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Sensors, Volume 15, Issue 3 (March 2015) , Pages 4605-7083

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Open AccessArticle
A Hybrid PCA-CART-MARS-Based Prognostic Approach of the Remaining Useful Life for Aircraft Engines
Sensors 2015, 15(3), 7062-7083; https://doi.org/10.3390/s150307062
Received: 18 January 2015 / Revised: 24 February 2015 / Accepted: 6 March 2015 / Published: 23 March 2015
Cited by 13 | Viewed by 2734 | PDF Full-text (1934 KB) | HTML Full-text | XML Full-text
Abstract
Prognostics is an engineering discipline that predicts the future health of a system. In this research work, a data-driven approach for prognostics is proposed. Indeed, the present paper describes a data-driven hybrid model for the successful prediction of the remaining useful life of [...] Read more.
Prognostics is an engineering discipline that predicts the future health of a system. In this research work, a data-driven approach for prognostics is proposed. Indeed, the present paper describes a data-driven hybrid model for the successful prediction of the remaining useful life of aircraft engines. The approach combines the multivariate adaptive regression splines (MARS) technique with the principal component analysis (PCA), dendrograms and classification and regression trees (CARTs). Elements extracted from sensor signals are used to train this hybrid model, representing different levels of health for aircraft engines. In this way, this hybrid algorithm is used to predict the trends of these elements. Based on this fitting, one can determine the future health state of a system and estimate its remaining useful life (RUL) with accuracy. To evaluate the proposed approach, a test was carried out using aircraft engine signals collected from physical sensors (temperature, pressure, speed, fuel flow, etc.). Simulation results show that the PCA-CART-MARS-based approach can forecast faults long before they occur and can predict the RUL. The proposed hybrid model presents as its main advantage the fact that it does not require information about the previous operation states of the input variables of the engine. The performance of this model was compared with those obtained by other benchmark models (multivariate linear regression and artificial neural networks) also applied in recent years for the modeling of remaining useful life. Therefore, the PCA-CART-MARS-based approach is very promising in the field of prognostics of the RUL for aircraft engines. Full article
(This article belongs to the Section Physical Sensors)
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Open AccessArticle
A Robust Trust Establishment Scheme for Wireless Sensor Networks
Sensors 2015, 15(3), 7040-7061; https://doi.org/10.3390/s150307040
Received: 21 October 2014 / Revised: 16 March 2015 / Accepted: 17 March 2015 / Published: 23 March 2015
Cited by 21 | Viewed by 2129 | PDF Full-text (864 KB) | HTML Full-text | XML Full-text
Abstract
Security techniques like cryptography and authentication can fail to protect a network once a node is compromised. Hence, trust establishment continuously monitors and evaluates node behavior to detect malicious and compromised nodes. However, just like other security schemes, trust establishment is also vulnerable [...] Read more.
Security techniques like cryptography and authentication can fail to protect a network once a node is compromised. Hence, trust establishment continuously monitors and evaluates node behavior to detect malicious and compromised nodes. However, just like other security schemes, trust establishment is also vulnerable to attack. Moreover, malicious nodes might misbehave intelligently to trick trust establishment schemes. Unfortunately, attack-resistance and robustness issues with trust establishment schemes have not received much attention from the research community. Considering the vulnerability of trust establishment to different attacks and the unique features of sensor nodes in wireless sensor networks, we propose a lightweight and robust trust establishment scheme. The proposed trust scheme is lightweight thanks to a simple trust estimation method. The comprehensiveness and flexibility of the proposed trust estimation scheme make it robust against different types of attack and misbehavior. Performance evaluation under different types of misbehavior and on-off attacks shows that the detection rate of the proposed trust mechanism is higher and more stable compared to other trust mechanisms. Full article
(This article belongs to the Section Sensor Networks)
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Open AccessArticle
Improving the Precision and Speed of Euler Angles Computation from Low-Cost Rotation Sensor Data
Sensors 2015, 15(3), 7016-7039; https://doi.org/10.3390/s150307016
Received: 5 January 2015 / Revised: 19 February 2015 / Accepted: 17 March 2015 / Published: 23 March 2015
Cited by 24 | Viewed by 3877 | PDF Full-text (6395 KB) | HTML Full-text | XML Full-text
Abstract
This article compares three different algorithms used to compute Euler angles from data obtained by the angular rate sensor (e.g., MEMS gyroscope)—the algorithms based on a rotational matrix, on transforming angular velocity to time derivations of the Euler angles and on unit quaternion [...] Read more.
This article compares three different algorithms used to compute Euler angles from data obtained by the angular rate sensor (e.g., MEMS gyroscope)—the algorithms based on a rotational matrix, on transforming angular velocity to time derivations of the Euler angles and on unit quaternion expressing rotation. Algorithms are compared by their computational efficiency and accuracy of Euler angles estimation. If attitude of the object is computed only from data obtained by the gyroscope, the quaternion-based algorithm seems to be most suitable (having similar accuracy as the matrix-based algorithm, but taking approx. 30% less clock cycles on the 8-bit microcomputer). Integration of the Euler angles’ time derivations has a singularity, therefore is not accurate at full range of object’s attitude. Since the error in every real gyroscope system tends to increase with time due to its offset and thermal drift, we also propose some measures based on compensation by additional sensors (a magnetic compass and accelerometer). Vector data of mentioned secondary sensors has to be transformed into the inertial frame of reference. While transformation of the vector by the matrix is slightly faster than doing the same by quaternion, the compensated sensor system utilizing a matrix-based algorithm can be approximately 10% faster than the system utilizing quaternions (depending on implementation and hardware). Full article
(This article belongs to the Special Issue Modeling, Testing and Reliability Issues in MEMS Engineering)
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Open AccessArticle
Degradation Prediction Model Based on a Neural Network with Dynamic Windows
Sensors 2015, 15(3), 6996-7015; https://doi.org/10.3390/s150306996
Received: 7 January 2015 / Revised: 1 March 2015 / Accepted: 13 March 2015 / Published: 23 March 2015
Cited by 6 | Viewed by 2317 | PDF Full-text (1297 KB) | HTML Full-text | XML Full-text
Abstract
Tracking degradation of mechanical components is very critical for effective maintenance decision making. Remaining useful life (RUL) estimation is a widely used form of degradation prediction. RUL prediction methods when enough run-to-failure condition monitoring data can be used have been fully researched, but [...] Read more.
