Next Issue
Previous Issue

E-Mail Alert

Add your e-mail address to receive forthcoming issues of this journal:

Journal Browser

Journal Browser

Table of Contents

Sensors, Volume 16, Issue 7 (July 2016)

  • Issues are regarded as officially published after their release is announced to the table of contents alert mailing list.
  • You may sign up for e-mail alerts to receive table of contents of newly released issues.
  • PDF is the official format for papers published in both, html and pdf forms. To view the papers in pdf format, click on the "PDF Full-text" link, and use the free Adobe Readerexternal link to open them.
View options order results:
result details:
Displaying articles 1-208
Export citation of selected articles as:

Editorial

Jump to: Research, Review, Other

Open AccessEditorial Sensors for Entertainment
Sensors 2016, 16(7), 1102; doi:10.3390/s16071102
Received: 14 July 2016 / Accepted: 14 July 2016 / Published: 15 July 2016
PDF Full-text (146 KB) | HTML Full-text | XML Full-text
Abstract
Sensors are becoming ubiquitous in all areas of science, technology, and society. In this Special Issue on “Sensors for Entertainment”, developments in progress and the current state of application scenarios for sensors in the field of entertainment is explored. Full article
(This article belongs to the Special Issue Sensors for Entertainment)

Research

Jump to: Editorial, Review, Other

Open AccessArticle Verification of Geometric Model-Based Plant Phenotyping Methods for Studies of Xerophytic Plants
Sensors 2016, 16(7), 924; doi:10.3390/s16070924
Received: 16 February 2016 / Revised: 9 May 2016 / Accepted: 31 May 2016 / Published: 27 June 2016
PDF Full-text (7886 KB) | HTML Full-text | XML Full-text
Abstract
This paper presents the results of verification of certain non-contact measurement methods of plant scanning to estimate morphological parameters such as length, width, area, volume of leaves and/or stems on the basis of computer models. The best results in reproducing the shape of
[...] Read more.
This paper presents the results of verification of certain non-contact measurement methods of plant scanning to estimate morphological parameters such as length, width, area, volume of leaves and/or stems on the basis of computer models. The best results in reproducing the shape of scanned objects up to 50 cm in height were obtained with the structured-light DAVID Laserscanner. The optimal triangle mesh resolution for scanned surfaces was determined with the measurement error taken into account. The research suggests that measuring morphological parameters from computer models can supplement or even replace phenotyping with classic methods. Calculating precise values of area and volume makes determination of the S/V (surface/volume) ratio for cacti and other succulents possible, whereas for classic methods the result is an approximation only. In addition, the possibility of scanning and measuring plant species which differ in morphology was investigated. Full article
(This article belongs to the Special Issue Sensors for Agriculture)
Open AccessArticle A Tightly-Coupled GPS/INS/UWB Cooperative Positioning Sensors System Supported by V2I Communication
Sensors 2016, 16(7), 944; doi:10.3390/s16070944
Received: 22 March 2016 / Revised: 30 May 2016 / Accepted: 8 June 2016 / Published: 27 June 2016
Cited by 4 | PDF Full-text (4041 KB) | HTML Full-text | XML Full-text
Abstract
This paper investigates a tightly-coupled Global Position System (GPS)/Ultra-Wideband (UWB)/Inertial Navigation System (INS) cooperative positioning scheme using a Robust Kalman Filter (RKF) supported by V2I communication. The scheme proposes a method that uses range measurements of UWB units transmitted among the terminals as
[...] Read more.
This paper investigates a tightly-coupled Global Position System (GPS)/Ultra-Wideband (UWB)/Inertial Navigation System (INS) cooperative positioning scheme using a Robust Kalman Filter (RKF) supported by V2I communication. The scheme proposes a method that uses range measurements of UWB units transmitted among the terminals as augmentation inputs of the observations. The UWB range inputs are used to reform the GPS observation equations that consist of pseudo-range and Doppler measurements and the updated observation equation is processed in a tightly-coupled GPS/UWB/INS integrated positioning equation using an adaptive Robust Kalman Filter. The result of the trial conducted on the roof of the Nottingham Geospatial Institute (NGI) at the University of Nottingham shows that the integrated solution provides better accuracy and improves the availability of the system in GPS denied environments. RKF can eliminate the effects of gross errors. Additionally, the internal and external reliabilities of the system are enhanced when the UWB observables received from the moving terminals are involved in the positioning algorithm. Full article
(This article belongs to the Section Remote Sensors)
Figures

Open AccessArticle An Efficient Implementation of Fixed Failure-Rate Ratio Test for GNSS Ambiguity Resolution
Sensors 2016, 16(7), 945; doi:10.3390/s16070945
Received: 24 April 2016 / Revised: 10 June 2016 / Accepted: 20 June 2016 / Published: 23 June 2016
Cited by 2 | PDF Full-text (14676 KB) | HTML Full-text | XML Full-text | Supplementary Files
Abstract
Ambiguity Resolution (AR) plays a vital role in precise GNSS positioning. Correctly-fixed integer ambiguities can significantly improve the positioning solution, while incorrectly-fixed integer ambiguities can bring large positioning errors and, therefore, should be avoided. The ratio test is an extensively used test to
[...] Read more.
Ambiguity Resolution (AR) plays a vital role in precise GNSS positioning. Correctly-fixed integer ambiguities can significantly improve the positioning solution, while incorrectly-fixed integer ambiguities can bring large positioning errors and, therefore, should be avoided. The ratio test is an extensively used test to validate the fixed integer ambiguities. To choose proper critical values of the ratio test, the Fixed Failure-rate Ratio Test (FFRT) has been proposed, which generates critical values according to user-defined tolerable failure rates. This contribution provides easy-to-implement fitting functions to calculate the critical values. With a massive Monte Carlo simulation, the functions for many different tolerable failure rates are provided, which enriches the choices of critical values for users. Moreover, the fitting functions for the fix rate are also provided, which for the first time allows users to evaluate the conditional success rate, i.e., the success rate once the integer candidates are accepted by FFRT. The superiority of FFRT over the traditional ratio test regarding controlling the failure rate and preventing unnecessary false alarms is shown by a simulation and a real data experiment. In the real data experiment with a baseline of 182.7 km, FFRT achieved much higher fix rates (up to 30% higher) and the same level of positioning accuracy from fixed solutions as compared to the traditional critical value. Full article
(This article belongs to the Section Remote Sensors)
Figures

Open AccessArticle Resolution-Enhanced Harmonic and Interharmonic Measurement for Power Quality Analysis in Cyber-Physical Energy System
Sensors 2016, 16(7), 946; doi:10.3390/s16070946
Received: 29 March 2016 / Revised: 12 June 2016 / Accepted: 16 June 2016 / Published: 27 June 2016
PDF Full-text (566 KB) | HTML Full-text | XML Full-text
Abstract
Power quality analysis issues, especially the measurement of harmonic and interharmonic in cyber-physical energy systems, are addressed in this paper. As new situations are introduced to the power system, the impact of electric vehicles, distributed generation and renewable energy has introduced extra demands
[...] Read more.
Power quality analysis issues, especially the measurement of harmonic and interharmonic in cyber-physical energy systems, are addressed in this paper. As new situations are introduced to the power system, the impact of electric vehicles, distributed generation and renewable energy has introduced extra demands to distributed sensors, waveform-level information and power quality data analytics. Harmonics and interharmonics, as the most significant disturbances, require carefully designed detection methods for an accurate measurement of electric loads whose information is crucial to subsequent analyzing and control. This paper gives a detailed description of the power quality analysis framework in networked environment and presents a fast and resolution-enhanced method for harmonic and interharmonic measurement. The proposed method first extracts harmonic and interharmonic components efficiently using the single-channel version of Robust Independent Component Analysis (RobustICA), then estimates the high-resolution frequency from three discrete Fourier transform (DFT) samples with little additional computation, and finally computes the amplitudes and phases with the adaptive linear neuron network. The experiments show that the proposed method is time-efficient and leads to a better accuracy of the simulated and experimental signals in the presence of noise and fundamental frequency deviation, thus providing a deeper insight into the (inter)harmonic sources or even the whole system. Full article
(This article belongs to the Special Issue Real-Time and Cyber-Physical Systems)
Figures

