineering, biological, and medicinal applications. For such systems, due to the particular environmental conditions and working medium, the research on the mechanical and structural properties at every scale (from macroscopic to nanoscopic), and the control of the [...] Read more.
Submerged systems are found in many engineering, biological, and medicinal applications. For such systems, due to the particular environmental conditions and working medium, the research on the mechanical and structural properties at every scale (from macroscopic to nanoscopic), and the control of the system dynamics and induced effects become very difficult tasks. For such purposes in submerged systems, piezoelectric patches (PZTp), which are light, small and economic, have been proved to be a very good solution. PZTp have been recently used as sensors/actuators for applications such as modal analysis, active sound and vibration control, energy harvesting and atomic force microscopes in submerged systems. As a consequence, in these applications, newly developed transducers based on PZTp have become the most used ones, which has improved the state of the art and methods used in these fields. This review paper carefully analyzes and summarizes these applications particularized to submerged structures and shows the most relevant results and findings, which have been obtained thanks to the use of PZTp. Full article
(This article belongs to the Special Issue Recent Advances of Piezoelectric Transducers and Applications)
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16 pages, 834 KiB  
Review
Acoustic Radiation Force Based Ultrasound Elasticity Imaging for Biomedical Applications
by Lulu Wang
Sensors 2018, 18(7), 2252; https://doi.org/10.3390/s18072252 - 12 Jul 2018
Cited by 11 | Viewed by 5842
Abstract
Pathological changes in biological tissue are related to the changes in mechanical properties of biological tissue. Conventional medical screening tools such as ultrasound, magnetic resonance imaging or computed tomography have failed to produce the elastic properties of biological tissues directly. Ultrasound elasticity imaging [...] Read more.
Pathological changes in biological tissue are related to the changes in mechanical properties of biological tissue. Conventional medical screening tools such as ultrasound, magnetic resonance imaging or computed tomography have failed to produce the elastic properties of biological tissues directly. Ultrasound elasticity imaging (UEI) has been proposed as a promising imaging tool to map the elastic parameters of soft tissues for the clinical diagnosis of various diseases include prostate, liver, breast, and thyroid gland. Existing UEI-based approaches can be classified into three groups: internal physiologic excitation, external excitation, and acoustic radiation force (ARF) excitation methods. Among these methods, ARF has become one of the most popular techniques for the clinical diagnosis and treatment of disease. This paper provides comprehensive information on the recently developed ARF-based UEI techniques and instruments for biomedical applications. The mechanical properties of soft tissue, ARF and displacement estimation methods, working principle and implementation instruments for each ARF-based UEI method are discussed. Full article
(This article belongs to the Special Issue Ultrasonic Sensors 2018)
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20 pages, 29521 KiB  
Article
Strategy for Determining the Stochastic Distance Characteristics of the 2D Laser Scanner Z + F Profiler 9012A with Special Focus on the Close Range
by Erik Heinz, Markus Mettenleiter, Heiner Kuhlmann and Christoph Holst
Sensors 2018, 18(7), 2253; https://doi.org/10.3390/s18072253 - 12 Jul 2018
Cited by 17 | Viewed by 6281
Abstract
Kinematic laser scanning with moving platforms has been used for the acquisition of 3D point clouds of our environment for many years. A main application of these mobile systems is the acquisition of the infrastructure, e.g., the road surface and buildings. Regarding this, [...] Read more.
Kinematic laser scanning with moving platforms has been used for the acquisition of 3D point clouds of our environment for many years. A main application of these mobile systems is the acquisition of the infrastructure, e.g., the road surface and buildings. Regarding this, the distance between laser scanner and object is often notably shorter than 20 m. In the close range, however, divergent incident laser light can lead to a deterioration of the precision of laser scanner distance measurements. In the light of this, we analyze the distance precision of the 2D laser scanner Z + F Profiler 9012A, purpose-built for kinematic applications, in the range of up to 20 m. In accordance with previous studies, a clear dependency between scan rate, intensity of the backscattered laser light and distance precision is evident, which is used to derive intensity-based stochastic models for the sensor. For this purpose, a new approach for 2D laser scanners is proposed that is based on the static scanning of surfaces with different backscatter. The approach is beneficial because the 2D laser scanner is operated in its normal measurement mode, no sophisticated equipment is required and no model assumptions for the scanned surface are made. The analysis reveals a lower precision in the range below 5 m caused by a decreased intensity. However, the Z + F Profiler 9012A is equipped with a special hardware-based close range optimization partially compensating for this. Our investigations show that this optimization works best at a distance of about 2 m. Although increased noise remains a critical factor in the close range, the derived stochastic models are also valid below 5 m. Full article
(This article belongs to the Special Issue Laser Sensors for Displacement, Distance and Position)
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18 pages, 2131 KiB  
Article
Estimation of Human Body Vital Signs Based on 60 GHz Doppler Radar Using a Bound-Constrained Optimization Algorithm
by Ting Zhang, Julien Sarrazin, Guido Valerio and Dan Istrate
Sensors 2018, 18(7), 2254; https://doi.org/10.3390/s18072254 - 12 Jul 2018
Cited by 22 | Viewed by 6189
Abstract
In this study, a bound-constrained optimization algorithm is applied for estimating physiological data (pulse and breathing rate) of human body using 60 GHz Doppler radar, by detecting displacements induced by breathing and the heartbeat of a human subject. The influence of mutual phasing [...] Read more.
In this study, a bound-constrained optimization algorithm is applied for estimating physiological data (pulse and breathing rate) of human body using 60 GHz Doppler radar, by detecting displacements induced by breathing and the heartbeat of a human subject. The influence of mutual phasing between the two movements is analyzed in a theoretical framework and the application of optimization algorithms is proved to be able to accurately detect both breathing and heartbeat rates, despite intermodulation effects between them. Different optimization procedures are compared and shown to be more robust to receiver noise and artifacts of random body motion than a direct spectrum analysis. In case of a large-scale constrained bound, a parallel optimization procedure executed in subranges is proposed to realize accurate detection in a reduced span of time. Full article
(This article belongs to the Section Physical Sensors)
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26 pages, 2452 KiB  
Review
Real-Time Early Warning System Design for Pluvial Flash Floods—A Review
by Melisa Acosta-Coll, Francisco Ballester-Merelo, Marcos Martinez-Peiró and Emiro De la Hoz-Franco
Sensors 2018, 18(7), 2255; https://doi.org/10.3390/s18072255 - 12 Jul 2018
Cited by 115 | Viewed by 23472
Abstract
Pluvial flash floods in urban areas are becoming increasingly frequent due to climate change and human actions, negatively impacting the life, work, production and infrastructure of a population. Pluvial flooding occurs when intense rainfall overflows the limits of urban drainage and water accumulation [...] Read more.
Pluvial flash floods in urban areas are becoming increasingly frequent due to climate change and human actions, negatively impacting the life, work, production and infrastructure of a population. Pluvial flooding occurs when intense rainfall overflows the limits of urban drainage and water accumulation causes hazardous flash floods. Although flash floods are hard to predict given their rapid formation, Early Warning Systems (EWS) are used to minimize casualties. We performed a systematic review to define the basic structure of an EWS for rain flash floods. The structure of the review is as follows: first, Section 2 describes the most important factors that affect the intensity of pluvial flash floods during rainfall events. Section 3 defines the key elements and actors involved in an effective EWS. Section 4 reviews different EWS architectures for pluvial flash floods implemented worldwide. It was identified that the reviewed projects did not follow guidelines to design early warning systems, neglecting important aspects that must be taken into account in their implementation. Therefore, this manuscript proposes a basic structure for an effective EWS for pluvial flash floods that guarantees the forecasting process and alerts dissemination during rainfall events. Full article
(This article belongs to the Special Issue Smart Sensing System for Real-Time Monitoring)
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22 pages, 4984 KiB  
Article
A Novel Carrier Loop Algorithm Based on Maximum Likelihood Estimation (MLE) and Kalman Filter (KF) for Weak TC-OFDM Signals
by Wen Liu, Xinmei Bian, Zhongliang Deng, Jun Mo and Buyun Jia
Sensors 2018, 18(7), 2256; https://doi.org/10.3390/s18072256 - 13 Jul 2018
Cited by 8 | Viewed by 4501
Abstract
Digital broadcasting signals represent a promising positioning signal for indoors applications. A novel positioning technology named Time & Code Division-Orthogonal Frequency Division Multiplexing (TC-OFDM) is mainly discussed in this paper, which is based on China mobile multimedia broadcasting (CMMB). Signal strength is an [...] Read more.
Digital broadcasting signals represent a promising positioning signal for indoors applications. A novel positioning technology named Time & Code Division-Orthogonal Frequency Division Multiplexing (TC-OFDM) is mainly discussed in this paper, which is based on China mobile multimedia broadcasting (CMMB). Signal strength is an important factor that affects the carrier loop performance of the TC-OFDM receiver. In the case of weak TC-OFDM signals, the current carrier loop algorithm has large residual carrier errors, which limit the tracking sensitivity of the existing carrier loop in complex indoor environments. This paper proposes a novel carrier loop algorithm based on Maximum Likelihood Estimation (MLE) and Kalman Filter (KF) to solve the above problem. The discriminator of the current carrier loop is replaced by the MLE discriminator function in the proposed algorithm. The Levenberg-Marquardt (LM) algorithm is utilized to obtain the MLE cost function consisting of signal amplitude, residual carrier frequency and carrier phase, and the MLE discriminator function is derived from the corresponding MLE cost function. The KF is used to smooth the MLE discriminator function results, which takes the carrier phase estimation, the angular frequency estimation and the angular frequency rate as the state vector. Theoretical analysis and simulation results show that the proposed algorithm can improve the tracking sensitivity of the TC-OFDM receiver by taking full advantage of the characteristics of the carrier loop parameters. Compared with the current carrier loop algorithms, the tracking sensitivity is effectively improved by 2–4 dB, and the better performance of the proposed algorithm is verified in the real environment. Full article
(This article belongs to the Special Issue Selected Papers from UPINLBS 2018)
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13 pages, 4392 KiB  
Article
Cost-Effective Technologies to Study the Arctic Ocean Environment
by Viviana Piermattei, Alice Madonia, Simone Bonamano, Riccardo Martellucci, Gabriele Bruzzone, Roberta Ferretti, Angelo Odetti, Maurizio Azzaro, Giuseppe Zappalà and Marco Marcelli
Sensors 2018, 18(7), 2257; https://doi.org/10.3390/s18072257 - 13 Jul 2018
Cited by 21 | Viewed by 5434
Abstract
The Arctic region is known to be severely affected by climate change, with evident alterations in both physical and biological processes. Monitoring the Arctic Ocean ecosystem is key to understanding the impact of natural and human-induced change on the environment. Large data sets [...] Read more.
The Arctic region is known to be severely affected by climate change, with evident alterations in both physical and biological processes. Monitoring the Arctic Ocean ecosystem is key to understanding the impact of natural and human-induced change on the environment. Large data sets are required to monitor the Arctic marine ecosystem and validate high-resolution satellite observations (e.g., Sentinel), which are necessary to feed climatic and biogeochemical forecasting models. However, the Global Observing System needs to complete its geographic coverage, particularly for the harsh, extreme environment of the Arctic Region. In this scenario, autonomous systems are proving to be valuable tools for increasing the resolution of existing data. To this end, a low-cost, miniaturized and flexible probe, ArLoC (Arctic Low-Cost probe), was designed, built and installed on an innovative unmanned marine vehicle, the PROTEUS (Portable RObotic TEchnology for Unmanned Surveys), during a preliminary scientific campaign in the Svalbard Archipelago within the UVASS project. This study outlines the instrumentation used and its design features, its preliminary integration on PROTEUS and its test results. Full article
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14 pages, 4147 KiB  
Article
Engineering Vehicles Detection Based on Modified Faster R-CNN for Power Grid Surveillance
by Xuezhi Xiang, Ning Lv, Xinli Guo, Shuai Wang and Abdulmotaleb El Saddik
Sensors 2018, 18(7), 2258; https://doi.org/10.3390/s18072258 - 13 Jul 2018
Cited by 53 | Viewed by 4742
Abstract
Engineering vehicles intrusion detection is a key problem for the security of power grid operation, which can warn of the regional invasion and prevent external damage from architectural construction. In this paper, we propose an intelligent surveillance method based on the framework of [...] Read more.
Engineering vehicles intrusion detection is a key problem for the security of power grid operation, which can warn of the regional invasion and prevent external damage from architectural construction. In this paper, we propose an intelligent surveillance method based on the framework of Faster R-CNN for locating and identifying the invading engineering vehicles. In our detection task, the type of the objects is varied and the monitoring scene is large and complex. In order to solve these challenging problems, we modify the network structure of the object detection model by adjusting the position of the ROI pooling layer. The convolutional layer is added to the feature classification part to improve the accuracy of the detection model. We verify that increasing the depth of the feature classification part is effective for detecting engineering vehicles in realistic transmission lines corridors. We also collect plenty of scene images taken from the monitor site and label the objects to create a fine-tuned dataset. We train the modified deep detection model based on the technology of transfer learning and conduct training and test on the newly labeled dataset. Experimental results show that the proposed intelligent surveillance method can detect engineering vehicles with high accuracy and a low false alarm rate, which can be used for the early warning of power grid surveillance. Full article
(This article belongs to the Section Intelligent Sensors)
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11 pages, 8224 KiB  
Article
Shaping Streamflow Using a Real-Time Stormwater Control Network
by Abhiram Mullapudi, Matthew Bartos, Brandon Wong and Branko Kerkez
Sensors 2018, 18(7), 2259; https://doi.org/10.3390/s18072259 - 13 Jul 2018
Cited by 32 | Viewed by 4979
Abstract
“Smart” water systems are transforming the field of stormwater management by enabling real-time monitoring and control of previously static infrastructure. While the localized benefits of active control are well-established, the potential for system-scale control of watersheds is poorly understood. This study shows how [...] Read more.
“Smart” water systems are transforming the field of stormwater management by enabling real-time monitoring and control of previously static infrastructure. While the localized benefits of active control are well-established, the potential for system-scale control of watersheds is poorly understood. This study shows how a real-world smart stormwater system can be leveraged to shape streamflow within an urban watershed. Specifically, we coordinate releases from two internet-controlled stormwater basins to achieve desired control objectives downstream—such as maintaining the flow at a set-point, and generating interleaved waves. In the first part of the study, we describe the construction of the control network using a low-cost, open-source hardware stack and a cloud-based controller scheduling application. Next, we characterize the system’s control capabilities by determining the travel times, decay times, and magnitudes of various waves released from the upstream retention basins. With this characterization in hand, we use the system to generate two desired responses at a critical downstream junction. First, we generate a set-point hydrograph, in which flow is maintained at an approximately constant rate. Next, we generate a series of overlapping and interleaved waves using timed releases from both retention basins. We discuss how these control strategies can be used to stabilize flows, thereby mitigating streambed erosion and reducing contaminant loads into downstream waterbodies. Full article
(This article belongs to the Special Issue Sensor Networks for Environmental Observations)
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14 pages, 3588 KiB  
Article
Development of a User-Adaptable Human Fall Detection Based on Fall Risk Levels Using Depth Sensor
by Yoosuf Nizam, Mohd Norzali Haji Mohd and M. Mahadi Abdul Jamil
Sensors 2018, 18(7), 2260; https://doi.org/10.3390/s18072260 - 13 Jul 2018
Cited by 26 | Viewed by 5122
Abstract
Unintentional falls are a major public health concern for many communities, especially with aging populations. There are various approaches used to classify human activities for fall detection. Related studies have employed wearable, non-invasive sensors, video cameras and depth sensor-based approaches to develop such [...] Read more.
Unintentional falls are a major public health concern for many communities, especially with aging populations. There are various approaches used to classify human activities for fall detection. Related studies have employed wearable, non-invasive sensors, video cameras and depth sensor-based approaches to develop such monitoring systems. The proposed approach in this study uses a depth sensor and employs a unique procedure which identifies the fall risk levels to adapt the algorithm for different people with their physical strength to withstand falls. The inclusion of the fall risk level identification, further enhanced and improved the accuracy of the fall detection. The experimental results showed promising performance in adapting the algorithm for people with different fall risk levels for fall detection. Full article
(This article belongs to the Special Issue Sensor Applications in Medical Monitoring and Assistive Devices)
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19 pages, 6790 KiB  
Article
LifeChair: A Conductive Fabric Sensor-Based Smart Cushion for Actively Shaping Sitting Posture
by Karlos Ishac and Kenji Suzuki
Sensors 2018, 18(7), 2261; https://doi.org/10.3390/s18072261 - 13 Jul 2018
Cited by 47 | Viewed by 12392
Abstract
The LifeChair is a smart cushion that provides vibrotactile feedback by actively sensing and classifying sitting postures to encourage upright posture and reduce slouching. The key component of the LifeChair is our novel conductive fabric pressure sensing array. Fabric sensors have been explored [...] Read more.
The LifeChair is a smart cushion that provides vibrotactile feedback by actively sensing and classifying sitting postures to encourage upright posture and reduce slouching. The key component of the LifeChair is our novel conductive fabric pressure sensing array. Fabric sensors have been explored in the past, but a full sensing solution for embedded real world use has not been proposed. We have designed our system with commercial use in mind, and as a result, it has a high focus on manufacturability, cost-effectiveness and adaptiveness. We demonstrate the performance of our fabric sensing system by installing it into the LifeChair and comparing its posture detection accuracy with our previous study that implemented a conventional flexible printed PCB-sensing system. In this study, it is shown that the LifeChair can detect all 11 postures across 20 participants with an improved average accuracy of 98.1%, and it demonstrates significantly lower variance when interfacing with different users. We also conduct a performance study with 10 participants to evaluate the effectiveness of the LifeChair device in improving upright posture and reducing slouching. Our performance study demonstrates that the LifeChair is effective in encouraging users to sit upright with an increase of 68.1% in time spent seated upright when vibrotactile feedback is activated. Full article
(This article belongs to the Special Issue Sensor Applications in Medical Monitoring and Assistive Devices)
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20 pages, 26704 KiB  
Article
A PolSAR Image Segmentation Algorithm Based on Scattering Characteristics and the Revised Wishart Distance
by Huiguo Yi, Jie Yang, Pingxiang Li, Lei Shi and Fengkai Lang
Sensors 2018, 18(7), 2262; https://doi.org/10.3390/s18072262 - 13 Jul 2018
Cited by 6 | Viewed by 4090
Abstract
A novel segmentation algorithm for polarimetric synthetic aperture radar (PolSAR) images is proposed in this paper. The method is composed of two essential components: a merging order and a merging predicate. The similarity measured by the complex-kind Hotelling–Lawley trace (HLT) statistic is used [...] Read more.
A novel segmentation algorithm for polarimetric synthetic aperture radar (PolSAR) images is proposed in this paper. The method is composed of two essential components: a merging order and a merging predicate. The similarity measured by the complex-kind Hotelling–Lawley trace (HLT) statistic is used to decide the merging order. The merging predicate is determined by the scattering characteristics and the revised Wishart distance between adjacent pixels, which can greatly improve the performance in speckle suppression and detail preservation. A postprocessing step is applied to obtain a satisfactory result after the merging operation. The decomposition and merging processes are iteratively executed until the termination criterion is met. The superiority of the proposed method was verified with experiments on two RADARSAT-2 PolSAR images and a Gaofen-3 PolSAR image, which demonstrated that the proposed method can obtain more accurate segmentation results and shows a better performance in speckle suppression and detail preservation than the other algorithms. Full article
(This article belongs to the Special Issue First Experiences with Chinese Gaofen-3 SAR Sensor)
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10 pages, 5789 KiB  
Article
Design of Security Paper with Selective Frequency Reflection Characteristics
by Sang-Hwa Lee, Min-Sik Kim, Jong-Kyu Kim and Ic-Pyo Hong
Sensors 2018, 18(7), 2263; https://doi.org/10.3390/s18072263 - 13 Jul 2018
Cited by 4 | Viewed by 4071
Abstract
In this research, a security paper based on frequency selective structure technologies was designed and fabricated using selective wave reflection characteristics to prevent the offline leakage of confidential documents. Document leakage detection systems using security papers detect security papers using transceiving antenna gates. [...] Read more.
In this research, a security paper based on frequency selective structure technologies was designed and fabricated using selective wave reflection characteristics to prevent the offline leakage of confidential documents. Document leakage detection systems using security papers detect security papers using transceiving antenna gates. For the application of such systems, the structure must be designed with excellent reflection performance and stability at the angle of incidence. For this purpose, a loop and patch-type frequency selective structure based on a four-legged element structure was designed to have X-band frequency reflection characteristics. This design was based on optimized variables and was realized through the screen printing method using silver ink on A4 paper. It was verified that both the design and simulation results matched well. To verify its actual applicability, a detector module operable at 10 GHz was manufactured to observe both the security paper detection range in relation to distance with a signal strength of −10 dBm and the detection area in relation to the number of times that the security paper had been folded. Full article
(This article belongs to the Special Issue Paper-Based Sensors)
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24 pages, 8794 KiB  
Review
Review of Low-Cost Photoacoustic Sensing and Imaging Based on Laser Diode and Light-Emitting Diode
by Hongtao Zhong, Tingyang Duan, Hengrong Lan, Meng Zhou and Fei Gao
Sensors 2018, 18(7), 2264; https://doi.org/10.3390/s18072264 - 13 Jul 2018
Cited by 98 | Viewed by 9698
Abstract
Photoacoustic tomography (PAT), a promising medical imaging method that combines optical and ultrasound techniques, has been developing for decades mostly in preclinical application. A recent trend is to utilize the economical laser source to develop a low-cost sensing and imaging system, which aims [...] Read more.
Photoacoustic tomography (PAT), a promising medical imaging method that combines optical and ultrasound techniques, has been developing for decades mostly in preclinical application. A recent trend is to utilize the economical laser source to develop a low-cost sensing and imaging system, which aims at an affordable solution in clinical application. These low-cost laser sources have different modulation modes such as pulsed modulation, continuous modulation and coded modulation to generate different profiles of PA signals in photoacoustic (PA) imaging. In this paper, we review the recent development of the photoacoustic sensing and imaging based on the economical laser sources such as laser diode (LD) and light-emitting diode (LED) in different kinds of modulation types, and discuss several representative methods to improve the performance of such imaging systems based on low-cost laser sources. Finally, some perspectives regarding the future development of portable PAT systems are discussed, followed by the conclusion. Full article
(This article belongs to the Special Issue Photoacoustic Sensing and Imaging in Biomedicine)
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13 pages, 3396 KiB  
Article
Deceptive Jamming Detection for SAR Based on Cross-Track Interferometry
by Qingqing Feng, Huaping Xu, Zhefeng Wu and Wei Liu
Sensors 2018, 18(7), 2265; https://doi.org/10.3390/s18072265 - 13 Jul 2018
Cited by 16 | Viewed by 5174
Abstract
Deceptive jamming against synthetic aperture radar (SAR) can create false targets or deceptive scenes in the image effectively. Based on the difference in interferometric phase between the target and deceptive jamming signals, a novel method for detecting deceptive jamming using cross-track interferometry is [...] Read more.
Deceptive jamming against synthetic aperture radar (SAR) can create false targets or deceptive scenes in the image effectively. Based on the difference in interferometric phase between the target and deceptive jamming signals, a novel method for detecting deceptive jamming using cross-track interferometry is proposed, where the echoes with deceptive jamming are received by two SAR antennas simultaneously and the false targets are identified through SAR interferometry. Since the derived false phase is close to a constant in interferogram, it is extracted through phase filtering and frequency detection. Finally, the false targets in the SAR image are obtained according to the detected false part in the interferogram. The effectiveness of the proposed method is validated by simulation results based on the TanDEM-X system. Full article
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11 pages, 1561 KiB  
Article
Modeling and Analysis of a Novel Ultrasensitive Differential Resonant Graphene Micro-Accelerometer with Wide Measurement Range
by Fu-Tao Shi, Shang-Chun Fan, Cheng Li and Xiao-Bin Peng
Sensors 2018, 18(7), 2266; https://doi.org/10.3390/s18072266 - 13 Jul 2018
Cited by 17 | Viewed by 4011
Abstract
A novel, ultrahigh-sensitivity wide-range resonant micro-accelerometer using two differential double-clamped monolayer graphene beams is designed and investigated by steady-state simulation via COMSOL Multiphysics software in this paper. Along with stiffness-enhanced optimized folded support beams, two symmetrical 3-GPa prestressed graphene nano-beams serve as resonant [...] Read more.
A novel, ultrahigh-sensitivity wide-range resonant micro-accelerometer using two differential double-clamped monolayer graphene beams is designed and investigated by steady-state simulation via COMSOL Multiphysics software in this paper. Along with stiffness-enhanced optimized folded support beams, two symmetrical 3-GPa prestressed graphene nano-beams serve as resonant sensitive elements with a size of 10 μm × 1 μm (length × width) to increase the acceleration sensitivity while extending the measurement range. The simulation results show that the accelerometer with cascade-connected graphene and proof-mass assembly exhibits the ultrahigh sensitivity of 21,224 Hz/g and quality factor of 9773 in the range of 0–1000 g. This is remarkably superior to previously reported studies characterized by attaching proof mass to the graphene components directly. The proposed accelerometer shows great potential as an alternative to quartz and silicon-based resonant sensors in high-impact and highly sensitive inertial measurement applications. Full article
(This article belongs to the Special Issue Sensors for MEMS and Microsystems)
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13 pages, 2340 KiB  
Article
Effects of Applying Different Resonance Amplitude on the Performance of the Impedance-Based Health Monitoring Technique Subjected to Damage
by Wongi S. Na, Dong-Woo Seo, Byeong-Cheol Kim and Ki-Tae Park
Sensors 2018, 18(7), 2267; https://doi.org/10.3390/s18072267 - 13 Jul 2018
Cited by 10 | Viewed by 3083
Abstract
Smart materials such as piezoelectric transducers can be used for monitoring the health of building structures. In this study, a structural health monitoring technique known as the electromechanical impedance (EMI) method is investigated. Although the EMI method has the advantage of using a [...] Read more.
Smart materials such as piezoelectric transducers can be used for monitoring the health of building structures. In this study, a structural health monitoring technique known as the electromechanical impedance (EMI) method is investigated. Although the EMI method has the advantage of using a single piezoelectric patch that acts both as the actuator and as the sensor, there are still many issues to be addressed. To further understand the problem, the performance of the EMI method on a structure subjected to progressive damage at different resonance frequency ranges and peak amplitudes was investigated using three different statistical metrics: root-mean-square deviation (RMSD), mean absolute percentage deviation (MAPD) and correlation coefficient deviation (CCD). Metal plates were used throughout the study. The results acquired could be used to further understand the damage identification performance of the EMI method. Full article
(This article belongs to the Special Issue Smart Sensors and Smart Structures)
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22 pages, 6138 KiB  
Article
Model-Based Position and Reflectivity Estimation of Fiber Bragg Grating Sensor Arrays
by Stefan Werzinger, Darko Zibar, Max Köppel and Bernhard Schmauss
Sensors 2018, 18(7), 2268; https://doi.org/10.3390/s18072268 - 13 Jul 2018
Cited by 3 | Viewed by 4190
Abstract
We propose an efficient model-based signal processing approach for optical fiber sensing with fiber Bragg grating (FBG) arrays. A position estimation based on an estimation of distribution algorithm (EDA) and a reflectivity estimation method using a parametric transfer matrix model (TMM) are outlined [...] Read more.
We propose an efficient model-based signal processing approach for optical fiber sensing with fiber Bragg grating (FBG) arrays. A position estimation based on an estimation of distribution algorithm (EDA) and a reflectivity estimation method using a parametric transfer matrix model (TMM) are outlined in detail. The estimation algorithms are evaluated with Monte Carlo simulations and measurement data from an incoherent optical frequency domain reflectometer (iOFDR). The model-based approach outperforms conventional Fourier transform processing, especially near the spatial resolution limit, saving electrical bandwidth and measurement time. The models provide great flexibility and can be easily expanded in complexity to meet different topologies and to include prior knowledge of the sensors. Systematic errors due to crosstalk between gratings caused by multiple reflections and spectral shadowing could be further considered with the TMM to improve the performance of large-scale FBG array sensor systems. Full article
(This article belongs to the Special Issue Optical Waveguide Based Sensors)
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12 pages, 4392 KiB  
Article
Application of Flexible Four-In-One Microsensor to Internal Real-Time Monitoring of Proton Exchange Membrane Fuel Cell
by Chi-Yuan Lee, Chia-Hung Chen, Chao-Yuan Chiu, Kuan-Lin Yu and Lung-Jieh Yang
Sensors 2018, 18(7), 2269; https://doi.org/10.3390/s18072269 - 13 Jul 2018
Cited by 7 | Viewed by 3141
Abstract
In recent years, the development of green energy sources, such as fuel cell, biomass energy, solar energy, and tidal energy, has become a popular research subject. This study aims at a flexible four-in-one microsensor, which can be embedded in the proton exchange membrane [...] Read more.
In recent years, the development of green energy sources, such as fuel cell, biomass energy, solar energy, and tidal energy, has become a popular research subject. This study aims at a flexible four-in-one microsensor, which can be embedded in the proton exchange membrane fuel cell (PEMFC) for real-time microscopic diagnosis so as to assist in developing and improving the technology of the fuel cell. Therefore, this study uses micro-electro-mechanical systems (MEMS) technology to integrate a micro humidity sensor, micro pH sensor, micro temperature sensor, and micro voltage sensor into a flexible four-in-one microsensor. This flexible four-in-one microsensor has four functions and is favorably characterized by small size, good acid resistance and temperature resistance, quick response, and real-time measurement. The goal was to be able to put the four-in-one microsensor in any place for measurement without affecting the performance of the fuel cell. Full article
(This article belongs to the Section Physical Sensors)
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16 pages, 3874 KiB  
Article
Evaluating Geometric Measurement Accuracy Based on 3D Reconstruction of Automated Imagery in a Greenhouse
by Jing Zhou, Xiuqing Fu, Leon Schumacher and Jianfeng Zhou
Sensors 2018, 18(7), 2270; https://doi.org/10.3390/s18072270 - 13 Jul 2018
Cited by 14 | Viewed by 4559
Abstract
Geometric dimensions of plants are significant parameters for showing plant dynamic responses to environmental variations. An image-based high-throughput phenotyping platform was developed to automatically measure geometric dimensions of plants in a greenhouse. The goal of this paper was to evaluate the accuracy in [...] Read more.
Geometric dimensions of plants are significant parameters for showing plant dynamic responses to environmental variations. An image-based high-throughput phenotyping platform was developed to automatically measure geometric dimensions of plants in a greenhouse. The goal of this paper was to evaluate the accuracy in geometric measurement using the Structure from Motion (SfM) method from images acquired using the automated image-based platform. Images of nine artificial objects of different shapes were taken under 17 combinations of three different overlaps in x and y directions, respectively, and two different spatial resolutions (SRs) with three replicates. Dimensions in x, y and z of these objects were measured from 3D models reconstructed using the SfM method to evaluate the geometric accuracy. A metric power of unit (POU) was proposed to combine the effects of image overlap and SR. Results showed that measurement error of dimension in z is the least affected by overlap and SR among the three dimensions and measurement error of dimensions in x and y increased following a power function with the decrease of POU (R2 = 0.78 and 0.88 for x and y respectively). POUs from 150 to 300 are a preferred range to obtain reasonable accuracy and efficiency for the developed image-based high-throughput phenotyping system. As a study case, the developed system was used to measure the height of 44 plants using an optimal POU in greenhouse environment. The results showed a good agreement (R2 = 92% and Root Mean Square Error = 9.4 mm) between the manual and automated method. Full article
(This article belongs to the Section Physical Sensors)
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22 pages, 9357 KiB  
Article
Inversion of Rice Biophysical Parameters Using Simulated Compact Polarimetric SAR C-Band Data
by Xianyu Guo, Kun Li, Yun Shao, Zhiyong Wang, Hongyu Li, Zhi Yang, Long Liu and Shuli Wang
Sensors 2018, 18(7), 2271; https://doi.org/10.3390/s18072271 - 13 Jul 2018
Cited by 19 | Viewed by 5466
Abstract
Timely and accurate estimation of rice parameters plays a significant role in rice monitoring and yield forecasting for ensuring food security. Compact-polarimetric (CP) synthetic aperture radar (SAR), a good compromise between the dual- and quad-polarized SARs, is an important part of the new [...] Read more.