Tracking degradation of mechanical components is very critical for effective maintenance decision making. Remaining useful life (RUL) estimation is a widely used form of degradation prediction. RUL prediction methods when enough run-to-failure condition monitoring data can be used have been fully researched, but for some high reliability components, it is very difficult to collect run-to-failure condition monitoring data, i.e., from normal to failure. Only a certain number of condition indicators in certain period can be used to estimate RUL. In addition, some existing prediction methods have problems which block RUL estimation due to poor extrapolability. The predicted value converges to a certain constant or fluctuates in certain range. Moreover, the fluctuant condition features also have bad effects on prediction. In order to solve these dilemmas, this paper proposes a RUL prediction model based on neural network with dynamic windows. This model mainly consists of three steps: window size determination by increasing rate, change point detection and rolling prediction. The proposed method has two dominant strengths. One is that the proposed approach does not need to assume the degradation trajectory is subject to a certain distribution. The other is it can adapt to variation of degradation indicators which greatly benefits RUL prediction. Finally, the performance of the proposed RUL prediction model is validated by real field data and simulation data. Full article
(This article belongs to the Section Physical Sensors)
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Open AccessReview
The Application of Biomedical Engineering Techniques to the Diagnosis and Management of Tropical Diseases: A Review
Sensors 2015, 15(3), 6947-6995; https://doi.org/10.3390/s150306947
Received: 7 August 2014 / Revised: 5 December 2014 / Accepted: 7 January 2015 / Published: 23 March 2015
Cited by 11 | Viewed by 4050 | PDF Full-text (3030 KB) | HTML Full-text | XML Full-text
Abstract
This paper reviews a number of biomedical engineering approaches to help aid in the detection and treatment of tropical diseases such as dengue, malaria, cholera, schistosomiasis, lymphatic filariasis, ebola, leprosy, leishmaniasis, and American trypanosomiasis (Chagas). Many different forms of non-invasive approaches such as [...] Read more.
This paper reviews a number of biomedical engineering approaches to help aid in the detection and treatment of tropical diseases such as dengue, malaria, cholera, schistosomiasis, lymphatic filariasis, ebola, leprosy, leishmaniasis, and American trypanosomiasis (Chagas). Many different forms of non-invasive approaches such as ultrasound, echocardiography and electrocardiography, bioelectrical impedance, optical detection, simplified and rapid serological tests such as lab-on-chip and micro-/nano-fluidic platforms and medical support systems such as artificial intelligence clinical support systems are discussed. The paper also reviewed the novel clinical diagnosis and management systems using artificial intelligence and bioelectrical impedance techniques for dengue clinical applications. Full article
(This article belongs to the Section Biosensors)
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Open AccessArticle
Bayesian Deconvolution for Angular Super-Resolution in Forward-Looking Scanning Radar
Sensors 2015, 15(3), 6924-6946; https://doi.org/10.3390/s150306924
Received: 16 January 2015 / Revised: 17 March 2015 / Accepted: 17 March 2015 / Published: 23 March 2015
Cited by 32 | Viewed by 2349 | PDF Full-text (7664 KB) | HTML Full-text | XML Full-text
Abstract
Scanning radar is of notable importance for ground surveillance, terrain mapping and disaster rescue. However, the angular resolution of a scanning radar image is poor compared to the achievable range resolution. This paper presents a deconvolution algorithm for angular super-resolution in scanning radar [...] Read more.
Scanning radar is of notable importance for ground surveillance, terrain mapping and disaster rescue. However, the angular resolution of a scanning radar image is poor compared to the achievable range resolution. This paper presents a deconvolution algorithm for angular super-resolution in scanning radar based on Bayesian theory, which states that the angular super-resolution can be realized by solving the corresponding deconvolution problem with the maximum a posteriori (MAP) criterion. The algorithm considers that the noise is composed of two mutually independent parts, i.e., a Gaussian signal-independent component and a Poisson signal-dependent component. In addition, the Laplace distribution is used to represent the prior information about the targets under the assumption that the radar image of interest can be represented by the dominant scatters in the scene. Experimental results demonstrate that the proposed deconvolution algorithm has higher precision for angular super-resolution compared with the conventional algorithms, such as the Tikhonov regularization algorithm, the Wiener filter and the Richardson–Lucy algorithm. Full article
(This article belongs to the Section Remote Sensors, Control, and Telemetry)
Open AccessArticle
Radar Imaging of Non-Uniformly Rotating Targets via a Novel Approach for Multi-Component AM-FM Signal Parameter Estimation
Sensors 2015, 15(3), 6905-6923; https://doi.org/10.3390/s150306905
Received: 30 January 2015 / Revised: 9 March 2015 / Accepted: 17 March 2015 / Published: 23 March 2015
Cited by 3 | Viewed by 1993 | PDF Full-text (771 KB) | HTML Full-text | XML Full-text
Abstract
A novel radar imaging approach for non-uniformly rotating targets is proposed in this study. It is assumed that the maneuverability of the non-cooperative target is severe, and the received signal in a range cell can be modeled as multi-component amplitude-modulated and frequency-modulated (AM-FM) [...] Read more.
A novel radar imaging approach for non-uniformly rotating targets is proposed in this study. It is assumed that the maneuverability of the non-cooperative target is severe, and the received signal in a range cell can be modeled as multi-component amplitude-modulated and frequency-modulated (AM-FM) signals after motion compensation. Then, the modified version of Chirplet decomposition (MCD) based on the integrated high order ambiguity function (IHAF) is presented for the parameter estimation of AM-FM signals, and the corresponding high quality instantaneous ISAR images can be obtained from the estimated parameters. Compared with the MCD algorithm based on the generalized cubic phase function (GCPF) in the authors’ previous paper, the novel algorithm presented in this paper is more accurate and efficient, and the results with simulated and real data demonstrate the superiority of the proposed method. Full article
(This article belongs to the Section Remote Sensors, Control, and Telemetry)
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Open AccessArticle
A Novel Abandoned Object Detection System Based on Three-Dimensional Image Information
Sensors 2015, 15(3), 6885-6904; https://doi.org/10.3390/s150306885
Received: 25 November 2014 / Revised: 11 March 2015 / Accepted: 12 March 2015 / Published: 23 March 2015
Cited by 11 | Viewed by 2698 | PDF Full-text (2439 KB) | HTML Full-text | XML Full-text
Abstract
A new idea of an abandoned object detection system for road traffic surveillance systems based on three-dimensional image information is proposed in this paper to prevent traffic accidents. A novel Binocular Information Reconstruction and Recognition (BIRR) algorithm is presented to implement the new [...] Read more.