Open AccessArticle Electronic Noses for Well-Being: Breath Analysis and Energy Expenditure
Sensors 2016, 16(7), 947; doi:10.3390/s16070947
Received: 22 April 2016 / Revised: 7 June 2016 / Accepted: 17 June 2016 / Published: 23 June 2016
PDF Full-text (1202 KB) | HTML Full-text | XML Full-text
Abstract
The wealth of information concealed in a single human breath has been of interest for many years, promising not only disease detection, but also the monitoring of our general well-being. Recent developments in the fields of nano-sensor arrays and MEMS have enabled once
[...] Read more.
The wealth of information concealed in a single human breath has been of interest for many years, promising not only disease detection, but also the monitoring of our general well-being. Recent developments in the fields of nano-sensor arrays and MEMS have enabled once bulky artificial olfactory sensor systems, or so-called “electronic noses”, to become smaller, lower power and portable devices. At the same time, wearable health monitoring devices are now available, although reliable breath sensing equipment is somewhat missing from the market of physical, rather than chemical sensor gadgets. In this article, we report on the unprecedented rise in healthcare problems caused by an increasingly overweight population. We first review recently-developed electronic noses for the detection of diseases by the analysis of basic volatile organic compounds (VOCs). Then, we discuss the primary cause of obesity from over eating and the high calorific content of food. We present the need to measure our individual energy expenditure from our exhaled breath. Finally, we consider the future for handheld or wearable devices to measure energy expenditure; and the potential of these devices to revolutionize healthcare, both at home and in hospitals. Full article
(This article belongs to the Special Issue E-noses: Sensors and Applications)
Open AccessArticle A Novel Line Space Voting Method for Vanishing-Point Detection of General Road Images
Sensors 2016, 16(7), 948; doi:10.3390/s16070948
Received: 16 April 2016 / Revised: 16 June 2016 / Accepted: 17 June 2016 / Published: 23 June 2016
Cited by 1 | PDF Full-text (4315 KB) | HTML Full-text | XML Full-text
Abstract
Vanishing-point detection is an important component for the visual navigation system of an autonomous mobile robot. In this paper, we present a novel line space voting method for fast vanishing-point detection. First, the line segments are detected from the road image by the
[...] Read more.
Vanishing-point detection is an important component for the visual navigation system of an autonomous mobile robot. In this paper, we present a novel line space voting method for fast vanishing-point detection. First, the line segments are detected from the road image by the line segment detector (LSD) method according to the pixel’s gradient and texture orientation computed by the Sobel operator. Then, the vanishing-point of the road is voted on by considering the points of the lines and their neighborhood spaces with weighting methods. Our algorithm is simple, fast, and easy to implement with high accuracy. It has been experimentally tested with over hundreds of structured and unstructured road images. The experimental results indicate that the proposed method is effective and can meet the real-time requirements of navigation for autonomous mobile robots and unmanned ground vehicles. Full article
(This article belongs to the Special Issue Sensors for Autonomous Road Vehicles)
Figures

Open AccessArticle Real-Time Visual Tracking through Fusion Features
Sensors 2016, 16(7), 949; doi:10.3390/s16070949
Received: 19 April 2016 / Revised: 16 June 2016 / Accepted: 16 June 2016 / Published: 23 June 2016
Cited by 5 | PDF Full-text (3673 KB) | HTML Full-text | XML Full-text
Abstract
Due to their high-speed, correlation filters for object tracking have begun to receive increasing attention. Traditional object trackers based on correlation filters typically use a single type of feature. In this paper, we attempt to integrate multiple feature types to improve the performance,
[...] Read more.
Due to their high-speed, correlation filters for object tracking have begun to receive increasing attention. Traditional object trackers based on correlation filters typically use a single type of feature. In this paper, we attempt to integrate multiple feature types to improve the performance, and we propose a new DD-HOG fusion feature that consists of discriminative descriptors (DDs) and histograms of oriented gradients (HOG). However, fusion features as multi-vector descriptors cannot be directly used in prior correlation filters. To overcome this difficulty, we propose a multi-vector correlation filter (MVCF) that can directly convolve with a multi-vector descriptor to obtain a single-channel response that indicates the location of an object. Experiments on the CVPR2013 tracking benchmark with the evaluation of state-of-the-art trackers show the effectiveness and speed of the proposed method. Moreover, we show that our MVCF tracker, which uses the DD-HOG descriptor, outperforms the structure-preserving object tracker (SPOT) in multi-object tracking because of its high-speed and ability to address heavy occlusion. Full article
(This article belongs to the Section Physical Sensors)
Figures