Timely and accurate estimation of rice parameters plays a significant role in rice monitoring and yield forecasting for ensuring food security. Compact-polarimetric (CP) synthetic aperture radar (SAR), a good compromise between the dual- and quad-polarized SARs, is an important part of the new generation of Earth observation systems. In this paper, the ability of CP SAR data to retrieve rice biophysical parameters was explored using a modified water cloud model. The results showed that S1 was superior to other CP variables in rice height inversion with a coefficient of determination (R2) of 0.92 and a root-mean-square error (RMSE) of 5.81 cm. RL was the most suitable for inverting the volumetric water content of the rice canopy, with an R2 of 0.95 and a RMSE of 0.31 kg/m3. The m-χ decomposition produced the highest accuracies for the ear biomass: R2 was 0.89 and RMSE was 0.17 kg/m2. The highest accuracy of leaf area index (LAI) retrieval was obtained for RH (right circular transmit and horizontal linear receive) with an R2 of 0.79 and a RMSE of 0.33. This study illustrated the capability of CP SAR data with respect to retrieval of rice biophysical parameters, especially for height, volumetric water content of the rice canopy, and ear biomass, and this mode may offer the best option for rice-monitoring applications because of swath coverage. Full article
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18 pages, 851 KiB  
Article
An Occlusion-Robust Feature Selection Framework in Pedestrian Detection
by Zhixin Guo, Wenzhi Liao, Yifan Xiao, Peter Veelaert and Wilfried Philips
Sensors 2018, 18(7), 2272; https://doi.org/10.3390/s18072272 - 13 Jul 2018
Cited by 4 | Viewed by 3120
Abstract
Better features have been driving the progress of pedestrian detection over the past years. However, as features become richer and higher dimensional, noise and redundancy in the feature sets become bigger problems. These problems slow down learning and can even reduce the performance [...] Read more.
Better features have been driving the progress of pedestrian detection over the past years. However, as features become richer and higher dimensional, noise and redundancy in the feature sets become bigger problems. These problems slow down learning and can even reduce the performance of the learned model. Current solutions typically exploit dimension reduction techniques. In this paper, we propose a simple but effective feature selection framework for pedestrian detection. Moreover, we introduce occluded pedestrian samples into the training process and combine it with a new feature selection criterion, which enables improved performances for occlusion handling problems. Experimental results on the Caltech Pedestrian dataset demonstrate the efficiency of our method over the state-of-art methods, especially for the occluded pedestrians. Full article
(This article belongs to the Section Intelligent Sensors)
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18 pages, 5021 KiB  
Article
Mouthwitch: A Novel Head Mount Type Hands-Free Input Device that Uses the Movement of the Temple to Control a Camera
by Kazuhiro Taniguchi and Atsushi Nishikawa
Sensors 2018, 18(7), 2273; https://doi.org/10.3390/s18072273 - 13 Jul 2018
Cited by 2 | Viewed by 4213
Abstract
We have developed an interface (mouthwitch) for a head-mounted type camera with which pictures can be taken with a head-mounted camera, hands-free, simply by “opening your mouth continuously for approximately one second and then closing it again”. This mouthwitch uses a sensor equipped [...] Read more.
We have developed an interface (mouthwitch) for a head-mounted type camera with which pictures can be taken with a head-mounted camera, hands-free, simply by “opening your mouth continuously for approximately one second and then closing it again”. This mouthwitch uses a sensor equipped with an LED and photo transistor on the temple to optically measure the changes in the form of the temple that occur when the mouth is opened and closed. Eight test subjects (males and females aged between 21 and 44 years old) performed evaluation tests using this mouthwitch when resting, speaking, chewing, walking, and running. The results showed that all test subjects were able to open and close the mouth, and the measurement results pertaining to the temple shape changes that occurred at this time were highly reproducible. Additionally, the average value for accuracy obtained for the eight test subjects through the verification tests was 100% when resting, chewing, or walking, and 99.8% when speaking or running. Similarly, the average values for precision were 100% for all items, and the average values for recall were 100% when resting or chewing, 98.8% when speaking, 97.5% when walking, and 87.5% when running. Full article
(This article belongs to the Special Issue Wearable Smart Devices)
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16 pages, 2490 KiB  
Article
Uncertainty Characterisation of Mobile Robot Localisation Techniques using Optical Surveying Grade Instruments
by Benjamin J. McLoughlin, Harry A. G. Pointon, John P. McLoughlin, Andy Shaw and Frederic A. Bezombes
Sensors 2018, 18(7), 2274; https://doi.org/10.3390/s18072274 - 13 Jul 2018
Cited by 11 | Viewed by 4699
Abstract
Recent developments in localisation systems for autonomous robotic technology have been a driving factor in the deployment of robots in a wide variety of environments. Estimating sensor measurement noise is an essential factor when producing uncertainty models for state-of-the-art robotic positioning systems. In [...] Read more.
Recent developments in localisation systems for autonomous robotic technology have been a driving factor in the deployment of robots in a wide variety of environments. Estimating sensor measurement noise is an essential factor when producing uncertainty models for state-of-the-art robotic positioning systems. In this paper, a surveying grade optical instrument in the form of a Trimble S7 Robotic Total Station is utilised to dynamically characterise the error of positioning sensors of a ground based unmanned robot. The error characteristics are used as inputs into the construction of a Localisation Extended Kalman Filter which fuses Pozyx Ultra-wideband range measurements with odometry to obtain an optimal position estimation, all whilst using the path generated from the remote tracking feature of the Robotic Total Station as a ground truth metric. Experiments show that the proposed method yields an improved positional estimation compared to the Pozyx systems’ native firmware algorithm as well as producing a smoother trajectory. Full article
(This article belongs to the Special Issue GNSS and Fusion with Other Sensors)
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11 pages, 2187 KiB  
Article
Wireless Chipless System for Humidity Sensing
by José F. Salmerón, Andreas Albrecht, Silmi Kaffah, Markus Becherer, Paolo Lugli and Almudena Rivadeneyra
Sensors 2018, 18(7), 2275; https://doi.org/10.3390/s18072275 - 13 Jul 2018
Cited by 27 | Viewed by 4251
Abstract
This work describes a fully wireless sensory system where a chipless strategy is followed in the sensor part. Alternatively, to characterize only the sensing element, we present the response of the reader antenna when the sensing element is placed in its vicinity: changes [...] Read more.
This work describes a fully wireless sensory system where a chipless strategy is followed in the sensor part. Alternatively, to characterize only the sensing element, we present the response of the reader antenna when the sensing element is placed in its vicinity: changes in the parameter of interest are seen by the reader through inductive coupling, varying its frequency response. The sensing part consists of a LC circuit manufactured by printing techniques on a flexible substrate, whose electrical permittivity shows dependence with the moisture content. The measurement distance show significant differences in the frequency response: a change of 700 kHz is observed when the measurement is performed directly on the wireless chipless sensor between 20% and 80%RH, while this variation in frequency is reduced more than three times when measuring at the reader antenna with 5 mm distance between elements. Furthermore, we demonstrate the importance of the separation between reader and sensor to get a reliable measuring system. Full article
(This article belongs to the Section Chemical Sensors)
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17 pages, 7754 KiB  
Article
Parameter Estimation of Signal-Dependent Random Noise in CMOS/CCD Image Sensor Based on Numerical Characteristic of Mixed Poisson Noise Samples
by Yu Zhang, Guangyi Wang and Jiangtao Xu
Sensors 2018, 18(7), 2276; https://doi.org/10.3390/s18072276 - 13 Jul 2018
Cited by 19 | Viewed by 4157
Abstract
Parameter estimation of Poisson-Gaussian signal-dependent random noise in the complementary metal-oxide semiconductor/charge-coupled device image sensor is a significant step in eliminating noise. The existing estimation algorithms, which are based on finding homogeneous regions, acquire the pair of the variances of noise and the [...] Read more.
Parameter estimation of Poisson-Gaussian signal-dependent random noise in the complementary metal-oxide semiconductor/charge-coupled device image sensor is a significant step in eliminating noise. The existing estimation algorithms, which are based on finding homogeneous regions, acquire the pair of the variances of noise and the intensities of every homogeneous region to fit the linear or piecewise linear curve and ascertain the noise parameters accordingly. In contrast to the existing algorithms, in this study, the Poisson noise samples of all homogeneous regions in every block image are pieced together to constitute a larger sample following the mixed Poisson noise distribution; then, the mean and variance of the mixed Poisson noise sample are deduced. Next, the mapping function among the noise parameters to be estimated—variance of Poisson-Gaussian noise and that of Gaussian noise corresponding to the stitched region in every block image—is constructed. Finally, the unbiased estimations of noise parameters are calculated from the mapping functions of all the image blocks. The experimental results confirm that the proposed method can obtain lower mean absolute error values of estimated noise parameters than the conventional ones. Full article
(This article belongs to the Section Physical Sensors)
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10 pages, 3319 KiB  
Article
A Sensitive Potentiometric Sensor for Isothermal Amplification-Coupled Detection of Nucleic Acids
by Kang-Ho Lee, Dongkyu Lee, Jongsu Yoon, Ohwon Kwon and Jaejong Lee
Sensors 2018, 18(7), 2277; https://doi.org/10.3390/s18072277 - 14 Jul 2018
Cited by 6 | Viewed by 4192
Abstract
A disposable potentiometric sensor was newly developed for the amplification-coupled detection of nucleic acids. The hydrogen-ion is generally released during isothermal amplification of nucleic acids. The surface potential on the oxide-functionalized electrode of the extended gate was directly measured using full electrical circuits [...] Read more.
A disposable potentiometric sensor was newly developed for the amplification-coupled detection of nucleic acids. The hydrogen-ion is generally released during isothermal amplification of nucleic acids. The surface potential on the oxide-functionalized electrode of the extended gate was directly measured using full electrical circuits with the commercial metal-oxide semiconductor field-effect transistors (MOSFETs) and ring oscillator components, which resulted in cost-effective, portable and scalable real-time nucleic acid analysis. The current-starved ring oscillator changes surface potential to its frequency depending on the square of the variation in pH with a high signal-to-noise ratio during isothermal amplification. The device achieves a conversion rate of 20.5 kHz/mV and a detection resolution of 200 µV for the surface potential. It is demonstrated that the sensor successfully monitors in real-time isothermal amplification of the extracted nucleic acids from Salmonella pathogenic bacteria. The in situ variations in the frequency of the pH-sensitive sensor were compared with the results of both a conventional optical device and pH-meter during isothermal amplification. Full article
(This article belongs to the Special Issue Label-Free Biosensors)
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16 pages, 3438 KiB  
Article
Design and Validation of an FPGA-Based Configurable Transcranial Doppler Neurofeedback System for Chronic Pain Patients
by Beatriz Rey, Alejandro Rodríguez, Enrique Lloréns-Bufort, José Tembl, Miguel Ángel Muñoz, Pedro Montoya, Vicente Herrero-Bosch and Jose M. Monzo
Sensors 2018, 18(7), 2278; https://doi.org/10.3390/s18072278 - 14 Jul 2018
Cited by 3 | Viewed by 4129
Abstract
Neurofeedback is a self-regulation technique that can be applied to learn to voluntarily control cerebral activity in specific brain regions. In this work, a Transcranial Doppler-based configurable neurofeedback system is proposed and described. The hardware configuration is based on the Red Pitaya board, [...] Read more.
Neurofeedback is a self-regulation technique that can be applied to learn to voluntarily control cerebral activity in specific brain regions. In this work, a Transcranial Doppler-based configurable neurofeedback system is proposed and described. The hardware configuration is based on the Red Pitaya board, which gives great flexibility and processing power to the system. The parameter to be trained can be selected between several temporal, spectral, or complexity features from the cerebral blood flow velocity signal in different vessels. As previous studies have found alterations in these parameters in chronic pain patients, the system could be applied to help them to voluntarily control these parameters. Two protocols based on different temporal lengths of the training periods have been proposed and tested with six healthy subjects that were randomly assigned to one of the protocols at the beginning of the procedure. For the purposes of the testing, the trained parameter was the mean cerebral blood flow velocity in the aggregated data from the two anterior cerebral arteries. Results show that, using the proposed neurofeedback system, the two groups of healthy volunteers can learn to self-regulate a parameter from their brain activity in a reduced number of training sessions. Full article
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12 pages, 3218 KiB  
Review
Porphyrin-Functionalized Zinc Oxide Nanostructures for Sensor Applications
by Mohammad Ekrami, Gabriele Magna, Zahra Emam-djomeh, Mohammad Saeed Yarmand, Roberto Paolesse and Corrado Di Natale
Sensors 2018, 18(7), 2279; https://doi.org/10.3390/s18072279 - 14 Jul 2018
Cited by 34 | Viewed by 7274
Abstract
Hybrid materials made of wide band gap semiconductors and dye molecules are largely studied mainly for photovoltaic applications. However, these materials also show interesting chemical sensitivity. Zinc oxides (ZnO) and porphyrins are good examples of a metal oxide semiconductor and a dye molecule [...] Read more.
Hybrid materials made of wide band gap semiconductors and dye molecules are largely studied mainly for photovoltaic applications. However, these materials also show interesting chemical sensitivity. Zinc oxides (ZnO) and porphyrins are good examples of a metal oxide semiconductor and a dye molecule that give rise to a hybrid material with such interesting properties. ZnO has been studied for sensors, optoelectronics, electronic devices, photo-anodes for dye-sensitized solar cells, and for mechanical energy harvesting. Porphyrins, on the other side, can be synthesized in order to mimic their roles in living systems such as oxygen transport and charge transfer for catalytic processes in animals and photosynthesis in plants. This paper provides a review of the chemical sensing properties of porphyrin-capped ZnO nanostructures. The methodologies to functionalize the ZnO surface with porphyrins are illustrated with emphasis on the relationships between the material preparation and its sensing properties. The development of sensors is described through the application of the hybrid materials to different transducers. Full article
(This article belongs to the Special Issue State-of-the-Art Sensors Technology in Italy 2017)
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18 pages, 6398 KiB  
Article
Loosening Monitoring of the Threaded Pipe Connection Using Time Reversal Technique and Piezoceramic Transducers
by Yabin Liang, Qian Feng and Dongsheng Li
Sensors 2018, 18(7), 2280; https://doi.org/10.3390/s18072280 - 14 Jul 2018
Cited by 19 | Viewed by 4631
Abstract
Threaded pipe connections are commonly used in the oil and gas industry in particular to connect casting strings, drill pipe strings, production and transportation risers, and pipelines. As the most critical components in the entire chain, maintaining a sealed and secure connection while [...] Read more.
Threaded pipe connections are commonly used in the oil and gas industry in particular to connect casting strings, drill pipe strings, production and transportation risers, and pipelines. As the most critical components in the entire chain, maintaining a sealed and secure connection while being subjected to environmental loads and pollution is very important and necessary to reduce potential leakage risk and guarantee the safety of the entire chain. In this paper, an effective approach using time reversal technique and lead zirconate titanate (PZT) transducer was developed to monitor the looseness of the threaded pipe connection. Two threaded pipeline segments connected with a metal coupling were assembled to simulate the threaded connection in the pipeline system. Two PZT patches were mounted on the surface of one pipeline segment and the pipe coupling, respectively. By loosening the threaded connection with different rotation angles, several looseness scenarios were experimentally investigated. For each looseness condition, the developed time reversal-based approach was performed and the corresponding response signal was acquired and analyzed. The experimental results demonstrate that the peak value of the focused signal detected by the PZT sensor decreases with the increase of the looseness degree. The entire test conducted from tightened connection to loosened connection was repeated eight times to validate the repeatability of the developed method and the consistency of the detection results. In addition, the reliability of the developed method was studied by involving high disturbances when the signal was measured. All the test results show that the developed method has a great potential to be employed in practical applications for monitoring the looseness condition of the threaded pipe connection, especially in an environment with severe noises and disturbances. Full article
(This article belongs to the Special Issue Recent Advances of Piezoelectric Transducers and Applications)
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14 pages, 5436 KiB  
Article
Lagging-Domain Model for Compensation of Hysteresis of xMR Sensors in Positioning Applications
by Dora Domajnko and Dejan Križaj
Sensors 2018, 18(7), 2281; https://doi.org/10.3390/s18072281 - 14 Jul 2018
Cited by 2 | Viewed by 4491
Abstract
The hysteresis of magnetoresistive sensors remains a considerable cause of inaccuracy of positioning applications. The phenomena itself has been well studied and described by different physical and phenomenological models. Various biasing techniques have been proposed. However, the increased fabrication and computational price they [...] Read more.
The hysteresis of magnetoresistive sensors remains a considerable cause of inaccuracy of positioning applications. The phenomena itself has been well studied and described by different physical and phenomenological models. Various biasing techniques have been proposed. However, the increased fabrication and computational price they require is undesirable. In this paper, a computational algorithm for the compensation of hysteresis of linear and rotary encoders is proposed. A lagging-domain model based on play operators is presented for prediction of hysteresis. The outlined procedure for the calibration of parameters allows the use of the algorithm for various types of encoders without knowing their exact material properties. The method was tested on different anisotropic magnetoresistive and tunneling magnetoresistive sensors. Results show that the impact of hysteresis was reduced by up to 90% without a significant increase of computational time or production costs. Full article
(This article belongs to the Special Issue Magnetic Sensors)
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18 pages, 11528 KiB  
Article
A Practical Approach for High Precision Reconstruction of a Motorcycle Trajectory Using a Low-Cost Multi-Sensor System
by Sarra Smaiah, Rabah Sadoun, Abdelhafid Elouardi, Bruno Larnaudie, Samir Bouaziz, Abderahmane Boubezoul, Bastien Vincke and Stéphane Espié
Sensors 2018, 18(7), 2282; https://doi.org/10.3390/s18072282 - 14 Jul 2018
Cited by 9 | Viewed by 6458
Abstract
Motorcycle drivers are considered among the most vulnerable road users, as attested by the number of crashes increasing every year. The significant part of the fatalities relates to “single vehicle” loss of control in bends. During this investigation, a system based on an [...] Read more.
Motorcycle drivers are considered among the most vulnerable road users, as attested by the number of crashes increasing every year. The significant part of the fatalities relates to “single vehicle” loss of control in bends. During this investigation, a system based on an instrumented multi-sensor platform and an algorithmic study was developed to accurately reconstruct motorcycle trajectories achieved when negotiating bends. This system is used by the French Gendarmerie in order to objectively evaluate and to examine the way riders take their bends in order to better train riders to adopt a safe trajectory and to improve road safety. Data required for the reconstruction are acquired using a motorcycle that has been fully instrumented (in VIROLO++ Project) with several redundant sensors (reference sensors and low-cost sensors) which measure the rider actions (roll, steering) and the motorcycle behavior (position, velocity, acceleration, odometry, heading, and attitude). The proposed solution allowed the reconstruction of motorcycle trajectories in bends with a high accuracy (equal to that of fixed point positioning). The developed algorithm will be used by the French Gendarmerie in order to objectively evaluate and examine the way riders negotiate bends. It will also be used for initial training and retraining in order to better train riders to learn and estimate a safe trajectory and to increase the safety, efficiency and comfort of motorcycle riders. Full article
(This article belongs to the Collection Multi-Sensor Information Fusion)
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22 pages, 11030 KiB  
Article
mPILOT-Magnetic Field Strength Based Pedestrian Indoor Localization
by Imran Ashraf, Soojung Hur and Yongwan Park
Sensors 2018, 18(7), 2283; https://doi.org/10.3390/s18072283 - 14 Jul 2018
Cited by 45 | Viewed by 5963
Abstract
An indoor localization system based on off-the-shelf smartphone sensors is presented which employs the magnetometer to find user location. Further assisted by the accelerometer and gyroscope, the proposed system is able to locate the user without any prior knowledge of user initial position. [...] Read more.
An indoor localization system based on off-the-shelf smartphone sensors is presented which employs the magnetometer to find user location. Further assisted by the accelerometer and gyroscope, the proposed system is able to locate the user without any prior knowledge of user initial position. The system exploits the fingerprint database approach for localization. Traditional fingerprinting technology stores data intensity values in database such as RSSI (Received Signal Strength Indicator) values in the case of WiFi fingerprinting and magnetic flux intensity values in the case of geomagnetic fingerprinting. The down side is the need to update the database periodically and device heterogeneity. We solve this problem by using the fingerprint database of patterns formed by magnetic flux intensity values. The pattern matching approach solves the problem of device heterogeneity and the algorithm’s performance with Samsung Galaxy S8 and LG G6 is comparable. A deep learning based artificial neural network is adopted to identify the user state of walking and stationary and its accuracy is 95%. The localization is totally infrastructure independent and does not require any other technology to constraint the search space. The experiments are performed to determine the accuracy in three buildings of Yeungnam University, Republic of Korea with different path lengths and path geometry. The results demonstrate that the error is 2–3 m for 50 percentile with various buildings. Even though many locations in the same building exhibit very similar magnetic attitude, the algorithm achieves an accuracy of 4 m for 75 percentile irrespective of the device used for localization. Full article
(This article belongs to the Collection Positioning and Navigation)
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18 pages, 11544 KiB  
Article
Optimal Camera Pose and Placement Configuration for Maximum Field-of-View Video Stitching
by Alex J. Watras, Jae-Jun Kim, Hewei Liu, Yu Hen Hu and Hongrui Jiang
Sensors 2018, 18(7), 2284; https://doi.org/10.3390/s18072284 - 14 Jul 2018
Cited by 10 | Viewed by 5612
Abstract
An optimal camera placement problem is investigated. The objective is to maximize the area of the field of view (FoV) of a stitched video obtained by stitching video streams from an array of cameras. The positions and poses of these cameras are restricted [...] Read more.
An optimal camera placement problem is investigated. The objective is to maximize the area of the field of view (FoV) of a stitched video obtained by stitching video streams from an array of cameras. The positions and poses of these cameras are restricted to a given set of selections. The camera array is designed to be placed inside the abdomen to support minimally invasive laparoscopic surgery. Hence, a few non-traditional requirements/constraints are imposed: Adjacent views are required to overlap to support image registration for seamless video stitching. The resulting effective FoV should be a contiguous region without any holes and should be a convex polygon. With these requirements, traditional camera placement algorithms cannot be directly applied to solve this problem. In this work, we show the complexity of this problem grows exponentially as a function of the problem size, and then present a greedy polynomial time heuristic solution that approximates well to the globally optimal solution. We present a new approach to directly evaluate the combined coverage area (area of FoV) as the union of a set of quadrilaterals. We also propose a graph-based approach to ensure the stitching requirement (overlap between adjacent views) is satisfied. We present a method to find a convex polygon with maximum area from a given polygon. Several design examples show that the proposed algorithm can achieve larger FoV area while using much less computing time. Full article
(This article belongs to the Section Sensor Networks)
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21 pages, 10564 KiB  
Article
A Non-Destructive System Based on Electrical Tomography and Machine Learning to Analyze the Moisture of Buildings
by Tomasz Rymarczyk, Grzegorz Kłosowski and Edward Kozłowski
Sensors 2018, 18(7), 2285; https://doi.org/10.3390/s18072285 - 14 Jul 2018
Cited by 125 | Viewed by 8443
Abstract
This article presents the results of research on a new method of spatial analysis of walls and buildings moisture. Due to the fact that destructive methods are not suitable for historical buildings of great architectural significance, a non-destructive method based on electrical tomography [...] Read more.
This article presents the results of research on a new method of spatial analysis of walls and buildings moisture. Due to the fact that destructive methods are not suitable for historical buildings of great architectural significance, a non-destructive method based on electrical tomography has been adopted. A hybrid tomograph with special sensors was developed for the measurements. This device enables the acquisition of data, which are then reconstructed by appropriately developed methods enabling spatial analysis of wet buildings. Special electrodes that ensure good contact with the surface of porous building materials such as bricks and cement were introduced. During the research, a group of algorithms enabling supervised machine learning was analyzed. They have been used in the process of converting input electrical values into conductance depicted by the output image pixels. The conductance values of individual pixels of the output vector made it possible to obtain images of the interior of building walls as both flat intersections (2D) and spatial (3D) images. The presented group of algorithms has a high application value. The main advantages of the new methods are: high accuracy of imaging, low costs, high processing speed, ease of application to walls of various thickness and irregular surface. By comparing the results of tomographic reconstructions, the most efficient algorithms were identified. Full article
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18 pages, 4284 KiB  
Article
Optimization of Scanning and Counting Sensor Layout for Full Route Observability with a Bi-Level Programming Model
by Donghui Shan, Xiaoduan Sun, Jianbei Liu and Ming Sun
Sensors 2018, 18(7), 2286; https://doi.org/10.3390/s18072286 - 14 Jul 2018
Cited by 13 | Viewed by 3656
Abstract
Utilizing the data obtained from both scanning and counting sensors is critical for efficiently managing traffic flow on roadways. Past studies mainly focused on the optimal layout of one type of sensor, and how to optimize the arrangement of more than one type [...] Read more.
Utilizing the data obtained from both scanning and counting sensors is critical for efficiently managing traffic flow on roadways. Past studies mainly focused on the optimal layout of one type of sensor, and how to optimize the arrangement of more than one type of sensor has not been fully researched. This paper develops a methodology that optimizes the deployment of different types of sensors to solve the well-recognized network sensors location problem (NSLP). To answer the questions of how many, where and what types of sensors should be deployed on each particular link of the network, a novel bi-level programming model for full route observability is presented to strategically locate scanning and counting sensors in a network. The methodology works in two steps. First, a mathematical program is formulated to determine the minimum number of scanning sensors. To solve this program, a new ‘differentiating matrix’ is introduced and the corresponding greedy algorithm of ‘differentiating first’ is put forward. In the second step, a scanning map and an incidence matrix are incorporated into the program, which extends the theoretical model for multiple sensors’ deployment and provides the replacement method to reduce total cost of sensors without loss of observability. The algorithm developed at the second step involved in two coefficient matrixes from scanning map and incidence parameter enumerate all possibilities of replacement schemes so that cost of different combination schemes can be compared. Finally, the proposed approach is demonstrated by comparison of Nguyen-Dupuis network and real network, which indicates the proposed method is capable to evaluate the trade-off between cost and all routes observability. Full article
(This article belongs to the Special Issue Sensor Networks for Smart Roads)
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26 pages, 5819 KiB  
Article
Short-Term Traffic State Prediction Based on the Spatiotemporal Features of Critical Road Sections
by Gang Yang, Yunpeng Wang, Haiyang Yu, Yilong Ren and Jindong Xie
Sensors 2018, 18(7), 2287; https://doi.org/10.3390/s18072287 - 14 Jul 2018
Cited by 62 | Viewed by 4736
Abstract
Recently, short-term traffic prediction under conditions with corrupted or missing data has become a popular topic. Since a road section has predictive power regarding the adjacent roads at a specific location, this paper proposes a novel hybrid convolutional long short-term memory neural network [...] Read more.
Recently, short-term traffic prediction under conditions with corrupted or missing data has become a popular topic. Since a road section has predictive power regarding the adjacent roads at a specific location, this paper proposes a novel hybrid convolutional long short-term memory neural network model based on critical road sections (CRS-ConvLSTM NN) to predict the traffic evolution of global networks. The critical road sections that have the most powerful impact on the subnetwork are identified by a spatiotemporal correlation algorithm. Subsequently, the traffic speed of the critical road sections is used as the input to the ConvLSTM to predict the future traffic states of the entire network. The experimental results from a Beijing traffic network indicate that the CRS-ConvLSTM outperforms prevailing deep learning (DL) approaches for cases that consider critical road sections and the results validate the capability and generalizability of the model when predicting with different numbers of critical road sections. Full article
(This article belongs to the Section Intelligent Sensors)
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12 pages, 1197 KiB  
Article
Polypyrrole/Agarose Hydrogel-Based Bladder Volume Sensor with a Resistor Ladder Structure
by Mi Kyung Kim, Sungwoo Lee, Inug Yoon, Geon Kook, Yeon Su Jung, Sarah S. M. Bawazir, Cesare Stefanini and Hyunjoo J. Lee
Sensors 2018, 18(7), 2288; https://doi.org/10.3390/s18072288 - 14 Jul 2018
Cited by 17 | Viewed by 5634
Abstract
Chronic monitoring of bladder activity and urine volume is essential for patients suffering from urinary dysfunctions. However, due to the anatomy and dynamics of the bladder, chronic and precise monitoring of bladder activity remains a challenge. Here, we propose a new sensing mechanism [...] Read more.
Chronic monitoring of bladder activity and urine volume is essential for patients suffering from urinary dysfunctions. However, due to the anatomy and dynamics of the bladder, chronic and precise monitoring of bladder activity remains a challenge. Here, we propose a new sensing mechanism that measures the bladder volume using a resistive ladder network with contact switches. Instead of measuring the impedance between the electrode continuously, the proposed sensor provides a digitized output (‘on’ or ‘off’) when the bladder volume reaches a certain threshold value. We present simple proof-of-concept sensors which compare the discrete-mode operation to the continuous-mode operation. In addition, by using multiple pairs of this contact-mode switch in a resistor ladder structure, we demonstrate monitoring of the bladder volume in four discrete steps using an idealized balloon and an ex vivo pig’s bladder. We implemented the resistive ladder network using a conductive polypyrrole/agarose hydrogel composite which exhibits a Young’s modulus comparable to that of the bladder wall. Compared to the continuous-mode operation, the proposed sensing mechanism is less susceptible to drift due to material degradation and environmental factors. Full article
(This article belongs to the Section Physical Sensors)
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16 pages, 5919 KiB  
Article
SiCILIA—Silicon Carbide Detectors for Intense Luminosity Investigations and Applications
by Salvatore Tudisco, Francesco La Via, Clementina Agodi, Carmen Altana, Giacomo Borghi, Maurizio Boscardin, Giancarlo Bussolino, Lucia Calcagno, Massimo Camarda, Francesco Cappuzzello, Diana Carbone, Salvatore Cascino, Giovanni Casini, Manuela Cavallaro, Caterina Ciampi, Giuseppe Cirrone, Giacomo Cuttone, Alberto Fazzi, Dario Giove, Giuseppe Gorini, Luca Labate, Gaetano Lanzalone, Grazia Litrico, Giuseppe Longo, Domenico Lo Presti, Marco Mauceri, Roberto Modica, Maurizio Moschetti, Annamaria Muoio, Franco Musumeci, Gabriele Pasquali, Giada Petringa, Nicolò Piluso, Giacomo Poggi, Stefania Privitera, Sebastiana Puglia, Valeria Puglisi, Marica Rebai, Sabina Ronchin, Antonello Santangelo, Andrea Stefanini, Antonio Trifirò and Massimo Zimboneadd Show full author list remove Hide full author list
Sensors 2018, 18(7), 2289; https://doi.org/10.3390/s18072289 - 15 Jul 2018
Cited by 64 | Viewed by 8632
Abstract
Silicon carbide (SiC) is a compound semiconductor, which is considered as a possible alternative to silicon for particles and photons detection. Its characteristics make it very promising for the next generation of nuclear and particle physics experiments at high beam luminosity. Silicon Carbide [...] Read more.