A new idea of an abandoned object detection system for road traffic surveillance systems based on three-dimensional image information is proposed in this paper to prevent traffic accidents. A novel Binocular Information Reconstruction and Recognition (BIRR) algorithm is presented to implement the new idea. As initial detection, suspected abandoned objects are detected by the proposed static foreground region segmentation algorithm based on surveillance video from a monocular camera. After detection of suspected abandoned objects, three-dimensional (3D) information of the suspected abandoned object is reconstructed by the proposed theory about 3D object information reconstruction with images from a binocular camera. To determine whether the detected object is hazardous to normal road traffic, road plane equation and height of suspected-abandoned object are calculated based on the three-dimensional information. Experimental results show that this system implements fast detection of abandoned objects and this abandoned object system can be used for road traffic monitoring and public area surveillance. Full article
(This article belongs to the Section Physical Sensors)
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Open AccessArticle
A CMOS Pressure Sensor Tag Chip for Passive Wireless Applications
Sensors 2015, 15(3), 6872-6884; https://doi.org/10.3390/s150306872
Received: 27 November 2014 / Revised: 8 March 2015 / Accepted: 9 March 2015 / Published: 23 March 2015
Cited by 12 | Viewed by 2510 | PDF Full-text (1008 KB) | HTML Full-text | XML Full-text
Abstract
This paper presents a novel monolithic pressure sensor tag for passive wireless applications. The proposed pressure sensor tag is based on an ultra-high frequency RFID system. The pressure sensor element is implemented in the 0.18 µm CMOS process and the membrane gap is [...] Read more.
This paper presents a novel monolithic pressure sensor tag for passive wireless applications. The proposed pressure sensor tag is based on an ultra-high frequency RFID system. The pressure sensor element is implemented in the 0.18 µm CMOS process and the membrane gap is formed by sacrificial layer release, resulting in a sensitivity of 1.2 fF/kPa within the range from 0 to 600 kPa. A three-stage rectifier adopts a chain of auxiliary floating rectifier cells to boost the gate voltage of the switching transistors, resulting in a power conversion efficiency of 53% at the low input power of −20 dBm. The capacitive sensor interface, using phase-locked loop archietcture, employs fully-digital blocks, which results in a 7.4 bits resolution and 0.8 µW power dissipation at 0.8 V supply voltage. The proposed passive wireless pressure sensor tag costs a total 3.2 µW power dissipation. Full article
(This article belongs to the Section Physical Sensors)
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Open AccessArticle
Global Coverage Measurement Planning Strategies for Mobile Robots Equipped with a Remote Gas Sensor
Sensors 2015, 15(3), 6845-6871; https://doi.org/10.3390/s150306845
Received: 24 November 2014 / Revised: 13 February 2015 / Accepted: 25 February 2015 / Published: 20 March 2015
Cited by 8 | Viewed by 3322 | PDF Full-text (7652 KB) | HTML Full-text | XML Full-text
Abstract
The problem of gas detection is relevant to many real-world applications, such as leak detection in industrial settings and landfill monitoring. In this paper, we address the problem of gas detection in large areas with a mobile robotic platform equipped with a remote [...] Read more.
The problem of gas detection is relevant to many real-world applications, such as leak detection in industrial settings and landfill monitoring. In this paper, we address the problem of gas detection in large areas with a mobile robotic platform equipped with a remote gas sensor. We propose an algorithm that leverages a novel method based on convex relaxation for quickly solving sensor placement problems, and for generating an efficient exploration plan for the robot. To demonstrate the applicability of our method to real-world environments, we performed a large number of experimental trials, both on randomly generated maps and on the map of a real environment. Our approach proves to be highly efficient in terms of computational requirements and to provide nearly-optimal solutions. Full article
(This article belongs to the Section Physical Sensors)
Open AccessArticle
Open Hardware: A Role to Play in Wireless Sensor Networks?
Sensors 2015, 15(3), 6818-6844; https://doi.org/10.3390/s150306818
Received: 30 October 2014 / Revised: 26 February 2015 / Accepted: 26 February 2015 / Published: 20 March 2015
Cited by 53 | Viewed by 3703 | PDF Full-text (1746 KB) | HTML Full-text | XML Full-text
Abstract
The concept of the Internet of Things is rapidly becoming a reality, with many applications being deployed within industrial and consumer sectors. At the ‘thing’ level—devices and inter-device network communication—the core technical building blocks are generally the same as those found in wireless [...] Read more.
The concept of the Internet of Things is rapidly becoming a reality, with many applications being deployed within industrial and consumer sectors. At the ‘thing’ level—devices and inter-device network communication—the core technical building blocks are generally the same as those found in wireless sensor network implementations. For the Internet of Things to continue growing, we need more plentiful resources for building intelligent devices and sensor networks. Unfortunately, current commercial devices, e.g., sensor nodes and network gateways, tend to be expensive and proprietary, which presents a barrier to entry and arguably slows down further development. There are, however, an increasing number of open embedded platforms available and also a wide selection of off-the-shelf components that can quickly and easily be built into device and network gateway solutions. The question is whether these solutions measure up to built-for-purpose devices. In the paper, we provide a comparison of existing built-for-purpose devices against open source devices. For comparison, we have also designed and rapidly prototyped a sensor node based on off-the-shelf components. We show that these devices compare favorably to built-for-purpose devices in terms of performance, power and cost. Using open platforms and off-the-shelf components would allow more developers to build intelligent devices and sensor networks, which could result in a better overall development ecosystem, lower barriers to entry and rapid growth in the number of IoT applications. Full article
(This article belongs to the Special Issue Wireless Sensor Networks and the Internet of Things)
Open AccessArticle
Broadband and High Sensitive Time-of-Flight Diffraction Ultrasonic Transducers Based on PMNT/Epoxy 1–3 Piezoelectric Composite
Sensors 2015, 15(3), 6807-6817; https://doi.org/10.3390/s150306807
Received: 4 January 2015 / Revised: 9 March 2015 / Accepted: 18 March 2015 / Published: 19 March 2015
Cited by 5 | Viewed by 3093 | PDF Full-text (1911 KB) | HTML Full-text | XML Full-text
Abstract
5–6 MHz PMNT/epoxy 1–3 composites were prepared by a modified dice-and-fill method. They exhibit excellent properties for ultrasonic transducer applications, such as ultrahigh thickness electromechanical coupling coefficient kt (85.7%), large piezoelectric coefficient d33 (1209 pC/N), and relatively low acoustic impedance Z [...] Read more.