Open AccessArticle Fast Orientation of Video Images of Buildings Acquired from a UAV without Stabilization
Sensors 2016, 16(7), 951; doi:10.3390/s16070951
Received: 16 March 2016 / Revised: 24 May 2016 / Accepted: 9 June 2016 / Published: 23 June 2016
Cited by 3 | PDF Full-text (6632 KB) | HTML Full-text | XML Full-text
Abstract
The aim of this research was to assess the possibility of conducting an absolute orientation procedure for video imagery, in which the external orientation for the first image was typical for aerial photogrammetry whereas the external orientation of the second was typical for
[...] Read more.
The aim of this research was to assess the possibility of conducting an absolute orientation procedure for video imagery, in which the external orientation for the first image was typical for aerial photogrammetry whereas the external orientation of the second was typical for terrestrial photogrammetry. Starting from the collinearity equations, assuming that the camera tilt angle is equal to 90°, a simplified mathematical model is proposed. The proposed method can be used to determine the X, Y, Z coordinates of points based on a set of collinearity equations of a pair of images. The use of simplified collinearity equations can considerably shorten the processing tine of image data from Unmanned Aerial Vehicles (UAVs), especially in low cost systems. The conducted experiments have shown that it is possible to carry out a complete photogrammetric project of an architectural structure using a camera tilted 85°–90° ( φ or ω) and simplified collinearity equations. It is also concluded that there is a correlation between the speed of the UAV and the discrepancy between the established and actual camera tilt angles. Full article
(This article belongs to the Special Issue UAV-Based Remote Sensing)
Open AccessArticle A Flexible Arrayed Eddy Current Sensor for Inspection of Hollow Axle Inner Surfaces
Sensors 2016, 16(7), 952; doi:10.3390/s16070952
Received: 19 April 2016 / Revised: 8 June 2016 / Accepted: 21 June 2016 / Published: 23 June 2016
Cited by 2 | PDF Full-text (6053 KB) | HTML Full-text | XML Full-text
Abstract
A reliable and accurate inspection of the hollow axle inner surface is important for the safe operation of high-speed trains. In order to improve the reliability of the inspection, a flexible arrayed eddy current sensor for non-destructive testing of the hollow axle inner
[...] Read more.
A reliable and accurate inspection of the hollow axle inner surface is important for the safe operation of high-speed trains. In order to improve the reliability of the inspection, a flexible arrayed eddy current sensor for non-destructive testing of the hollow axle inner surface was designed, fabricated and characterized. The sensor, consisting of two excitation traces and 28 sensing traces, was developed by using the flexible printed circuit board (FPCB) technique to conform the geometric features of the inner surfaces of the hollow axles. The main innovative aspect of the sensor was the new arrangement of excitation/sensing traces to achieve a differential configuration. Finite element model was established to analyze sensor responses and to determine the optimal excitation frequency. Experimental validations were conducted on a specimen with several artificial defects. Results from experiments and simulations were consistent with each other, with the maximum relative error less than 4%. Both results proved that the sensor was capable of detecting longitudinal and transverse defects with the depth of 0.5 mm under the optimal excitation frequency of 0.9 MHz. Full article
(This article belongs to the Section Physical Sensors)
Open AccessArticle Aluminum–Titanium Bilayer for Near-Infrared Transition Edge Sensors
Sensors 2016, 16(7), 953; doi:10.3390/s16070953
Received: 5 May 2016 / Revised: 15 June 2016 / Accepted: 17 June 2016 / Published: 23 June 2016
PDF Full-text (2488 KB) | HTML Full-text | XML Full-text
Abstract
Transition-edge sensors (TESs) are single photon detectors attractive for applications in quantum optics and quantum information experiments owing to their photon number resolving capability. Nowadays, high-energy resolution TESs for telecommunication are based on either W or Au/Ti films, demonstrating slow recovery time constants.
[...] Read more.
Transition-edge sensors (TESs) are single photon detectors attractive for applications in quantum optics and quantum information experiments owing to their photon number resolving capability. Nowadays, high-energy resolution TESs for telecommunication are based on either W or Au/Ti films, demonstrating slow recovery time constants. We report our progress on the development of an Al/Ti TES. Since bulk aluminum has a critical temperature (Tc) of ca. 1.2 K and a sufficiently low specific heat (less than 10−4 J/cm3K2), it can be employed to produce the sensitive material for optical TESs. Furthermore, exploiting its high Tc, Al-based TESs can be trimmed in a wider temperature range with respect to Ti or W. A first Al/Ti TES with a Tc ≈ 142 mK, investigated from a thermal and optical point of view, has shown a response time constant of about 2 μs and single photon discrimination with 0.34 eV energy resolution at telecom wavelength, demonstrating that Al/Ti films are suitable to produce TESs for visible and NIR photon counting. Full article
(This article belongs to the Section Physical Sensors)
Open AccessArticle A Method of Data Aggregation for Wearable Sensor Systems
Sensors 2016, 16(7), 954; doi:10.3390/s16070954
Received: 26 April 2016 / Revised: 6 June 2016 / Accepted: 21 June 2016 / Published: 23 June 2016
Cited by 1 | PDF Full-text (6096 KB) | HTML Full-text | XML Full-text
Abstract
Data aggregation has been considered as an effective way to decrease the data to be transferred in sensor networks. Particularly for wearable sensor systems, smaller battery has less energy, which makes energy conservation in data transmission more important. Nevertheless, wearable sensor systems usually
[...] Read more.
Data aggregation has been considered as an effective way to decrease the data to be transferred in sensor networks. Particularly for wearable sensor systems, smaller battery has less energy, which makes energy conservation in data transmission more important. Nevertheless, wearable sensor systems usually have features like frequently dynamic changes of topologies and data over a large range, of which current aggregating methods can’t adapt to the demand. In this paper, we study the system composed of many wearable devices with sensors, such as the network of a tactical unit, and introduce an energy consumption-balanced method of data aggregation, named LDA-RT. In the proposed method, we develop a query algorithm based on the idea of ‘happened-before’ to construct a dynamic and energy-balancing routing tree. We also present a distributed data aggregating and sorting algorithm to execute top-k query and decrease the data that must be transferred among wearable devices. Combining these algorithms, LDA-RT tries to balance the energy consumptions for prolonging the lifetime of wearable sensor systems. Results of evaluation indicate that LDA-RT performs well in constructing routing trees and energy balances. It also outperforms the filter-based top-k monitoring approach in energy consumption, load balance, and the network’s lifetime, especially for highly dynamic data sources. Full article
Open AccessArticle Semantic Registration and Discovery System of Subsystems and Services within an Interoperable Coordination Platform in Smart Cities
Sensors 2016, 16(7), 955; doi:10.3390/s16070955
Received: 5 February 2016 / Revised: 1 June 2016 / Accepted: 17 June 2016 / Published: 24 June 2016
Cited by 2 | PDF Full-text (4965 KB) | HTML Full-text | XML Full-text
Abstract
Smart subsystems like traffic, Smart Homes, the Smart Grid, outdoor lighting, etc. are built in many urban areas, each with a set of services that are offered to citizens. These subsystems are managed by self-contained embedded systems. However, coordination and cooperation between them
[...] Read more.
Smart subsystems like traffic, Smart Homes, the Smart Grid, outdoor lighting, etc. are built in many urban areas, each with a set of services that are offered to citizens. These subsystems are managed by self-contained embedded systems. However, coordination and cooperation between them are scarce. An integration of these systems which truly represents a “system of systems” could introduce more benefits, such as allowing the development of new applications and collective optimization. The integration should allow maximum reusability of available services provided by entities (e.g., sensors or Wireless Sensor Networks). Thus, it is of major importance to facilitate the discovery and registration of available services and subsystems in an integrated way. Therefore, an ontology-based and automatic system for subsystem and service registration and discovery is presented. Using this proposed system, heterogeneous subsystems and services could be registered and discovered in a dynamic manner with additional semantic annotations. In this way, users are able to build customized applications across different subsystems by using available services. The proposed system has been fully implemented and a case study is presented to show the usefulness of the proposed method. Full article
Open AccessArticle Use of MODIS Sensor Images Combined with Reanalysis Products to Retrieve Net Radiation in Amazonia
Sensors 2016, 16(7), 956; doi:10.3390/s16070956
Received: 30 March 2016 / Revised: 17 May 2016 / Accepted: 13 June 2016 / Published: 24 June 2016
Cited by 2 | PDF Full-text (10668 KB) | HTML Full-text | XML Full-text
Abstract
In the Amazon region, the estimation of radiation fluxes through remote sensing techniques is hindered by the lack of ground measurements required as input in the models, as well as the difficulty to obtain cloud-free images. Here, we assess an approach to estimate
[...] Read more.
In the Amazon region, the estimation of radiation fluxes through remote sensing techniques is hindered by the lack of ground measurements required as input in the models, as well as the difficulty to obtain cloud-free images. Here, we assess an approach to estimate net radiation (Rn) and its components under all-sky conditions for the Amazon region through the Surface Energy Balance Algorithm for Land (SEBAL) model utilizing only remote sensing and reanalysis data. The study period comprised six years, between January 2001–December 2006, and images from MODIS sensor aboard the Terra satellite and GLDAS reanalysis products were utilized. The estimates were evaluated with flux tower measurements within the Large-Scale Biosphere-Atmosphere Experiment in Amazonia (LBA) project. Comparison between estimates obtained by the proposed method and observations from LBA towers showed errors between 12.5% and 16.4% and 11.3% and 15.9% for instantaneous and daily Rn, respectively. Our approach was adequate to minimize the problem related to strong cloudiness over the region and allowed to map consistently the spatial distribution of net radiation components in Amazonia. We conclude that the integration of reanalysis products and satellite data, eliminating the need for surface measurements as input model, was a useful proposition for the spatialization of the radiation fluxes in the Amazon region, which may serve as input information needed by algorithms that aim to determine evapotranspiration, the most important component of the Amazon hydrological balance. Full article
(This article belongs to the Section Remote Sensors)
Open AccessArticle Source Anonymity in WSNs against Global Adversary Utilizing Low Transmission Rates with Delay Constraints
Sensors 2016, 16(7), 957; doi:10.3390/s16070957
Received: 14 April 2016 / Revised: 15 June 2016 / Accepted: 18 June 2016 / Published: 27 June 2016
Cited by 2 | PDF Full-text (3114 KB) | HTML Full-text | XML Full-text
Abstract
Wireless sensor networks (WSN) are deployed for many applications such as tracking and monitoring of endangered species, military applications, etc. which require anonymity of the origin, known as Source Location Privacy (SLP). The aim in SLP is to prevent unauthorized observers from tracing
[...] Read more.
Wireless sensor networks (WSN) are deployed for many applications such as tracking and monitoring of endangered species, military applications, etc. which require anonymity of the origin, known as Source Location Privacy (SLP). The aim in SLP is to prevent unauthorized observers from tracing the source of a real event by analyzing the traffic in the network. Previous approaches to SLP such as Fortified Anonymous Communication Protocol (FACP) employ transmission of real or fake packets in every time slot, which is inefficient. To overcome this shortcoming, we developed three different techniques presented in this paper. Dummy Uniform Distribution (DUD), Dummy Adaptive Distribution (DAD) and Controlled Dummy Adaptive Distribution (CAD) were developed to overcome the anonymity problem against a global adversary (which has the capability of analyzing and monitoring the entire network). Most of the current techniques try to prevent the adversary from perceiving the location and time of the real event whereas our proposed techniques confuse the adversary about the existence of the real event by introducing low rate fake messages, which subsequently lead to location and time privacy. Simulation results demonstrate that the proposed techniques provide reasonable delivery ratio, delay, and overhead of a real event's packets while keeping a high level of anonymity. Three different analysis models are conducted to verify the performance of our techniques. A visualization of the simulation data is performed to confirm anonymity. Further, neural network models are developed to ensure that the introduced techniques preserve SLP. Finally, a steganography model based on probability is implemented to prove the anonymity of the techniques. Full article
(This article belongs to the Section Sensor Networks)
Figures