Silicon carbide (SiC) is a compound semiconductor, which is considered as a possible alternative to silicon for particles and photons detection. Its characteristics make it very promising for the next generation of nuclear and particle physics experiments at high beam luminosity. Silicon Carbide detectors for Intense Luminosity Investigations and Applications (SiCILIA) is a project starting as a collaboration between the Italian National Institute of Nuclear Physics (INFN) and IMM-CNR, aiming at the realization of innovative detection systems based on SiC. In this paper, we discuss the main features of silicon carbide as a material and its potential application in the field of particles and photons detectors, the project structure and the strategies used for the prototype realization, and the first results concerning prototype production and their performance. Full article
(This article belongs to the Section Chemical Sensors)
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14 pages, 5342 KiB  
Article
A 35 MHz/105 MHz Dual-Element Focused Transducer for Intravascular Ultrasound Tissue Imaging Using the Third Harmonic
by Junsu Lee, Ju-Young Moon and Jin Ho Chang
Sensors 2018, 18(7), 2290; https://doi.org/10.3390/s18072290 - 15 Jul 2018
Cited by 37 | Viewed by 6265
Abstract
The superharmonic imaging of tissue has the potential for high spatial and contrast resolutions, compared to the fundamental and second harmonic imaging. For this technique, the spectral bandwidth of an ultrasound transducer is divided for transmission of ultrasound and reception of its superharmonics [...] Read more.
The superharmonic imaging of tissue has the potential for high spatial and contrast resolutions, compared to the fundamental and second harmonic imaging. For this technique, the spectral bandwidth of an ultrasound transducer is divided for transmission of ultrasound and reception of its superharmonics (i.e., higher than the second harmonic). Due to the spectral division for the transmission and reception, transmitted ultrasound energy is not sufficient to induce superharmonics in media without using contrast agents, and it is difficult that a transducer has a −6 dB fractional bandwidth of higher than 100%. For the superharmonic imaging of tissue, thus, multi-frequency array transducers are the best choice if available; transmit and receive elements are separate and have different center frequencies. However, the construction of a multi-frequency transducer for intravascular ultrasound (IVUS) imaging is particularly demanding because of its small size of less than 1 mm. Here, we report a recently developed dual-element focused IVUS transducer for the third harmonic imaging of tissue, which consists of a 35-MHz element for ultrasound transmission and a 105-MHz element for third harmonic reception. For high quality third harmonic imaging, both elements were fabricated to have the same focus at 2.5 mm. The results of tissue mimicking phantom tests demonstrated that the third harmonic images produced by the developed transducer had higher spatial resolution and deeper imaging depth than the fundamental images. Full article
(This article belongs to the Special Issue Ultrasound Transducers)
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18 pages, 3530 KiB  
Article
Strategic Location-Based Random Routing for Source Location Privacy in Wireless Sensor Networks
by Lilian C. Mutalemwa and Seokjoo Shin
Sensors 2018, 18(7), 2291; https://doi.org/10.3390/s18072291 - 15 Jul 2018
Cited by 32 | Viewed by 4952
Abstract
Wireless sensor networks (WSNs) are deployed in sensitive applications, such as in military and asset monitoring. In these applications, it is important to ensure good source location privacy. This is owing to the open nature of WSNs and the easiness of an adversary [...] Read more.
Wireless sensor networks (WSNs) are deployed in sensitive applications, such as in military and asset monitoring. In these applications, it is important to ensure good source location privacy. This is owing to the open nature of WSNs and the easiness of an adversary to eavesdrop on sensor communication and back trace the location of the source node. This paper proposes a scheme to preserve the source location privacy based on random routing techniques. To achieve high privacy, packets are randomly routed from the source to the sink node through strategically positioned mediate or diversion nodes. The random selection of mediate or diversion nodes is location-based. Depending on the location of the source node, packets are forwarded through different regions of the network. The proposed scheme guarantees that successive packets are routed through very different routing paths and adversaries find it confusing to back trace them to the source node location. Simulation results demonstrate that the proposed scheme effectively confuses the adversary and provides higher source location privacy to outperform other routing-based source location privacy schemes. Full article
(This article belongs to the Special Issue Security, Trust and Privacy for Sensor Networks)
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22 pages, 6227 KiB  
Article
A Novel Method for Estimating Free Space 3D Point-of-Regard Using Pupillary Reflex and Line-of-Sight Convergence Points
by Zijing Wan, Xiangjun Wang, Kai Zhou, Xiaoyun Chen and Xiaoqing Wang
Sensors 2018, 18(7), 2292; https://doi.org/10.3390/s18072292 - 15 Jul 2018
Cited by 3 | Viewed by 4214
Abstract
In this paper, a novel 3D gaze estimation method for a wearable gaze tracking device is proposed. This method is based on the pupillary accommodation reflex of human vision. Firstly, a 3D gaze measurement model is built. By uniting the line-of-sight convergence point [...] Read more.
In this paper, a novel 3D gaze estimation method for a wearable gaze tracking device is proposed. This method is based on the pupillary accommodation reflex of human vision. Firstly, a 3D gaze measurement model is built. By uniting the line-of-sight convergence point and the size of the pupil, this model can be used to measure the 3D Point-of-Regard in free space. Secondly, a gaze tracking device is described. By using four cameras and semi-transparent mirrors, the gaze tracking device can accurately extract the spatial coordinates of the pupil and eye corner of the human eye from images. Thirdly, a simple calibration process of the measuring system is proposed. This method can be sketched as follows: (1) each eye is imaged by a pair of binocular stereo cameras, and the setting of semi-transparent mirrors can support a better field of view; (2) the spatial coordinates of the pupil center and the inner corner of the eye in the images of the stereo cameras are extracted, and the pupil size is calculated with the features of the gaze estimation method; (3) the pupil size and the line-of-sight convergence point when watching the calibration target at different distances are computed, and the parameters of the gaze estimation model are determined. Fourthly, an algorithm for searching the line-of-sight convergence point is proposed, and the 3D Point-of-Regard is estimated by using the obtained line-of-sight measurement model. Three groups of experiments were conducted to prove the effectiveness of the proposed method. This approach enables people to obtain the spatial coordinates of the Point-of-Regard in free space, which has great potential in the application of wearable devices. Full article
(This article belongs to the Special Issue Wearable Smart Devices)
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21 pages, 3691 KiB  
Article
Lagrange Programming Neural Network for TOA-Based Localization with Clock Asynchronization and Sensor Location Uncertainties
by Changgui Jia, Jiexin Yin, Ding Wang and Li Zhang
Sensors 2018, 18(7), 2293; https://doi.org/10.3390/s18072293 - 15 Jul 2018
Cited by 8 | Viewed by 2847
Abstract
Source localization based on time of arrival (TOA) measurements in the presence of clock asynchronization and sensor position uncertainties is investigated in this paper. Different from the traditional numerical algorithms, a neural circuit named Lagrange programming neural network (LPNN) is employed to tackle [...] Read more.
Source localization based on time of arrival (TOA) measurements in the presence of clock asynchronization and sensor position uncertainties is investigated in this paper. Different from the traditional numerical algorithms, a neural circuit named Lagrange programming neural network (LPNN) is employed to tackle the nonlinear and nonconvex constrained optimization problem of source localization. With the augmented term, two types of neural networks are developed from the original maximum likelihood functions based on the general framework provided by LPNN. The convergence and local stability of the proposed neural networks are analyzed in this paper. In addition, the Cramér-Rao lower bound is also derived as a benchmark in the presence of clock asynchronization and sensor position uncertainties. Simulation results verify the superior performance of the proposed LPNN over the traditional numerical algorithms and its robustness to resist the impact of a high level of measurement noise, clock asynchronization, as well as sensor position uncertainties. Full article
(This article belongs to the Section Sensor Networks)
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21 pages, 9000 KiB  
Article
A Component Decomposition Model for 3D Laser Scanning Pavement Data Based on High-Pass Filtering and Sparse Analysis
by Rong Gui, Xin Xu, Dejin Zhang, Hong Lin, Fangling Pu, Li He and Min Cao
Sensors 2018, 18(7), 2294; https://doi.org/10.3390/s18072294 - 15 Jul 2018
Cited by 36 | Viewed by 6159
Abstract
High-precision 3D laser scanning pavement data contains rich pavement scene information and certain components associations. Moreover, for pavement maintenance and management, there is an urgent need to develop automatic methods that can extract comprehensive information about different pavement indicators simultaneously. By analyzing the [...] Read more.
High-precision 3D laser scanning pavement data contains rich pavement scene information and certain components associations. Moreover, for pavement maintenance and management, there is an urgent need to develop automatic methods that can extract comprehensive information about different pavement indicators simultaneously. By analyzing the frequency and sparse characteristics of pavement distresses and performance indicators—including the cracks, road markings, rutting, potholes, textures—this paper proposes 3D pavement components decomposition model (3D-PCDM) which decomposes the 3D pavement profiles into sparse components x, low-frequency components f, and vibration components t. Designed high-pass filter was first employed to separate f, then, x and t are separated by total variation de-noising which based on sparse characteristics. Decomposed x can be used to characterize the location and depth information of sparse and sparse derived signals such as cracks, road marks, grooves, and potholes in profiles. Decomposed f can be used to determine the slow deformation of pavement. While decomposed t reflects the fluctuation of the pavement material particles. Experiments were conducted using actual pavement 3D data, the decomposed components can obtain by 3D-PCDM. The effectiveness and accuracy of the x are verified by actual cracks and road markings, the accuracy of extracted sparse components is over 92.75%. Full article
(This article belongs to the Section Remote Sensors)
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25 pages, 937 KiB  
Article
Joint Full-Duplex/Half-Duplex Transmission-Switching Scheduling and Transmission-Energy Allocation in Cognitive Radio Networks with Energy Harvesting
by Tran Nhut Khai Hoan, Hiep Vu-Van and Insoo Koo
Sensors 2018, 18(7), 2295; https://doi.org/10.3390/s18072295 - 15 Jul 2018
Cited by 5 | Viewed by 4378
Abstract
The full-duplex transmission protocol has been widely investigated in the literature in order to improve radio spectrum usage efficiency. Unfortunately, due to the effect of imperfect self-interference suppression, the change in transmission power and path loss of non-line-of-sight fading channels will strongly affect [...] Read more.
The full-duplex transmission protocol has been widely investigated in the literature in order to improve radio spectrum usage efficiency. Unfortunately, due to the effect of imperfect self-interference suppression, the change in transmission power and path loss of non-line-of-sight fading channels will strongly affect performance of full-duplex transmission mode. This entails that the full-duplex transmission protocol is not always a better selection compared to the traditional half-duplex transmission protocol. Considering solar energy-harvesting-powered cognitive radio networks (CRNs), we investigate a joint full-duplex/half-duplex transmission switching scheduling and transmission power allocation in which we utilize the advantages of both half-duplex and full-duplex transmission modes for maximizing the long-term throughput of cognitive radio networks. First, we formulate the transmission rate of half-duplex and full-duplex links for fading channels between cognitive user and base station in which the channel gain is assumed to follow an exponential distribution. Afterward, by considering the availability probability of the primary channel, the limitation of the energy-harvesting capacity of the cognitive user, and the transmission capacity of half-duplex and full-duplex links, we describe the problem in terms of long-term expected throughput. The problem is then solved by adopting the partially observable Markov decision process framework to find the optimal transmission policy for the transmission pair between cognitive user and base station in order to maximize the long-term expected throughput. The optimal policy consists of either the half-duplex or the full-duplex transmission protocols as well as the corresponding amount of transmission energy in each time slot. In addition, to reduce the complexity in formulation and calculation, we also apply the actor–critic-based learning method to solve the considered problem. Finally, the performance of the proposed scheme was evaluated by comparing it with a conventional scheme in which the context of energy harvesting and long-term throughput is not considered. Full article
(This article belongs to the Section Sensor Networks)
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34 pages, 11095 KiB  
Article
Multimodal Biometric Recognition Based on Convolutional Neural Network by the Fusion of Finger-Vein and Finger Shape Using Near-Infrared (NIR) Camera Sensor
by Wan Kim, Jong Min Song and Kang Ryoung Park
Sensors 2018, 18(7), 2296; https://doi.org/10.3390/s18072296 - 15 Jul 2018
Cited by 108 | Viewed by 7794
Abstract
Finger-vein recognition, which is one of the conventional biometrics, hinders fake attacks, is cheaper, and it features a higher level of user-convenience than other biometrics because it uses miniaturized devices. However, the recognition performance of finger-vein recognition methods may decrease due to a [...] Read more.
Finger-vein recognition, which is one of the conventional biometrics, hinders fake attacks, is cheaper, and it features a higher level of user-convenience than other biometrics because it uses miniaturized devices. However, the recognition performance of finger-vein recognition methods may decrease due to a variety of factors, such as image misalignment that is caused by finger position changes during image acquisition or illumination variation caused by non-uniform near-infrared (NIR) light. To solve such problems, multimodal biometric systems that are able to simultaneously recognize both finger-veins and fingerprints have been researched. However, because the image-acquisition positions for finger-veins and fingerprints are different, not to mention that finger-vein images must be acquired in NIR light environments and fingerprints in visible light environments, either two sensors must be used, or the size of the image acquisition device must be enlarged. Hence, there are multimodal biometrics based on finger-veins and finger shapes. However, such methods recognize individuals that are based on handcrafted features, which present certain limitations in terms of performance improvement. To solve these problems, finger-vein and finger shape multimodal biometrics using near-infrared (NIR) light camera sensor based on a deep convolutional neural network (CNN) are proposed in this research. Experimental results obtained using two types of open databases, the Shandong University homologous multi-modal traits (SDUMLA-HMT) and the Hong Kong Polytechnic University Finger Image Database (version 1), revealed that the proposed method in the present study features superior performance to the conventional methods. Full article
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18 pages, 3986 KiB  
Article
Potentiometric Sensors for Iodide and Bromide Based on Pt(II)-Porphyrin
by Dana Vlascici, Nicoleta Plesu, Gheorghe Fagadar-Cosma, Anca Lascu, Mihaela Petric, Manuela Crisan, Anca Belean and Eugenia Fagadar-Cosma
Sensors 2018, 18(7), 2297; https://doi.org/10.3390/s18072297 - 16 Jul 2018
Cited by 32 | Viewed by 5015
Abstract
Pt(II) 5,10,15,20-tetra(4-methoxy-phenyl)-porphyrin (PtTMeOPP) was used in the construction of new ion-selective sensors. The potentiometric response characteristics (slope and selectivity) of iodide and bromide-selective electrodes based on (PtTMeOPP) metalloporphyrin in o-nitrophenyloctylether (NPOE), dioctylphtalate (DOP) and dioctylsebacate (DOS) plasticized poly(vinyl chloride) membranes are compared. [...] Read more.
Pt(II) 5,10,15,20-tetra(4-methoxy-phenyl)-porphyrin (PtTMeOPP) was used in the construction of new ion-selective sensors. The potentiometric response characteristics (slope and selectivity) of iodide and bromide-selective electrodes based on (PtTMeOPP) metalloporphyrin in o-nitrophenyloctylether (NPOE), dioctylphtalate (DOP) and dioctylsebacate (DOS) plasticized poly(vinyl chloride) membranes are compared. The best results were obtained for the membranes plasticized with DOP and NPOE. The sensors have linear responses with near-Nernstian slopes toward bromide and iodide ions and good selectivity. The membrane plasticized with NPOE was electrochemically characterized using the EIS method to determine its water absorption and the diffusion coefficient into the membrane. Full article
(This article belongs to the Special Issue Potentiometric Chemical Sensors)
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14 pages, 1999 KiB  
Review
Sensors for Enhanced Detection of Acetone as a Potential Tool for Noninvasive Diabetes Monitoring
by Artur Rydosz
Sensors 2018, 18(7), 2298; https://doi.org/10.3390/s18072298 - 16 Jul 2018
Cited by 149 | Viewed by 10484
Abstract
Measurement of blood-borne volatile organic compounds (VOCs) occurring in human exhaled breath as a result of metabolic changes or pathological disorders is a promising tool for noninvasive medical diagnosis, such as exhaled acetone measurements in terms of diabetes monitoring. The conventional methods for [...] Read more.
Measurement of blood-borne volatile organic compounds (VOCs) occurring in human exhaled breath as a result of metabolic changes or pathological disorders is a promising tool for noninvasive medical diagnosis, such as exhaled acetone measurements in terms of diabetes monitoring. The conventional methods for exhaled breath analysis are based on spectrometry techniques, however, the development of gas sensors has made them more and more attractive from a medical point of view. This review focuses on the latest achievements in gas sensors for exhaled acetone detection. Several different methods and techniques are presented and discussed as well. Full article
(This article belongs to the Special Issue Biosensors for the Detection of Biomarkers)
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17 pages, 6366 KiB  
Article
Sensitivity Tests of Pellets Made from Manganese Antimonate Nanoparticles in Carbon Monoxide and Propane Atmospheres
by Héctor Guillén-Bonilla, Verónica-M. Rodríguez-Betancourtt, José Trinidad Guillen-Bonilla, Lorenzo Gildo-Ortiz, Alex Guillen-Bonilla, Y. L. Casallas-Moreno, Oscar Blanco-Alonso and Juan Reyes-Gómez
Sensors 2018, 18(7), 2299; https://doi.org/10.3390/s18072299 - 16 Jul 2018
Cited by 25 | Viewed by 3862
Abstract
Nanoparticles of manganese antimonate (MnSb2O6) were prepared using the microwave-assisted colloidal method for its potential application as a gas sensor. For the synthesis of the oxide, manganese nitrate, antimony chloride, ethylenediamine and ethyl alcohol (as a solvent) were used. [...] Read more.
Nanoparticles of manganese antimonate (MnSb2O6) were prepared using the microwave-assisted colloidal method for its potential application as a gas sensor. For the synthesis of the oxide, manganese nitrate, antimony chloride, ethylenediamine and ethyl alcohol (as a solvent) were used. The precursor material was calcined at 800 °C in air and analyzed by X-ray diffraction. The oxide crystallized into a hexagonal structure with spatial group P321 and cell parameters a = b = 8.8054 Å and c = 4.7229 Å. The microstructure of the material was analyzed by scanning electron microscopy (SEM), finding the growth of microrods with a size of around ~10.27 μm and some other particles with an average size of ~1.3 μm. Photoacoustic spectroscopy (PAS) studies showed that the optical energy band (Eg) of the oxide was of ~1.79 eV. Transmission electron microscopy (TEM) analyses indicated that the size of the nanoparticles was of ~29.5 nm on average. The surface area of the powders was estimated at 14.6 m2/g by the Brunauer–Emmett–Teller (BET) method. Pellets prepared from the nanoparticles were tested in carbon monoxide (CO) and propane (C3H8) atmospheres at different concentrations (0–500 ppm) and operating temperatures (100, 200 and 300 °C). The pellets were very sensitive to changes in gas concentration and temperature: the response of the material rose as the concentration and temperature increased. The results showed that the MnSb2O6 nanoparticles can be a good candidate to be used as a novel gas sensor. Full article
(This article belongs to the Section Chemical Sensors)
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24 pages, 3528 KiB  
Article
DCO-MAC: A Hybrid MAC Protocol for Data Collection in Underwater Acoustic Sensor Networks
by Min Deng, Huifang Chen and Lei Xie
Sensors 2018, 18(7), 2300; https://doi.org/10.3390/s18072300 - 16 Jul 2018
Cited by 24 | Viewed by 4276
Abstract
In underwater acoustic sensor networks (UASNs), medium access control (MAC) is an important issue because of its potentially significant effect on the network performance. However, designing a suitable MAC protocol for the UASN is challenging because of the specific characteristics of the underwater [...] Read more.
In underwater acoustic sensor networks (UASNs), medium access control (MAC) is an important issue because of its potentially significant effect on the network performance. However, designing a suitable MAC protocol for the UASN is challenging because of the specific characteristics of the underwater acoustic channel and network, such as limited available bandwidth, long propagation delay, high bit-error-rate, and sparse network topology. In addition, as the traffic load is non-uniformly distributed in a UASN for data collection, it is essential to consider the application feature for the MAC protocol. In this paper, we propose a MAC protocol in a data-collection-oriented UASN, abbreviated as the DCO-MAC protocol. In the proposed protocol, the network is partitioned into two kinds of sub-networks according to the traffic load. A contention-based MAC protocol is used in the sub-network with a light traffic load, while a reservation-based MAC protocol is used in the sub-network with a heavy traffic load. Meanwhile, the DCO-MAC protocol supports the access of mobile nodes. The theoretical analysis and simulation results demonstrate that, in a UASN for data collection, the proposed MAC protocol outperforms the other existing MAC protocols, in terms of the network throughput, end-to-end packet delay, energy overhead, and fairness. Full article
(This article belongs to the Section Sensor Networks)
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11 pages, 5800 KiB  
Article
Surface-Acoustic-Wave Sensor Design for Acceleration Measurement
by Sergey Shevchenko, Alexander Kukaev, Maria Khivrich and Dmitry Lukyanov
Sensors 2018, 18(7), 2301; https://doi.org/10.3390/s18072301 - 16 Jul 2018
Cited by 21 | Viewed by 5345
Abstract
We suggest a concept design of a SAW-based microaccelerometer with an original triangular-shaped console-type sensing element. Our design is particularly optimized to increase the robustness against positioning errors of the SAW resonators on the opposite sides of the console. We also describe the [...] Read more.
We suggest a concept design of a SAW-based microaccelerometer with an original triangular-shaped console-type sensing element. Our design is particularly optimized to increase the robustness against positioning errors of the SAW resonators on the opposite sides of the console. We also describe the results of computer simulations and laboratory tests that are in a perfect agreement with each other and present the sensitivity characteristics of a manufactured experimental design device. Full article
(This article belongs to the Special Issue Piezoelectric Micro- and Nano-Devices)
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27 pages, 3239 KiB  
Article
Efficient 3D Objects Recognition Using Multifoveated Point Clouds
by Fabio F. Oliveira, Anderson A. S. Souza, Marcelo A. C. Fernandes, Rafael B. Gomes and Luiz M. G. Goncalves
Sensors 2018, 18(7), 2302; https://doi.org/10.3390/s18072302 - 16 Jul 2018
Cited by 10 | Viewed by 5036
Abstract
Technological innovations in the hardware of RGB-D sensors have allowed the acquisition of 3D point clouds in real time. Consequently, various applications have arisen related to the 3D world, which are receiving increasing attention from researchers. Nevertheless, one of the main problems that [...] Read more.
Technological innovations in the hardware of RGB-D sensors have allowed the acquisition of 3D point clouds in real time. Consequently, various applications have arisen related to the 3D world, which are receiving increasing attention from researchers. Nevertheless, one of the main problems that remains is the demand for computationally intensive processing that required optimized approaches to deal with 3D vision modeling, especially when it is necessary to perform tasks in real time. A previously proposed multi-resolution 3D model known as foveated point clouds can be a possible solution to this problem. Nevertheless, this is a model limited to a single foveated structure with context dependent mobility. In this work, we propose a new solution for data reduction and feature detection using multifoveation in the point cloud. Nonetheless, the application of several foveated structures results in a considerable increase of processing since there are intersections between regions of distinct structures, which are processed multiple times. Towards solving this problem, the current proposal brings an approach that avoids the processing of redundant regions, which results in even more reduced processing time. Such approach can be used to identify objects in 3D point clouds, one of the key tasks for real-time applications as robotics vision, with efficient synchronization allowing the validation of the model and verification of its applicability in the context of computer vision. Experimental results demonstrate a performance gain of at least 27.21% in processing time while retaining the main features of the original, and maintaining the recognition quality rate in comparison with state-of-the-art 3D object recognition methods. Full article
(This article belongs to the Special Issue Depth Sensors and 3D Vision)
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10 pages, 2952 KiB  
Article
Near Real-Time Detection of E. coli in Reclaimed Water
by Samendra Sherchan, Syreeta Miles, Luisa Ikner, Hye-Weon Yu, Shane A. Snyder and Ian L. Pepper
Sensors 2018, 18(7), 2303; https://doi.org/10.3390/s18072303 - 16 Jul 2018
Cited by 18 | Viewed by 4632
Abstract
Advanced treatment of reclaimed water prior to potable reuse normally results in the inactivation of bacterial populations, however, incremental treatment failure can result in bacteria, including pathogens, remaining viable. Therefore, potential microorganisms need to be detected in real-time to preclude potential adverse human [...] Read more.
Advanced treatment of reclaimed water prior to potable reuse normally results in the inactivation of bacterial populations, however, incremental treatment failure can result in bacteria, including pathogens, remaining viable. Therefore, potential microorganisms need to be detected in real-time to preclude potential adverse human health effects. Real-time detection of microbes presents unique problems which are dependent on the water quality of the test water, including parameters such as particulate content and turbidity, and natural organic matter content. In addition, microbes are unusual in that: (i) viability and culturability are not always synonymous; (ii) viability in water can be reduced by osmotic stress; and (iii) bacteria can invoke repair mechanisms in response to UV disinfection resulting in regrowth of bacterial populations. All these issues related to bacteria affect the efficacy of real-time detection for bacteria. Here we evaluate three different sensors suitable for specific water qualities. The sensor A is an on-line, real-time sensor that allows for the continuous monitoring of particulates (including microbial contaminants) using multi-angle-light scattering (MALS) technology. The sensor B is a microbial detection system that uses optical technique, Mie light scattering, for particle sizing and fluorescence emission for viable bacteria detection. The last sensor C was based on adenosine triphosphate (ATP) production. E. coli was used a model organism and out of all tested sensors, we found the sensor C to be the most accurate. It has a great potential as a surrogate parameter for microbial loads in test waters and be useful for process control in treatment trains. Full article
(This article belongs to the Special Issue Sensors for Cell Analysis)
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24 pages, 8718 KiB  
Article
Smart Meter Data Collection Using Public Taxis
by Kabeya Gilbert Ngandu, Khmaies Ouahada and Suvendi Rimer
Sensors 2018, 18(7), 2304; https://doi.org/10.3390/s18072304 - 16 Jul 2018
Cited by 4 | Viewed by 5291
Abstract
The advent of wireless sensor networks (WSN) has opened up an array of applications. Due to the ad-hoc nature of WSN and the small size of wireless nodes, multiple system configurations are possible. In order to collect data from WSN, some systems utilize [...] Read more.
The advent of wireless sensor networks (WSN) has opened up an array of applications. Due to the ad-hoc nature of WSN and the small size of wireless nodes, multiple system configurations are possible. In order to collect data from WSN, some systems utilize static nodes with a network setup that consists of multiple relays to facilitate the dissemination of data to a gateway. Other WSN architectures consist of a mixture of static and mobile nodes. Mobile nodes are able to collect data from the WSN when in close proximity to a static node. Such nodes are referred to as data mules. Data mules presents multiple advantages including the improvement of the network life as communication usually takes place via a single hop. In order to collect smart meter data, we propose the usage of mini-bus taxis carrying a data collector node as an alternative to traditional GSM models where data collected is directly uploaded from a data concentrator to a server. Using the vast network of mini-bus taxis in South Africa, data collection in areas lacking GSM network will be possible. This paper will attempt to present all the relevant parameters required for such data collection scheme to be successful. Full article
(This article belongs to the Section Sensor Networks)
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12 pages, 6485 KiB  
Article
Design of the Fall-Block Sensing of the Railway Line Pantograph Based on 3D Machine Vision Sensors
by Kai Yang, Jianping Peng, Chaozhe Jiang, Xi Jiang, Longfei Xiao, Bangping Wang, Xiaorong Gao, Liming Xie and Hua Peng
Sensors 2018, 18(7), 2305; https://doi.org/10.3390/s18072305 - 16 Jul 2018
Cited by 10 | Viewed by 3962
Abstract
As an important part of the electric locomotive in railway transportation, the sensing and inspection of the pantograph has a significant effect on the safe operation of the train. In general, the pantograph carbon slip detection items include slide wear detection, slip strip [...] Read more.
As an important part of the electric locomotive in railway transportation, the sensing and inspection of the pantograph has a significant effect on the safe operation of the train. In general, the pantograph carbon slip detection items include slide wear detection, slip strip crack detection, carbon slip fall-block detection and slip strip wear detection. The emergence and development of structured light measurement technology with 3D sensors provide new technical means for the acquisition of spatial 3D information. The three-dimensional data can not only obtain more information but also reduce the data deviation, thereby improving the measurement accuracy and work efficiency. At present, few studies have been conducted on the slide block and partial wear of the carbon slide. Therefore, this paper studies the detection of the pantograph slide block based on 3D sensor measurement technology. The experimental results indicate that it is feasible to adopt 3D measurement technology to detect the fall-block of the pantograph slide. In addition, a sound detection effect can also be obtained. Full article
(This article belongs to the Section Physical Sensors)
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22 pages, 394 KiB  
Article
A Topology Control with Energy Balance in Underwater Wireless Sensor Networks for IoT-Based Application
by Zhen Hong, Xiaoman Pan, Ping Chen, Xianchuang Su, Ning Wang and Wenqi Lu
Sensors 2018, 18(7), 2306; https://doi.org/10.3390/s18072306 - 16 Jul 2018
Cited by 50 | Viewed by 4542
Abstract
As part of the IoT-based application, underwater wireless sensor networks (UWSN), which are typically self-organized heterogeneous wireless network, are one of the research hot-spots using various sensors in marine exploration and water environment monitoring application fields, recently. Due to the serious attenuation of [...] Read more.
As part of the IoT-based application, underwater wireless sensor networks (UWSN), which are typically self-organized heterogeneous wireless network, are one of the research hot-spots using various sensors in marine exploration and water environment monitoring application fields, recently. Due to the serious attenuation of radio in water, acoustic or hybrid communication is a usual way for transmitting information among nodes, which dissipates much more energy to prevent the network failure and guarantee the quality of service (QoS). To address this issue, a topology control with energy balance, namely TCEB, is proposed for UWSN to overcome time-delay and other interference, as well as make the entire network load balance. With the given underwater network model and its specialized energy consumption model, we introduce the non-cooperative-game-based scheme to select the nodes with better performance as the cluster-heads. Afterwards, the intra-cluster and inter-cluster topology construction are, respectively, to form the effective communication links of the intra-cluster and inter-cluster, which aim to build energy-efficient topology to reduce energy consumption. With the demonstration of the simulation, the results show the proposed TCEB has better performance on energy-efficiency and throughput than three other representative algorithms in complex underwater environments. Full article
(This article belongs to the Section Sensor Networks)
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16 pages, 921 KiB  
Article
Data Privacy Protection Based on Micro Aggregation with Dynamic Sensitive Attribute Updating
by Yancheng Shi, Zhenjiang Zhang, Han-Chieh Chao and Bo Shen
Sensors 2018, 18(7), 2307; https://doi.org/10.3390/s18072307 - 16 Jul 2018
Cited by 16 | Viewed by 4023
Abstract
With the rapid development of information technology, large-scale personal data, including those collected by sensors or IoT devices, is stored in the cloud or data centers. In some cases, the owners of the cloud or data centers need to publish the data. Therefore, [...] Read more.