5–6 MHz PMNT/epoxy 1–3 composites were prepared by a modified dice-and-fill method. They exhibit excellent properties for ultrasonic transducer applications, such as ultrahigh thickness electromechanical coupling coefficient kt (85.7%), large piezoelectric coefficient d33 (1209 pC/N), and relatively low acoustic impedance Z (1.82 × 107 kg/(m2·s)). Besides, two types of Time-of-Flight Diffraction (TOFD) ultrasonic transducers have been designed, fabricated, and characterized, which have different matching layer schemes with the acoustic impedance of 4.8 and 5.7 × 106 kg/(m2·s), respectively. In the detection on a backwall of 12.7 mm polystyrene, the former exhibits higher detectivity, the relative pulse-echo sensitivity and −6 dB relative bandwidth are −21.93 dB and 102.7%, respectively, while the later exhibits broader bandwidth, the relative pulse-echo sensitivity and −6 dB relative bandwidth are −24.08 dB and 117.3%, respectively. These TOFD ultrasonic transducers based on PMNT/epoxy 1–3 composite exhibit considerably improved performance over the commercial PZT/epoxy 1–3 composite TOFD ultrasonic transducer. Full article
(This article belongs to the Special Issue Acoustic Waveguide Sensors)
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Open AccessArticle
Development of a Microfluidic-Based Optical Sensing Device for Label-Free Detection of Circulating Tumor Cells (CTCs) Through Their Lactic Acid Metabolism
Sensors 2015, 15(3), 6789-6806; https://doi.org/10.3390/s150306789
Received: 30 January 2015 / Revised: 2 March 2015 / Accepted: 17 March 2015 / Published: 19 March 2015
Cited by 11 | Viewed by 3450 | PDF Full-text (4143 KB) | HTML Full-text | XML Full-text
Abstract
This study reports a microfluidic-based optical sensing device for label-free detection of circulating tumor cells (CTCs), a rare cell species in blood circulation. Based on the metabolic features of cancer cells, live CTCs can be quantified indirectly through their lactic acid production. Compared [...] Read more.
This study reports a microfluidic-based optical sensing device for label-free detection of circulating tumor cells (CTCs), a rare cell species in blood circulation. Based on the metabolic features of cancer cells, live CTCs can be quantified indirectly through their lactic acid production. Compared with the conventional schemes for CTC detection, this label-free approach could prevent the biological bias due to the heterogeneity of the surface antigens on cancer cells. In this study, a microfluidic device was proposed to generate uniform water-in-oil cell-encapsulating micro-droplets, followed by the fluorescence-based optical detection of lactic acid produced within the micro-droplets. To test its feasibility to quantify cancer cells, experiments were carried out. Results showed that the detection signals were proportional to the number of cancer cells within the micro-droplets, whereas such signals were insensitive to the existence and number of leukocytes within. To further demonstrate its feasibility for cancer cell detection, the cancer cells with known cell number in a cell suspension was detected based on the method. Results revealed that there was no significant difference between the detected number and the real number of cancer cells. As a whole, the proposed method opens up a new route to detect live CTCs in a label-free manner. Full article
(This article belongs to the Special Issue On-Chip Sensors)
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Open AccessArticle
Human Detection Based on the Generation of a Background Image by Using a Far-Infrared Light Camera
Sensors 2015, 15(3), 6763-6788; https://doi.org/10.3390/s150306763
Received: 15 January 2015 / Revised: 17 February 2015 / Accepted: 9 March 2015 / Published: 19 March 2015
Cited by 21 | Viewed by 3346 | PDF Full-text (2658 KB) | HTML Full-text | XML Full-text
Abstract
The need for computer vision-based human detection has increased in fields, such as security, intelligent surveillance and monitoring systems. However, performance enhancement of human detection based on visible light cameras is limited, because of factors, such as nonuniform illumination, shadows and low external [...] Read more.
The need for computer vision-based human detection has increased in fields, such as security, intelligent surveillance and monitoring systems. However, performance enhancement of human detection based on visible light cameras is limited, because of factors, such as nonuniform illumination, shadows and low external light in the evening and night. Consequently, human detection based on thermal (far-infrared light) cameras has been considered as an alternative. However, its performance is influenced by the factors, such as low image resolution, low contrast and the large noises of thermal images. It is also affected by the high temperature of backgrounds during the day. To solve these problems, we propose a new method for detecting human areas in thermal camera images. Compared to previous works, the proposed research is novel in the following four aspects. One background image is generated by median and average filtering. Additional filtering procedures based on maximum gray level, size filtering and region erasing are applied to remove the human areas from the background image. Secondly, candidate human regions in the input image are located by combining the pixel and edge difference images between the input and background images. The thresholds for the difference images are adaptively determined based on the brightness of the generated background image. Noise components are removed by component labeling, a morphological operation and size filtering. Third, detected areas that may have more than two human regions are merged or separated based on the information in the horizontal and vertical histograms of the detected area. This procedure is adaptively operated based on the brightness of the generated background image. Fourth, a further procedure for the separation and removal of the candidate human regions is performed based on the size and ratio of the height to width information of the candidate regions considering the camera viewing direction and perspective projection. Experimental results with two types of databases confirm that the proposed method outperforms other methods. Full article
(This article belongs to the Special Issue Frontiers in Infrared Photodetection)
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Open AccessArticle
Location Detection and Tracking of Moving Targets by a 2D IR-UWB Radar System
Sensors 2015, 15(3), 6740-6762; https://doi.org/10.3390/s150306740
Received: 30 October 2014 / Revised: 8 March 2015 / Accepted: 9 March 2015 / Published: 19 March 2015
Cited by 27 | Viewed by 3852 | PDF Full-text (2138 KB) | HTML Full-text | XML Full-text
Abstract
In indoor environments, the Global Positioning System (GPS) and long-range tracking radar systems are not optimal, because of signal propagation limitations in the indoor environment. In recent years, the use of ultra-wide band (UWB) technology has become a possible solution for object detection, [...] Read more.