Open AccessArticle Behavioral Modeling Based on Probabilistic Finite Automata: An Empirical Study
Sensors 2016, 16(7), 958; doi:10.3390/s16070958
Received: 28 April 2016 / Revised: 18 June 2016 / Accepted: 21 June 2016 / Published: 24 June 2016
Cited by 2 | PDF Full-text (769 KB) | HTML Full-text | XML Full-text
Abstract
Imagine an agent that performs tasks according to different strategies. The goal of Behavioral Recognition (BR) is to identify which of the available strategies is the one being used by the agent, by simply observing the agent’s actions and the environmental conditions during
[...] Read more.
Imagine an agent that performs tasks according to different strategies. The goal of Behavioral Recognition (BR) is to identify which of the available strategies is the one being used by the agent, by simply observing the agent’s actions and the environmental conditions during a certain period of time. The goal of Behavioral Cloning (BC) is more ambitious. In this last case, the learner must be able to build a model of the behavior of the agent. In both settings, the only assumption is that the learner has access to a training set that contains instances of observed behavioral traces for each available strategy. This paper studies a machine learning approach based on Probabilistic Finite Automata (PFAs), capable of achieving both the recognition and cloning tasks. We evaluate the performance of PFAs in the context of a simulated learning environment (in this case, a virtual Roomba vacuum cleaner robot), and compare it with a collection of other machine learning approaches. Full article
(This article belongs to the Special Issue Selected Papers from UCAmI, IWAAL and AmIHEALTH 2015)
Open AccessArticle Experimental Analysis of Bisbenzocyclobutene Bonded Capacitive Micromachined Ultrasonic Transducers
Sensors 2016, 16(7), 959; doi:10.3390/s16070959
Received: 22 April 2016 / Revised: 19 June 2016 / Accepted: 20 June 2016 / Published: 24 June 2016
Cited by 2 | PDF Full-text (6405 KB) | HTML Full-text | XML Full-text
Abstract
Experimental measurement results of a 1.75 mm × 1.75 mm footprint area Capacitive Micromachined Ultrasonic Transducer (CMUT) planar array fabricated using a bisbenzocyclobutene (BCB)-based adhesive wafer bonding technique has been presented. The array consists of 40 × 40 square diaphragm CMUT cells with
[...] Read more.
Experimental measurement results of a 1.75 mm × 1.75 mm footprint area Capacitive Micromachined Ultrasonic Transducer (CMUT) planar array fabricated using a bisbenzocyclobutene (BCB)-based adhesive wafer bonding technique has been presented. The array consists of 40 × 40 square diaphragm CMUT cells with a cavity thickness of 900 nm and supported by 10 µm wide dielectric spacers patterned on a thin layer of BCB. A 150 µm wide one µm thick gold strip has been used as the contact pad for gold wire bonding. The measured resonant frequency of 19.3 MHz using a Polytec™ laser Doppler vibrometer (Polytec™ MSA-500) is in excellent agreement with the 3-D FEA simulation result using IntelliSuite™. An Agilent ENA5061B vector network analyzer (VNA) has been used for impedance measurement and the resonance and anti-resonance values from the imaginary impedance curve were used to determine the electromechanical coupling co-efficient. The measured coupling coefficient of 0.294 at 20 V DC bias exhibits 40% higher transduction efficiency as compared to a measured value published elsewhere for a silicon nitride based CMUT. A white light interferometry method was used to measure the diaphragm deflection profiles at different DC bias. The diaphragm center velocity was measured for different sub-resonant frequencies using a Polytec™ laser Doppler vibrometer that confirms vibration of the diaphragm at different excitation frequencies and bias voltages. Transmit and receive operations of CMUT cells were characterized using a pitch-catch method and a −6 dB fractional bandwidth of 23% was extracted from the received signal in frequency domain. From the measurement, it appears that BCB-based CMUTs offer superior transduction efficiency as compared to silicon nitride or silicon dioxide insulator-based CMUTs, and provide a very uniform deflection profile thus making them a suitable candidate to fabricate highly energy efficient CMUTs. Full article
(This article belongs to the Special Issue Integrated Sensor Arrays and Array Signal Processing)
Open AccessArticle DARAL: A Dynamic and Adaptive Routing Algorithm for Wireless Sensor Networks
Sensors 2016, 16(7), 960; doi:10.3390/s16070960
Received: 16 March 2016 / Revised: 23 May 2016 / Accepted: 15 June 2016 / Published: 24 June 2016
Cited by 3 | PDF Full-text (1912 KB) | HTML Full-text | XML Full-text | Supplementary Files
Abstract
The evolution of Smart City projects is pushing researchers and companies to develop more efficient embedded hardware and also more efficient communication technologies. These communication technologies are the focus of this work, presenting a new routing algorithm based on dynamically-allocated sub-networks and node
[...] Read more.
The evolution of Smart City projects is pushing researchers and companies to develop more efficient embedded hardware and also more efficient communication technologies. These communication technologies are the focus of this work, presenting a new routing algorithm based on dynamically-allocated sub-networks and node roles. Among these features, our algorithm presents a fast set-up time, a reduced overhead and a hierarchical organization, which allows for the application of complex management techniques. This work presents a routing algorithm based on a dynamically-allocated hierarchical clustering, which uses the link quality indicator as a reference parameter, maximizing the network coverage and minimizing the control message overhead and the convergence time. The present work based its test scenario and analysis in the density measure, considered as a node degree. The routing algorithm is compared with some of the most well known routing algorithms for different scenario densities. Full article
(This article belongs to the Special Issue Trusted and Secure Wireless Sensor Network Designs and Deployments)
Open AccessArticle A Novel Low-Cost, Large Curvature Bend Sensor Based on a Bowden-Cable
Sensors 2016, 16(7), 961; doi:10.3390/s16070961
Received: 12 May 2016 / Revised: 14 June 2016 / Accepted: 20 June 2016 / Published: 24 June 2016
Cited by 2 | PDF Full-text (17351 KB) | HTML Full-text | XML Full-text
Abstract
Bend sensors have been developed based on conductive ink, optical fiber, and electronic textiles. Each type has advantages and disadvantages in terms of performance, ease of use, and cost. This study proposes a new and low-cost bend sensor that can measure a wide
[...] Read more.
Bend sensors have been developed based on conductive ink, optical fiber, and electronic textiles. Each type has advantages and disadvantages in terms of performance, ease of use, and cost. This study proposes a new and low-cost bend sensor that can measure a wide range of accumulated bend angles with large curvatures. This bend sensor utilizes a Bowden-cable, which consists of a coil sheath and an inner wire. Displacement changes of the Bowden-cable’s inner wire, when the shape of the sheath changes, have been considered to be a position error in previous studies. However, this study takes advantage of this position error to detect the bend angle of the sheath. The bend angle of the sensor can be calculated from the displacement measurement of the sensing wire using a Hall-effect sensor or a potentiometer. Simulations and experiments have shown that the accumulated bend angle of the sensor is linearly related to the sensor signal, with an R-square value up to 0.9969 and a root mean square error of 2% of the full sensing range. The proposed sensor is not affected by a bend curvature of up to 80.0 m−1, unlike previous bend sensors. The proposed sensor is expected to be useful for various applications, including motion capture devices, wearable robots, surgical devices, or generally any device that requires an affordable and low-cost bend sensor. Full article
(This article belongs to the Section Physical Sensors)
Figures