With the rapid development of information technology, large-scale personal data, including those collected by sensors or IoT devices, is stored in the cloud or data centers. In some cases, the owners of the cloud or data centers need to publish the data. Therefore, how to make the best use of the data in the risk of personal information leakage has become a popular research topic. The most common method of data privacy protection is the data anonymization, which has two main problems: (1) The availability of information after clustering will be reduced, and it cannot be flexibly adjusted. (2) Most methods are static. When the data is released multiple times, it will cause personal privacy leakage. To solve the problems, this article has two contributions. The first one is to propose a new method based on micro-aggregation to complete the process of clustering. In this way, the data availability and the privacy protection can be adjusted flexibly by considering the concepts of distance and information entropy. The second contribution of this article is to propose a dynamic update mechanism that guarantees that the individual privacy is not compromised after the data has been subjected to multiple releases, and minimizes the loss of information. At the end of the article, the algorithm is simulated with real data sets. The availability and advantages of the method are demonstrated by calculating the time, the average information loss and the number of forged data. Full article
(This article belongs to the Special Issue Sensor-based E-Healthcare System: Greenness and Security)
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24 pages, 1164 KiB  
Article
Constrained Multi-Sensor Control Using a Multi-Target MSE Bound and a δ-GLMB Filter
by Feng Lian, Liming Hou, Jing Liu and Chongzhao Han
Sensors 2018, 18(7), 2308; https://doi.org/10.3390/s18072308 - 16 Jul 2018
Cited by 10 | Viewed by 3767
Abstract
The existing multi-sensor control algorithms for multi-target tracking (MTT) within the random finite set (RFS) framework are all based on the distributed processing architecture, so the rule of generalized covariance intersection (GCI) has to be used to obtain the multi-sensor posterior density. However, [...] Read more.
The existing multi-sensor control algorithms for multi-target tracking (MTT) within the random finite set (RFS) framework are all based on the distributed processing architecture, so the rule of generalized covariance intersection (GCI) has to be used to obtain the multi-sensor posterior density. However, there has still been no reliable basis for setting the normalized fusion weight of each sensor in GCI until now. Therefore, to avoid the GCI rule, the paper proposes a new constrained multi-sensor control algorithm based on the centralized processing architecture. A multi-target mean-square error (MSE) bound defined in our paper is served as cost function and the multi-sensor control commands are just the solutions that minimize the bound. In order to derive the bound by using the generalized information inequality to RFS observation, the error between state set and its estimation is measured by the second-order optimal sub-pattern assignment metric while the multi-target Bayes recursion is performed by using a δ-generalized labeled multi-Bernoulli filter. An additional benefit of our method is that the proposed bound can provide an online indication of the achievable limit for MTT precision after the sensor control. Two suboptimal algorithms, which are mixed penalty function (MPF) method and complex method, are used to reduce the computation cost of solving the constrained optimization problem. Simulation results show that for the constrained multi-sensor control system with different observation performance, our method significantly outperforms the GCI-based Cauchy-Schwarz divergence method in MTT precision. Besides, when the number of sensors is relatively large, the computation time of the MPF and complex methods is much shorter than that of the exhaustive search method at the expense of completely acceptable loss of tracking accuracy. Full article
(This article belongs to the Special Issue Sensor Signal and Information Processing)
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10 pages, 1891 KiB  
Article
Gold Nanocage-Based Electrochemical Sensing Platform for Sensitive Detection of Luteolin
by Xiaobao Li, Ruyi Zou, Yanyan Niu, Wei Sun, Taiming Shao and Xiaoqin Chen
Sensors 2018, 18(7), 2309; https://doi.org/10.3390/s18072309 - 17 Jul 2018
Cited by 35 | Viewed by 3803
Abstract
A simple and sensitive electrochemical sensor was developed for the detection of tracelevels of luteolin. The sensoris based on a novel type of chemically modified electrode: gold nanocage (AuNCs)-modified carbon ionic liquid electrode (CILE). To construct this electrochemical sensing platform for luteolin, CILE [...] Read more.
A simple and sensitive electrochemical sensor was developed for the detection of tracelevels of luteolin. The sensoris based on a novel type of chemically modified electrode: gold nanocage (AuNCs)-modified carbon ionic liquid electrode (CILE). To construct this electrochemical sensing platform for luteolin, CILE is initially prepared by using 1-hexylpyridinium hexafluorophosphate as the binder and then AuNCs are coated on the surface of CILE to fabricate AuNCs-modified CILE (AuNCs/CILE). Electrochemical studies have shown that AuNCs/CILE can exhibit enhanced electrocatalytic activity toward the redox reaction of luteolin, therefore, the redox peak current of luteolin can be greatly improved, resulting in the high sensitivity of the developed sensor. Under the optimal conditions, the oxidation peak currents of the sensor increase linearly with an increase in the luteolin concentration in a range from 1 to 1000 nM with a detection limit of 0.4 nM, which is lower than those of most reported electrochemical luteolin sensors. Moreover, the reproducibility, precision, selectivity, and stability of this sensor are excellent. Finally, the sensing system was applied to the analysis of luteolin-spiked drug samples and the recovery in all cases was 95.0–96.7%, indicating the potential application of this simple, facile, and sensitive sensing system in pharmaceutical analysis. Full article
(This article belongs to the Section Chemical Sensors)
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22 pages, 1331 KiB  
Article
A Smart Sensing Architecture for Domestic Monitoring: Methodological Approach and Experimental Validation
by Andrea Monteriù, Mario Rosario Prist, Emanuele Frontoni, Sauro Longhi, Filippo Pietroni, Sara Casaccia, Lorenzo Scalise, Annalisa Cenci, Luca Romeo, Riccardo Berta, Loreto Pescosolido, Gianni Orlandi and Gian Marco Revel
Sensors 2018, 18(7), 2310; https://doi.org/10.3390/s18072310 - 17 Jul 2018
Cited by 53 | Viewed by 8590
Abstract
Smart homes play a strategic role for improving life quality of people, enabling to monitor people at home with numerous intelligent devices. Sensors can be installed to provide a continuous assistance without limiting the resident’s daily routine, giving her/him greater comfort, well-being and [...] Read more.
Smart homes play a strategic role for improving life quality of people, enabling to monitor people at home with numerous intelligent devices. Sensors can be installed to provide a continuous assistance without limiting the resident’s daily routine, giving her/him greater comfort, well-being and safety. This paper is based on the development of domestic technological solutions to improve the life quality of citizens and monitor the users and the domestic environment, based on features extracted from the collected data. The proposed smart sensing architecture is based on an integrated sensor network to monitor the user and the environment to derive information about the user’s behavior and her/his health status. The proposed platform includes biomedical, wearable, and unobtrusive sensors for monitoring user’s physiological parameters and home automation sensors to obtain information about her/his environment. The sensor network stores the heterogeneous data both locally and remotely in Cloud, where machine learning algorithms and data mining strategies are used for user behavior identification, classification of user health conditions, classification of the smart home profile, and data analytics to implement services for the community. The proposed solution has been experimentally tested in a pilot study based on the development of both sensors and services for elderly users at home. Full article
(This article belongs to the Special Issue Smart Homes)
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11 pages, 2420 KiB  
Article
Experimental Verification of the Pumping Effect Caused by the Micro-Tapered Hole in a Piezoelectric Atomizer
by Jianhui Zhang, Qiufeng Yan, Jun Huang and Chuanyu Wu
Sensors 2018, 18(7), 2311; https://doi.org/10.3390/s18072311 - 17 Jul 2018
Cited by 21 | Viewed by 4100
Abstract
In this study, we examined the use of a dynamic micro-tapered hole as a micro-scale tapered flow tube valveless piezoelectric pump. Firstly, we obtained photographs of a micro-tapered hole by using an environmental scanning electron microscope (ESEM). Then, we explained the pump effect [...] Read more.
In this study, we examined the use of a dynamic micro-tapered hole as a micro-scale tapered flow tube valveless piezoelectric pump. Firstly, we obtained photographs of a micro-tapered hole by using an environmental scanning electron microscope (ESEM). Then, we explained the pump effect of the micro-tapered hole, and derived the atomization rate equation. Furthermore, we reported an atomization rate measurement experiment that eliminated the atomization caused by a pressure increase, and demonstrated that a change in the volume of a micro-tapered hole could produce atomization. The experimental results indicate that, under the same voltage, the forward atomization rate is much higher than the reverse atomization rate and that the atomization rate increases with the micro-tapered hole volume. The experimental results show that the atomization of the micro-tapered aperture atomizer is caused by its pumping effect. Moreover, the flow resistance and volume of the micro-tapered hole can affect the atomization rate. Full article
(This article belongs to the Special Issue Recent Advances of Piezoelectric Transducers and Applications)
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18 pages, 4784 KiB  
Article
Amplitude-Based Filtering for Video Magnification in Presence of Large Motion
by Xiu Wu, Xuezhi Yang, Jing Jin and Zhao Yang
Sensors 2018, 18(7), 2312; https://doi.org/10.3390/s18072312 - 17 Jul 2018
Cited by 22 | Viewed by 5327
Abstract
Video magnification reveals important and informative subtle variations in the world. These signals are often combined with large motions which result in significant blurring artifacts and haloes when conventional video magnification approaches are used. To counter these issues, this paper presents an amplitude-based [...] Read more.
Video magnification reveals important and informative subtle variations in the world. These signals are often combined with large motions which result in significant blurring artifacts and haloes when conventional video magnification approaches are used. To counter these issues, this paper presents an amplitude-based filtering algorithm that can magnify small changes in video in presence of large motions. We seek to understand the amplitude characteristic of small changes and large motions with the goal of extracting accurate signals for visualization. Based on spectrum amplitude filtering, the large motions can be removed while small changes can still be magnified by Eulerian approach. An advantage of this algorithm is that it can handle large motions, whether they are linear or nonlinear. Our experimental results show that the proposed method can amplify subtle variations in the presence of large motion, as well as significantly reduce artifacts. We demonstrate the presented algorithm by comparing to the state-of-the-art and provide subjective and objective evidence for the proposed method. Full article
(This article belongs to the Special Issue Sensors Signal Processing and Visual Computing)
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25 pages, 15184 KiB  
Article
Fast Visual Odometry for a Low-Cost Underwater Embedded Stereo System
by Mohamad Motasem Nawaf, Djamal Merad, Jean-Philip Royer, Jean-Marc Boï, Mauro Saccone, Mohamed Ben Ellefi and Pierre Drap
Sensors 2018, 18(7), 2313; https://doi.org/10.3390/s18072313 - 17 Jul 2018
Cited by 16 | Viewed by 4751
Abstract
This paper provides details of hardware and software conception and realization of a stereo embedded system for underwater imaging. The system provides several functions that facilitate underwater surveys and run smoothly in real-time. A first post-image acquisition module provides direct visual feedback on [...] Read more.
This paper provides details of hardware and software conception and realization of a stereo embedded system for underwater imaging. The system provides several functions that facilitate underwater surveys and run smoothly in real-time. A first post-image acquisition module provides direct visual feedback on the quality of the taken images which helps appropriate actions to be taken regarding movement speed and lighting conditions. Our main contribution is a light visual odometry method adapted to the underwater context. The proposed method uses the captured stereo image stream to provide real-time navigation and a site coverage map which is necessary to conduct a complete underwater survey. The visual odometry uses a stochastic pose representation and semi-global optimization approach to handle large sites and provides long-term autonomy, whereas a novel stereo matching approach adapted to underwater imaging and system attached lighting allows fast processing and suitability to low computational resource systems. The system is tested in a real context and shows its robustness and promising future potential. Full article
(This article belongs to the Special Issue Visual Sensors)
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20 pages, 32642 KiB  
Article
Accelerating the K-Nearest Neighbors Filtering Algorithm to Optimize the Real-Time Classification of Human Brain Tumor in Hyperspectral Images
by Giordana Florimbi, Himar Fabelo, Emanuele Torti, Raquel Lazcano, Daniel Madroñal, Samuel Ortega, Ruben Salvador, Francesco Leporati, Giovanni Danese, Abelardo Báez-Quevedo, Gustavo M. Callicó, Eduardo Juárez, César Sanz and Roberto Sarmiento
Sensors 2018, 18(7), 2314; https://doi.org/10.3390/s18072314 - 17 Jul 2018
Cited by 38 | Viewed by 8065
Abstract
The use of hyperspectral imaging (HSI) in the medical field is an emerging approach to assist physicians in diagnostic or surgical guidance tasks. However, HSI data processing involves very high computational requirements due to the huge amount of information captured by the sensors. [...] Read more.
The use of hyperspectral imaging (HSI) in the medical field is an emerging approach to assist physicians in diagnostic or surgical guidance tasks. However, HSI data processing involves very high computational requirements due to the huge amount of information captured by the sensors. One of the stages with higher computational load is the K-Nearest Neighbors (KNN) filtering algorithm. The main goal of this study is to optimize and parallelize the KNN algorithm by exploiting the GPU technology to obtain real-time processing during brain cancer surgical procedures. This parallel version of the KNN performs the neighbor filtering of a classification map (obtained from a supervised classifier), evaluating the different classes simultaneously. The undertaken optimizations and the computational capabilities of the GPU device throw a speedup up to 66.18× when compared to a sequential implementation. Full article
(This article belongs to the Special Issue Sensors Signal Processing and Visual Computing)
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10 pages, 4825 KiB  
Article
Sensitivity-Improved Ultrasonic Sensor for 3D Imaging of Seismic Physical Model Using a Compact Microcavity
by Tingting Gang, Manli Hu, Xiaohong Bai and Qiangzhou Rong
Sensors 2018, 18(7), 2315; https://doi.org/10.3390/s18072315 - 17 Jul 2018
Cited by 7 | Viewed by 4743
Abstract
A sensitivity-improved ultrasonic sensor is proposed and demonstrated experimentally in this present study. The device is comprised only a fiber-optic microcavity that is formed by discharging a short section of hollow core fiber (HCF). The key to ensuring the success of the sensor [...] Read more.
A sensitivity-improved ultrasonic sensor is proposed and demonstrated experimentally in this present study. The device is comprised only a fiber-optic microcavity that is formed by discharging a short section of hollow core fiber (HCF). The key to ensuring the success of the sensor relies on the preprocessing of hydrogen loading for HCF. When discharging the HCF, the hydrogen is heated up during the formation of the air bubble, which enlarges the bubble diameter, smoothens its surfaces simultaneously and decreases Young’s modulus of the material of the bubble. Ultimately, this results in the probe being highly sensitive to ultrasound with a SNR of 69.28 dB. Once the compact air cavity is formed between the end face of the leading-in fiber and the top wall of the bubble, a well-defined interference spectrum is achieved based on the Fabry–Perot interference. By using spectral side-band filtering technology, we detect the ultrasonic waves reflected by the seismic physical model (SMF) and then reconstruct its three-dimensional image. Full article
(This article belongs to the Special Issue Ultrasonic Sensors 2018)
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21 pages, 9390 KiB  
Article
Health Management Decision of Sensor System Based on Health Reliability Degree and Grey Group Decision-Making
by Kai Song, Peng Xu, Guo Wei, Yinsheng Chen and Qi Wang
Sensors 2018, 18(7), 2316; https://doi.org/10.3390/s18072316 - 17 Jul 2018
Cited by 13 | Viewed by 4163
Abstract
Metal Oxide Semiconductor (MOS) gas sensor has been widely used in sensor systems for the advantages of fast response, high sensitivity, low cost, and so on. But, limited to the properties of materials, the phenomenon, such as aging, poisoning, and damage of the [...] Read more.
Metal Oxide Semiconductor (MOS) gas sensor has been widely used in sensor systems for the advantages of fast response, high sensitivity, low cost, and so on. But, limited to the properties of materials, the phenomenon, such as aging, poisoning, and damage of the gas sensitive material will affect the measurement quality of MOS gas sensor array. To ensure the stability of the system, a health management decision strategy for the prognostics and health management (PHM) of a sensor system that is based on health reliability degree (HRD) and grey group decision-making (GGD) is proposed in this paper. The health management decision-making model is presented to choose the best health management strategy. Specially, GGD is utilized to provide health management suggestions for the sensor system. To evaluate the status of the sensor system, a joint HRD-GGD framework is declared as the health management decision-making. In this method, HRD of sensor system is obtained by fusing the output data of each sensor. The optimal decision-making recommendations for health management of the system is proposed by combining historical health reliability degree, maintenance probability, and overhaul rate. Experimental results on four different kinds of health levels demonstrate that the HRD-GGD method outperforms other methods in decision-making accuracy of sensor system. Particularly, the proposed HRD-GGD decision-making method achieves the best decision accuracy of 98.25%. Full article
(This article belongs to the Collection Multi-Sensor Information Fusion)
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12 pages, 7958 KiB  
Article
Development of Wheel Pressure Control Algorithm for Electronic Stability Control (ESC) System of Commercial Trucks
by Minjun Seo, Changhee Yoo, Sang-Shin Park and Kanghyun Nam
Sensors 2018, 18(7), 2317; https://doi.org/10.3390/s18072317 - 17 Jul 2018
Cited by 12 | Viewed by 7132
Abstract
This paper presents a wheel cylinder pressure control algorithm for application to the vehicle electronic stability control (ESC) systems for commercial trucks. An ESC system is an active system that improves the driving stability by distributing the appropriate braking pressure to each wheel, [...] Read more.
This paper presents a wheel cylinder pressure control algorithm for application to the vehicle electronic stability control (ESC) systems for commercial trucks. An ESC system is an active system that improves the driving stability by distributing the appropriate braking pressure to each wheel, which is an essential system for safe driving. It is important that the ESC system, through proper braking pressure supply, delivers the correct pressure under control. However, to reduce the cost involved, commercial trucks use a solenoid valve of the on/off-type, rather than a proportional valve that has good pressure control capability. The performance of a proposed wheel pressure control system based on an on/off solenoid valve control was verified by means of experiments conducted using the wheel pressure control algorithm presented in this paper. Full article
(This article belongs to the Special Issue Mechatronic Systems for Automatic Vehicles)
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14 pages, 2876 KiB  
Article
An Ultrahigh Sensitivity Acetone Sensor Enhanced by Light Illumination
by Heng Zhang, Hongwei Qin, Chengyong Gao and Jifan Hu
Sensors 2018, 18(7), 2318; https://doi.org/10.3390/s18072318 - 17 Jul 2018
Cited by 9 | Viewed by 3162
Abstract
Au:SmFe0.9Zn0.1O3 is synthesized by a sol-gel method and annealed at 750 °C. Through XRD, SEM and XPS analysis methods, the microstructure of the material has been observed. The average particle size is about 50 nm. The sensor shows [...] Read more.
Au:SmFe0.9Zn0.1O3 is synthesized by a sol-gel method and annealed at 750 °C. Through XRD, SEM and XPS analysis methods, the microstructure of the material has been observed. The average particle size is about 50 nm. The sensor shows a high sensitivity toward acetone vapor. As the relative humidity increases, the resistance and sensitivity of the sensor decline. To obtain a low optimum operating temperature, light illumination with different wavelengths has been introduced. The sensitivity toward acetone is improved at lower operating temperature when the sensor is irradiated by light. The smaller the wavelengths, the better the sensitivity of the sensor. Compared with other gases, the sensor shows excellent selectivity to acetone vapor, with better sensitivity, selectivity and stability when under light illumination. Full article
(This article belongs to the Section Chemical Sensors)
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14 pages, 375 KiB  
Article
Optical Strain Measurement with Step-Index Polymer Optical Fiber Based on the Phase Measurement of an Intensity-Modulated Signal
by Thomas Becker, Olaf Ziemann, Rainer Engelbrecht and Bernhard Schmauss
Sensors 2018, 18(7), 2319; https://doi.org/10.3390/s18072319 - 17 Jul 2018
Cited by 13 | Viewed by 4406
Abstract
Polymer optical fibers (POFs) have been proposed for optical strain sensors due to their large elastic strain range compared to glass optical fibers (GOFs). The phase response of a single-mode polymer optical fiber (SM-POF) is well-known in the literature, and depends on the [...] Read more.
Polymer optical fibers (POFs) have been proposed for optical strain sensors due to their large elastic strain range compared to glass optical fibers (GOFs). The phase response of a single-mode polymer optical fiber (SM-POF) is well-known in the literature, and depends on the physical deformation of the fiber as well as the impact on the refractive index of the core. In this paper, we investigate the impact of strain on a step-index polymer optical fiber (SI-POF). In particular, we discuss the responsivity of an optical strain sensor which is based on the phase measurement of an intensity-modulated signal. In comparison to the phase response of an SM-POF, we must take additional influences into account. Firstly, the SI-POF is a multi-mode fiber (MMF). Consequently, we not only consider the strain dependence of the refractive index, but also its dependency on the propagation angle θz. Second, we investigate the phase of an intensity-modulated signal. The development of this modulation phase along the fiber is influenced by modal dispersion, scattering, and attenuation. The modulation phase therefore has no linear dependency on the length of the fiber, even in the unstrained state. For the proper consideration of these effects, we rely on a novel model for step-index multi-mode fibers (SI-MMFs). We expand the model to consider the strain-induced effects, simulate the strain responsivity of the sensor, and compare it to experimental results. This led to the conclusion that the scattering behavior of a SI-POF is strain-dependent, which was further proven by measuring the far field at the end of a SI-POF under different strain conditions. Full article
(This article belongs to the Special Issue Optical Waveguide Based Sensors)
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18 pages, 3071 KiB  
Article
Dissimilarity Metric Based on Local Neighboring Information and Genetic Programming for Data Dissemination in Vehicular Ad Hoc Networks (VANETs)
by Daniel Gutiérrez-Reina, Vishal Sharma, Ilsun You and Sergio Toral
Sensors 2018, 18(7), 2320; https://doi.org/10.3390/s18072320 - 17 Jul 2018
Cited by 15 | Viewed by 3870
Abstract
This paper presents a novel dissimilarity metric based on local neighboring information and a genetic programming approach for efficient data dissemination in Vehicular Ad Hoc Networks (VANETs). The primary aim of the dissimilarity metric is to replace the Euclidean distance in probabilistic data [...] Read more.
This paper presents a novel dissimilarity metric based on local neighboring information and a genetic programming approach for efficient data dissemination in Vehicular Ad Hoc Networks (VANETs). The primary aim of the dissimilarity metric is to replace the Euclidean distance in probabilistic data dissemination schemes, which use the relative Euclidean distance among vehicles to determine the retransmission probability. The novel dissimilarity metric is obtained by applying a metaheuristic genetic programming approach, which provides a formula that maximizes the Pearson Correlation Coefficient between the novel dissimilarity metric and the Euclidean metric in several representative VANET scenarios. Findings show that the obtained dissimilarity metric correlates with the Euclidean distance up to 8.9% better than classical dissimilarity metrics. Moreover, the obtained dissimilarity metric is evaluated when used in well-known data dissemination schemes, such as p-persistence, polynomial and irresponsible algorithm. The obtained dissimilarity metric achieves significant improvements in terms of reachability in comparison with the classical dissimilarity metrics and the Euclidean metric-based schemes in the studied VANET urban scenarios. Full article
(This article belongs to the Section Sensor Networks)
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16 pages, 3428 KiB  
Article
Experimental Evaluation on Depth Control Using Improved Model Predictive Control for Autonomous Underwater Vehicle (AUVs)
by Feng Yao, Chao Yang, Xing Liu and Mingjun Zhang
Sensors 2018, 18(7), 2321; https://doi.org/10.3390/s18072321 - 17 Jul 2018
Cited by 27 | Viewed by 4215
Abstract
Due to the growing interest using model predictive control (MPC), there are more and more researches about the applications of MPC on autonomous underwater vehicle (AUV), and these researches are mainly focused on simulation and simple application of MPC on AUV. This paper [...] Read more.
Due to the growing interest using model predictive control (MPC), there are more and more researches about the applications of MPC on autonomous underwater vehicle (AUV), and these researches are mainly focused on simulation and simple application of MPC on AUV. This paper focuses on the improvement of MPC based on the state space model of an AUV. Unlike the previous approaches using a fixed weighting matrix, in this paper, a coefficient, varied with the error, is introduced to adjust the control increment vector weighting matrix to reduce the settling time. Then, an analysis on the effect of the adjustment to the stability is given. In addition, there is always a lag between the AUV real trajectory and the desired trajectory when the AUV tracks a continuous trajectory. To solve this problem, a simple re-planning of the desired trajectory is developed. Specifically, the point certain steps ahead from current time on the desired trajectory is treated as the current desired point and input to the controller. Finally, experimental results for depth control are given to demonstrate the feasibility and effectiveness of the improved MPC. Experimental results show that the method of real-time adjusting control increment weighting matrix can reduce settling time by about 2 s when tracking step trajectory of 1 m, and the simple re-planning of the desired trajectory method can reduce the average of absolute error by about 15% and standard deviation of error by about 17%. Full article
(This article belongs to the Section Remote Sensors)
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18 pages, 4905 KiB  
Article
Levenberg-Marquardt Neural Network Algorithm for Degree of Arteriovenous Fistula Stenosis Classification Using a Dual Optical Photoplethysmography Sensor
by Yi-Chun Du and Alphin Stephanus
Sensors 2018, 18(7), 2322; https://doi.org/10.3390/s18072322 - 17 Jul 2018
Cited by 100 | Viewed by 6288
Abstract
This paper proposes a noninvasive dual optical photoplethysmography (PPG) sensor to classify the degree of arteriovenous fistula (AVF) stenosis in hemodialysis (HD) patients. Dual PPG measurement node (DPMN) becomes the primary tool in this work for detecting abnormal narrowing vessel simultaneously in multi-beds [...] Read more.
This paper proposes a noninvasive dual optical photoplethysmography (PPG) sensor to classify the degree of arteriovenous fistula (AVF) stenosis in hemodialysis (HD) patients. Dual PPG measurement node (DPMN) becomes the primary tool in this work for detecting abnormal narrowing vessel simultaneously in multi-beds monitoring patients. The mean and variance of Rising Slope (RS) and Falling Slope (FS) values between before and after HD treatment was used as the major features to classify AVF stenosis. Multilayer perceptron neural networks (MLPN) training algorithms are implemented for this analysis, which are the Levenberg-Marquardt, Scaled Conjugate Gradient, and Resilient Back-propagation, to identify the degree of HD patient stenosis. Eleven patients were recruited with mean age of 77 ± 10.8 years for analysis. The experimental results indicated that the variance of RS in the HD hand between before and after treatment was significant difference statistically to stenosis (p < 0.05). Levenberg-Marquardt algorithm (LMA) was significantly outperforms the other training algorithm. The classification accuracy and precision reached 94.82% and 92.22% respectively, thus this technique has a potential contribution to the early identification of stenosis for a medical diagnostic support system. Full article
(This article belongs to the Special Issue Selected Papers from IEEE ICASI 2018)
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30 pages, 11050 KiB  
Article
Cellular Simulation for Distributed Sensing over Complex Terrains
by Tuyen Phong Truong, Bernard Pottier and Hiep Xuan Huynh
Sensors 2018, 18(7), 2323; https://doi.org/10.3390/s18072323 - 17 Jul 2018
Cited by 12 | Viewed by 6641
Abstract
Long-range radio transmissions open new sensor application fields, in particular for environment monitoring. For example, the LoRa radio protocol enables connecting remote sensors at a distance as long as ten kilometers in a line-of-sight. However, the large area covered also brings several difficulties, [...] Read more.
Long-range radio transmissions open new sensor application fields, in particular for environment monitoring. For example, the LoRa radio protocol enables connecting remote sensors at a distance as long as ten kilometers in a line-of-sight. However, the large area covered also brings several difficulties, such as the placement of sensing devices in regards to topology in geography, or the variability of communication latency. Sensing the environment also carries constraints related to the interest of sensing points in relation to a physical phenomenon. Thus, criteria for designs are evolving a lot from the existing methods, especially in complex terrains. This article describes simulation techniques based on geography analysis to compute long-range radio coverages and radio characteristics in these situations. As radio propagation is just a particular case of physical phenomena, it is shown how a unified approach also allows for characterizing the behavior of potential physical risks. The case of heavy rainfall and flooding is investigated. Geography analysis is achieved using segmentation tools to produce cellular systems which are in turn translated into code for high-performance computations. The paper provides results from practical complex terrain experiments using LoRa, which confirm the accuracy of the simulation, and scheduling characteristics for sample networks. Performance tables are produced for these simulations on current Graphics Processing Units (GPUs). Full article
(This article belongs to the Special Issue Dependable Monitoring in Wireless Sensor Networks)
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19 pages, 5968 KiB  
Article
Behavior of an Inductive Loop Sensor in the Measurement of Partial Discharge Pulses with Variations in Its Separation from the Primary Conductor
by Jorge Alfredo Ardila-Rey, Aldo Barrueto, Alvaro Zerene, Bruno Albuquerque de Castro, José Alfredo Covolan Ulson, Abdullahi Abubakar Mas’ud and Patricio Valdivia
Sensors 2018, 18(7), 2324; https://doi.org/10.3390/s18072324 - 18 Jul 2018
Cited by 17 | Viewed by 4768
Abstract
Ideally, an insulation system must be capable of electrically insulating the active components of a machine or device subjected to high voltages. However, due to the presence of polluting agents or imperfections inside or on the surface of the insulation, small current pulses [...] Read more.
Ideally, an insulation system must be capable of electrically insulating the active components of a machine or device subjected to high voltages. However, due to the presence of polluting agents or imperfections inside or on the surface of the insulation, small current pulses called partial discharges (PDs) are common, which partially short-circuit the insulation and cause it to lose its insulating properties, and thus its insulation capacity, over time. In some cases, measurements of this phenomenon are limited by the type of sensor used; if it is not adequate, it can distort the obtained results, which can lead to a misdiagnosis of the state of the device. The inductive loop sensor has experimentally been demonstrated to be capable of properly measuring different types of PDs. However, because of its current design, there are several practical limitations on its use in real devices or environments. An example is the presence of a primary conductor located at a fixed distance from the sensor, through which PD pulses must flow for the sensor to capture them. In this article, the sensor’s behavior is studied at different separation distances from the line through which the PD pulses flow. In addition, the measuring capacity of the sensor is tested by removing the presence of the primary conductor and placing the sensor directly over the line through which the PD pulses of a real device flow. Full article
(This article belongs to the Section Physical Sensors)
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14 pages, 6029 KiB  
Article
Trivariate Empirical Mode Decomposition via Convex Optimization for Rolling Bearing Condition Identification
by Yong Lv, Houzhuang Zhang and Cancan Yi
Sensors 2018, 18(7), 2325; https://doi.org/10.3390/s18072325 - 18 Jul 2018
Cited by 6 | Viewed by 3429
Abstract
As a multichannel signal processing method based on data-driven, multivariate empirical mode decomposition (MEMD) has attracted much attention due to its potential ability in self-adaption and multi-scale decomposition for multivariate data. Commonly, the uniform projection scheme on a hypersphere is used to estimate [...] Read more.
As a multichannel signal processing method based on data-driven, multivariate empirical mode decomposition (MEMD) has attracted much attention due to its potential ability in self-adaption and multi-scale decomposition for multivariate data. Commonly, the uniform projection scheme on a hypersphere is used to estimate the local mean. However, the unbalanced data distribution in high-dimensional space often conflicts with the uniform samples and its performance is sensitive to the noise components. Considering the common fact that the vibration signal is generated by three sensors located in different measuring positions in the domain of the structural health monitoring for the key equipment, thus a novel trivariate empirical mode decomposition via convex optimization was proposed for rolling bearing condition identification in this paper. For the trivariate data matrix, the low-rank matrix approximation via convex optimization was firstly conducted to achieve the denoising. It is worthy to note that the non-convex penalty function as a regularization term is introduced to enhance the performance. Moreover, the non-uniform sample scheme was determined by applying singular value decomposition (SVD) to the obtained low-rank trivariate data and then the approach used in conventional MEMD algorithm was employed to estimate the local mean. Numerical examples of synthetic defined by the fault model and real data generated by the fault rolling bearing on the experimental bench are provided to demonstrate the fruitful applications of the proposed method. Full article
(This article belongs to the Special Issue Sensors for Fault Detection)
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15 pages, 5338 KiB  
Article
Clutter and Range Ambiguity Suppression Using Diverse Pulse Train in Pulse Doppler System
by Jiacen Xu, Lixiang Ren, Huayu Fan, Erke Mao and Quanhua Liu
Sensors 2018, 18(7), 2326; https://doi.org/10.3390/s18072326 - 18 Jul 2018
Cited by 14 | Viewed by 3987
Abstract
Pulse Doppler (PD) systems are widely used for moving target detection, especially in scenarios with clutter. Range ambiguity, which arises from fixed parameters in waveforms, is an inherent drawback in conventional systems. By using a diverse pulse train such as a train of [...] Read more.