In indoor environments, the Global Positioning System (GPS) and long-range tracking radar systems are not optimal, because of signal propagation limitations in the indoor environment. In recent years, the use of ultra-wide band (UWB) technology has become a possible solution for object detection, localization and tracking in indoor environments, because of its high range resolution, compact size and low cost. This paper presents improved target detection and tracking techniques for moving objects with impulse-radio UWB (IR-UWB) radar in a short-range indoor area. This is achieved through signal-processing steps, such as clutter reduction, target detection, target localization and tracking. In this paper, we introduce a new combination consisting of our proposed signal-processing procedures. In the clutter-reduction step, a filtering method that uses a Kalman filter (KF) is proposed. Then, in the target detection step, a modification of the conventional CLEAN algorithm which is used to estimate the impulse response from observation region is applied for the advanced elimination of false alarms. Then, the output is fed into the target localization and tracking step, in which the target location and trajectory are determined and tracked by using unscented KF in two-dimensional coordinates. In each step, the proposed methods are compared to conventional methods to demonstrate the differences in performance. The experiments are carried out using actual IR-UWB radar under different scenarios. The results verify that the proposed methods can improve the probability and efficiency of target detection and tracking. Full article
(This article belongs to the Special Issue Sensors for Indoor Mapping and Navigation)
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Open AccessArticle
Multi-Layer Sparse Representation for Weighted LBP-Patches Based Facial Expression Recognition
Sensors 2015, 15(3), 6719-6739; https://doi.org/10.3390/s150306719
Received: 15 December 2014 / Revised: 28 February 2015 / Accepted: 10 March 2015 / Published: 19 March 2015
Cited by 12 | Viewed by 2539 | PDF Full-text (2047 KB) | HTML Full-text | XML Full-text
Abstract
In this paper, a novel facial expression recognition method based on sparse representation is proposed. Most contemporary facial expression recognition systems suffer from limited ability to handle image nuisances such as low resolution and noise. Especially for low intensity expression, most of the [...] Read more.
In this paper, a novel facial expression recognition method based on sparse representation is proposed. Most contemporary facial expression recognition systems suffer from limited ability to handle image nuisances such as low resolution and noise. Especially for low intensity expression, most of the existing training methods have quite low recognition rates. Motivated by sparse representation, the problem can be solved by finding sparse coefficients of the test image by the whole training set. Deriving an effective facial representation from original face images is a vital step for successful facial expression recognition. We evaluate facial representation based on weighted local binary patterns, and Fisher separation criterion is used to calculate the weighs of patches. A multi-layer sparse representation framework is proposed for multi-intensity facial expression recognition, especially for low-intensity expressions and noisy expressions in reality, which is a critical problem but seldom addressed in the existing works. To this end, several experiments based on low-resolution and multi-intensity expressions are carried out. Promising results on publicly available databases demonstrate the potential of the proposed approach. Full article
(This article belongs to the Section Physical Sensors)
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Open AccessArticle
Soil Water Content Assessment: Critical Issues Concerning the Operational Application of the Triangle Method
Sensors 2015, 15(3), 6699-6718; https://doi.org/10.3390/s150306699
Received: 29 December 2014 / Revised: 10 March 2015 / Accepted: 13 March 2015 / Published: 19 March 2015
Cited by 5 | Viewed by 2496 | PDF Full-text (4424 KB) | HTML Full-text | XML Full-text
Abstract
Knowledge of soil water content plays a key role in water management efforts to improve irrigation efficiency. Among the indirect estimation methods of soil water content via Earth Observation data is the triangle method, used to analyze optical and thermal features because these [...] Read more.
Knowledge of soil water content plays a key role in water management efforts to improve irrigation efficiency. Among the indirect estimation methods of soil water content via Earth Observation data is the triangle method, used to analyze optical and thermal features because these are primarily controlled by water content within the near-surface evaporation layer and root zone in bare and vegetated soils. Although the soil-vegetation-atmosphere transfer theory describes the ongoing processes, theoretical models reveal limits for operational use. When applying simplified empirical formulations, meteorological forcing could be replaced with alternative variables when the above-canopy temperature is unknown, to mitigate the effects of calibration inaccuracies or to account for the temporal admittance of the soil. However, if applied over a limited area, a characterization of both dry and wet edges could not be properly achieved; thus, a multi-temporal analysis can be exploited to include outer extremes in soil water content. A diachronic empirical approach introduces the need to assume a constancy of other meteorological forcing variables that control thermal features. Airborne images were acquired on a Sicilian vineyard during most of an entire irrigation period (fruit-set to ripening stages, vintage 2008), during which in situ soil water content was measured to set up the triangle method. Within this framework, we tested the triangle method by employing alternative thermal forcing. The results were inaccurate when air temperature at airborne acquisition was employed. Sonic and aerodynamic air temperatures confirmed and partially explained the limits of simultaneous meteorological forcing, and the use of proxy variables improved model accuracy. The analysis indicates that high spatial resolution does not necessarily imply higher accuracies. Full article
(This article belongs to the Section Remote Sensors, Control, and Telemetry)
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Open AccessArticle
Development of a Capacitive Ice Sensor to Measure Ice Growth in Real Time
Sensors 2015, 15(3), 6688-6698; https://doi.org/10.3390/s150306688
Received: 30 December 2014 / Revised: 27 February 2015 / Accepted: 10 March 2015 / Published: 19 March 2015
Cited by 4 | Viewed by 2991 | PDF Full-text (2273 KB) | HTML Full-text | XML Full-text
Abstract
This paper presents the development of the capacitive sensor to measure the growth of ice on a fuel pipe surface in real time. The ice sensor consists of pairs of electrodes to detect the change in capacitance and a thermocouple temperature sensor to [...] Read more.
This paper presents the development of the capacitive sensor to measure the growth of ice on a fuel pipe surface in real time. The ice sensor consists of pairs of electrodes to detect the change in capacitance and a thermocouple temperature sensor to examine the ice formation situation. In addition, an environmental chamber was specially designed to control the humidity and temperature to simulate the ice formation conditions. From the humidity, a water film is formed on the ice sensor, which results in an increase in capacitance. Ice nucleation occurs, followed by the rapid formation of frost ice that decreases the capacitance suddenly. The capacitance is saturated. The developed ice sensor explains the ice growth providing information about the icing temperature in real time. Full article
(This article belongs to the Section Physical Sensors)
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Open AccessArticle
Beamforming and Power Control in Sensor Arrays Using Reinforcement Learning
Sensors 2015, 15(3), 6668-6687; https://doi.org/10.3390/s150306668
Received: 31 October 2014 / Revised: 14 February 2015 / Accepted: 4 March 2015 / Published: 19 March 2015
Cited by 2 | Viewed by 2243 | PDF Full-text (1504 KB) | HTML Full-text | XML Full-text
Abstract
The use of beamforming and power control, combined or separately, has advantages and disadvantages, depending on the application. The combined use of beamforming and power control has been shown to be highly effective in applications involving the suppression of interference signals from different [...] Read more.