Open AccessArticle A Real-Time Orbit Determination Method for Smooth Transition from Optical Tracking to Laser Ranging of Debris
Sensors 2016, 16(7), 962; doi:10.3390/s16070962
Received: 29 March 2016 / Revised: 18 June 2016 / Accepted: 20 June 2016 / Published: 24 June 2016
PDF Full-text (1857 KB) | HTML Full-text | XML Full-text
Abstract
A critical requirement to achieve high efficiency of debris laser tracking is to have sufficiently accurate orbit predictions (OP) in both the pointing direction (better than 20 arc seconds) and distance from the tracking station to the debris objects, with the former more
[...] Read more.
A critical requirement to achieve high efficiency of debris laser tracking is to have sufficiently accurate orbit predictions (OP) in both the pointing direction (better than 20 arc seconds) and distance from the tracking station to the debris objects, with the former more important than the latter because of the narrow laser beam. When the two line element (TLE) is used to provide the orbit predictions, the resultant pointing errors are usually on the order of tens to hundreds of arc seconds. In practice, therefore, angular observations of debris objects are first collected using an optical tracking sensor, and then used to guide the laser beam pointing to the objects. The manual guidance may cause interrupts to the laser tracking, and consequently loss of valuable laser tracking data. This paper presents a real-time orbit determination (OD) and prediction method to realize smooth and efficient debris laser tracking. The method uses TLE-computed positions and angles over a short-arc of less than 2 min as observations in an OD process where simplified force models are considered. After the OD convergence, the OP is performed from the last observation epoch to the end of the tracking pass. Simulation and real tracking data processing results show that the pointing prediction errors are usually less than 10″, and the distance errors less than 100 m, therefore, the prediction accuracy is sufficient for the blind laser tracking. Full article
(This article belongs to the Section Remote Sensors)
Open AccessArticle Normalized Metadata Generation for Human Retrieval Using Multiple Video Surveillance Cameras
Sensors 2016, 16(7), 963; doi:10.3390/s16070963
Received: 20 March 2016 / Revised: 16 June 2016 / Accepted: 21 June 2016 / Published: 24 June 2016
PDF Full-text (9821 KB) | HTML Full-text | XML Full-text | Supplementary Files
Abstract
Since it is impossible for surveillance personnel to keep monitoring videos from a multiple camera-based surveillance system, an efficient technique is needed to help recognize important situations by retrieving the metadata of an object-of-interest. In a multiple camera-based surveillance system, an object detected
[...] Read more.
Since it is impossible for surveillance personnel to keep monitoring videos from a multiple camera-based surveillance system, an efficient technique is needed to help recognize important situations by retrieving the metadata of an object-of-interest. In a multiple camera-based surveillance system, an object detected in a camera has a different shape in another camera, which is a critical issue of wide-range, real-time surveillance systems. In order to address the problem, this paper presents an object retrieval method by extracting the normalized metadata of an object-of-interest from multiple, heterogeneous cameras. The proposed metadata generation algorithm consists of three steps: (i) generation of a three-dimensional (3D) human model; (ii) human object-based automatic scene calibration; and (iii) metadata generation. More specifically, an appropriately-generated 3D human model provides the foot-to-head direction information that is used as the input of the automatic calibration of each camera. The normalized object information is used to retrieve an object-of-interest in a wide-range, multiple-camera surveillance system in the form of metadata. Experimental results show that the 3D human model matches the ground truth, and automatic calibration-based normalization of metadata enables a successful retrieval and tracking of a human object in the multiple-camera video surveillance system. Full article
(This article belongs to the Special Issue Advances in Multi-Sensor Information Fusion: Theory and Applications)
Figures

Open AccessArticle A Novel Microfluidic Flow Rate Detection Method Based on Surface Plasmon Resonance Temperature Imaging
Sensors 2016, 16(7), 964; doi:10.3390/s16070964
Received: 29 April 2016 / Revised: 7 June 2016 / Accepted: 21 June 2016 / Published: 24 June 2016
Cited by 4 | PDF Full-text (4360 KB) | HTML Full-text | XML Full-text
Abstract
A novel microfluidic flow rate detection method based on surface plasmon resonance (SPR) temperature imaging is proposed. The measurement is performed by space-resolved SPR imaging of the flow induced temperature variations. Theoretical simulations and analysis were performed to demonstrate a proof of concept
[...] Read more.
A novel microfluidic flow rate detection method based on surface plasmon resonance (SPR) temperature imaging is proposed. The measurement is performed by space-resolved SPR imaging of the flow induced temperature variations. Theoretical simulations and analysis were performed to demonstrate a proof of concept using this approach. Experiments were implemented and results showed that water flow rates within a wide range of tens to hundreds of μL/min could be detected. The flow rate sensor is resistant to disturbances and can be easily integrated into microfluidic lab-on-chip systems. Full article
(This article belongs to the Special Issue Microfluidics-Based Microsystem Integration Research)
Figures

Open AccessArticle Intelligent Multisensor Prodder for Training Operators in Humanitarian Demining
Sensors 2016, 16(7), 965; doi:10.3390/s16070965
Received: 23 May 2016 / Accepted: 20 June 2016 / Published: 24 June 2016
Cited by 1 | PDF Full-text (15130 KB) | HTML Full-text | XML Full-text | Supplementary Files
Abstract
Manual prodding is still one of the most utilized procedures for identifying buried landmines during humanitarian demining activities. However, due to the high number of accidents reported during its practice, it is considered an outmoded and risky procedure and there is a general
[...] Read more.
Manual prodding is still one of the most utilized procedures for identifying buried landmines during humanitarian demining activities. However, due to the high number of accidents reported during its practice, it is considered an outmoded and risky procedure and there is a general consensus about the need of introducing upgrades for enhancing the safety of human operators. With the aim of contributing to reduce the number of demining accidents, this paper presents an intelligent multisensory system for training operators in the use of prodders. The proposed tool is able to provide to deminers useful information in two critical issues: (a) the amount of force exerted on the target and if it is greater than the safe limit and, (b) to alert them when the angle of insertion of the prodder is approaching or exceeding a certain dangerous limit. Results of preliminary tests show the feasibility and reliability of the proposed design and highlight the potential benefits of the tool. Full article
Figures