Pulse Doppler (PD) systems are widely used for moving target detection, especially in scenarios with clutter. Range ambiguity, which arises from fixed parameters in waveforms, is an inherent drawback in conventional systems. By using a diverse pulse train such as a train of coherent diverse phase coded pulses, these ambiguous peaks can be suppressed effectively but at the cost of sidelobe dispersions. In this work, a novel efficient PD process is proposed to suppress range ambiguity and detect moving targets under strong clutter. Poly-phase coded pulses are employed along with optimal receiving filters, by which the dispersed sidelobes are mitigated to a great extent. Moreover, a novel clutter suppression procedure is included in the PD process, by which strong clutter can be greatly suppressed. Well-designed receiving and inverse filters are employed. Simulation examples are presented to verify the theories. Compared with conventional methods, much better detection results are obtained for both near and remote targets, especially in scenarios with strong clutter. Full article
(This article belongs to the Section Remote Sensors)
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19 pages, 3371 KiB  
Article
Terahertz Image Detection with the Improved Faster Region-Based Convolutional Neural Network
by Jinsong Zhang, Wenjie Xing, Mengdao Xing and Guangcai Sun
Sensors 2018, 18(7), 2327; https://doi.org/10.3390/s18072327 - 18 Jul 2018
Cited by 60 | Viewed by 7533
Abstract
In recent years, terahertz imaging systems and techniques have been developed and have gradually become a leading frontier field. With the advantages of low radiation and clothing-penetrable, terahertz imaging technology has been widely used for the detection of concealed weapons or other contraband [...] Read more.
In recent years, terahertz imaging systems and techniques have been developed and have gradually become a leading frontier field. With the advantages of low radiation and clothing-penetrable, terahertz imaging technology has been widely used for the detection of concealed weapons or other contraband carried on personnel at airports and other secure locations. This paper aims to detect these concealed items with deep learning method for its well detection performance and real-time detection speed. Based on the analysis of the characteristics of terahertz images, an effective detection system is proposed in this paper. First, a lots of terahertz images are collected and labeled as the standard data format. Secondly, this paper establishes the terahertz classification dataset and proposes a classification method based on transfer learning. Then considering the special distribution of terahertz image, an improved faster region-based convolutional neural network (Faster R-CNN) method based on threshold segmentation is proposed for detecting human body and other objects independently. Finally, experimental results demonstrate the effectiveness and efficiency of the proposed method for terahertz image detection. Full article
(This article belongs to the Special Issue Automatic Target Recognition of High Resolution SAR/ISAR Images)
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24 pages, 3095 KiB  
Article
Efficient Node and Sensed Module Management for Multisensory Wireless Sensor Networks
by Juan Feng and Xiaozhu Shi
Sensors 2018, 18(7), 2328; https://doi.org/10.3390/s18072328 - 18 Jul 2018
Cited by 5 | Viewed by 3382
Abstract
In target tracking wireless sensor networks, choosing a part of sensor nodes to execute tracking tasks and letting the other nodes sleep to save energy are efficient node management strategies. However, at present more and more sensor nodes carry many different types of [...] Read more.
In target tracking wireless sensor networks, choosing a part of sensor nodes to execute tracking tasks and letting the other nodes sleep to save energy are efficient node management strategies. However, at present more and more sensor nodes carry many different types of sensed modules, and the existing researches on node selection are mainly focused on sensor nodes with a single sensed module. Few works involved the management and selection of the sensed modules for sensor nodes which have several multi-mode sensed modules. This work proposes an efficient node and sensed module management strategy, called ENSMM, for multisensory WSNs (wireless sensor networks). ENSMM considers not only node selection, but also the selection of the sensed modules for each node, and then the power management of sensor nodes is performed according to the selection results. Moreover, a joint weighted information utility measurement is proposed to estimate the information utility of the multiple sensed modules in the different nodes. Through extensive and realistic experiments, the results show that, ENSMM outperforms the state-of-the-art approaches by decreasing the energy consumption and prolonging the network lifetime. Meanwhile, it reduces the computational complexity with guaranteeing the tracking accuracy. Full article
(This article belongs to the Special Issue Aerospace Sensors and Multisensor Systems)
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17 pages, 298 KiB  
Review
The Odor Characterizations and Reproductions in Machine Olfactions: A Review
by Tengteng Wen, Dehan Luo, Jiafeng He and Kai Mei
Sensors 2018, 18(7), 2329; https://doi.org/10.3390/s18072329 - 18 Jul 2018
Cited by 13 | Viewed by 5900
Abstract
Machine olfaction is a novel technology and has been developed for many years. The electronic nose with an array of gas sensors, a crucial application form of the machine olfaction, is capable of sensing not only odorous compounds, but also odorless chemicals. Because [...] Read more.
Machine olfaction is a novel technology and has been developed for many years. The electronic nose with an array of gas sensors, a crucial application form of the machine olfaction, is capable of sensing not only odorous compounds, but also odorless chemicals. Because of its fast response, mobility and easy of use, the electronic nose has been applied to scientific and commercial uses such as environment monitoring and food processing inspection. Additionally, odor characterization and reproduction are the two novel parts of machine olfaction, which extend the field of machine olfaction. Odor characterization is the technique that characterizes odorants as some form of general odor information. At present, there have already been odor characterizations by means of the electronic nose. Odor reproduction is the technique that re-produces an odor by some form of general odor information and displays the odor by the olfactory display. It enhances the human ability of controlling odors just as the control of light and voice. In analogy to visual and auditory display technologies, is it possible that the olfactory display will be used in our daily life? There have already been some efforts toward odor reproduction and olfactory displays. Full article
(This article belongs to the Section Chemical Sensors)
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24 pages, 976 KiB  
Article
Towards a Scalable Software Defined Network-on-Chip for Next Generation Cloud
by Alberto Scionti, Somnath Mazumdar and Antoni Portero
Sensors 2018, 18(7), 2330; https://doi.org/10.3390/s18072330 - 18 Jul 2018
Cited by 16 | Viewed by 4911
Abstract
The rapid evolution of Cloud-based services and the growing interest in deep learning (DL)-based applications is putting increasing pressure on hyperscalers and general purpose hardware designers to provide more efficient and scalable systems. Cloud-based infrastructures must consist of more energy efficient components. The [...] Read more.
The rapid evolution of Cloud-based services and the growing interest in deep learning (DL)-based applications is putting increasing pressure on hyperscalers and general purpose hardware designers to provide more efficient and scalable systems. Cloud-based infrastructures must consist of more energy efficient components. The evolution must take place from the core of the infrastructure (i.e., data centers (DCs)) to the edges (Edge computing) to adequately support new/future applications. Adaptability/elasticity is one of the features required to increase the performance-to-power ratios. Hardware-based mechanisms have been proposed to support system reconfiguration mostly at the processing elements level, while fewer studies have been carried out regarding scalable, modular interconnected sub-systems. In this paper, we propose a scalable Software Defined Network-on-Chip (SDNoC)-based architecture. Our solution can easily be adapted to support devices ranging from low-power computing nodes placed at the edge of the Cloud to high-performance many-core processors in the Cloud DCs, by leveraging on a modular design approach. The proposed design merges the benefits of hierarchical network-on-chip (NoC) topologies (via fusing the ring and the 2D-mesh topology), with those brought by dynamic reconfiguration (i.e., adaptation). Our proposed interconnect allows for creating different types of virtualised topologies aiming at serving different communication requirements and thus providing better resource partitioning (virtual tiles) for concurrent tasks. To further allow the software layer controlling and monitoring of the NoC subsystem, a few customised instructions supporting a data-driven program execution model (PXM) are added to the processing element’s instruction set architecture (ISA). In general, the data-driven programming and execution models are suitable for supporting the DL applications. We also introduce a mechanism to map a high-level programming language embedding concurrent execution models into the basic functionalities offered by our SDNoC for easing the programming of the proposed system. In the reported experiments, we compared our lightweight reconfigurable architecture to a conventional flattened 2D-mesh interconnection subsystem. Results show that our design provides an increment of the data traffic throughput of 9.5% and a reduction of 2.2× of the average packet latency, compared to the flattened 2D-mesh topology connecting the same number of processing elements (PEs) (up to 1024 cores). Similarly, power and resource (on FPGA devices) consumption is also low, confirming good scalability of the proposed architecture. Full article
(This article belongs to the Special Issue Software-Defined Networking Based Mobile Networks)
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30 pages, 2358 KiB  
Article
Coalition Formation Based Compressive Sensing in Wireless Sensor Networks
by Alireza Masoum, Nirvana Meratnia and Paul J. M. Havinga
Sensors 2018, 18(7), 2331; https://doi.org/10.3390/s18072331 - 18 Jul 2018
Cited by 6 | Viewed by 3748
Abstract
Compressive sensing originates in the field of signal processing and has recently become a topic of energy-efficient data gathering in wireless sensor networks. In this paper, we propose an energy efficient distributed compressive sensing solution for sensor networks. The proposed solution utilizes sparsity [...] Read more.
Compressive sensing originates in the field of signal processing and has recently become a topic of energy-efficient data gathering in wireless sensor networks. In this paper, we propose an energy efficient distributed compressive sensing solution for sensor networks. The proposed solution utilizes sparsity distribution of signals to group sensor nodes into several coalitions and then implements localized compressive sensing inside coalitions. This solution improves data-gathering performance in terms of both data accuracy and energy consumption. The approach curbs both data-transmission costs and number of measurements. Coalition-based data gathering cuts transmission costs, and the number of measurements is reduced by scheduling sensor nodes and adjusting their sampling frequency. Our simulation showed that our approach enhances network performance by minimizing energy cost and improving data accuracy. Full article
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22 pages, 1281 KiB  
Article
Fault Detection and Isolation via the Interacting Multiple Model Approach Applied to Drive-By-Wire Vehicles
by Vincent Judalet, Sébastien Glaser, Dominique Gruyer and Saïd Mammar
Sensors 2018, 18(7), 2332; https://doi.org/10.3390/s18072332 - 18 Jul 2018
Cited by 20 | Viewed by 4801
Abstract
The place of driving assistance systems is currently increasing drastically for road vehicles. Paving the road to the fully autonomous vehicle, the drive-by-wire technology could improve the potential of the vehicle control. The implementation of these new embedded systems is still limited, mainly [...] Read more.
The place of driving assistance systems is currently increasing drastically for road vehicles. Paving the road to the fully autonomous vehicle, the drive-by-wire technology could improve the potential of the vehicle control. The implementation of these new embedded systems is still limited, mainly for reliability reasons, thus requiring the development of diagnostic mechanisms. In this paper, we investigate the detection and the identification of sensor and actuator faults for a drive-by-wire road vehicle. An Interacting Multiple Model approach is proposed, based on a non-linear vehicle dynamics observer. The adequacy of different probabilistic observers is discussed. The results, based on experimental vehicle signals, show a fast and robust identification of sensor faults while the actuator faults are more challenging. Full article
(This article belongs to the Special Issue Sensors for Fault Detection)
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19 pages, 2756 KiB  
Article
Geo-Positioning Accuracy Improvement of Multi-Mode GF-3 Satellite SAR Imagery Based on Error Sources Analysis
by Niangang Jiao, Feng Wang, Hongjian You, Xiaolan Qiu and Mudan Yang
Sensors 2018, 18(7), 2333; https://doi.org/10.3390/s18072333 - 18 Jul 2018
Cited by 20 | Viewed by 3587
Abstract
The GaoFen-3 (GF-3) satellite is the only synthetic aperture radar (SAR) satellite in the High-Resolution Earth Observation System Project, which is the first C-band full-polarization SAR satellite in China. In this paper, we proposed some error sources-based weight strategies to improve the geometric [...] Read more.
The GaoFen-3 (GF-3) satellite is the only synthetic aperture radar (SAR) satellite in the High-Resolution Earth Observation System Project, which is the first C-band full-polarization SAR satellite in China. In this paper, we proposed some error sources-based weight strategies to improve the geometric performance of multi-mode GF-3 satellite SAR images without using ground control points (GCPs). To get enough tie points, a robust SAR image registration method and the SAR-features from accelerated segment test (SAR-FAST) method is used to achieve the image registration and tie point extraction. Then, the original position of these tie points in object-space is calculated with the help of the space intersection method. With the dataset clustered by the density-based spatial clustering of applications with noise (DBSCAN) algorithm, we undertake the block adjustment with a bias-compensated rational function model (RFM) aided to improve the geometric performance of these multi-mode GF-3 satellite SAR images. Different weight strategies are proposed to develop the normal equation matrix according to the error sources analysis of GF-3 satellite SAR images, and the preconditioned conjugate gradient (PCG) method is utilized to solve the normal equation. The experimental results indicate that our proposed method can improve the geometric positioning accuracy of GF-3 satellite SAR images within 2 pixels. Full article
(This article belongs to the Special Issue First Experiences with Chinese Gaofen-3 SAR Sensor)
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16 pages, 1628 KiB  
Article
Peptide-Cellulose Conjugates on Cotton-Based Materials Have Protease Sensor/Sequestrant Activity
by J. Vincent Edwards, Krystal R. Fontenot, Falk Liebner and Brian D. Condon
Sensors 2018, 18(7), 2334; https://doi.org/10.3390/s18072334 - 18 Jul 2018
Cited by 21 | Viewed by 4213
Abstract
The growing incidence of chronic wounds in the world population has prompted increased interest in chronic wound dressings with protease-modulating activity and protease point of care sensors to treat and enable monitoring of elevated protease-based wound pathology. However, the overall design features needed [...] Read more.
The growing incidence of chronic wounds in the world population has prompted increased interest in chronic wound dressings with protease-modulating activity and protease point of care sensors to treat and enable monitoring of elevated protease-based wound pathology. However, the overall design features needed for the combination of a chronic wound dressing that lowers protease activity along with protease detection capability as a single platform for semi-occlusive dressings has scarcely been addressed. The interface of dressing and sensor specific properties (porosity, permeability, moisture uptake properties, specific surface area, surface charge, and detection) relative to sensor bioactivity and protease sequestrant performance is explored here. Measurement of the material’s zeta potential demonstrated a correlation between negative charge and the ability of materials to bind positively charged Human Neutrophil Elastase. Peptide-cellulose conjugates as protease substrates prepared on a nanocellulosic aerogel were assessed for their compatibility with chronic wound dressing design. The porosity, wettability and absorption capacity of the nanocellulosic aerogel were consistent with values observed for semi-occlusive chronic wound dressing designs. The relationship of properties that effect dressing functionality and performance as well as impact sensor sensitivity are discussed in the context of the enzyme kinetics. The sensor sensitivity of the aerogel-based sensor is contrasted with current clinical studies on elastase. Taken together, comparative analysis of the influence of molecular features on the physical properties of three forms of cellulosic transducer surfaces provides a meaningful assessment of the interface compatibility of cellulose-based sensors and corresponding protease sequestrant materials for potential use in chronic wound sensor/dressing design platforms. Full article
(This article belongs to the Special Issue Biosensors for Theranostics)
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12 pages, 3624 KiB  
Article
Rapid Airplane Detection in Remote Sensing Images Based on Multilayer Feature Fusion in Fully Convolutional Neural Networks
by Yuelei Xu, Mingming Zhu, Peng Xin, Shuai Li, Min Qi and Shiping Ma
Sensors 2018, 18(7), 2335; https://doi.org/10.3390/s18072335 - 18 Jul 2018
Cited by 42 | Viewed by 4501
Abstract
To address the issues encountered when using traditional airplane detection methods, including the low accuracy rate, high false alarm rate, and low detection speed due to small object sizes in aerial remote sensing images, we propose a remote sensing image airplane detection method [...] Read more.
To address the issues encountered when using traditional airplane detection methods, including the low accuracy rate, high false alarm rate, and low detection speed due to small object sizes in aerial remote sensing images, we propose a remote sensing image airplane detection method that uses multilayer feature fusion in fully convolutional neural networks. The shallow layer and deep layer features are fused at the same scale after sampling to overcome the problems of low dimensionality in the deep layer and the inadequate expression of small objects. The sizes of candidate regions are modified to fit the size of the actual airplanes in the remote sensing images. The fully connected layers are replaced with convolutional layers to reduce the network parameters and adapt to different input image sizes. The region proposal network shares convolutional layers with the detection network, which ensures high detection efficiency. The simulation results indicate that, when compared to typical airplane detection methods, the proposed method is more accurate and has a lower false alarm rate. Additionally, the detection speed is considerably faster and the method can accurately and rapidly complete airplane detection tasks in aerial remote sensing images. Full article
(This article belongs to the Special Issue High-Performance Computing in Geoscience and Remote Sensing)
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12 pages, 2469 KiB  
Article
Evaluation of Atmospheric Effects on Interferograms Using DEM Errors of Fixed Ground Points
by Takashi Nonaka, Tomohito Asaka and Keishi Iwashita
Sensors 2018, 18(7), 2336; https://doi.org/10.3390/s18072336 - 18 Jul 2018
Cited by 4 | Viewed by 3418
Abstract
High-resolution synthetic aperture radar (SAR) data are widely used for disaster monitoring. To extract damaged areas automatically, it is essential to understand the relationships among the sensor specifications, acquisition conditions, and land cover. Our previous studies developed a method for estimating the phase [...] Read more.
High-resolution synthetic aperture radar (SAR) data are widely used for disaster monitoring. To extract damaged areas automatically, it is essential to understand the relationships among the sensor specifications, acquisition conditions, and land cover. Our previous studies developed a method for estimating the phase noise of interferograms using several pairs of TerraSAR-X series (TerraSAR-X and TanDEM-X) datasets. Atmospheric disturbance data are also necessary to interpret the interferograms; therefore, the purpose of this study is to estimate the atmospheric effects by focusing on the difference in digital elevation model (DEM) errors between repeat-pass (two interferometric SAR images acquired at different times) and single-pass (two interferometric SAR images acquired simultaneously) interferometry. Single-pass DEM errors are reduced due to the lack of temporal decorrelation and atmospheric disturbances. At a study site in the city of Tsukuba, a quantitative analysis of DEM errors at fixed ground objects shows that the atmospheric effects are estimated to contribute 75% to 80% of the total phase noise in interferograms. Full article
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15 pages, 2769 KiB  
Article
Adaptive Square-Root Unscented Particle Filtering Algorithm for Dynamic Navigation
by Wenhui Wei, Shesheng Gao, Yongmin Zhong, Chengfan Gu and Gaoge Hu
Sensors 2018, 18(7), 2337; https://doi.org/10.3390/s18072337 - 18 Jul 2018
Cited by 42 | Viewed by 4053
Abstract
This paper presents a new adaptive square-root unscented particle filtering algorithm by combining the adaptive filtering and square-root filtering into the unscented particle filter to inhibit the disturbance of kinematic model noise and the instability of filtering data in the process of nonlinear [...] Read more.
This paper presents a new adaptive square-root unscented particle filtering algorithm by combining the adaptive filtering and square-root filtering into the unscented particle filter to inhibit the disturbance of kinematic model noise and the instability of filtering data in the process of nonlinear filtering. To prevent particles from degeneracy, the proposed algorithm adaptively adjusts the adaptive factor, which is constructed from predicted residuals, to refrain from the disturbance of abnormal observation and the kinematic model noise. Cholesky factorization is also applied to suppress the negative definiteness of the covariance matrices of the predicted state vector and observation vector. Experiments and comparison analysis were conducted to comprehensively evaluate the performance of the proposed algorithm. The results demonstrate that the proposed algorithm exhibits a strong overall performance for integrated navigation systems. Full article
(This article belongs to the Special Issue Sensor Fusion and Novel Technologies in Positioning and Navigation)
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12 pages, 2590 KiB  
Review
Update of Single Event Effects Radiation Hardness Assurance of Readout Integrated Circuit of Infrared Image Sensors at Cryogenic Temperature
by Laurent Artola, Ahmad Al Youssef, Samuel Ducret, Franck Perrier, Raphael Buiron, Olivier Gilard, Julien Mekki, Mathieu Boutillier, Guillaume Hubert and Christian Poivey
Sensors 2018, 18(7), 2338; https://doi.org/10.3390/s18072338 - 18 Jul 2018
Cited by 8 | Viewed by 4693
Abstract
This paper review presents Single Event Effects (SEE) irradiation tests under heavy ions of the test-chip of D-Flip-Flop (DFF) cells and complete readout integrated circuits (ROIC) as a function of temperature, down to 50 K. The analyses of the experimental data are completed [...] Read more.
This paper review presents Single Event Effects (SEE) irradiation tests under heavy ions of the test-chip of D-Flip-Flop (DFF) cells and complete readout integrated circuits (ROIC) as a function of temperature, down to 50 K. The analyses of the experimental data are completed using the SEE prediction tool MUSCA SEP3. The conclusions derived from the experimental measurements and related analyses allow to update the current SEE radiation hardness assurance (RHA) for readout integrated circuits of infrared image sensors used at cryogenic temperatures. The current RHA update is performed on SEE irradiation tests at room temperature, as opposed to the operational cryogenic temperature. These tests include SET (Single Event Transient), SEU (Single Event Upset) and SEFI (Single Event Functional Interrupt) irradiation tests. This update allows for reducing the cost of ROIC qualifications and the test setup complexity for each space mission. Full article
(This article belongs to the Special Issue Sensors and Materials for Harsh Environments)
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23 pages, 23067 KiB  
Article
Extending QGroundControl for Automated Mission Planning of UAVs
by Cristian Ramirez-Atencia and David Camacho
Sensors 2018, 18(7), 2339; https://doi.org/10.3390/s18072339 - 18 Jul 2018
Cited by 42 | Viewed by 9642
Abstract
Unmanned Aerial Vehicle (UAVs) have become very popular in the last decade due to some advantages such as strong terrain adaptation, low cost, zero casualties, and so on. One of the most interesting advances in this field is the automation of mission planning [...] Read more.
Unmanned Aerial Vehicle (UAVs) have become very popular in the last decade due to some advantages such as strong terrain adaptation, low cost, zero casualties, and so on. One of the most interesting advances in this field is the automation of mission planning (task allocation) and real-time replanning, which are highly useful to increase the autonomy of the vehicle and reduce the operator workload. These automated mission planning and replanning systems require a Human Computer Interface (HCI) that facilitates the visualization and selection of plans that will be executed by the vehicles. In addition, most missions should be assessed before their real-life execution. This paper extends QGroundControl, an open-source simulation environment for flight control of multiple vehicles, by adding a mission designer that permits the operator to build complex missions with tasks and other scenario items; an interface for automated mission planning and replanning, which works as a test bed for different algorithms, and a Decision Support System (DSS) that helps the operator in the selection of the plan. In this work, a complete guide of these systems and some practical use cases are provided. Full article
(This article belongs to the Special Issue Internet of Things Middleware Platforms and Sensing Infrastructure)
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25 pages, 11977 KiB  
Article
Partial Inductance Model of Induction Machines for Fault Diagnosis
by Manuel Pineda-Sanchez, Ruben Puche-Panadero, Javier Martinez-Roman, Angel Sapena-Bano, Martin Riera-Guasp and Juan Perez-Cruz
Sensors 2018, 18(7), 2340; https://doi.org/10.3390/s18072340 - 18 Jul 2018
Cited by 13 | Viewed by 5358
Abstract
The development of advanced fault diagnostic systems for induction machines through the stator current requires accurate and fast models that can simulate the machine under faulty conditions, both in steady-state and in transient regime. These models are far more complex than the models [...] Read more.
The development of advanced fault diagnostic systems for induction machines through the stator current requires accurate and fast models that can simulate the machine under faulty conditions, both in steady-state and in transient regime. These models are far more complex than the models used for healthy machines, because one of the effect of the faults is to change the winding configurations (broken bar faults, rotor asymmetries, and inter-turn short circuits) or the magnetic circuit (eccentricity and bearing faults). This produces a change of the self and mutual phase inductances, which induces in the stator currents the characteristic fault harmonics used to detect and to quantify the fault. The development of a machine model that can reflect these changes is a challenging task, which is addressed in this work with a novel approach, based on the concept of partial inductances. Instead of developing the machine model based on the phases’ coils, it is developed using the partial inductance of a single conductor, obtained through the magnetic vector potential, and combining the partial inductances of all the conductors with a fast Fourier transform for obtaining the phases’ inductances. The proposed method is validated using a commercial induction motor with forced broken bars. Full article
(This article belongs to the Special Issue Sensors for Fault Detection)
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14 pages, 2243 KiB  
Article
A Parameter Self-Calibration Method for GNSS/INS Deeply Coupled Navigation Systems in Highly Dynamic Environments
by Zang Chen, Jizhou Lai, Jianye Liu, Rongbing Li and Guotian Ji
Sensors 2018, 18(7), 2341; https://doi.org/10.3390/s18072341 - 18 Jul 2018
Cited by 3 | Viewed by 3689
Abstract
The GNSS/INS (Global Navigation Satellite System/Inertial Navigation System) navigation system has been widely discussed in recent years. Because of the unique INS-aided loop structure, the deeply coupled system performs very well in highly dynamic environments. In practice, vehicle maneuvering has a big influence [...] Read more.
The GNSS/INS (Global Navigation Satellite System/Inertial Navigation System) navigation system has been widely discussed in recent years. Because of the unique INS-aided loop structure, the deeply coupled system performs very well in highly dynamic environments. In practice, vehicle maneuvering has a big influence on the performance of IMUs (Inertial Measurement Unit), and determining whether the selected IMUs and receiver parameters satisfy the loop dynamic requirement is still a critical problem for deeply coupled systems. Aiming at this, a new parameter self-calibration method based on the norm principle is proposed which explains the relationship between IMU precision and the velocity error of the system; the method will also provide a detailed solution to calculate the loop steady-state tracking error, so it will eventually make a judgment about the stability of the tracking loop under present system parameter settings. Lastly, a full digital simulation platform is set up, and the results of simulations show good agreement with the proposed method. Full article
(This article belongs to the Special Issue Inertial Sensors and Systems 2018)
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20 pages, 5450 KiB  
Article
Design and Optimization of FBG Implantable Flexible Morphological Sensor to Realize the Intellisense for Displacement
by Changbin Tian, Zhengfang Wang, Qingmei Sui, Jing Wang, Yanan Dong, Yijia Li, Mingjuan Han, Lei Jia and Hanpeng Wang
Sensors 2018, 18(7), 2342; https://doi.org/10.3390/s18072342 - 19 Jul 2018
Cited by 9 | Viewed by 3485
Abstract
The measurement accuracy of the intelligent flexible morphological sensor based on fiber Bragg grating (FBG) structure was limited in the application of geotechnical engineering and other fields. In order to improve the precision of intellisense for displacement, an FBG implantable flexible morphological sensor [...] Read more.
The measurement accuracy of the intelligent flexible morphological sensor based on fiber Bragg grating (FBG) structure was limited in the application of geotechnical engineering and other fields. In order to improve the precision of intellisense for displacement, an FBG implantable flexible morphological sensor was designed in this study, and the classification morphological correction method based on conjugate gradient method and extreme learning machine (ELM) algorithm was proposed. This study utilized finite element simulations and experiments, in order to analyze the feasibility of the proposed method. Then, following the corrections, the results indicated that the maximum relative error percentages of the displacements at measuring points in different bending shapes were determined to be 6.39% (Type 1), 7.04% (Type 2), and 7.02% (Type 3), respectively. Therefore, it was confirmed that the proposed correction method was feasible, and could effectively improve the abilities of sensors for displacement intellisense. In this paper, the designed intelligent sensor was characterized by temperature self-compensation, bending shape self-classification, and displacement error self-correction, which could be used for real-time monitoring of deformation field in rock, subgrade, bridge, and other geotechnical engineering, presenting the vital significance and application promotion value. Full article
(This article belongs to the Section Intelligent Sensors)
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16 pages, 1106 KiB  
Article
Characteristics, Usability, and Users Experience of a System Combining Cognitive and Physical Therapy in a Virtual Environment: Positive Bike
by Elisa Pedroli, Luca Greci, Desirèe Colombo, Silvia Serino, Pietro Cipresso, Sara Arlati, Marta Mondellini, Lorenzo Boilini, Valentina Giussani, Karine Goulene, Monica Agostoni, Marco Sacco, Marco Stramba-Badiale, Giuseppe Riva and Andrea Gaggioli
Sensors 2018, 18(7), 2343; https://doi.org/10.3390/s18072343 - 19 Jul 2018
Cited by 92 | Viewed by 8716
Abstract
We present the architecture and usability evaluation of virtual reality system—“Positive Bike”—designed for improving cognitive and motor conditions in frail elderly patients. The system consists of a cycle-ergometer integrated in an immersive virtual reality system (CAVE) which allows combining motor and cognitive exercises [...] Read more.
We present the architecture and usability evaluation of virtual reality system—“Positive Bike”—designed for improving cognitive and motor conditions in frail elderly patients. The system consists of a cycle-ergometer integrated in an immersive virtual reality system (CAVE) which allows combining motor and cognitive exercises according to a “dual-task” paradigm. We tested the usability and user’s experience of the prototype in a pilot evaluation study that involved five elderly patients. The prototype was tested in one-session training to understand the limitations and areas for improvement of our system. The evaluation consisted in (i) usability assessment using the system usability scale; (ii) evaluation of user’s engagement using the flow state scale; and (iii) expert evaluation involving interviews with domain experts. Results showed a good usability, both for system usability scale and the semi-structured interview. The level of flow (i.e., enjoyment with the task at hand) measured using the short flow state scale, was also high. Analysis of semi-structured interview carried out with domain experts provided further indications to improve the system. Overall, these findings show that, despite some limitations, the system is usable and provides an enjoyable user’s experience. Full article
(This article belongs to the Special Issue New Trends in Psychophysiology and Mental Health)
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23 pages, 3588 KiB  
Article
Intersection and Complement Set (IACS) Method to Reduce Redundant Node in Mobile WSN Localization
by Muhammad Zar Mohd. Zaid Harith, Noorzaily Mohamed Noor, Mohd. Yamani Idna Idris and Emran Mohd. Tamil
Sensors 2018, 18(7), 2344; https://doi.org/10.3390/s18072344 - 19 Jul 2018
Cited by 5 | Viewed by 3282
Abstract
The majority of the Wireless Sensor Network (WSN) localization methods utilize a large number of nodes to achieve high localization accuracy. However, there are many unnecessary data redundancies that contributes to high computation, communication, and energy cost between these nodes. Therefore, we propose [...] Read more.
The majority of the Wireless Sensor Network (WSN) localization methods utilize a large number of nodes to achieve high localization accuracy. However, there are many unnecessary data redundancies that contributes to high computation, communication, and energy cost between these nodes. Therefore, we propose the Intersection and Complement Set (IACS) method to reduce these redundant data by selecting the most significant neighbor nodes for the localization process. Through duplication cleaning and average filtering steps, the proposed IACS selects the normal nodes with unique intersection and complement sets in the first and second hop neighbors to localize the unknown node. If the intersection or complement sets of the normal nodes are duplicated, IACS only selects the node with the shortest distance to the blind node and nodes that have total elements larger than the average of the intersection or complement sets. The proposed IACS is tested in various simulation settings and compared with MSL* and LCC. The performance of all methods is investigated using the default settings and a different number of degree of irregularity, normal node density, maximum velocity of sensor node and number of samples. From the simulation, IACS successfully reduced 25% of computation cost, 25% of communication cost and 6% of energy consumption compared to MSL*, while 15% of computation cost, 13% of communication cost and 3% of energy consumption compared to LCC. Full article
(This article belongs to the Special Issue Sensor Fusion and Novel Technologies in Positioning and Navigation)
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24 pages, 2328 KiB  
Article
Calibration and Noise Identification of a Rolling Shutter Camera and a Low-Cost Inertial Measurement Unit
by Chang-Ryeol Lee, Ju Hong Yoon and Kuk-Jin Yoon
Sensors 2018, 18(7), 2345; https://doi.org/10.3390/s18072345 - 19 Jul 2018
Cited by 8 | Viewed by 5284
Abstract
A low-cost inertial measurement unit (IMU) and a rolling shutter camera form a conventional device configuration for localization of a mobile platform due to their complementary properties and low costs. This paper proposes a new calibration method that jointly estimates calibration and noise [...] Read more.