The use of beamforming and power control, combined or separately, has advantages and disadvantages, depending on the application. The combined use of beamforming and power control has been shown to be highly effective in applications involving the suppression of interference signals from different sources. However, it is necessary to identify efficient methodologies for the combined operation of these two techniques. The most appropriate technique may be obtained by means of the implementation of an intelligent agent capable of making the best selection between beamforming and power control. The present paper proposes an algorithm using reinforcement learning (RL) to determine the optimal combination of beamforming and power control in sensor arrays. The RL algorithm used was Q-learning, employing an ε-greedy policy, and training was performed using the offline method. The simulations showed that RL was effective for implementation of a switching policy involving the different techniques, taking advantage of the positive characteristics of each technique in terms of signal reception. Full article
(This article belongs to the Section Physical Sensors)
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Open AccessArticle
Water Area Extraction Using RADARSAT SAR Imagery Combined with Landsat Imagery and Terrain Information
Sensors 2015, 15(3), 6652-6667; https://doi.org/10.3390/s150306652
Received: 19 January 2015 / Revised: 2 March 2015 / Accepted: 3 March 2015 / Published: 19 March 2015
Cited by 23 | Viewed by 2398 | PDF Full-text (3719 KB) | HTML Full-text | XML Full-text
Abstract
This paper exploits an effective water extraction method using SAR imagery in preparation for flood mapping in unpredictable flood situations. The proposed method is based on the thresholding method using SAR amplitude, terrain information, and object-based classification techniques for noise removal. Since the [...] Read more.
This paper exploits an effective water extraction method using SAR imagery in preparation for flood mapping in unpredictable flood situations. The proposed method is based on the thresholding method using SAR amplitude, terrain information, and object-based classification techniques for noise removal. Since the water areas in SAR images have the lowest amplitude value, the thresholding method using SAR amplitude could effectively extract water bodies. However, the reflective properties of water areas in SAR imagery cannot distinguish the occluded areas caused by steep relief and they can be eliminated with terrain information. In spite of the thresholding method using SAR amplitude and terrain information, noises which interfered with users’ interpretation of water maps still remained and the object-based classification using an object size criterion was applied for the noise removal and the criterion was determined by a histogram-based technique. When only using SAR amplitude information, the overall accuracy was 83.67%. However, using SAR amplitude, terrain information and the noise removal technique, the overall classification accuracy over the study area turned out to be 96.42%. In particular, user accuracy was improved by 46.00%. Full article
(This article belongs to the Section Remote Sensors, Control, and Telemetry)
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Open AccessArticle
Wavelength-Adaptive Dehazing Using Histogram Merging-Based Classification for UAV Images
Sensors 2015, 15(3), 6633-6651; https://doi.org/10.3390/s150306633
Received: 9 December 2014 / Revised: 13 February 2015 / Accepted: 10 March 2015 / Published: 19 March 2015
Cited by 9 | Viewed by 2807 | PDF Full-text (21391 KB) | HTML Full-text | XML Full-text
Abstract
Since incoming light to an unmanned aerial vehicle (UAV) platform can be scattered by haze and dust in the atmosphere, the acquired image loses the original color and brightness of the subject. Enhancement of hazy images is an important task in improving the [...] Read more.
Since incoming light to an unmanned aerial vehicle (UAV) platform can be scattered by haze and dust in the atmosphere, the acquired image loses the original color and brightness of the subject. Enhancement of hazy images is an important task in improving the visibility of various UAV images. This paper presents a spatially-adaptive dehazing algorithm that merges color histograms with consideration of the wavelength-dependent atmospheric turbidity. Based on the wavelength-adaptive hazy image acquisition model, the proposed dehazing algorithm consists of three steps: (i) image segmentation based on geometric classes; (ii) generation of the context-adaptive transmission map; and (iii) intensity transformation for enhancing a hazy UAV image. The major contribution of the research is a novel hazy UAV image degradation model by considering the wavelength of light sources. In addition, the proposed transmission map provides a theoretical basis to differentiate visually important regions from others based on the turbidity and merged classification results. Full article
(This article belongs to the Special Issue UAV Sensors for Environmental Monitoring) Printed Edition available
Open AccessArticle
Sensing in the Collaborative Internet of Things
Sensors 2015, 15(3), 6607-6632; https://doi.org/10.3390/s150306607
Received: 1 December 2014 / Revised: 12 February 2015 / Accepted: 26 February 2015 / Published: 19 March 2015
Cited by 16 | Viewed by 3150 | PDF Full-text (909 KB) | HTML Full-text | XML Full-text
Abstract
We are entering a new era of computing technology, the era of Internet of Things (IoT). An important element for this popularization is the large use of off-the-shelf sensors. Most of those sensors will be deployed by different owners, generally common users, creating [...] Read more.
We are entering a new era of computing technology, the era of Internet of Things (IoT). An important element for this popularization is the large use of off-the-shelf sensors. Most of those sensors will be deployed by different owners, generally common users, creating what we call the Collaborative IoT. This collaborative IoT helps to increase considerably the amount and availability of collected data for different purposes, creating new interesting opportunities, but also several challenges. For example, it is very challenging to search for and select a desired sensor or a group of sensors when there is no description about the provided sensed data or when it is imprecise. Given that, in this work we characterize the properties of the sensed data in the Internet of Things, mainly the sensed data contributed by several sources, including sensors from common users. We conclude that, in order to safely use data available in the IoT, we need a filtering process to increase the data reliability. In this direction, we propose a new simple and powerful approach that helps to select reliable sensors. We tested our method for different types of sensed data, and the results reveal the effectiveness in the correct selection of sensor data. Full article
(This article belongs to the Special Issue Wireless Sensor Networks and the Internet of Things)
Open AccessArticle
Tracking Systems for Virtual Rehabilitation: Objective Performance vs. Subjective Experience. A Practical Scenario
Sensors 2015, 15(3), 6586-6606; https://doi.org/10.3390/s150306586
Received: 30 January 2015 / Revised: 5 March 2015 / Accepted: 13 March 2015 / Published: 19 March 2015
Cited by 10 | Viewed by 3065 | PDF Full-text (4074 KB) | HTML Full-text | XML Full-text
Abstract
Motion tracking systems are commonly used in virtual reality-based interventions to detect movements in the real world and transfer them to the virtual environment. There are different tracking solutions based on different physical principles, which mainly define their performance parameters. However, special requirements [...] Read more.