Open AccessArticle A New Sparse Adaptive Channel Estimation Method Based on Compressive Sensing for FBMC/OQAM Transmission Network
Sensors 2016, 16(7), 966; doi:10.3390/s16070966
Received: 17 April 2016 / Revised: 19 June 2016 / Accepted: 21 June 2016 / Published: 24 June 2016
PDF Full-text (2678 KB) | HTML Full-text | XML Full-text
Abstract
The conventional channel estimation methods based on a preamble for filter bank multicarrier with offset quadrature amplitude modulation (FBMC/OQAM) systems in mobile-to-mobile sensor networks are inefficient. By utilizing the intrinsicsparsity of wireless channels, channel estimation is researched as a compressive sensing (CS) problem
[...] Read more.
The conventional channel estimation methods based on a preamble for filter bank multicarrier with offset quadrature amplitude modulation (FBMC/OQAM) systems in mobile-to-mobile sensor networks are inefficient. By utilizing the intrinsicsparsity of wireless channels, channel estimation is researched as a compressive sensing (CS) problem to improve the estimation performance. In this paper, an AdaptiveRegularized Compressive Sampling Matching Pursuit (ARCoSaMP) algorithm is proposed. Unlike anterior greedy algorithms, the new algorithm can achieve the accuracy of reconstruction by choosing the support set adaptively, and exploiting the regularization process, which realizes the second selecting of atoms in the support set although the sparsity of the channel is unknown. Simulation results show that CS-based methods obtain significant channel estimation performance improvement compared to that of conventional preamble-based methods. The proposed ARCoSaMP algorithm outperforms the conventional sparse adaptive matching pursuit (SAMP) algorithm. ARCoSaMP provides even more interesting results than the mostadvanced greedy compressive sampling matching pursuit (CoSaMP) algorithm without a prior sparse knowledge of the channel. Full article
(This article belongs to the Section Sensor Networks)
Open AccessArticle Comparison of Metal-Backed Free-Space and Open-Ended Coaxial Probe Techniques for the Dielectric Characterization of Aeronautical Composites
Sensors 2016, 16(7), 967; doi:10.3390/s16070967
Received: 31 March 2016 / Revised: 17 June 2016 / Accepted: 20 June 2016 / Published: 24 June 2016
Cited by 2 | PDF Full-text (6893 KB) | HTML Full-text | XML Full-text
Abstract
The trend in the last few decades is that current unmanned aerial vehicles are completely made of composite materials rather than metallic, such as carbon-fiber or fiberglass composites. From the electromagnetic point of view, this fact forces engineers and scientists to assess how
[...] Read more.
The trend in the last few decades is that current unmanned aerial vehicles are completely made of composite materials rather than metallic, such as carbon-fiber or fiberglass composites. From the electromagnetic point of view, this fact forces engineers and scientists to assess how these materials may affect their radar response or their electronics in terms of electromagnetic compatibility. In order to evaluate this, electromagnetic characterization of different composite materials has become a need. Several techniques exist to perform this characterization, all of them based on the utilization of different sensors for measuring different parameters. In this paper, an implementation of the metal-backed free-space technique, based on the employment of antenna probes, is utilized for the characterization of composite materials that belong to an actual drone. Their extracted properties are compared with those given by a commercial solution, an open-ended coaxial probe (OECP). The discrepancies found between both techniques along with a further evaluation of the methodologies, including measurements with a split-cavity resonator, conclude that the implemented free-space technique provides more reliable results for this kind of composites than the OECP technique. Full article
Figures

Open AccessArticle Combining Charge Couple Devices and Rate Sensors for the Feedforward Control System of a Charge Coupled Device Tracking Loop
Sensors 2016, 16(7), 968; doi:10.3390/s16070968
Received: 23 April 2016 / Revised: 21 June 2016 / Accepted: 21 June 2016 / Published: 25 June 2016
Cited by 3 | PDF Full-text (2304 KB) | HTML Full-text | XML Full-text
Abstract
A rate feed forward control-based sensor fusion is proposed to improve the closed-loop performance for a charge couple device (CCD) tracking loop. The target trajectory is recovered by combining line of sight (LOS) errors from the CCD and the angular rate from a
[...] Read more.
A rate feed forward control-based sensor fusion is proposed to improve the closed-loop performance for a charge couple device (CCD) tracking loop. The target trajectory is recovered by combining line of sight (LOS) errors from the CCD and the angular rate from a fiber-optic gyroscope (FOG). A Kalman filter based on the Singer acceleration model utilizes the reconstructive target trajectory to estimate the target velocity. Different from classical feed forward control, additive feedback loops are inevitably added to the original control loops due to the fact some closed-loop information is used. The transfer function of the Kalman filter in the frequency domain is built for analyzing the closed loop stability. The bandwidth of the Kalman filter is the major factor affecting the control stability and close-loop performance. Both simulations and experiments are provided to demonstrate the benefits of the proposed algorithm. Full article
(This article belongs to the Section Physical Sensors)
Open AccessArticle Sensor Network-Based and User-Friendly User Location Discovery for Future Smart Homes
Sensors 2016, 16(7), 969; doi:10.3390/s16070969
Received: 23 March 2016 / Revised: 6 June 2016 / Accepted: 20 June 2016 / Published: 27 June 2016
Cited by 1 | PDF Full-text (1196 KB) | HTML Full-text | XML Full-text
Abstract
User location is crucial context information for future smart homes where many location based services will be proposed. This location necessarily means that User Location Discovery (ULD) will play an important role in future smart homes. Concerns about privacy and the need to
[...] Read more.
User location is crucial context information for future smart homes where many location based services will be proposed. This location necessarily means that User Location Discovery (ULD) will play an important role in future smart homes. Concerns about privacy and the need to carry a mobile or a tag device within a smart home currently make conventional ULD systems uncomfortable for users. Future smart homes will need a ULD system to consider these challenges. This paper addresses the design of such a ULD system for context-aware services in future smart homes stressing the following challenges: (i) users’ privacy; (ii) device-/tag-free; and (iii) fault tolerance and accuracy. On the other hand, emerging new technologies, such as the Internet of Things, embedded systems, intelligent devices and machine-to-machine communication, are penetrating into our daily life with more and more sensors available for use in our homes. Considering this opportunity, we propose a ULD system that is capitalizing on the prevalence of sensors for the home while satisfying the aforementioned challenges. The proposed sensor network-based and user-friendly ULD system relies on different types of inexpensive sensors, as well as a context broker with a fuzzy-based decision-maker. The context broker receives context information from different types of sensors and evaluates that data using the fuzzy set theory. We demonstrate the performance of the proposed system by illustrating a use case, utilizing both an analytical model and simulation. Full article
(This article belongs to the Special Issue Smart City: Vision and Reality)
Open AccessArticle Non-Contact Measurement of the Spectral Emissivity through Active/Passive Synergy of CO2 Laser at 10.6 µm and 102F FTIR (Fourier Transform Infrared) Spectrometer
Sensors 2016, 16(7), 970; doi:10.3390/s16070970
Received: 11 April 2016 / Revised: 11 June 2016 / Accepted: 21 June 2016 / Published: 24 June 2016
PDF Full-text (1861 KB) | HTML Full-text | XML Full-text
Abstract
In the inversion of land surface temperature (LST) from satellite data, obtaining the information on land surface emissivity is most challenging. How to solve both the emissivity and the LST from the underdetermined equations for thermal infrared radiation is a hot research topic
[...] Read more.
In the inversion of land surface temperature (LST) from satellite data, obtaining the information on land surface emissivity is most challenging. How to solve both the emissivity and the LST from the underdetermined equations for thermal infrared radiation is a hot research topic related to quantitative thermal infrared remote sensing. The academic research and practical applications based on the temperature-emissivity retrieval algorithms show that directly measuring the emissivity of objects at a fixed thermal infrared waveband is an important way to close the underdetermined equations for thermal infrared radiation. Based on the prior research results of both the authors and others, this paper proposes a new approach of obtaining the spectral emissivity of the object at 8–14 µm with a single-band CO2 laser at 10.6 µm and a 102F FTIR spectrometer. Through experiments, the spectral emissivity of several key samples, including aluminum plate, iron plate, copper plate, marble plate, rubber sheet, and paper board, at 8–14 µm is obtained, and the measured data are basically consistent with the hemispherical emissivity measurement by a Nicolet iS10 FTIR spectrometer for the same objects. For the rough surface of materials, such as marble and rusty iron, the RMSE of emissivity is below 0.05. The differences in the field of view angle and in the measuring direction between the Nicolet FTIR method and the method proposed in the paper, and the heterogeneity in the degree of oxidation, polishing and composition of the samples, are the main reasons for the differences of the emissivities between the two methods. Full article
(This article belongs to the Section Remote Sensors)
Figures