A low-cost inertial measurement unit (IMU) and a rolling shutter camera form a conventional device configuration for localization of a mobile platform due to their complementary properties and low costs. This paper proposes a new calibration method that jointly estimates calibration and noise parameters of the low-cost IMU and the rolling shutter camera for effective sensor fusion in which accurate sensor calibration is very critical. Based on the graybox system identification, the proposed method estimates unknown noise density so that we can minimize calibration error and its covariance by using the unscented Kalman filter. Then, we refine the estimated calibration parameters with the estimated noise density in batch manner. Experimental results on synthetic and real data demonstrate the accuracy and stability of the proposed method and show that the proposed method provides consistent results even with unknown noise density of the IMU. Furthermore, a real experiment using a commercial smartphone validates the performance of the proposed calibration method in off-the-shelf devices. Full article
(This article belongs to the Special Issue Gyroscopes and Accelerometers)
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18 pages, 2621 KiB  
Article
Software Sensor for Activity-Time Monitoring and Fault Detection in Production Lines
by Tamas Ruppert and Janos Abonyi
Sensors 2018, 18(7), 2346; https://doi.org/10.3390/s18072346 - 19 Jul 2018
Cited by 30 | Viewed by 6377
Abstract
Industry 4.0-based human-in-the-loop cyber-physical production systems are transforming the industrial workforce to accommodate the ever-increasing variability of production. Real-time operator support and performance monitoring require accurate information on the activities of operators. The problem with tracing hundreds of activity times is critical due [...] Read more.
Industry 4.0-based human-in-the-loop cyber-physical production systems are transforming the industrial workforce to accommodate the ever-increasing variability of production. Real-time operator support and performance monitoring require accurate information on the activities of operators. The problem with tracing hundreds of activity times is critical due to the enormous variability and complexity of products. To handle this problem a software-sensor-based activity-time and performance measurement system is proposed. To ensure a real-time connection between operator performance and varying product complexity, fixture sensors and an indoor positioning system (IPS) were designed and this multi sensor data merged with product-relevant information. The proposed model-based performance monitoring system tracks the recursively estimated parameters of the activity-time estimation model. As the estimation problem can be ill-conditioned and poor raw sensor data can result in unrealistic parameter estimates, constraints were introduced into the parameter-estimation algorithm to increase the robustness of the software sensor. The applicability of the proposed methodology is demonstrated on a well-documented benchmark problem of a wire harness manufacturing process. The fully reproducible and realistic simulation study confirms that the indoor positioning system-based integration of primary sensor signals and product-relevant information can be efficiently utilized in terms of the constrained recursive estimation of the operator activity. Full article
(This article belongs to the Special Issue Sensors for Fault Detection)
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15 pages, 8299 KiB  
Article
Research and Fabrication of High-Frequency Broadband and Omnidirectional Transmitting Transducer
by Shaohua Hao, Hongwei Wang, Chao Zhong, Likun Wang and Hao Zhang
Sensors 2018, 18(7), 2347; https://doi.org/10.3390/s18072347 - 19 Jul 2018
Cited by 28 | Viewed by 4340
Abstract
A wide-band cylindrical transducer was developed by using the wide band of the composite material and the matched matching layer for multimode coupling. Firstly, the structure size of the transducer’s sensitive component was designed by using ANSYS simulation software. Secondly, the piezoelectric composite [...] Read more.
A wide-band cylindrical transducer was developed by using the wide band of the composite material and the matched matching layer for multimode coupling. Firstly, the structure size of the transducer’s sensitive component was designed by using ANSYS simulation software. Secondly, the piezoelectric composite ring-shaped sensitive component was fabricated by the piezoelectric composite curved-surface forming process, and the matching layer was coated on the periphery of the ring-shaped piezoelectric composite material. Finally, it was encapsulated and the electrodes were drawn out to make a high-frequency broadband horizontal omnidirectional water acoustic transducer prototype. After testing, the working frequency range of the transducer was 230–380 kHz, and the maximum transmission voltage response was 168 dB in the water. Full article
(This article belongs to the Section Physical Sensors)
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26 pages, 8795 KiB  
Article
A Hierarchical Voting Based Mixed Filter Localization Method for Wireless Sensor Network in Mixed LOS/NLOS Environments
by Yan Wang, Jinquan Hang, Long Cheng, Chen Li and Xin Song
Sensors 2018, 18(7), 2348; https://doi.org/10.3390/s18072348 - 19 Jul 2018
Cited by 20 | Viewed by 4057
Abstract
In recent years, the rapid development of microelectronics, wireless communications, and electro-mechanical systems has occurred. The wireless sensor network (WSN) has been widely used in many applications. The localization of a mobile node is one of the key technologies for WSN. Among the [...] Read more.
In recent years, the rapid development of microelectronics, wireless communications, and electro-mechanical systems has occurred. The wireless sensor network (WSN) has been widely used in many applications. The localization of a mobile node is one of the key technologies for WSN. Among the factors that would affect the accuracy of mobile localization, non-line of sight (NLOS) propagation caused by a complicated environment plays a vital role. In this paper, we present a hierarchical voting based mixed filter (HVMF) localization method for a mobile node in a mixed line of sight (LOS) and NLOS environment. We firstly propose a condition detection and distance correction algorithm based on hierarchical voting. Then, a mixed square root unscented Kalman filter (SRUKF) and a particle filter (PF) are used to filter the larger measurement error. Finally, the filtered results are subjected to convex optimization and the maximum likelihood estimation to estimate the position of the mobile node. The proposed method does not require prior information about the statistical properties of the NLOS errors and operates in a 2D scenario. It can be applied to time of arrival (TOA), time difference of arrival (TDOA), received signal (RSS), and other measurement methods. The simulation results show that the HVMF algorithm can efficiently reduce the effect of NLOS errors and can achieve higher localization accuracy than the Kalman filter and PF. The proposed algorithm is robust to the NLOS errors. Full article
(This article belongs to the Special Issue Sensor Fusion and Novel Technologies in Positioning and Navigation)
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29 pages, 10049 KiB  
Article
Differentiated Data Aggregation Routing Scheme for Energy Conserving and Delay Sensitive Wireless Sensor Networks
by Xujing Li, Wei Liu, Mande Xie, Anfeng Liu, Ming Zhao, Neal N. Xiong, Miao Zhao and Wan Dai
Sensors 2018, 18(7), 2349; https://doi.org/10.3390/s18072349 - 19 Jul 2018
Cited by 46 | Viewed by 5192
Abstract
Data aggregation is a widely adopted method to effectively reduce the data transmission volume and improve the lifetime of wireless sensor networks (WSNs). In the data aggregation networks, some parameters directly determine the delay of aggregation. In industrial applications, the data generated by [...] Read more.
Data aggregation is a widely adopted method to effectively reduce the data transmission volume and improve the lifetime of wireless sensor networks (WSNs). In the data aggregation networks, some parameters directly determine the delay of aggregation. In industrial applications, the data generated by different sensors have different requirements for delay or other QoS performance. In the previous study, a common strategy is that all kinds of data is aggregated into one frame when the condition is satisfied with a QoS requirement, which causes excessive energy consumption and severely impairs the lifetime of network. A Differentiated Data Aggregation Routing (DDAR) scheme is proposed to reduce energy consumption and guarantee that the delay could be controlled within the corresponding QoS requirement constraint. The primary contributions of the DDAR scheme are the following: (a) The DDAR scheme makes data with different QoS requirement route to the sink along the different paths. The parameters of the aggregators in each path, such as aggregation deadline (Tt) and the aggregation threshold (Nt), are configured according to the QoS requirements. Accordingly, energy consumption can be reduced without degrading the performance of data transmission. (b) Based on DDAR scheme, an improved DDAR scheme is proposed to further improve performance through fully utilize the residual energy in the nodes which are far from the sink. The frequency of aggregation of these nodes increases by reducing the value of Tt and Nt so as to further improve the energy efficiency and reduce delay. Simulation results demonstrate that compared with the previous scheme, this scheme reduces the delay by 25.01%, improves the lifetime by 55.45%, and increases energy efficiency by 83.99%. The improved DDAR scheme improves the energy efficiency by 33.97% and service guarantee rate by 10.11%. Full article
(This article belongs to the Collection Smart Industrial Wireless Sensor Networks)
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20 pages, 482 KiB  
Article
Towards an Efficient Identification Process for Large-Scale RFID Systems
by Leonardo Sanchez and Victor Ramos
Sensors 2018, 18(7), 2350; https://doi.org/10.3390/s18072350 - 19 Jul 2018
Cited by 4 | Viewed by 2793
Abstract
Radio Frequency Identification (RFID) is one of the most widely used wireless communications technologies nowadays. Among the numerous processes executed within an RFID system, the identification processis the most important one. There have been several proposals to efficiently execute such a mechanism, which [...] Read more.
Radio Frequency Identification (RFID) is one of the most widely used wireless communications technologies nowadays. Among the numerous processes executed within an RFID system, the identification processis the most important one. There have been several proposals to efficiently execute such a mechanism, which are based on the use of an RFID identification method. Besides, one of the most studied scenarios comprises one reader and a set of RFID tags, which we call the centralized approach. Recent work shows that executing the identification process in a distributed or parallel way may be of great benefit for applications with high requirements on time and resources usage, i.e., applications where the time required to execute the identification process needs to be low. In this paper, we focus is on large RFID systems and compare two identification mechanisms, one based on the centralized approach and the other based on the distributed approach. Our aim is to find the advantages and disadvantages of each approach for general RFID scenarios. We observe that the distributed approach is very promising compared to the traditional approach since considerable improvements are found in identification delay, and also the implementation costs would be highly reduced. Full article
(This article belongs to the Section Internet of Things)
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22 pages, 3546 KiB  
Article
Accurate Indoor Sound Level Measurement on a Low-Power and Low-Cost Wireless Sensor Node
by Vladimir Risojević, Robert Rozman, Ratko Pilipović, Rok Češnovar and Patricio Bulić
Sensors 2018, 18(7), 2351; https://doi.org/10.3390/s18072351 - 19 Jul 2018
Cited by 26 | Viewed by 9550
Abstract
Wireless sensor networks can provide a cheap and flexible infrastructure to support the measurement of noise pollution. However, the processing of the gathered data is challenging to implement on resource-constrained nodes, because each node has its own limited power supply, low-performance and low-power [...] Read more.
Wireless sensor networks can provide a cheap and flexible infrastructure to support the measurement of noise pollution. However, the processing of the gathered data is challenging to implement on resource-constrained nodes, because each node has its own limited power supply, low-performance and low-power micro-controller unit and other limited processing resources, as well as limited amount of memory. We propose a sensor node for monitoring of indoor ambient noise. The sensor node is based on a hardware platform with limited computational resources and utilizes several simplifications to approximate more complex and costly signal processing stage. Furthermore, to reduce the communication between the sensor node and a sink node, as well as the power consumed by the IEEE 802.15.4 (ZigBee) transceiver, we perform digital A-weighting filtering and non-calibrated calculation of the sound pressure level on the node. According to experimental results, the proposed sound level meter can accurately measure the noise levels of up to 100 dB, with the mean difference of less than 2 dB compared to Class 1 sound level meter. The proposed device can continuously monitor indoor noise for several days. Despite the limitations of the used hardware platform, the presented node is a promising low-cost and low-power solution for indoor ambient noise monitoring. Full article
(This article belongs to the Section Sensor Networks)
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19 pages, 2428 KiB  
Article
Robust Adaptive Cubature Kalman Filter and Its Application to Ultra-Tightly Coupled SINS/GPS Navigation System
by Xin Zhao, Jianli Li, Xunliang Yan and Shaowen Ji
Sensors 2018, 18(7), 2352; https://doi.org/10.3390/s18072352 - 20 Jul 2018
Cited by 39 | Viewed by 4847
Abstract
In this paper, we propose a robust adaptive cubature Kalman filter (CKF) to deal with the problem of an inaccurately known system model and noise statistics. In order to overcome the kinematic model error, we introduce an adaptive factor to adjust the covariance [...] Read more.
In this paper, we propose a robust adaptive cubature Kalman filter (CKF) to deal with the problem of an inaccurately known system model and noise statistics. In order to overcome the kinematic model error, we introduce an adaptive factor to adjust the covariance matrix of state prediction, and process the influence introduced by dynamic disturbance error. Aiming at overcoming the abnormality error, we propose the robust estimation theory to adjust the CKF algorithm online. The proposed adaptive CKF can detect the degree of gross error and subsequently process it, so the influence produced by the abnormality error can be solved. The paper also studies a typical application system for the proposed method, which is the ultra-tightly coupled navigation system of a hypersonic vehicle. Highly dynamical scene experimental results show that the proposed method can effectively process errors aroused by the abnormality data and inaccurate model, and has better tracking performance than UKF and CKF tracking methods. Simultaneously, the proposed method is superior to the tracing method based on a single-modulating loop in the tracking performance. Thus, the stable and high-precision tracking for GPS satellite signals are preferably achieved and the applicability of the system is promoted under the circumstance of high dynamics and weak signals. The effectiveness of the proposed method is verified by a highly dynamical scene experiment. Full article
(This article belongs to the Special Issue Aerospace Sensors and Multisensor Systems)
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14 pages, 2208 KiB  
Communication
On the Einthoven Triangle: A Critical Analysis of the Single Rotating Dipole Hypothesis
by Gaetano D. Gargiulo, Paolo Bifulco, Mario Cesarelli, Alistair L. McEwan, Hossein Moeinzadeh, Aiden O’Loughlin, Ibrahim M. Shugman, Jonathan C. Tapson and Aravinda Thiagalingam
Sensors 2018, 18(7), 2353; https://doi.org/10.3390/s18072353 - 20 Jul 2018
Cited by 18 | Viewed by 23342
Abstract
Since its inception, electrocardiography has been based on the simplifying hypothesis that cardinal limb leads form an equilateral triangle of which, at the center/centroid, the electrical equivalent of the cardiac activity rotates during the cardiac cycle. Therefore, it is thought that the three [...] Read more.
Since its inception, electrocardiography has been based on the simplifying hypothesis that cardinal limb leads form an equilateral triangle of which, at the center/centroid, the electrical equivalent of the cardiac activity rotates during the cardiac cycle. Therefore, it is thought that the three limbs (right arm, left arm, and left leg) which enclose the heart into a circuit, where each branch directly implies current circulation through the heart, can be averaged together to form a stationary reference (central terminal) for precordials/chest-leads. Our hypothesis is that cardinal limbs do not form a triangle for the majority of the duration of the cardiac cycle. As a corollary, the central point may not lie in the plane identified by the limb leads. Using a simple and efficient algorithm, we demonstrate that the portion of the cardiac cycle where the three limb leads form a triangle is, on average less, than 50%. Full article
(This article belongs to the Section Biosensors)
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16 pages, 4134 KiB  
Article
An Empirical-Mathematical Approach for Calibration and Fitting Cell-Electrode Electrical Models in Bioimpedance Tests
by Juan A. Serrano, Gloria Huertas, Andrés Maldonado-Jacobi, Alberto Olmo, Pablo Pérez, María E. Martín, Paula Daza and Alberto Yúfera
Sensors 2018, 18(7), 2354; https://doi.org/10.3390/s18072354 - 20 Jul 2018
Cited by 12 | Viewed by 4096
Abstract
This paper proposes a new yet efficient method allowing a significant improvement in the on-line analysis of biological cell growing and evolution. The procedure is based on an empirical-mathematical approach for calibration and fitting of any cell-electrode electrical model. It is valid and [...] Read more.
This paper proposes a new yet efficient method allowing a significant improvement in the on-line analysis of biological cell growing and evolution. The procedure is based on an empirical-mathematical approach for calibration and fitting of any cell-electrode electrical model. It is valid and can be extrapolated for any type of cellular line used in electrical cell-substrate impedance spectroscopy (ECIS) tests. Parameters of the bioimpedance model, acquired from ECIS experiments, vary for each cell line, which makes obtaining results difficult and—to some extent-renders them inaccurate. We propose a fitting method based on the cell line initial characterization, and carry out subsequent experiments with the same line to approach the percentage of well filling and the cell density (or cell number in the well). To perform our calibration technique, the so-called oscillation-based test (OBT) approach is employed for each cell density. Calibration results are validated by performing other experiments with different concentrations on the same cell line with the same measurement technique. Accordingly, a bioimpedance electrical model of each cell line is determined, which is valid for any further experiment and leading to a more precise electrical model of the electrode-cell system. Furthermore, the model parameters calculated can be also used by any other measurement techniques. Promising experimental outcomes for three different cell-lines have been achieved, supporting the usefulness of this technique. Full article
(This article belongs to the Special Issue Sensors for Cell Analysis)
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17 pages, 3790 KiB  
Article
Robot Imitation Learning of Social Gestures with Self-Collision Avoidance Using a 3D Sensor
by Tan Zhang, Wing-Yue Louie, Goldie Nejat and Beno Benhabib
Sensors 2018, 18(7), 2355; https://doi.org/10.3390/s18072355 - 20 Jul 2018
Cited by 8 | Viewed by 4629
Abstract
To effectively interact with people, social robots need to perceive human behaviors and in turn display their own behaviors using social communication modes such as gestures. The modeling of gestures can be difficult due to the high dimensionality of the robot configuration space. [...] Read more.
To effectively interact with people, social robots need to perceive human behaviors and in turn display their own behaviors using social communication modes such as gestures. The modeling of gestures can be difficult due to the high dimensionality of the robot configuration space. Imitation learning can be used to teach a robot to implement multi-jointed arm gestures by directly observing a human teacher’s arm movements (for example, using a non-contact 3D sensor) and then mapping these movements onto the robot arms. In this paper, we present a novel imitation learning system with robot self-collision awareness and avoidance. The proposed method uses a kinematical approach with bounding volumes to detect and avoid collisions with the robot itself while performing gesticulations. We conducted experiments with a dual arm social robot and a 3D sensor to determine the effectiveness of our imitation system in being able to mimic gestures while avoiding self-collisions. Full article
(This article belongs to the Section Physical Sensors)
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19 pages, 3169 KiB  
Article
Theoretical and Numerical Study on Stress Intensity Factors for FRP-Strengthened Steel Plates with Double-Edged Cracks
by Hai-Tao Wang, Gang Wu and Yu-Yang Pang
Sensors 2018, 18(7), 2356; https://doi.org/10.3390/s18072356 - 20 Jul 2018
Cited by 34 | Viewed by 7016
Abstract
This paper presents a theoretical and numerical study on the stress intensity factors for double-edged cracked steel plates strengthened with fiber reinforced polymer (FRP) plates. Based on the stress intensity factor solution for infinite center-cracked steel plates strengthened with FRP plates, expressions of [...] Read more.
This paper presents a theoretical and numerical study on the stress intensity factors for double-edged cracked steel plates strengthened with fiber reinforced polymer (FRP) plates. Based on the stress intensity factor solution for infinite center-cracked steel plates strengthened with FRP plates, expressions of the stress intensity factors were proposed for double-edged cracked steel plates strengthened with FRP plates by introducing two correction factors: β and f. A finite element (FE) simulation was carried out to calculate the stress intensity factors of the steel plate specimens. Numerous combinations of the specimen width, crack length, FRP thickness and Young’s modulus, adhesive thickness, and shear modulus were considered to conduct the parametric investigation. The FE results were used to investigate the main influencing factors of the stress intensity factors and the correction factor, β. The expression of the correction factor, β, was formulated and calibrated based on the FE results. The proposed expressions of the stress intensity factors were a function of the applied stress, the crack length, the ratio between the crack length and the width of the steel plate, the stiffness ratio between the FRP plate and steel plate, the adhesive thickness, and the shear modulus. Finally, the theoretical results and numerical results were compared to validate the proposed expressions. Full article
(This article belongs to the Special Issue Advances in FRP Composites: Applications, Sensing, and Monitoring)
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17 pages, 7627 KiB  
Review
A Review of Ion Implantation Technology for Image Sensors
by Nobukazu Teranishi, Genshu Fuse and Michiro Sugitani
Sensors 2018, 18(7), 2358; https://doi.org/10.3390/s18072358 - 20 Jul 2018
Cited by 36 | Viewed by 16655
Abstract
Ion implantation technology is reviewed mainly from the viewpoint of image sensors, which play a significant role in implantation technology development. Image sensors are so sensitive to metal contamination that they can detect even one metal atom per pixel. To reduce the metal [...] Read more.
Ion implantation technology is reviewed mainly from the viewpoint of image sensors, which play a significant role in implantation technology development. Image sensors are so sensitive to metal contamination that they can detect even one metal atom per pixel. To reduce the metal contamination, the plasma shower using RF (radio frequency) plasma generation is a representative example. The electrostatic angular energy filter after the mass analyzing magnet is a highly effective method to remove energetic metal contamination. The protection layer on the silicon is needed to protect the silicon wafer against the physisorbed metals. The thickness of the protection layer should be determined by considering the knock-on depth. The damage by ion implantation also causes blemishes. It becomes larger in the following conditions if the other conditions are the same; a. higher energy; b. larger dose; c. smaller beam size (higher beam current density); d. longer ion beam irradiation time; e. larger ion mass. To reduce channeling, the most effective method is to choose proper tilt and twist angles. For P+ pinning layer formation, the low-energy B+ implantation method might have less metal contamination and damage, compared with the BF2+ method. Full article
(This article belongs to the Section Physical Sensors)
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17 pages, 9848 KiB  
Article
Robust Visual Tracking Based on Adaptive Convolutional Features and Offline Siamese Tracker
by Ximing Zhang and Mingang Wang
Sensors 2018, 18(7), 2359; https://doi.org/10.3390/s18072359 - 20 Jul 2018
Cited by 4 | Viewed by 3525
Abstract
Robust and accurate visual tracking is one of the most challenging computer vision problems. Due to the inherent lack of training data, a robust approach for constructing a target appearance model is crucial. The existing spatially regularized discriminative correlation filter (SRDCF) method learns [...] Read more.
Robust and accurate visual tracking is one of the most challenging computer vision problems. Due to the inherent lack of training data, a robust approach for constructing a target appearance model is crucial. The existing spatially regularized discriminative correlation filter (SRDCF) method learns partial-target information or background information when experiencing rotation, out of view, and heavy occlusion. In order to reduce the computational complexity by creating a novel method to enhance tracking ability, we first introduce an adaptive dimensionality reduction technique to extract the features from the image, based on pre-trained VGG-Net. We then propose an adaptive model update to assign weights during an update procedure depending on the peak-to-sidelobe ratio. Finally, we combine the online SRDCF-based tracker with the offline Siamese tracker to accomplish long term tracking. Experimental results demonstrate that the proposed tracker has satisfactory performance in a wide range of challenging tracking scenarios. Full article
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35 pages, 3125 KiB  
Review
Monitoring System Analysis for Evaluating a Building’s Envelope Energy Performance through Estimation of Its Heat Loss Coefficient
by Catalina Giraldo-Soto, Aitor Erkoreka, Laurent Mora, Irati Uriarte and Luis Alfonso Del Portillo
Sensors 2018, 18(7), 2360; https://doi.org/10.3390/s18072360 - 20 Jul 2018
Cited by 19 | Viewed by 5583
Abstract
The present article investigates the question of building energy monitoring systems used for data collection to estimate the Heat Loss Coefficient (HLC) with existing methods, in order to determine the Thermal Envelope Performance (TEP) of a building. The data requirements of HLC estimation [...] Read more.
The present article investigates the question of building energy monitoring systems used for data collection to estimate the Heat Loss Coefficient (HLC) with existing methods, in order to determine the Thermal Envelope Performance (TEP) of a building. The data requirements of HLC estimation methods are related to commonly used methods for fault detection, calibration, and supervision of energy monitoring systems in buildings. Based on an extended review of experimental tests to estimate the HLC undertaken since 1978, qualitative and quantitative analyses of the Monitoring and Controlling System (MCS) specifications have been carried out. The results show that no Fault Detection and Diagnosis (FDD) methods have been implemented in the reviewed literature. Furthermore, it was not possible to identify a trend of technology type used in sensors, hardware, software, and communication protocols, because a high percentage of the reviewed experimental tests do not specify the model, technical characteristics, or selection criteria of the implemented MCSs. Although most actual Building Automation Systems (BAS) may measure the required parameters, further research is still needed to ensure that these data are accurate enough to rigorously apply HLC estimation methods. Full article
(This article belongs to the Special Issue Sensors for Fault Detection)
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23 pages, 3129 KiB  
Article
Activities of Daily Living Ontology for Ubiquitous Systems: Development and Evaluation
by Przemysław R. Woznowski, Emma L. Tonkin and Peter A. Flach
Sensors 2018, 18(7), 2361; https://doi.org/10.3390/s18072361 - 20 Jul 2018
Cited by 17 | Viewed by 4706
Abstract
Ubiquitous eHealth systems based on sensor technologies are seen as key enablers in the effort to reduce the financial impact of an ageing society. At the heart of such systems sit activity recognition algorithms, which need sensor data to reason over, and a [...] Read more.
Ubiquitous eHealth systems based on sensor technologies are seen as key enablers in the effort to reduce the financial impact of an ageing society. At the heart of such systems sit activity recognition algorithms, which need sensor data to reason over, and a ground truth of adequate quality used for training and validation purposes. The large set up costs of such research projects and their complexity limit rapid developments in this area. Therefore, information sharing and reuse, especially in the context of collected datasets, is key in overcoming these barriers. One approach which facilitates this process by reducing ambiguity is the use of ontologies. This article presents a hierarchical ontology for activities of daily living (ADL), together with two use cases of ground truth acquisition in which this ontology has been successfully utilised. Requirements placed on the ontology by ongoing work are discussed. Full article
(This article belongs to the Special Issue Annotation of User Data for Sensor-Based Systems)
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19 pages, 4780 KiB  
Article
Improvement of CO2-DIAL Signal-to-Noise Ratio Using Lifting Wavelet Transform
by Chengzhi Xiang, Ge Han, Yuxin Zheng, Xin Ma and Wei Gong
Sensors 2018, 18(7), 2362; https://doi.org/10.3390/s18072362 - 20 Jul 2018
Cited by 8 | Viewed by 4024
Abstract
Atmospheric CO2 plays an important role in controlling climate change and its effect on the carbon cycle. However, detailed information on the dynamics of CO2 vertical mixing remains lacking, which hinders the accurate understanding of certain key features of the carbon [...] Read more.
Atmospheric CO2 plays an important role in controlling climate change and its effect on the carbon cycle. However, detailed information on the dynamics of CO2 vertical mixing remains lacking, which hinders the accurate understanding of certain key features of the carbon cycle. Differential absorption lidar (DIAL) is a promising technology for CO2 detection due to its characteristics of high precision, high time resolution, and high spatial resolution. Ground-based CO2-DIAL can provide the continuous observations of the vertical profile of CO2 concentration, which can be highly significant to gaining deeper insights into the rectification effect of CO2, the ratio of respiration photosynthesis, and the CO2 dome in urban areas. A set of ground-based CO2-DIAL systems were developed by our team and highly accurate long-term laboratory experiments were conducted. Nonetheless, the performance suffered from low signal-to-noise ratio (SNR) in field explorations because of decreasing aerosol concentrations with increasing altitude and surrounding interference according to the results of our experiments in Wuhan and Huainan. The concentration of atmospheric CO2 is derived from the difference of signals between on-line and off-line wavelengths; thus, low SNR will cause the superimposition of the final inversion error. In such a situation, an efficient and accurate denoising algorithm is critical for a ground-based CO2-DIAL system, particularly in field experiments. In this study, a method based on lifting wavelet transform (LWT) for CO2-DIAL signal denoising was proposed. This method, which is an improvement of the traditional wavelet transform, can select different predictive and update functions according to the characteristics of lidar signals, thereby making it suitable for the signal denoising of CO2-DIAL. Experiment analyses were conducted to evaluate the denoising effect of LWT. For comparison, ensemble empirical mode decomposition denoising was also performed on the same lidar signal. In addition, this study calculated the coefficient of variation (CV) at the same altitude among multiple original signals within 10 min and then performed the same calculation on the denoised signal. Finally, high-quality signal of ground-based CO2-DIAL was obtained using the LWT denoising method. The differential absorption optical depths of the denoised signals obtained via LWT were calculated, and the profile distribution information of CO2 concentration was acquired during field detection by using our developed CO2-DIAL systems. Full article
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20 pages, 3878 KiB  
Article
A 3D Relative-Motion Context Constraint-Based MAP Solution for Multiple-Object Tracking Problems
by Zhongli Wang, Litong Fan and Baigen Cai
Sensors 2018, 18(7), 2363; https://doi.org/10.3390/s18072363 - 20 Jul 2018
Cited by 1 | Viewed by 4775
Abstract
Multi-object tracking (MOT), especially by using a moving monocular camera, is a very challenging task in the field of visual object tracking. To tackle this problem, the traditional tracking-by-detection-based method is heavily dependent on detection results. Occlusion and mis-detections will often lead to [...] Read more.
Multi-object tracking (MOT), especially by using a moving monocular camera, is a very challenging task in the field of visual object tracking. To tackle this problem, the traditional tracking-by-detection-based method is heavily dependent on detection results. Occlusion and mis-detections will often lead to tracklets or drifting. In this paper, the tasks of MOT and camera motion estimation are formulated as finding a maximum a posteriori (MAP) solution of joint probability and synchronously solved in a unified framework. To improve performance, we incorporate the three-dimensional (3D) relative-motion model into a sequential Bayesian framework to track multiple objects and the camera’s ego-motion estimation. A 3D relative-motion model that describes spatial relations among objects is exploited for predicting object states robustly and recovering objects when occlusion and mis-detections occur. Reversible jump Markov chain Monte Carlo (RJMCMC) particle filtering is applied to solve the posteriori estimation problem. Both quantitative and qualitative experiments with benchmark datasets and video collected on campus were conducted, which confirms that the proposed method is outperformed in many evaluation metrics. Full article
(This article belongs to the Special Issue Sensors Signal Processing and Visual Computing)
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17 pages, 9629 KiB  
Article
Generalized Vision-Based Detection, Identification and Pose Estimation of Lamps for BIM Integration
by Francisco Troncoso-Pastoriza, Javier López-Gómez and Lara Febrero-Garrido
Sensors 2018, 18(7), 2364; https://doi.org/10.3390/s18072364 - 20 Jul 2018
Cited by 8 | Viewed by 4018
Abstract
This paper introduces a comprehensive approach based on computer vision for the automatic detection, identification and pose estimation of lamps in a building using the image and location data from low-cost sensors, allowing the incorporation into the building information modelling (BIM). The procedure [...] Read more.