Motion tracking systems are commonly used in virtual reality-based interventions to detect movements in the real world and transfer them to the virtual environment. There are different tracking solutions based on different physical principles, which mainly define their performance parameters. However, special requirements have to be considered for rehabilitation purposes. This paper studies and compares the accuracy and jitter of three tracking solutions (optical, electromagnetic, and skeleton tracking) in a practical scenario and analyzes the subjective perceptions of 19 healthy subjects, 22 stroke survivors, and 14 physical therapists. The optical tracking system provided the best accuracy (1.074 ± 0.417 cm) while the electromagnetic device provided the most inaccurate results (11.027 ± 2.364 cm). However, this tracking solution provided the best jitter values (0.324 ± 0.093 cm), in contrast to the skeleton tracking, which had the worst results (1.522 ± 0.858 cm). Healthy individuals and professionals preferred the skeleton tracking solution rather than the optical and electromagnetic solution (in that order). Individuals with stroke chose the optical solution over the other options. Our results show that subjective perceptions and preferences are far from being constant among different populations, thus suggesting that these considerations, together with the performance parameters, should be also taken into account when designing a rehabilitation system. Full article
(This article belongs to the collection Sensors for Globalized Healthy Living and Wellbeing)
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Open AccessArticle
New Calibration Method Using Low Cost MEM IMUs to Verify the Performance of UAV-Borne MMS Payloads
Sensors 2015, 15(3), 6560-6585; https://doi.org/10.3390/s150306560
Received: 9 January 2015 / Revised: 9 January 2015 / Accepted: 6 March 2015 / Published: 19 March 2015
Cited by 12 | Viewed by 2859 | PDF Full-text (8337 KB) | HTML Full-text | XML Full-text
Abstract
Spatial information plays a critical role in remote sensing and mapping applications such as environment surveying and disaster monitoring. An Unmanned Aerial Vehicle (UAV)-borne mobile mapping system (MMS) can accomplish rapid spatial information acquisition under limited sky conditions with better mobility and flexibility [...] Read more.
Spatial information plays a critical role in remote sensing and mapping applications such as environment surveying and disaster monitoring. An Unmanned Aerial Vehicle (UAV)-borne mobile mapping system (MMS) can accomplish rapid spatial information acquisition under limited sky conditions with better mobility and flexibility than other means. This study proposes a long endurance Direct Geo-referencing (DG)-based fixed-wing UAV photogrammetric platform and two DG modules that each use different commercial Micro-Electro Mechanical Systems’ (MEMS) tactical grade Inertial Measurement Units (IMUs). Furthermore, this study develops a novel kinematic calibration method which includes lever arms, boresight angles and camera shutter delay to improve positioning accuracy. The new calibration method is then compared with the traditional calibration approach. The results show that the accuracy of the DG can be significantly improved by flying at a lower altitude using the new higher specification hardware. The new proposed method improves the accuracy of DG by about 20%. The preliminary results show that two-dimensional (2D) horizontal DG positioning accuracy is around 5.8 m at a flight height of 300 m using the newly designed tactical grade integrated Positioning and Orientation System (POS). The positioning accuracy in three-dimensions (3D) is less than 8 m. Full article
(This article belongs to the Special Issue UAV Sensors for Environmental Monitoring) Printed Edition available
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Open AccessArticle
Single- and Two-Phase Flow Characterization Using Optical Fiber Bragg Gratings
Sensors 2015, 15(3), 6549-6559; https://doi.org/10.3390/s150306549
Received: 29 September 2014 / Revised: 10 November 2014 / Accepted: 24 December 2014 / Published: 17 March 2015
Cited by 7 | Viewed by 2210 | PDF Full-text (1586 KB) | HTML Full-text | XML Full-text
Abstract
Single- and two-phase flow characterization using optical fiber Bragg gratings (FBGs) is presented. The sensor unit consists of the optical fiber Bragg grating positioned transversely to the flow and fixed in the pipe walls. The hydrodynamic pressure applied by the liquid or air/liquid [...] Read more.
Single- and two-phase flow characterization using optical fiber Bragg gratings (FBGs) is presented. The sensor unit consists of the optical fiber Bragg grating positioned transversely to the flow and fixed in the pipe walls. The hydrodynamic pressure applied by the liquid or air/liquid flow to the optical fiber induces deformation that can be detected by the FBG. Given that the applied pressure is directly related to the mass flow, it is possible to establish a relationship using the grating resonance wavelength shift to determine the mass flow when the flow velocity is well known. For two phase flows of air and liquid, there is a significant change in the force applied to the fiber that accounts for the very distinct densities of these substances. As a consequence, the optical fiber deformation and the correspondent grating wavelength shift as a function of the flow will be very different for an air bubble or a liquid slug, allowing their detection as they flow through the pipe. A quasi-distributed sensing tool with 18 sensors evenly spread along the pipe is developed and characterized, making possible the characterization of the flow, as well as the tracking of the bubbles over a large section of the test bed. Results show good agreement with standard measurement methods and open up plenty of opportunities to both laboratory measurement tools and field applications. Full article
(This article belongs to the Section Physical Sensors)
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Open AccessArticle
Game Design to Measure Reflexes and Attention Based on Biofeedback Multi-Sensor Interaction
Sensors 2015, 15(3), 6520-6548; https://doi.org/10.3390/s150306520
Received: 21 January 2015 / Revised: 5 March 2015 / Accepted: 6 March 2015 / Published: 17 March 2015
Cited by 6 | Viewed by 2706 | PDF Full-text (3901 KB) | HTML Full-text | XML Full-text | Supplementary Files
Abstract
This paper presents a multi-sensor system for implementing biofeedback as a human-computer interaction technique in a game involving driving cars in risky situations. The sensors used are: Eye Tracker, Kinect, pulsometer, respirometer, electromiography (EMG) and galvanic skin resistance (GSR). An algorithm has been [...] Read more.
This paper presents a multi-sensor system for implementing biofeedback as a human-computer interaction technique in a game involving driving cars in risky situations. The sensors used are: Eye Tracker, Kinect, pulsometer, respirometer, electromiography (EMG) and galvanic skin resistance (GSR). An algorithm has been designed which gives rise to an interaction logic with the game according to the set of physiological constants obtained from the sensors. The results reflect a 72.333 response to the System Usability Scale (SUS), a significant difference of p = 0.026 in GSR values in terms of the difference between the start and end of the game, and an r = 0.659 and p = 0.008 correlation while playing with the Kinect between the breathing level and the energy and joy factor. All the sensors used had an impact on the end results, whereby none of them should be disregarded in future lines of research, even though it would be interesting to obtain separate breathing values from that of the cardio. Full article
(This article belongs to the Special Issue Sensors for Entertainment)
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Open AccessArticle
Sparse Component Analysis Using Time-Frequency Representations for Operational Modal Analysis
Sensors 2015, 15(3), 6497-6519; https://doi.org/10.3390/s150306497
Received: 27 November 2014 / Revised: 20 February 2015 / Accepted: 27 February 2015 / Published: 17 March 2015
Cited by 15 | Viewed by 2319 | PDF Full-text (1421 KB) | HTML Full-text | XML Full-text
Abstract
Sparse component analysis (SCA) has been widely used for blind source separation(BSS) for many years. Recently, SCA has been applied to operational modal analysis (OMA), which is also known as output-only modal identification. This paper considers the sparsity of sources’ time-frequency (TF) representation [...] Read more.