Open AccessArticle Sensitivity Analysis of the Scattering-Based SARBM3D Despeckling Algorithm
Sensors 2016, 16(7), 971; doi:10.3390/s16070971
Received: 5 April 2016 / Revised: 2 June 2016 / Accepted: 21 June 2016 / Published: 25 June 2016
Cited by 2 | PDF Full-text (8315 KB) | HTML Full-text | XML Full-text
Abstract
Synthetic Aperture Radar (SAR) imagery greatly suffers from multiplicative speckle noise, typical of coherent image acquisition sensors, such as SAR systems. Therefore, a proper and accurate despeckling preprocessing step is almost mandatory to aid the interpretation and processing of SAR data by human
[...] Read more.
Synthetic Aperture Radar (SAR) imagery greatly suffers from multiplicative speckle noise, typical of coherent image acquisition sensors, such as SAR systems. Therefore, a proper and accurate despeckling preprocessing step is almost mandatory to aid the interpretation and processing of SAR data by human users and computer algorithms, respectively. Very recently, a scattering-oriented version of the popular SAR Block-Matching 3D (SARBM3D) despeckling filter, named Scattering-Based (SB)-SARBM3D, was proposed. The new filter is based on the a priori knowledge of the local topography of the scene. In this paper, an experimental sensitivity analysis of the above-mentioned despeckling algorithm is carried out, and the main results are shown and discussed. In particular, the role of both electromagnetic and geometrical parameters of the surface and the impact of its scattering behavior are investigated. Furthermore, a comprehensive sensitivity analysis of the SB-SARBM3D filter against the Digital Elevation Model (DEM) resolution and the SAR image-DEM coregistration step is also provided. The sensitivity analysis shows a significant robustness of the algorithm against most of the surface parameters, while the DEM resolution plays a key role in the despeckling process. Furthermore, the SB-SARBM3D algorithm outperforms the original SARBM3D in the presence of the most realistic scattering behaviors of the surface. An actual scenario is also presented to assess the DEM role in real-life conditions. Full article
Open AccessArticle An Approach to the Use of Depth Cameras for Weed Volume Estimation
Sensors 2016, 16(7), 972; doi:10.3390/s16070972
Received: 4 May 2016 / Revised: 12 June 2016 / Accepted: 22 June 2016 / Published: 25 June 2016
Cited by 5 | PDF Full-text (2871 KB) | HTML Full-text | XML Full-text
Abstract
The use of depth cameras in precision agriculture is increasing day by day. This type of sensor has been used for the plant structure characterization of several crops. However, the discrimination of small plants, such as weeds, is still a challenge within agricultural
[...] Read more.
The use of depth cameras in precision agriculture is increasing day by day. This type of sensor has been used for the plant structure characterization of several crops. However, the discrimination of small plants, such as weeds, is still a challenge within agricultural fields. Improvements in the new Microsoft Kinect v2 sensor can capture the details of plants. The use of a dual methodology using height selection and RGB (Red, Green, Blue) segmentation can separate crops, weeds, and soil. This paper explores the possibilities of this sensor by using Kinect Fusion algorithms to reconstruct 3D point clouds of weed-infested maize crops under real field conditions. The processed models showed good consistency among the 3D depth images and soil measurements obtained from the actual structural parameters. Maize plants were identified in the samples by height selection of the connected faces and showed a correlation of 0.77 with maize biomass. The lower height of the weeds made RGB recognition necessary to separate them from the soil microrelief of the samples, achieving a good correlation of 0.83 with weed biomass. In addition, weed density showed good correlation with volumetric measurements. The canonical discriminant analysis showed promising results for classification into monocots and dictos. These results suggest that estimating volume using the Kinect methodology can be a highly accurate method for crop status determination and weed detection. It offers several possibilities for the automation of agricultural processes by the construction of a new system integrating these sensors and the development of algorithms to properly process the information provided by them. Full article
Open AccessArticle Comparison and Analysis of Geometric Correction Models of Spaceborne SAR
Sensors 2016, 16(7), 973; doi:10.3390/s16070973
Received: 16 March 2016 / Revised: 16 June 2016 / Accepted: 22 June 2016 / Published: 25 June 2016
Cited by 1 | PDF Full-text (4177 KB) | HTML Full-text | XML Full-text
Abstract
Following the development of synthetic aperture radar (SAR), SAR images have become increasingly common. Many researchers have conducted large studies on geolocation models, but little work has been conducted on the available models for the geometric correction of SAR images of different terrain.
[...] Read more.
Following the development of synthetic aperture radar (SAR), SAR images have become increasingly common. Many researchers have conducted large studies on geolocation models, but little work has been conducted on the available models for the geometric correction of SAR images of different terrain. To address the terrain issue, four different models were compared and are described in this paper: a rigorous range-doppler (RD) model, a rational polynomial coefficients (RPC) model, a revised polynomial (PM) model and an elevation derivation (EDM) model. The results of comparisons of the geolocation capabilities of the models show that a proper model for a SAR image of a specific terrain can be determined. A solution table was obtained to recommend a suitable model for users. Three TerraSAR-X images, two ALOS-PALSAR images and one Envisat-ASAR image were used for the experiment, including flat terrain and mountain terrain SAR images as well as two large area images. Geolocation accuracies of the models for different terrain SAR images were computed and analyzed. The comparisons of the models show that the RD model was accurate but was the least efficient; therefore, it is not the ideal model for real-time implementations. The RPC model is sufficiently accurate and efficient for the geometric correction of SAR images of flat terrain, whose precision is below 0.001 pixels. The EDM model is suitable for the geolocation of SAR images of mountainous terrain, and its precision can reach 0.007 pixels. Although the PM model does not produce results as precise as the other models, its efficiency is excellent and its potential should not be underestimated. With respect to the geometric correction of SAR images over large areas, the EDM model has higher accuracy under one pixel, whereas the RPC model consumes one third of the time of the EDM model. Full article
Open AccessArticle Mobility-Aware Caching and Computation Offloading in 5G Ultra-Dense Cellular Networks
Sensors 2016, 16(7), 974; doi:10.3390/s16070974
Received: 6 April 2016 / Revised: 18 June 2016 / Accepted: 20 June 2016 / Published: 25 June 2016
Cited by 22 | PDF Full-text (653 KB) | HTML Full-text | XML Full-text
Abstract
Recent trends show that Internet traffic is increasingly dominated by content, which is accompanied by the exponential growth of traffic. To cope with this phenomena, network caching is introduced to utilize the storage capacity of diverse network devices. In this paper, we first
[...] Read more.
Recent trends show that Internet traffic is increasingly dominated by content, which is accompanied by the exponential growth of traffic. To cope with this phenomena, network caching is introduced to utilize the storage capacity of diverse network devices. In this paper, we first summarize four basic caching placement strategies, i.e., local caching, Device-to-Device (D2D) caching, Small cell Base Station (SBS) caching and Macrocell Base Station (MBS) caching. However, studies show that so far, much of the research has ignored the impact of user mobility. Therefore, taking the effect of the user mobility into consideration, we proposes a joint mobility-aware caching and SBS density placement scheme (MS caching). In addition, differences and relationships between caching and computation offloading are discussed. We present a design of a hybrid computation offloading and support it with experimental results, which demonstrate improved performance in terms of energy cost. Finally, we discuss the design of an incentive mechanism by considering network dynamics, differentiated user’s quality of experience (QoE) and the heterogeneity of mobile terminals in terms of caching and computing capabilities. Full article
(This article belongs to the Special Issue Millimeter Wave Wireless Communications and Networks)
Figures