This paper introduces a comprehensive approach based on computer vision for the automatic detection, identification and pose estimation of lamps in a building using the image and location data from low-cost sensors, allowing the incorporation into the building information modelling (BIM). The procedure is based on our previous work, but the algorithms are substantially improved by generalizing the detection to any light surface type, including polygonal and circular shapes, and refining the BIM integration. We validate the complete methodology with a case study at the Mining and Energy Engineering School and achieve reliable results, increasing the successful real-time processing detections while using low computational resources, leading to an accurate, cost-effective and advanced method. The suitability and the adequacy of the method are proved and concluded. Full article
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22 pages, 1728 KiB  
Article
Talk, Text, Tag? Understanding Self-Annotation of Smart Home Data from a User’s Perspective
by Emma L. Tonkin, Alison Burrows, Przemysław R. Woznowski, Pawel Laskowski, Kristina Y. Yordanova, Niall Twomey and Ian J. Craddock
Sensors 2018, 18(7), 2365; https://doi.org/10.3390/s18072365 - 20 Jul 2018
Cited by 16 | Viewed by 5310
Abstract
Delivering effortless interactions and appropriate interventions through pervasive systems requires making sense of multiple streams of sensor data. This is particularly challenging when these concern people’s natural behaviours in the real world. This paper takes a multidisciplinary perspective of annotation and draws on [...] Read more.
Delivering effortless interactions and appropriate interventions through pervasive systems requires making sense of multiple streams of sensor data. This is particularly challenging when these concern people’s natural behaviours in the real world. This paper takes a multidisciplinary perspective of annotation and draws on an exploratory study of 12 people, who were encouraged to use a multi-modal annotation app while living in a prototype smart home. Analysis of the app usage data and of semi-structured interviews with the participants revealed strengths and limitations regarding self-annotation in a naturalistic context. Handing control of the annotation process to research participants enabled them to reason about their own data, while generating accounts that were appropriate and acceptable to them. Self-annotation provided participants an opportunity to reflect on themselves and their routines, but it was also a means to express themselves freely and sometimes even a backchannel to communicate playfully with the researchers. However, self-annotation may not be an effective way to capture accurate start and finish times for activities, or location associated with activity information. This paper offers new insights and recommendations for the design of self-annotation tools for deployment in the real world. Full article
(This article belongs to the Special Issue Annotation of User Data for Sensor-Based Systems)
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11 pages, 1354 KiB  
Article
A Vision-Driven Collaborative Robotic Grasping System Tele-Operated by Surface Electromyography
by Andrés Úbeda, Brayan S. Zapata-Impata, Santiago T. Puente, Pablo Gil, Francisco Candelas and Fernando Torres
Sensors 2018, 18(7), 2366; https://doi.org/10.3390/s18072366 - 20 Jul 2018
Cited by 7 | Viewed by 4405
Abstract
This paper presents a system that combines computer vision and surface electromyography techniques to perform grasping tasks with a robotic hand. In order to achieve a reliable grasping action, the vision-driven system is used to compute pre-grasping poses of the robotic system based [...] Read more.
This paper presents a system that combines computer vision and surface electromyography techniques to perform grasping tasks with a robotic hand. In order to achieve a reliable grasping action, the vision-driven system is used to compute pre-grasping poses of the robotic system based on the analysis of tridimensional object features. Then, the human operator can correct the pre-grasping pose of the robot using surface electromyographic signals from the forearm during wrist flexion and extension. Weak wrist flexions and extensions allow a fine adjustment of the robotic system to grasp the object and finally, when the operator considers that the grasping position is optimal, a strong flexion is performed to initiate the grasping of the object. The system has been tested with several subjects to check its performance showing a grasping accuracy of around 95% of the attempted grasps which increases in more than a 13% the grasping accuracy of previous experiments in which electromyographic control was not implemented. Full article
(This article belongs to the Special Issue Assistance Robotics and Biosensors)
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34 pages, 4518 KiB  
Review
Aptamer-Based Biosensors to Detect Aquatic Phycotoxins and Cyanotoxins
by Isabel Cunha, Rita Biltes, MGF Sales and Vitor Vasconcelos
Sensors 2018, 18(7), 2367; https://doi.org/10.3390/s18072367 - 20 Jul 2018
Cited by 68 | Viewed by 9273
Abstract
Aptasensors have a great potential for environmental monitoring, particularly for real-time on-site detection of aquatic toxins produced by marine and freshwater microorganisms (cyanobacteria, dinoflagellates, and diatoms), with several advantages over other biosensors that are worth considering. Freshwater monitoring is of vital importance for [...] Read more.
Aptasensors have a great potential for environmental monitoring, particularly for real-time on-site detection of aquatic toxins produced by marine and freshwater microorganisms (cyanobacteria, dinoflagellates, and diatoms), with several advantages over other biosensors that are worth considering. Freshwater monitoring is of vital importance for public health, in numerous human activities, and animal welfare, since these toxins may cause fatal intoxications. Similarly, in marine waters, very effective monitoring programs have been put in place in many countries to detect when toxins exceed established regulatory levels and accordingly enforce shellfish harvesting closures. Recent advances in the fields of aptamer selection, nanomaterials and communication technologies, offer a vast array of possibilities to develop new imaginative strategies to create improved, ultrasensitive, reliable and real-time devices, featuring unique characteristics to produce and amplify the signal. So far, not many strategies have been used to detect aquatic toxins, mostly limited to the optic and electrochemical sensors, the majority applied to detect microcystin-LR using a target-induced switching mode. The limits of detection of these aptasensors have been decreasing from the nM to the fM order of magnitude in the past 20 years. Aspects related to sensor components, performance, aptamers sequences, matrices analyzed and future perspectives, are considered and discussed. Full article
(This article belongs to the Special Issue Environmental Monitoring Biosensors)
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16 pages, 3068 KiB  
Article
Giok the Alien: An AR-Based Integrated System for the Empowerment of Problem-Solving, Pragmatic, and Social Skills in Pre-School Children
by Maria Luisa Lorusso, Marisa Giorgetti, Simona Travellini, Luca Greci, Andrea Zangiacomi, Marta Mondellini, Marco Sacco and Gianluigi Reni
Sensors 2018, 18(7), 2368; https://doi.org/10.3390/s18072368 - 21 Jul 2018
Cited by 32 | Viewed by 6569
Abstract
The use of technology for educational purposes is a consolidated reality, and many new tools are constantly being devised and offered for use with both normally developing children and children with special needs. Nonetheless, a detailed analysis of the processes being stimulated and [...] Read more.
The use of technology for educational purposes is a consolidated reality, and many new tools are constantly being devised and offered for use with both normally developing children and children with special needs. Nonetheless, a detailed analysis of the processes being stimulated and of the goals being pursued is often lacking or absent. In this work we describe the design, development and preliminary testing of an integrated system which combines the use of smart devices, a physical cube, augmented reality (AR) technology, a smart TV, and a software application especially designed to stimulate cognitive and social functions in pre-school children. The system was tested with three groups of children (25 children in total) during kindergarten activities. The results show that the system is easy to understand, elicits high levels of participation and social interaction, favors strategic behaviors, and can be used by the children with limited need of instruction and support by the adult. The implications for empowerment in typically developing children and the possibilities for use with children who have specific impairments in social communication are discussed. Full article
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22 pages, 7983 KiB  
Article
A Wearable Textile Thermograph
by Pasindu Lugoda, Theodore Hughes-Riley, Rob Morris and Tilak Dias
Sensors 2018, 18(7), 2369; https://doi.org/10.3390/s18072369 - 21 Jul 2018
Cited by 30 | Viewed by 8004
Abstract
In medicine, temperature changes can indicate important underlying pathologies such as wound infection. While thermographs for the detection of wound infection exist, a textile substrate offers a preferable solution to the designs that exist in the literature, as a textile is very comfortable [...] Read more.
In medicine, temperature changes can indicate important underlying pathologies such as wound infection. While thermographs for the detection of wound infection exist, a textile substrate offers a preferable solution to the designs that exist in the literature, as a textile is very comfortable to wear. This work presents a fully textile, wearable, thermograph created using temperature-sensing yarns. As described in earlier work, temperature-sensing yarns are constructed by encapsulating an off-the-shelf thermistor into a polymer resin micro-pod and then embedding this within the fibres of a yarn. This process creates a temperature-sensing yarn that is conformal, drapeable, mechanically resilient, and washable. This work first explored a refined yarn design and characterised its accuracy to take absolute temperature measurements. The influence of contact errors with the refined yarns was explored seeing a 0.24 ± 0.03 measurement error when the yarn was held just 0.5 mm away from the surface being measured. Subsequently, yarns were used to create a thermograph. This work characterises the operation of the thermograph under a variety of simulated conditions to better understand the functionality of this type of textile temperature sensor. Ambient temperature, insulating material, humidity, moisture, bending, compression and stretch were all explored. This work is an expansion of an article published in The 4th International Conference on Sensor and Applications. Full article
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11 pages, 2689 KiB  
Article
Ambient Refractive-Index Measurement with Simultaneous Temperature Monitoring Based on a Dual-Resonance Long-Period Grating Inside a Fiber Loop Mirror Structure
by Renata Zawisza, Tinko Eftimov, Predrag Mikulic, Wojtek J. Bock and Leszek R. Jaroszewicz
Sensors 2018, 18(7), 2370; https://doi.org/10.3390/s18072370 - 21 Jul 2018
Cited by 15 | Viewed by 4281
Abstract
In this work, we report the experimental results on optimizing the optical structure for ambient refractive index measuring with temperature changes monitoring. The presented optical structure is based on a dual-resonance long-period grating embedded inside a fiber loop mirror, where the long-period grating [...] Read more.
In this work, we report the experimental results on optimizing the optical structure for ambient refractive index measuring with temperature changes monitoring. The presented optical structure is based on a dual-resonance long-period grating embedded inside a fiber loop mirror, where the long-period grating acts as the head of the refractive-index sensor, whereas the section of polarization maintaining fiber in the loop mirror ensures suitable temperature sensing. The optimization process was comprised of tuning the resonance and interferometric peaks by changing the state of polarization of propagating beams. Experimental results establish that the response of the proposed sensor structure is linear and goes in opposite directions: an increase in the ambient refractive index reduces the signal response, whereas a temperature increase produces an increased response. This enables us to distinguish between the signals from changes in the refractive index and temperature. Due to the filtering properties of the interferometric structure, it is possible to monitor variation in these physical parameters by observing optical power changes instead of wavelength shifts. Hence, the refractive index sensitivity has been established up to 2375.8 dB/RIU in the narrow RI range (1.333–1.341 RIU) and temperature sensitivities up to 1.1 dBm/°C in the range of 23–41 °C. The proposed sensor is dedicated to advanced chemical and biological sensor applications. Full article
(This article belongs to the Special Issue Optical Waveguide Based Sensors)
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30 pages, 14132 KiB  
Article
Advanced SBAS-DInSAR Technique for Controlling Large Civil Infrastructures: An Application to the Genzano di Lucania Dam
by Marco Corsetti, Fabrizio Fossati, Michele Manunta and Maria Marsella
Sensors 2018, 18(7), 2371; https://doi.org/10.3390/s18072371 - 21 Jul 2018
Cited by 36 | Viewed by 4935
Abstract
Monitoring surface deformation on dams is commonly carried out by in situ geodetic surveying, which is time consuming and characterized by some limitations in space coverage and frequency. More recently microwave satellite-based technologies, such as advanced-DInSAR (Differential Synthetic Aperture Radar Interferometry), have allowed [...] Read more.
Monitoring surface deformation on dams is commonly carried out by in situ geodetic surveying, which is time consuming and characterized by some limitations in space coverage and frequency. More recently microwave satellite-based technologies, such as advanced-DInSAR (Differential Synthetic Aperture Radar Interferometry), have allowed the integration and improvement of the observation capabilities of ground-based methods thanks to their effectiveness in collecting displacement measurements on many non-destructive control points, corresponding to radar reflecting targets. The availability of such a large number of points of measurement, which are distributed along the whole structure and are characterized by millimetric accuracy on displacement rates, can be profitably adopted for the calibration of numerical models. These models are implemented to simulate the structural behaviour of a dam under conditions of stress thus improving the ability to maintain safety standards. In this work, after having analysed how advanced DInSAR can effectively enhance the results from traditional monitoring systems that provide comparable accuracy measurements on a limited number of points, an FEM model of the Genzano di Lucania earth dam is developed and calibrated. This work is concentrated on the advanced DInSAR technique referred to as Small BAseline Subset (SBAS) approach, benefiting from its capability to generate deformation time series at full spatial resolution and from multi-sensor SAR data, to measure the vertical consolidation displacement of the Genzano di Lucania earth dam. Full article
(This article belongs to the Special Issue Sensors for Deformation Monitoring of Large Civil Infrastructures)
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13 pages, 3641 KiB  
Article
A Colorimetric Probe Based on Functionalized Gold Nanorods for Sensitive and Selective Detection of As(III) Ions
by Kun Ge, Jingmin Liu, Guozhen Fang, Peihua Wang, Dongdong Zhang and Shuo Wang
Sensors 2018, 18(7), 2372; https://doi.org/10.3390/s18072372 - 21 Jul 2018
Cited by 20 | Viewed by 5482
Abstract
A colorimetric probe for determination of As(III) ions in aqueous solutions on basis of localized surface plasmon resonance (LSPR) was synthesized. The dithiothreitol molecules with two end thiols covalently combined with Au Nanorods (AuNRs) with an aspect ratio of 2.9 by Au-S bond [...] Read more.
A colorimetric probe for determination of As(III) ions in aqueous solutions on basis of localized surface plasmon resonance (LSPR) was synthesized. The dithiothreitol molecules with two end thiols covalently combined with Au Nanorods (AuNRs) with an aspect ratio of 2.9 by Au-S bond to form dithiothreitol coated Au Nanorods (DTT-AuNRs), acting as colorimetric probe for the determination of As(III) ions. With the adding of As(III) ions, the AuNRs will be aggregated and leading the longitudinal SPR absorption band of DTT-AuNRs decrease due to the As(III) ions can bind with three DTT molecules through an As-S linkage. The potential factors affect the response of DTT-AuNRs to As(III) ions including the concentration of DTT, pH values of DTT-AuNRs, reaction time and NaCl concentration were optimized. Under optimum assay conditions, the DTT-AuNRs colorimetric probe has high sensitivity towards As(III) ions with low detection limit of 38 nM by rules of 3σ/k and excellent linear range of 0.13–10.01 μM. The developed colorimetric probe shows high selectivity for As(III) ions sensing and has applied to determine of As(III) in environmental water samples with quantitative spike-recoveries range from 95.2% to 100.4% with low relative standard deviation of less than 4.4% (n = 3). Full article
(This article belongs to the Special Issue Colorimetric Nanosensors)
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16 pages, 4641 KiB  
Article
A 2D Magneto-Acousto-Electrical Tomography Method to Detect Conductivity Variation Using Multifocus Image Method
by Ming Dai, Xin Chen, Tong Sun, Lingyao Yu, Mian Chen, Haoming Lin and Siping Chen
Sensors 2018, 18(7), 2373; https://doi.org/10.3390/s18072373 - 21 Jul 2018
Cited by 20 | Viewed by 4458
Abstract
As magneto-acoustic-electrical tomography (MAET) combines the merits of high contrast and high imaging resolution, and is extremely useful for electrical conductivity measurement, so it is expected to be a promising medical imaging modalities for diagnosis of early-stage cancer. Based on the Verasonics system [...] Read more.
As magneto-acoustic-electrical tomography (MAET) combines the merits of high contrast and high imaging resolution, and is extremely useful for electrical conductivity measurement, so it is expected to be a promising medical imaging modalities for diagnosis of early-stage cancer. Based on the Verasonics system and the MC600 displacement platform, we designed and implemented a MAET system with a chirp pulse stimulation (MAET-CPS) method and a focal probe was utilized for stepscan focus excitation to enhance the imaging resolution. The relevant experiments were conducted to explore the influence of excitation positions of the single-focus point, and the effect of the excitation position on the amplitudes of the conductivity variation was clearly demonstrated. In order to take advantage of the merits of multifocus imaging, we firstly proposed a single focus MAET system with a chirp pulse stimulation (sfMAET-CPS) method and a multifocus MAET system with a chirp pulse stimulation (mfMAET-CPS) method for high-resolution conductivity imaging, and a homogenous gelatin phantom with a cuboid-shaped hole was used to investigate the accuracy of mfMAET-CPS. Comparative experiments were carried out on the same uniform phantom by the sfMAET-CPS and the mfMAET-CPS, respectively. The results showed that: (1) the electrical conductivity distributions of the homogenous phantom with a cuboid-shaped hole were detected by the sfMAET-CPS but were easily affected by the focal point, which demonstrated that the sfMAET-CPS had a low imaging resolution. (2) Compared with the sfMAET-CPS, the imaging effect of the mfMAET-CPS was much better than that of the sfMAET-CPS. (3) A linear interpolation algorithm was used to process the 2D conductivity distribution; it increased the smoothness of the conductivity distribution and improved the imaging effect. The stepscan focus excitation and the linearly frequency-modulated theory provide an alternative scheme for the clinical application of MAET. Full article
(This article belongs to the Section Biosensors)
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14 pages, 4658 KiB  
Article
Design and Fabrication Technology of Low Profile Tactile Sensor with Digital Interface for Whole Body Robot Skin
by Mitsutoshi Makihata, Masanori Muroyama, Shuji Tanaka, Takahiro Nakayama, Yutaka Nonomura and Masayoshi Esashi
Sensors 2018, 18(7), 2374; https://doi.org/10.3390/s18072374 - 21 Jul 2018
Cited by 24 | Viewed by 6555
Abstract
Covering a whole surface of a robot with tiny sensors which can measure local pressure and transmit the data through a network is an ideal solution to give an artificial skin to robots to improve a capability of action and safety. The crucial [...] Read more.
Covering a whole surface of a robot with tiny sensors which can measure local pressure and transmit the data through a network is an ideal solution to give an artificial skin to robots to improve a capability of action and safety. The crucial technological barrier is to package force sensor and communication function in a small volume. In this paper, we propose the novel device structure based on a wafer bonding technology to integrate and package capacitive force sensor using silicon diaphragm and an integrated circuit separately manufactured. Unique fabrication processes are developed, such as the feed-through forming using a dicing process, a planarization of the Benzocyclobutene (BCB) polymer filled in the feed-through and a wafer bonding to stack silicon diaphragm onto ASIC (application specific integrated circuit) wafer. The ASIC used in this paper has a capacitance measurement circuit and a digital communication interface mimicking a tactile receptor of a human. We successfully integrated the force sensor and the ASIC into a 2.5×2.5×0.3 mm die and confirmed autonomously transmitted packets which contain digital sensing data with the linear force sensitivity of 57,640 Hz/N and 10 mN of data fluctuation. A small stray capacitance of 1.33 pF is achieved by use of 10 μm thick BCB isolation layer and this minimum package structure. Full article
(This article belongs to the Section Physical Sensors)
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16 pages, 3457 KiB  
Article
Three-Dimensional Registration of Freehand-Tracked Ultrasound to CT Images of the Talocrural Joint
by Nazlı Tümer, Aimee C. Kok, Frans M. Vos, Geert J. Streekstra, Christian Askeland, Gabrielle J. M. Tuijthof and Amir A. Zadpoor
Sensors 2018, 18(7), 2375; https://doi.org/10.3390/s18072375 - 21 Jul 2018
Cited by 4 | Viewed by 4813
Abstract
A rigid surface–volume registration scheme is presented in this study to register computed tomography (CT) and free-hand tracked ultrasound (US) images of the talocrural joint. Prior to registration, bone surfaces expected to be visible in US are extracted from the CT volume and [...] Read more.
A rigid surface–volume registration scheme is presented in this study to register computed tomography (CT) and free-hand tracked ultrasound (US) images of the talocrural joint. Prior to registration, bone surfaces expected to be visible in US are extracted from the CT volume and bone contours in 2D US data are enhanced based on monogenic signal representation of 2D US images. A 3D monogenic signal data is reconstructed from the 2D data using the position of the US probe recorded with an optical tracking system. When registering the surface extracted from the CT scan to the monogenic signal feature volume, six transformation parameters are estimated so as to optimize the sum of monogenic signal features over the transformed surface. The robustness of the registration algorithm was tested on a dataset collected from 12 cadaveric ankles. The proposed method was used in a clinical case study to investigate the potential of US imaging for pre-operative planning of arthroscopic access to talar (osteo)chondral defects (OCDs). The results suggest that registrations with a registration error of 2 mm and less is achievable, and US has the potential to be used in assessment of an OCD’ arthroscopic accessibility, given the fact that 51% of the talar surface could be visualized. Full article
(This article belongs to the Section Biosensors)
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14 pages, 3737 KiB  
Article
Inductive Loop Axle Detector based on Resistance and Reactance Vehicle Magnetic Profiles
by Zbigniew Marszalek, Tadeusz Zeglen, Ryszard Sroka and Janusz Gajda
Sensors 2018, 18(7), 2376; https://doi.org/10.3390/s18072376 - 21 Jul 2018
Cited by 13 | Viewed by 8242
Abstract
The article presents a measurement system that captures two components of a motor vehicle’s magnetic profile, which are associated with the real and imaginary part of the impedance of a narrow inductive loop sensor. The proposed algorithm utilizes both components of the impedance [...] Read more.
The article presents a measurement system that captures two components of a motor vehicle’s magnetic profile, which are associated with the real and imaginary part of the impedance of a narrow inductive loop sensor. The proposed algorithm utilizes both components of the impedance magnetic profile to detect vehicle axles, including lifted axles. Accuracies of no less than 71.8% were achieved for vehicles travelling with a lifted axle, and no less than 98.8% for other vehicles. The axle detection accuracy was determined during a series of experiments carried out under normal traffic conditions, using profile analysis, video footage and reference signals from an axle load detector on a total of 4000 vehicles. Full article
(This article belongs to the Special Issue Intelligent Sensor Systems for Environmental Monitoring)
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27 pages, 1051 KiB  
Article
Distributed Compressed Sensing Based Ground Moving Target Indication for Dual-Channel SAR System
by Jing Liu, Xiaoqing Tian, Jiayuan Jiang and Kaiyu Huang
Sensors 2018, 18(7), 2377; https://doi.org/10.3390/s18072377 - 21 Jul 2018
Cited by 2 | Viewed by 4434
Abstract
The dual-channel synthetic aperture radar (SAR) system is widely applied in the field of ground moving-target indication (GMTI). With the increase of the imaging resolution, the resulting substantial raw data samples increase the transmission and storage burden. We tackle the problem by adopting [...] Read more.
The dual-channel synthetic aperture radar (SAR) system is widely applied in the field of ground moving-target indication (GMTI). With the increase of the imaging resolution, the resulting substantial raw data samples increase the transmission and storage burden. We tackle the problem by adopting the joint sparsity model 1 (JSM-1) in distributed compressed sensing (DCS) to exploit the correlation between the two channels of the dual-channel SAR system. We propose a novel algorithm, namely the hierarchical variational Bayesian based distributed compressed sensing (HVB-DCS) algorithm for the JSM-1 model, which decouples the common component from the innovation components by applying variational Bayesian approximation. Using the proposed HVB-DCS algorithm in the dual-channel SAR based GMTI (SAR-GMTI) system, we can jointly reconstruct the dual-channel signals, and simultaneously detect the moving targets and stationary clutter, which enables sampling at a further lower rate in azimuth as well as improves the reconstruction accuracy. The simulation and experimental results show that the proposed HVB-DCS algorithm is capable of detecting multiple moving targets while suppressing the clutter at a much lower data rate in azimuth compared with the compressed sensing (CS) and range-Doppler (RD) algorithms. Full article
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23 pages, 12853 KiB  
Article
Time-Frequency Energy Sensing of Communication Signals and Its Application in Co-Channel Interference Suppression
by Yue Li, Liang Ye and Xuejun Sha
Sensors 2018, 18(7), 2378; https://doi.org/10.3390/s18072378 - 21 Jul 2018
Cited by 2 | Viewed by 3925
Abstract
As the number of mobile users and video traffics grow explosively, the data rate demands increase tremendously. To improve the spectral efficiency, the spectrum are reused inter cell or intra cell, such as the ultra dense network with multi-cell or the cellular network [...] Read more.
As the number of mobile users and video traffics grow explosively, the data rate demands increase tremendously. To improve the spectral efficiency, the spectrum are reused inter cell or intra cell, such as the ultra dense network with multi-cell or the cellular network with Device-to-Device communications, where the co-channel interferences are brought and needs to be suppressed. According to the time-frequency energy sensing to the communication signals, the desired signal and the interference signal have different energy concentration areas on the time frequency plane, which provide opportunities to suppress the co-channel interference with time varying filter. This paper analyzes the time-frequency distributions of the Gaussian pulse shaping signals, discusses the effect of the analyzing window length on the time-frequency resolution, exploits the equivalence between the time frequency analysis at the baseband and at the radio front end, and finally reveals the advantages of the proposed masking threshold constrained time varying filter based co-channel interference mitigation method. The pass region for the linear time varying filter is generated according to the time-varying energy characteristics of the I/Q separated 4-QAM pulse shaping signals, where the optimum masking threshold is obtained by the optimum-BER criterion. The proposed co-channel interference suppression method is evaluated in aspect of BER performance, and simulation results show that the proposed method outperforms existing methods with low-pass or band-pass filters. Full article
(This article belongs to the Section Sensor Networks)
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14 pages, 9816 KiB  
Article
Fast Feature-Preserving Approach to Carpal Bone Surface Denoising
by Ibrahim Salim and A. Ben Hamza
Sensors 2018, 18(7), 2379; https://doi.org/10.3390/s18072379 - 21 Jul 2018
Viewed by 4170
Abstract
We present a geometric framework for surface denoising using graph signal processing, which is an emerging field that aims to develop new tools for processing and analyzing graph-structured data. The proposed approach is formulated as a constrained optimization problem whose objective function consists [...] Read more.
We present a geometric framework for surface denoising using graph signal processing, which is an emerging field that aims to develop new tools for processing and analyzing graph-structured data. The proposed approach is formulated as a constrained optimization problem whose objective function consists of a fidelity term specified by a noise model and a regularization term associated with prior data. Both terms are weighted by a normalized mesh Laplacian, which is defined in terms of a data-adaptive kernel similarity matrix in conjunction with matrix balancing. Minimizing the objective function reduces it to iteratively solve a sparse system of linear equations via the conjugate gradient method. Extensive experiments on noisy carpal bone surfaces demonstrate the effectiveness of our approach in comparison with existing methods. We perform both qualitative and quantitative comparisons using various evaluation metrics. Full article
(This article belongs to the Special Issue Sensor Signal and Information Processing)
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18 pages, 5318 KiB  
Article
A Portable Quantum Cascade Laser Spectrometer for Atmospheric Measurements of Carbon Monoxide
by Silvia Viciani, Alessio Montori, Antonio Chiarugi and Francesco D’Amato
Sensors 2018, 18(7), 2380; https://doi.org/10.3390/s18072380 - 21 Jul 2018
Cited by 25 | Viewed by 4906
Abstract
Trace gas concentration measurements in the stratosphere and troposphere are critically required as inputs to constrain climate models. For this purpose, measurement campaigns on stratospheric aircraft and balloons are being carried out all over the world, each one involving sensors which are tailored [...] Read more.
Trace gas concentration measurements in the stratosphere and troposphere are critically required as inputs to constrain climate models. For this purpose, measurement campaigns on stratospheric aircraft and balloons are being carried out all over the world, each one involving sensors which are tailored for the specific gas and environmental conditions. This paper describes an automated, portable, mid-infrared quantum cascade laser spectrometer, for in situ carbon monoxide mixing ratio measurements in the stratosphere and troposphere. The instrument was designed to be versatile, suitable for easy installation on different platforms and capable of operating completely unattended, without the presence of an operator, not only during one flight but for the whole period of a campaign. The spectrometer features a small size (80 × 25 × 41 cm3), light weight (23 kg) and low power consumption (85 W typical), without being pressurized and without the need of calibration on the ground or during in-flight operation. The device was tested in the laboratory and in-field during a research campaign carried out in Nepal in summer 2017, onboard the stratospheric aircraft M55 Geophysica. The instrument worked extremely well, without external maintenance during all flights, proving an in-flight sensitivity of 1–2 ppbV with a time resolution of 1 s. Full article
(This article belongs to the Special Issue Sensors for Emerging Environmental Markers and Contaminants)
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13 pages, 3080 KiB  
Article
Estimation of Cough Peak Flow Using Cough Sounds
by Yasutaka Umayahara, Zu Soh, Kiyokazu Sekikawa, Toshihiro Kawae, Akira Otsuka and Toshio Tsuji
Sensors 2018, 18(7), 2381; https://doi.org/10.3390/s18072381 - 22 Jul 2018
Cited by 19 | Viewed by 7129
Abstract
Cough peak flow (CPF) is a measurement for evaluating the risk of cough dysfunction and can be measured using various devices, such as spirometers. However, complex device setup and the face mask required to be firmly attached to the mouth impose burdens on [...] Read more.
Cough peak flow (CPF) is a measurement for evaluating the risk of cough dysfunction and can be measured using various devices, such as spirometers. However, complex device setup and the face mask required to be firmly attached to the mouth impose burdens on both patients and their caregivers. Therefore, this study develops a novel cough strength evaluation method using cough sounds. This paper presents an exponential model to estimate CPF from the cough peak sound pressure level (CPSL). We investigated the relationship between cough sounds and cough flows and the effects of a measurement condition of cough sound, microphone type and participant’s height and gender on CPF estimation accuracy. The results confirmed that the proposed model estimated CPF with a high accuracy. The absolute error between CPFs and estimated CPFs were significantly lower when the microphone distance from the participant’s mouth was within 30 cm than when the distance exceeded 30 cm. Analysis of the model parameters showed that the estimation accuracy was not affected by participant’s height or gender. These results indicate that the proposed model has the potential to improve the feasibility of measuring and assessing CPF. Full article
(This article belongs to the Special Issue Wearable Sensors and Devices for Healthcare Applications)
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20 pages, 7169 KiB  
Article
Design and Development of a 5-Channel Arduino-Based Data Acquisition System (ABDAS) for Experimental Aerodynamics Research
by Antonio Vidal-Pardo and Santiago Pindado
Sensors 2018, 18(7), 2382; https://doi.org/10.3390/s18072382 - 22 Jul 2018
Cited by 21 | Viewed by 7810
Abstract
In this work, a new and low-cost Arduino-Based Data Acquisition System (ABDAS) for use in an aerodynamics lab is developed. Its design is simple and reliable. The accuracy of the system has been checked by being directly compared with a commercial and high [...] Read more.
In this work, a new and low-cost Arduino-Based Data Acquisition System (ABDAS) for use in an aerodynamics lab is developed. Its design is simple and reliable. The accuracy of the system has been checked by being directly compared with a commercial and high accuracy level hardware from National Instruments. Furthermore, ABDAS has been compared to the accredited calibration system in the IDR/UPM Institute, its measurements during this testing campaign being used to analyzed two different cup anemometer frequency determination procedures: counting pulses and the Fourier transform. The results indicate a more accurate transfer function of the cup anemometers when counting pulses procedure is used. Full article
(This article belongs to the Section Physical Sensors)
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9 pages, 19501 KiB  
Article
Polymer Based Whispering Gallery Mode Humidity Sensor
by Ann Britt Petermann, Thomas Hildebrandt, Uwe Morgner, Bernhard Wilhelm Roth and Merve Meinhardt-Wollweber
Sensors 2018, 18(7), 2383; https://doi.org/10.3390/s18072383 - 22 Jul 2018
Cited by 23 | Viewed by 4718
Abstract
Whispering gallery mode (WGM) resonators are versatile high sensitivity sensors, but applications regularly suffer from elaborate and expensive manufacturing and read-out. We have realized a simple and inexpensive concept for an all-polymer WGM sensor. Here, we evaluate its performance for relative humidity measurements [...] Read more.