Sparse component analysis (SCA) has been widely used for blind source separation(BSS) for many years. Recently, SCA has been applied to operational modal analysis (OMA), which is also known as output-only modal identification. This paper considers the sparsity of sources’ time-frequency (TF) representation and proposes a new TF-domain SCA under the OMA framework. First, the measurements from the sensors are transformed to the TF domain to get a sparse representation. Then, single-source-points (SSPs) are detected to better reveal the hyperlines which correspond to the columns of the mixing matrix. The K-hyperline clustering algorithm is used to identify the direction vectors of the hyperlines and then the mixing matrix is calculated. Finally, basis pursuit de-noising technique is used to recover the modal responses, from which the modal parameters are computed. The proposed method is valid even if the number of active modes exceed the number of sensors. Numerical simulation and experimental verification demonstrate the good performance of the proposed method. Full article
(This article belongs to the Section Physical Sensors)
Open AccessArticle
Cooperative Environment Scans Based on a Multi-Robot System
Sensors 2015, 15(3), 6483-6496; https://doi.org/10.3390/s150306483
Received: 19 January 2015 / Revised: 21 February 2015 / Accepted: 6 March 2015 / Published: 17 March 2015
Cited by 3 | Viewed by 2265 | PDF Full-text (1961 KB) | HTML Full-text | XML Full-text
Abstract
This paper proposes a cooperative environment scan system (CESS) using multiple robots, where each robot has low-cost range finders and low processing power. To organize and maintain the CESS, a base robot monitors the positions of the child robots, controls them, and builds [...] Read more.
This paper proposes a cooperative environment scan system (CESS) using multiple robots, where each robot has low-cost range finders and low processing power. To organize and maintain the CESS, a base robot monitors the positions of the child robots, controls them, and builds a map of the unknown environment, while the child robots with low performance range finders provide obstacle information. Even though each child robot provides approximated and limited information of the obstacles, CESS replaces the single LRF, which has a high cost, because much of the information is acquired and accumulated by a number of the child robots. Moreover, the proposed CESS extends the measurement boundaries and detects obstacles hidden behind others. To show the performance of the proposed system and compare this with the numerical models of the commercialized 2D and 3D laser scanners, simulation results are included. Full article
(This article belongs to the Section Physical Sensors)
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Open AccessArticle
A Solid-State Thin-Film Ag/AgCl Reference Electrode Coated with Graphene Oxide and Its Use in a pH Sensor
Sensors 2015, 15(3), 6469-6482; https://doi.org/10.3390/s150306469
Received: 12 February 2015 / Revised: 10 March 2015 / Accepted: 12 March 2015 / Published: 17 March 2015
Cited by 25 | Viewed by 4194 | PDF Full-text (1345 KB) | HTML Full-text | XML Full-text
Abstract
In this study, we describe a novel solid-state thin-film Ag/AgCl reference electrode (SSRE) that was coated with a protective layer of graphene oxide (GO). This layer was prepared by drop casting a solution of GO on the Ag/AgCl thin film. The potential differences [...] Read more.
In this study, we describe a novel solid-state thin-film Ag/AgCl reference electrode (SSRE) that was coated with a protective layer of graphene oxide (GO). This layer was prepared by drop casting a solution of GO on the Ag/AgCl thin film. The potential differences exhibited by the SSRE were less than 2 mV for 26 days. The cyclic voltammograms of the SSRE were almost similar to those of a commercial reference electrode, while the diffusion coefficient of Fe(CN)63− as calculated from the cathodic peaks of the SSRE was 6.48 × 10−6 cm2/s. The SSRE was used in conjunction with a laboratory-made working electrode to determine its suitability for practical use. The average pH sensitivity of this combined sensor was 58.5 mV/pH in the acid-to-base direction; the correlation coefficient was greater than 0.99. In addition, an integrated pH sensor that included the SSRE was packaged in a secure digital (SD) card and tested. The average sensitivity of the chip was 56.8 mV/pH, with the correlation coefficient being greater than 0.99. In addition, a pH sensing test was also performed by using a laboratory-made potentiometer, which showed a sensitivity of 55.4 mV/pH, with the correlation coefficient being greater than 0.99. Full article
(This article belongs to the Section Chemical Sensors)
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Open AccessReview
MEMS Sensor Technologies for Human Centred Applications in Healthcare, Physical Activities, Safety and Environmental Sensing: A Review on Research Activities in Italy
Sensors 2015, 15(3), 6441-6468; https://doi.org/10.3390/s150306441
Received: 15 December 2014 / Revised: 8 February 2015 / Accepted: 4 March 2015 / Published: 17 March 2015
Cited by 47 | Viewed by 3964 | PDF Full-text (754 KB) | HTML Full-text | XML Full-text
Abstract
Over the past few decades the increased level of public awareness concerning healthcare, physical activities, safety and environmental sensing has created an emerging need for smart sensor technologies and monitoring devices able to sense, classify, and provide feedbacks to users’ health status and [...] Read more.
Over the past few decades the increased level of public awareness concerning healthcare, physical activities, safety and environmental sensing has created an emerging need for smart sensor technologies and monitoring devices able to sense, classify, and provide feedbacks to users’ health status and physical activities, as well as to evaluate environmental and safety conditions in a pervasive, accurate and reliable fashion. Monitoring and precisely quantifying users’ physical activity with inertial measurement unit-based devices, for instance, has also proven to be important in health management of patients affected by chronic diseases, e.g., Parkinson’s disease, many of which are becoming highly prevalent in Italy and in the Western world. This review paper will focus on MEMS sensor technologies developed in Italy in the last three years describing research achievements for healthcare and physical activity, safety and environmental sensing, in addition to smart systems integration. Innovative and smart integrated solutions for sensing devices, pursued and implemented in Italian research centres, will be highlighted, together with specific applications of such technologies. Finally, the paper will depict the future perspective of sensor technologies and corresponding exploitation opportunities, again with a specific focus on Italy. Full article
(This article belongs to the Special Issue State-of-the-Art Sensors Technology in Italy 2014)
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