Whispering gallery mode (WGM) resonators are versatile high sensitivity sensors, but applications regularly suffer from elaborate and expensive manufacturing and read-out. We have realized a simple and inexpensive concept for an all-polymer WGM sensor. Here, we evaluate its performance for relative humidity measurements demonstrating a sensitivity of 47 pm/% RH. Our results show the sensor concepts’ promising potential for use in real-life applications and environments. Full article
(This article belongs to the Special Issue State-of-the-Art Sensors Technology in Germany)
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10 pages, 2277 KiB  
Article
Self-Power Dynamic Sensor Based on Triboelectrification for Tilt of Direction and Angle
by Hyeonhee Roh, Inkyum Kim, Jinsoo Yu and Daewon Kim
Sensors 2018, 18(7), 2384; https://doi.org/10.3390/s18072384 - 22 Jul 2018
Cited by 9 | Viewed by 3643
Abstract
With the great development of the Internet of Things (IoT), the use of sensors have increased rapidly because of the importance in the connection between machines and people. A huge number of IoT sensors consume vast amounts of electrical power for stable operation [...] Read more.
With the great development of the Internet of Things (IoT), the use of sensors have increased rapidly because of the importance in the connection between machines and people. A huge number of IoT sensors consume vast amounts of electrical power for stable operation and they are also used for a wide range of applications. Therefore, sensors need to operate independently, sustainably, and wirelessly to improve their capabilities. In this paper, we propose an orientation and the tilt triboelectric sensor (OT-TES) as a self-powered active sensor, which can simultaneously sense the tilting direction and angle by using the two classical principles of triboelectrification and electrostatic induction. The OT-TES device consists of a rectangular acrylic box containing polytetrafluoroethylene (PTFE) balls moved by gravity. The output voltage and current were 2 V and 20 nA, respectively, with a PTFE ball and Al electrode. The multi-channel system was adopted for measuring the degree and direction of tilt by integrating the results of measured electrical signals from the eight electrodes. This OT-TES can be attached on the equipment for drones or divers to measure their stability. As a result, this proposed device is expected to expand the field of TES, as a sensor for sky and the underwater. Full article
(This article belongs to the Section Physical Sensors)
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25 pages, 6746 KiB  
Article
Passive RFID-Based Inventory of Traffic Signs on Roads and Urban Environments
by José Ramón García Oya, Rubén Martín Clemente, Eduardo Hidalgo Fort, Ramón González Carvajal and Fernando Muñoz Chavero
Sensors 2018, 18(7), 2385; https://doi.org/10.3390/s18072385 - 22 Jul 2018
Cited by 28 | Viewed by 7648
Abstract
This paper presents a system with location functionalities for the inventory of traffic signs based on passive RFID technology. The proposed system simplifies the current video-based techniques, whose requirements regarding visibility are difficult to meet in some scenarios, such as dense urban areas. [...] Read more.
This paper presents a system with location functionalities for the inventory of traffic signs based on passive RFID technology. The proposed system simplifies the current video-based techniques, whose requirements regarding visibility are difficult to meet in some scenarios, such as dense urban areas. In addition, the system can be easily extended to consider any other street facilities, such as dumpsters or traffic lights. Furthermore, the system can perform the inventory process at night and at a vehicle’s usual speed, thus avoiding interfering with the normal traffic flow of the road. Moreover, the proposed system exploits the benefits of the passive RFID technologies over active RFID, which are typically employed on inventory and vehicular routing applications. Since the performance of passive RFID is not obvious for the required distance ranges on these in-motion scenarios, this paper, as its main contribution, addresses the problem in two different ways, on the one hand theoretically, presenting a radio wave propagation model at theoretical and simulation level for these scenarios; and on the other hand experimentally, comparing passive and active RFID alternatives regarding costs, power consumption, distance ranges, collision problems, and ease of reconfiguration. Finally, the performance of the proposed on-board system is experimentally validated, testing its capabilities for inventory purposes. Full article
(This article belongs to the Section Sensor Networks)
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19 pages, 1334 KiB  
Article
Supplemental Boosting and Cascaded ConvNet Based Transfer Learning Structure for Fast Traffic Sign Detection in Unknown Application Scenes
by Chunsheng Liu, Shuang Li, Faliang Chang and Wenhui Dong
Sensors 2018, 18(7), 2386; https://doi.org/10.3390/s18072386 - 22 Jul 2018
Cited by 10 | Viewed by 3927
Abstract
With rapid calculation speed and relatively high accuracy, the AdaBoost-based detection framework has been successfully applied in some real applications of machine vision-based intelligent systems. The main shortcoming of the AdaBoost-based detection framework is that the off-line trained detector cannot be transfer retrained [...] Read more.
With rapid calculation speed and relatively high accuracy, the AdaBoost-based detection framework has been successfully applied in some real applications of machine vision-based intelligent systems. The main shortcoming of the AdaBoost-based detection framework is that the off-line trained detector cannot be transfer retrained to adapt to unknown application scenes. In this paper, a new transfer learning structure based on two novel methods of supplemental boosting and cascaded ConvNet is proposed to address this shortcoming. The supplemental boosting method is proposed to supplementally retrain an AdaBoost-based detector for the purpose of transferring a detector to adapt to unknown application scenes. The cascaded ConvNet is designed and attached to the end of the AdaBoost-based detector for improving the detection rate and collecting supplemental training samples. With the added supplemental training samples provided by the cascaded ConvNet, the AdaBoost-based detector can be retrained with the supplemental boosting method. The detector combined with the retrained boosted detector and cascaded ConvNet detector can achieve high accuracy and a short detection time. As a representative object detection problem in intelligent transportation systems, the traffic sign detection problem is chosen to show our method. Through experiments with the public datasets from different countries, we show that the proposed framework can quickly detect objects in unknown application scenes. Full article
(This article belongs to the Section Intelligent Sensors)
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15 pages, 2695 KiB  
Article
Determination of Optimal Heart Rate Variability Features Based on SVM-Recursive Feature Elimination for Cumulative Stress Monitoring Using ECG Sensor
by Dajeong Park, Miran Lee, Sunghee E. Park, Joon-Kyung Seong and Inchan Youn
Sensors 2018, 18(7), 2387; https://doi.org/10.3390/s18072387 - 23 Jul 2018
Cited by 27 | Viewed by 5777
Abstract
Routine stress monitoring in daily life can predict potentially serious health impacts. Effective stress monitoring in medical and healthcare fields is dependent upon accurate determination of stress-related features. In this study, we determined the optimal stress-related features for effective monitoring of cumulative stress. [...] Read more.
Routine stress monitoring in daily life can predict potentially serious health impacts. Effective stress monitoring in medical and healthcare fields is dependent upon accurate determination of stress-related features. In this study, we determined the optimal stress-related features for effective monitoring of cumulative stress. We first investigated the effects of short- and long-term stress on various heart rate variability (HRV) features using a rodent model. Subsequently, we determined an optimal HRV feature set using support vector machine-recursive feature elimination (SVM-RFE). Experimental results indicate that the HRV time domain features generally decrease under long-term stress, and the HRV frequency domain features have substantially significant differences under short-term stress. Further, an SVM classifier with a radial basis function kernel proved most accurate (93.11%) when using an optimal HRV feature set comprising the mean of R-R intervals (mRR), the standard deviation of R-R intervals (SDRR), and the coefficient of variance of R-R intervals (CVRR) as time domain features, and the normalized low frequency (nLF) and the normalized high frequency (nHF) as frequency domain features. Our findings indicate that the optimal HRV features identified in this study can effectively and efficiently detect stress. This knowledge facilitates development of in-facility and mobile healthcare system designs to support stress monitoring in daily life. Full article
(This article belongs to the Section Biosensors)
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14 pages, 21753 KiB  
Article
The Influence of Radial Undersampling Schemes on Compressed Sensing in Cardiac DTI
by Jianping Huang, Wenlong Song, Lihui Wang and Yuemin Zhu
Sensors 2018, 18(7), 2388; https://doi.org/10.3390/s18072388 - 23 Jul 2018
Cited by 3 | Viewed by 4333
Abstract
Diffusion tensor imaging (DTI) is known to suffer from long acquisition time, which greatly limits its practical and clinical use. Undersampling of k-space data provides an effective way to reduce the amount of data to acquire while maintaining image quality. Radial undersampling is [...] Read more.
Diffusion tensor imaging (DTI) is known to suffer from long acquisition time, which greatly limits its practical and clinical use. Undersampling of k-space data provides an effective way to reduce the amount of data to acquire while maintaining image quality. Radial undersampling is one of the most popular non-Cartesian k-space sampling schemes, since it has relatively lower sensitivity to motion than Cartesian trajectories, and artifacts from linear reconstruction are more noise-like. Therefore, radial imaging is a promising strategy of undersampling to accelerate acquisitions. The purpose of this study is to investigate various radial sampling schemes as well as reconstructions using compressed sensing (CS). In particular, we propose two randomly perturbed radial undersampling schemes: golden-angle and random angle. The proposed methods are compared with existing radial undersampling methods, including uniformity-angle, randomly perturbed uniformity-angle, golden-angle, and random angle. The results on both simulated and real human cardiac diffusion weighted (DW) images show that, for the same amount of k-space data, randomly sampling around a random radial line results in better reconstruction quality for DTI indices, such as fractional anisotropy (FA), mean diffusivities (MD), and that the randomly perturbed golden-angle undersampling yields the best results for cardiac CS-DTI image reconstruction. Full article
(This article belongs to the Section Physical Sensors)
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19 pages, 2239 KiB  
Article
ED-FNN: A New Deep Learning Algorithm to Detect Percentage of the Gait Cycle for Powered Prostheses
by Huong Thi Thu Vu, Felipe Gomez, Pierre Cherelle, Dirk Lefeber, Ann Nowé and Bram Vanderborght
Sensors 2018, 18(7), 2389; https://doi.org/10.3390/s18072389 - 23 Jul 2018
Cited by 69 | Viewed by 16844
Abstract
Throughout the last decade, a whole new generation of powered transtibial prostheses and exoskeletons has been developed. However, these technologies are limited by a gait phase detection which controls the wearable device as a function of the activities of the wearer. Consequently, gait [...] Read more.
Throughout the last decade, a whole new generation of powered transtibial prostheses and exoskeletons has been developed. However, these technologies are limited by a gait phase detection which controls the wearable device as a function of the activities of the wearer. Consequently, gait phase detection is considered to be of great importance, as achieving high detection accuracy will produce a more precise, stable, and safe rehabilitation device. In this paper, we propose a novel gait percent detection algorithm that can predict a full gait cycle discretised within a 1% interval. We called this algorithm an exponentially delayed fully connected neural network (ED-FNN). A dataset was obtained from seven healthy subjects that performed daily walking activities on the flat ground and a 15-degree slope. The signals were taken from only one inertial measurement unit (IMU) attached to the lower shank. The dataset was divided into training and validation datasets for every subject, and the mean square error (MSE) error between the model prediction and the real percentage of the gait was computed. An average MSE of 0.00522 was obtained for every subject in both training and validation sets, and an average MSE of 0.006 for the training set and 0.0116 for the validation set was obtained when combining all subjects’ signals together. Although our experiments were conducted in an offline setting, due to the forecasting capabilities of the ED-FNN, our system provides an opportunity to eliminate detection delays for real-time applications. Full article
(This article belongs to the Special Issue Assistance Robotics and Biosensors)
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22 pages, 22998 KiB  
Article
Watermarking Based on Compressive Sensing for Digital Speech Detection and Recovery
by Wenhuan Lu, Zonglei Chen, Ling Li, Xiaochun Cao, Jianguo Wei, Naixue Xiong, Jian Li and Jianwu Dang
Sensors 2018, 18(7), 2390; https://doi.org/10.3390/s18072390 - 23 Jul 2018
Cited by 22 | Viewed by 4996
Abstract
In this paper, a novel imperceptible, fragile and blind watermark scheme is proposed for speech tampering detection and self-recovery. The embedded watermark data for content recovery is calculated from the original discrete cosine transform (DCT) coefficients of host speech. The watermark information is [...] Read more.
In this paper, a novel imperceptible, fragile and blind watermark scheme is proposed for speech tampering detection and self-recovery. The embedded watermark data for content recovery is calculated from the original discrete cosine transform (DCT) coefficients of host speech. The watermark information is shared in a frames-group instead of stored in one frame. The scheme trades off between the data waste problem and the tampering coincidence problem. When a part of a watermarked speech signal is tampered with, one can accurately localize the tampered area, the watermark data in the area without any modification still can be extracted. Then, a compressive sensing technique is employed to retrieve the coefficients by exploiting the sparseness in the DCT domain. The smaller the tampered the area, the better quality of the recovered signal is. Experimental results show that the watermarked signal is imperceptible, and the recovered signal is intelligible for high tampering rates of up to 47.6%. A deep learning-based enhancement method is also proposed and implemented to increase the SNR of recovered speech signal. Full article
(This article belongs to the Special Issue Advances on Resources Management for Multi-Platform Infrastructures)
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21 pages, 1281 KiB  
Article
Staged Incentive and Punishment Mechanism for Mobile Crowd Sensing
by Dan Tao, Shan Zhong and Hong Luo
Sensors 2018, 18(7), 2391; https://doi.org/10.3390/s18072391 - 23 Jul 2018
Cited by 7 | Viewed by 4556
Abstract
Having an incentive mechanism is crucial for the recruitment of mobile users to participate in a sensing task and to ensure that participants provide high-quality sensing data. In this paper, we investigate a staged incentive and punishment mechanism for mobile crowd sensing. We [...] Read more.
Having an incentive mechanism is crucial for the recruitment of mobile users to participate in a sensing task and to ensure that participants provide high-quality sensing data. In this paper, we investigate a staged incentive and punishment mechanism for mobile crowd sensing. We first divide the incentive process into two stages: the recruiting stage and the sensing stage. In the recruiting stage, we introduce the payment incentive coefficient and design a Stackelberg-based game method. The participants can be recruited via game interaction. In the sensing stage, we propose a sensing data utility algorithm in the interaction. After the sensing task, the winners can be filtered out using data utility, which is affected by time–space correlation. In particular, the participants’ reputation accumulation can be carried out based on data utility, and a punishment mechanism is presented to reduce the waste of payment costs caused by malicious participants. Finally, we conduct an extensive study of our solution based on realistic data. Extensive experiments show that compared to the existing positive auction incentive mechanism (PAIM) and reverse auction incentive mechanism (RAIM), our proposed staged incentive mechanism (SIM) can effectively extend the incentive behavior from the recruiting stage to the sensing stage. It not only achieves being a real-time incentive in both the recruiting and sensing stages but also improves the utility of sensing data. Full article
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19 pages, 9095 KiB  
Article
Geometric Parameter Calibration for a Cable-Driven Parallel Robot Based on a Single One-Dimensional Laser Distance Sensor Measurement and Experimental Modeling
by XueJun Jin, Jinwoo Jung, Seong Young Ko, Eunpyo Choi, Jong-Oh Park and Chang-Sei Kim
Sensors 2018, 18(7), 2392; https://doi.org/10.3390/s18072392 - 23 Jul 2018
Cited by 33 | Viewed by 8100
Abstract
A cable-driven parallel robot has benefits of wide workspace, high payload, and high dynamic response owing to its light cable actuator utilization. For wide workspace applications, in particular, the body frame becomes large to cover the wide workspace that causes robot kinematic errors [...] Read more.
A cable-driven parallel robot has benefits of wide workspace, high payload, and high dynamic response owing to its light cable actuator utilization. For wide workspace applications, in particular, the body frame becomes large to cover the wide workspace that causes robot kinematic errors resulting from geometric uncertainty. However, appropriate sensors as well as inexpensive and easy calibration methods to measure the actual robot kinematic parameters are not currently available. Hence, we present a calibration sensor device and an auto-calibration methodology for the over-constrained cable-driven parallel robots using one-dimension laser distance sensors attached to the robot end-effector, to overcome the robot geometric uncertainty and to implement precise robot control. A novel calibration workflow with five phases—preparation, modeling, measuring, identification, and adjustment—is proposed. The proposed calibration algorithms cover the cable-driven parallel robot kinematics, as well as uncertainty modeling such as cable elongation and pulley kinematics. We performed extensive simulations and experiments to verify the performance of the suggested method using the MINI cable robot. The experimental results show that the kinematic parameters can be identified correctly with 0.92 mm accuracy, and the robot position control accuracy is increased by 58%. Finally, we verified that the developed calibration sensor devices and the calibration methodology are applicable to the massive-size cable-driven parallel robot system. Full article
(This article belongs to the Section Intelligent Sensors)
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10 pages, 2059 KiB  
Article
Cooperative Dynamic Game-Based Optimal Power Control in Wireless Sensor Network Powered by RF Energy
by Manxi Wang, Haitao Xu and Xianwei Zhou
Sensors 2018, 18(7), 2393; https://doi.org/10.3390/s18072393 - 23 Jul 2018
Cited by 6 | Viewed by 3858
Abstract
This paper focuses on optimal power control in wireless sensor networks powered by RF energy, under the simultaneous wireless information and power transfer (SWIFT) protocol, where the information and power can be transmitted at the same time. We aim to maximize the utility [...] Read more.
This paper focuses on optimal power control in wireless sensor networks powered by RF energy, under the simultaneous wireless information and power transfer (SWIFT) protocol, where the information and power can be transmitted at the same time. We aim to maximize the utility for each sensor through the optimal power control, considering the influences of both the SINR and the harvested energy. The utility maximization problem is formulated as a cooperative dynamic game of a given time duration. All the sensors cooperate together to control their transmission power to maximize the utility and agree to act cooperatively so that a team optimum can be achieved. As a result, a feedback Nash equilibrium solution for each sensor is given based on the dynamic programming theory. Simulation results verify the effectiveness of the proposed approach, by comparing the grand coalition solutions with the non-cooperative solutions. Full article
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19 pages, 444 KiB  
Article
A Multi-Server Two-Factor Authentication Scheme with Un-Traceability Using Elliptic Curve Cryptography
by Guosheng Xu, Shuming Qiu, Haseeb Ahmad, Guoai Xu, Yanhui Guo, Miao Zhang and Hong Xu
Sensors 2018, 18(7), 2394; https://doi.org/10.3390/s18072394 - 23 Jul 2018
Cited by 39 | Viewed by 5862
Abstract
To provide secure communication, the authentication-and-key-agreement scheme plays a vital role in multi-server environments, Internet of Things (IoT), wireless sensor networks (WSNs), etc. This scheme enables users and servers to negotiate for a common session initiation key. Our proposal first analyzes Amin et [...] Read more.
To provide secure communication, the authentication-and-key-agreement scheme plays a vital role in multi-server environments, Internet of Things (IoT), wireless sensor networks (WSNs), etc. This scheme enables users and servers to negotiate for a common session initiation key. Our proposal first analyzes Amin et al.’s authentication scheme based on RSA and proves that it cannot provide perfect forward secrecy and user un-traceability, and is susceptible to offline password guessing attack and key-compromise user impersonation attack. Secondly, we provide that Srinivas et al.’s multi-server authentication scheme is not secured against offline password guessing attack and key-compromise user impersonation attack, and is unable to ensure user un-traceability. To remedy such limitations and improve computational efficiency, we present a multi-server two-factor authentication scheme using elliptic curve cryptography (ECC). Subsequently, employing heuristic analysis and Burrows–Abadi–Needham logic (BAN-Logic) proof, it is proven that the presented scheme provides security against all known attacks, and in particular provides user un-traceability and perfect forward security. Finally, appropriate comparisons with prevalent works demonstrate the robustness and feasibility of the presented solution in multi-server environments. Full article
(This article belongs to the Section Internet of Things)
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10 pages, 2164 KiB  
Article
A Flexible Capacitive Pressure Sensor Based on Ionic Liquid
by Xiaofeng Yang, Yishou Wang and Xinlin Qing
Sensors 2018, 18(7), 2395; https://doi.org/10.3390/s18072395 - 23 Jul 2018
Cited by 52 | Viewed by 9870
Abstract
A flexible microfluidic super-capacitive pressure sensor is developed to measure the surface pressure of a complex structure. The innovative sensor contains a filter paper filled with ionic liquid, and coated with two indium tin oxide polyethylene terephthalate (ITO-PET) films on the top and [...] Read more.
A flexible microfluidic super-capacitive pressure sensor is developed to measure the surface pressure of a complex structure. The innovative sensor contains a filter paper filled with ionic liquid, and coated with two indium tin oxide polyethylene terephthalate (ITO-PET) films on the top and bottom, respectively. When external pressure is applied on the top ITO-PET film of the sensor mounted on the surface of an aircraft, the capacitance between the two ITO-PET films will change because of the deformation of the top ITO-PET film. The external pressure will be determined based on the change of the capacitance. Compared to the traditional pressure sensor, the developed sensor provides a high sensitivity of up to 178.5 nF/KPa and rapid dynamic responses for pressure measurement. Meanwhile, experiments are also conducted to study the influence of the thickness of the sensing film, sensing area, temperature, and humidity. Full article
(This article belongs to the Section Physical Sensors)
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9 pages, 2839 KiB  
Article
Intensity Demodulated Refractive Index Sensor Based on Front-Tapered Single-Mode-Multimode-Single-Mode Fiber Structure
by Jing Kang, Jiuru Yang, Xudong Zhang, Chunyu Liu and Lu Wang
Sensors 2018, 18(7), 2396; https://doi.org/10.3390/s18072396 - 23 Jul 2018
Cited by 23 | Viewed by 4279
Abstract
A novel intensity demodulated refractive index (RI) sensor is theoretically and experimentally demonstrated based on the front-tapered single-mode-multimode-single-mode (FT-SMS) fiber structure. The front taper is fabricated in a section of multimode fiber by flame-heated drawing technique. The intensity feature in the taper area [...] Read more.
A novel intensity demodulated refractive index (RI) sensor is theoretically and experimentally demonstrated based on the front-tapered single-mode-multimode-single-mode (FT-SMS) fiber structure. The front taper is fabricated in a section of multimode fiber by flame-heated drawing technique. The intensity feature in the taper area is analyzed through the beam propagation method and the comprehensive tests are then conducted in terms of RI and temperature. The experimental results show that, in FT-SMS, the relative sensitivity is −342.815 dB/RIU in the range of 1.33~1.37. The corresponding resolution reaches 2.92 × 10−5 RIU, which is more than four times higher than that in wavelength demodulation. The temperature sensitivity is 0.307 dB/°C and the measurement error from cross-sensitivity is less than 2 × 10−4. In addition, fabricated RI sensor presents high stability in terms of wavelength (±0.045 nm) and intensity (±0.386 dB) within 2 h of continuous operation. Full article
(This article belongs to the Section Physical Sensors)
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14 pages, 5115 KiB  
Article
Detection of Broken Strands of Transmission Line Conductors Using Fiber Bragg Grating Sensors
by Long Zhao, Xinbo Huang, Jianyuan Jia, Yongcan Zhu and Wen Cao
Sensors 2018, 18(7), 2397; https://doi.org/10.3390/s18072397 - 23 Jul 2018
Cited by 27 | Viewed by 6666
Abstract
Transmission lines are affected by Aeolian vibration, which causes strands to break and eventually causes an entire line to break. In this paper, a method for monitoring strand breaking based on modal identification is proposed. First, the natural frequency variation of a conductor [...] Read more.
Transmission lines are affected by Aeolian vibration, which causes strands to break and eventually causes an entire line to break. In this paper, a method for monitoring strand breaking based on modal identification is proposed. First, the natural frequency variation of a conductor caused by strand breakage is analyzed, and a modal experiment of the LGJ-95/15 conductor is conducted. The measurement results show that the natural frequencies of the conductor decrease with an increasing number of broken strands. Next, a monitoring system incorporating a fiber Bragg grating (FBG)-based accelerometer is designed in detail. The FBG sensor is mounted on the conductor to measure the vibration signal. A wind speed sensor is used to measure the wind speed signal and is installed on the tower. An analyzer is also installed on the tower to calculate the natural frequencies, and the data are sent to the monitoring center via 3G. Finally, a monitoring system is tested on a 110 kV experimental transmission line, and the short-time Fourier transform (STFT) method and stochastic subspace identification (SSI) method are used to identify the natural frequencies of the conductor vibration. The experimental results show that SSI analysis provides a higher precision than does STFT and can extract the natural frequency under various wind speeds as an effective basis for discriminating between broken strands. Full article
(This article belongs to the Special Issue Optical Waveguide Based Sensors)
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22 pages, 896 KiB  
Article
Impact of Node Speed on Energy-Constrained Opportunistic Internet-of-Things with Wireless Power Transfer
by Seung-Woo Ko and Seong-Lyun Kim
Sensors 2018, 18(7), 2398; https://doi.org/10.3390/s18072398 - 23 Jul 2018
Cited by 10 | Viewed by 4640
Abstract
Wireless power transfer (WPT) is a promising technology to realize the vision of Internet-of-Things (IoT) by powering energy-hungry IoT nodes by electromagnetic waves, overcoming the difficulty in battery recharging for massive numbers of nodes. Specifically, wireless charging stations (WCS) are deployed to transfer [...] Read more.
Wireless power transfer (WPT) is a promising technology to realize the vision of Internet-of-Things (IoT) by powering energy-hungry IoT nodes by electromagnetic waves, overcoming the difficulty in battery recharging for massive numbers of nodes. Specifically, wireless charging stations (WCS) are deployed to transfer energy wirelessly to IoT nodes in the charging coverage. However, the coverage is restricted due to the limited hardware capability and safety issue, making mobile nodes have different battery charging patterns depending on their moving speeds. For example, slow moving nodes outside the coverage resort to waiting for energy charging from WCSs for a long time while those inside the coverage consistently recharge their batteries. On the other hand, fast moving nodes are able to receive energy within a relatively short waiting time. This paper investigates the above impact of node speed on energy provision and the resultant throughput of energy-constrained opportunistic IoT networks when data exchange between nodes are constrained by their intermittent connections as well as the levels of remaining energy. To this end, we design a two-dimensional Markov chain of which the state dimensions represent remaining energy and distance to the nearest WCS normalized by node speed, respectively. Solving this enables providing the following three insights. First, faster node speed makes the inter-meeting time between a node and a WCS shorter, leading to more frequent energy supply and higher throughput. Second, the above effect of node speed becomes marginal as the battery capacity increases. Finally, as nodes are more densely deployed, the throughput becomes scaling with the density ratio between mobiles and WCSs but independent of node speed, meaning that the throughput improvement from node speed disappears in dense networks. The results provide useful guidelines for IoT network provisioning and planning to achieve the maximum throughput performance given mobile environments. Full article
(This article belongs to the Special Issue Green, Energy-Efficient and Sustainable Networks)
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22 pages, 8784 KiB  
Article
Voiceprint Identification for Limited Dataset Using the Deep Migration Hybrid Model Based on Transfer Learning
by Cunwei Sun, Yuxin Yang, Chang Wen, Kai Xie and Fangqing Wen
Sensors 2018, 18(7), 2399; https://doi.org/10.3390/s18072399 - 23 Jul 2018
Cited by 39 | Viewed by 7440
Abstract
The convolutional neural network (CNN) has made great strides in the area of voiceprint recognition; but it needs a huge number of data samples to train a deep neural network. In practice, it is too difficult to get a large number of training [...] Read more.
The convolutional neural network (CNN) has made great strides in the area of voiceprint recognition; but it needs a huge number of data samples to train a deep neural network. In practice, it is too difficult to get a large number of training samples, and it cannot achieve a better convergence state due to the limited dataset. In order to solve this question, a new method using a deep migration hybrid model is put forward, which makes it easier to realize voiceprint recognition for small samples. Firstly, it uses Transfer Learning to transfer the trained network from the big sample voiceprint dataset to our limited voiceprint dataset for the further training. Fully-connected layers of a pre-training model are replaced by restricted Boltzmann machine layers. Secondly, the approach of Data Augmentation is adopted to increase the number of voiceprint datasets. Finally, we introduce fast batch normalization algorithms to improve the speed of the network convergence and shorten the training time. Our new voiceprint recognition approach uses the TLCNN-RBM (convolutional neural network mixed restricted Boltzmann machine based on transfer learning) model, which is the deep migration hybrid model that is used to achieve an average accuracy of over 97%, which is higher than that when using either CNN or the TL-CNN network (convolutional neural network based on transfer learning). Thus, an effective method for a small sample of voiceprint recognition has been provided. Full article
(This article belongs to the Special Issue Artificial Intelligence and Machine Learning in Sensors Networks)
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21 pages, 47301 KiB  
Article
Integrity and Collaboration in Dynamic Sensor Networks
by Steffen Schön, Claus Brenner, Hamza Alkhatib, Max Coenen, Hani Dbouk, Nicolas Garcia-Fernandez, Colin Fischer, Christian Heipke, Katja Lohmann, Ingo Neumann, Uyen Nguyen, Jens-André Paffenholz, Torben Peters, Franz Rottensteiner, Julia Schachtschneider, Monika Sester, Ligang Sun, Sören Vogel, Raphael Voges and Bernardo Wagner
Sensors 2018, 18(7), 2400; https://doi.org/10.3390/s18072400 - 23 Jul 2018
Cited by 32 | Viewed by 9332
Abstract
Global Navigation Satellite Systems (GNSS) deliver absolute position and velocity, as well as time information (P, V, T). However, in urban areas, the GNSS navigation performance is restricted due to signal obstructions and multipath. This is especially true for applications dealing with highly [...] Read more.
Global Navigation Satellite Systems (GNSS) deliver absolute position and velocity, as well as time information (P, V, T). However, in urban areas, the GNSS navigation performance is restricted due to signal obstructions and multipath. This is especially true for applications dealing with highly automatic or even autonomous driving. Subsequently, multi-sensor platforms including laser scanners and cameras, as well as map data are used to enhance the navigation performance, namely in accuracy, integrity, continuity and availability. Although well-established procedures for integrity monitoring exist for aircraft navigation, for sensors and fusion algorithms used in automotive navigation, these concepts are still lacking. The research training group i.c.sens, integrity and collaboration in dynamic sensor networks, aims to fill this gap and to contribute to relevant topics. This includes the definition of alternative integrity concepts for space and time based on set theory and interval mathematics, establishing new types of maps that report on the trustworthiness of the represented information, as well as taking advantage of collaboration by improved filters incorporating person and object tracking. In this paper, we describe our approach and summarize the preliminary results. Full article
(This article belongs to the Special Issue GNSS and Fusion with Other Sensors)
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9 pages, 2692 KiB  
Article
Characteristics of Surface Acoustic Wave Sensors with Nanoparticles Embedded in Polymer Sensitive Layers for VOC Detection
by Cristian Viespe and Dana Miu
Sensors 2018, 18(7), 2401; https://doi.org/10.3390/s18072401 - 23 Jul 2018
Cited by 28 | Viewed by 4819
Abstract
Surface Acoustic Wave (SAW) sensors with several types of polymer sensing films, containing embedded Fe3O4 nanoparticles (NPs) with various dimensions and concentrations, were studied. A sensor with a sensing film consisting of the polymer alone was used for comparison. NPs [...] Read more.
Surface Acoustic Wave (SAW) sensors with several types of polymer sensing films, containing embedded Fe3O4 nanoparticles (NPs) with various dimensions and concentrations, were studied. A sensor with a sensing film consisting of the polymer alone was used for comparison. NPs with a mean diameter of 7 nm were produced by laser ablation with 5 ns pulse durations, and NPs with 13 nm diameters were obtained with a laser having 10 ps pulse durations. The properties of the Surface Acoustic Wave sensors with such sensing films were analyzed. Their response (frequency shift, sensitivity, noise and response time) to three different volatile organic components (VOCs) at various concentrations were compared with one another. The frequency shift and sensitivity increased with increasing NP concentration in the polymer for a given NP dimension and with decreasing NP diameter for a given concentration. The best results were obtained for the smallest NPs used. The SAW sensor containing 7 nm NPs had a limit of detection (LOD) of 65 ppm (almost five times better than the sensor with polymer alone), and a response time of about 9 s for ethanol. Full article
(This article belongs to the Section Chemical Sensors)
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