Open AccessArticle Model Study of the Influence of Ambient Temperature and Installation Types on Surface Temperature Measurement by Using a Fiber Bragg Grating Sensor
Sensors 2016, 16(7), 975; doi:10.3390/s16070975
Received: 2 April 2016 / Revised: 21 June 2016 / Accepted: 21 June 2016 / Published: 1 July 2016
Cited by 2 | PDF Full-text (4505 KB) | HTML Full-text | XML Full-text
Abstract
Surface temperature is an important parameter in clinical diagnosis, equipment state control, and environmental monitoring fields. The Fiber Bragg Grating (FBG) temperature sensor possesses numerous significant advantages over conventional electrical sensors, thus it is an ideal choice to achieve high-accuracy surface temperature measurements.
[...] Read more.
Surface temperature is an important parameter in clinical diagnosis, equipment state control, and environmental monitoring fields. The Fiber Bragg Grating (FBG) temperature sensor possesses numerous significant advantages over conventional electrical sensors, thus it is an ideal choice to achieve high-accuracy surface temperature measurements. However, the effects of the ambient temperature and installation types on the measurement of surface temperature are often overlooked. A theoretical analysis is implemented and a thermal transfer model of a surface FBG sensor is established. The theoretical and simulated analysis shows that both substrate strain and the temperature difference between the fiber core and hot surface are the most important factors which affect measurement accuracy. A surface-type temperature standard setup is proposed to study the measurement error of the FBG temperature sensor. Experimental results show that there are two effects influencing measurement results. One is the “gradient effect”. This results in a positive linear error with increasing surface temperature. Another is the “substrate effect”. This results in a negative non-linear error with increasing surface temperature. The measurement error of the FBG sensor with single-ended fixation are determined by the gradient effect and is a linear error. It is not influenced by substrate expansion. Thus, it can be compensated easily. The measurement errors of the FBG sensor with double-ended fixation are determined by the two effects and the substrate effect is dominant. The measurement error change trend of the FBG sensor with fully-adhered fixation is similar to that with double-ended fixation. The adhesive layer can reduce the two effects and measurement error. The fully-adhered fixation has lower error, however, it is easily affected by substrate strain. Due to its linear error and strain-resistant characteristics, the single-ended fixation will play an important role in the FBG sensor encapsulation design field in the near future. Full article
(This article belongs to the Special Issue Optical Fiber Sensors 2016)
Figures

Open AccessArticle Smart Sensing System for the Prognostic Monitoring of Bone Health
Sensors 2016, 16(7), 976; doi:10.3390/s16070976
Received: 8 May 2016 / Revised: 21 June 2016 / Accepted: 22 June 2016 / Published: 24 June 2016
PDF Full-text (3989 KB) | HTML Full-text | XML Full-text
Abstract
The objective of this paper is to report a novel non-invasive, real-time, and label-free smart assay technique for the prognostic detection of bone loss by electrochemical impedance spectroscopy (EIS). The proposed system incorporated an antibody-antigen-based sensor functionalization to induce selectivity for the C-terminal
[...] Read more.
The objective of this paper is to report a novel non-invasive, real-time, and label-free smart assay technique for the prognostic detection of bone loss by electrochemical impedance spectroscopy (EIS). The proposed system incorporated an antibody-antigen-based sensor functionalization to induce selectivity for the C-terminal telopeptide type one collagen (CTx-I) molecules—a bone loss biomarker. Streptavidin agarose was immobilized on the sensing area of a silicon substrate-based planar sensor, patterned with gold interdigital electrodes, to capture the antibody-antigen complex. Calibration experiments were conducted with various known CTx-I concentrations in a buffer solution to obtain a reference curve that was used to quantify the concentration of an analyte in the unknown serum samples. Multivariate chemometric analyses were done to determine the performance viability of the developed system. The analyses suggested that a frequency of 710 Hz is the most discriminating regarding the system sensitivity. A detection limit of 0.147 ng/mL was achieved for the proposed sensor and the corresponding reference curve was linear in the range of 0.147 ng/mL to 2.669 ng/mL. Two sheep blood samples were tested by the developed technique and the results were validated using enzyme-linked immunosorbent assay (ELISA). The results from the proposed technique match those from the ELISA. Full article
(This article belongs to the Special Issue Sensing Technology for Healthcare System)
Figures

Open AccessCommunication Real-Time Two-Dimensional Mapping of Relative Local Surface Temperatures with a Thin-Film Sensor Array
Sensors 2016, 16(7), 977; doi:10.3390/s16070977
Received: 14 March 2016 / Revised: 8 June 2016 / Accepted: 9 June 2016 / Published: 25 June 2016
Cited by 4 | PDF Full-text (3095 KB) | HTML Full-text | XML Full-text | Supplementary Files
Abstract
Dynamic mapping of an object’s local temperature distribution may offer valuable information for failure analysis, system control and improvement. In this letter we present a computerized measurement system which is equipped with a hybrid, low-noise mechanical-electrical multiplexer for real-time two-dimensional (2D) mapping of
[...] Read more.
Dynamic mapping of an object’s local temperature distribution may offer valuable information for failure analysis, system control and improvement. In this letter we present a computerized measurement system which is equipped with a hybrid, low-noise mechanical-electrical multiplexer for real-time two-dimensional (2D) mapping of surface temperatures. We demonstrate the performance of the system on a device embedded with 32 pieces of built-in Cr-Pt thin-film thermocouples arranged in a 4 × 8 matrix. The system can display a continuous 2D mapping movie of relative temperatures with a time interval around 1 s. This technique may find applications in a variety of practical devices and systems. Full article
(This article belongs to the Section Physical Sensors)
Open AccessArticle Comparison of Phase-Based 3D Near-Field Source Localization Techniques for UHF RFID
Sensors 2016, 16(7), 978; doi:10.3390/s16070978
Received: 23 March 2016 / Revised: 3 June 2016 / Accepted: 21 June 2016 / Published: 25 June 2016
Cited by 2 | PDF Full-text (2369 KB) | HTML Full-text | XML Full-text
Abstract
In this paper, we present multiple techniques for phase-based narrowband backscatter tag localization in three-dimensional space with planar antenna arrays or synthetic apertures. Beamformer and MUSIC localization algorithms, known from near-field source localization and direction-of-arrival estimation, are applied to the 3D backscatter scenario
[...] Read more.
In this paper, we present multiple techniques for phase-based narrowband backscatter tag localization in three-dimensional space with planar antenna arrays or synthetic apertures. Beamformer and MUSIC localization algorithms, known from near-field source localization and direction-of-arrival estimation, are applied to the 3D backscatter scenario and their performance in terms of localization accuracy is evaluated. We discuss the impact of different transceiver modes known from the literature, which evaluate different send and receive antenna path combinations for a single localization, as in multiple input multiple output (MIMO) systems. Furthermore, we propose a new Singledimensional-MIMO (S-MIMO) transceiver mode, which is especially suited for use with mobile robot systems. Monte-Carlo simulations based on a realistic multipath error model ensure spatial correlation of the simulated signals, and serve to critically appraise the accuracies of the different localization approaches. A synthetic uniform rectangular array created by a robotic arm is used to evaluate selected localization techniques. We use an Ultra High Frequency (UHF) Radiofrequency Identification (RFID) setup to compare measurements with the theory and simulation. The results show how a mean localization accuracy of less than 30 cm can be reached in an indoor environment. Further simulations demonstrate how the distance between aperture and tag affects the localization accuracy and how the size and grid spacing of the rectangular array need to be adapted to improve the localization accuracy down to orders of magnitude in the centimeter range, and to maximize array efficiency in terms of localization accuracy per number of elements. Full article
(This article belongs to the Section Remote Sensors)
Figures

Open AccessArticle Parameters Identification of Fluxgate Magnetic Core Adopting the Biogeography-Based Optimization Algorithm
Sensors 2016, 16(7), 979; doi:10.3390/s16070979
Received: 15 May 2016 / Revised: 14 June 2016 / Accepted: 17 June 2016 / Published: 25 June 2016
Cited by 4 | PDF Full-text (2002 KB) | HTML Full-text | XML Full-text
Abstract
The main part of the magnetic fluxgate sensor is the magnetic core, the hysteresis characteristic of which affects the performance of the sensor. When the fluxgate sensors are modelled for design purposes, an accurate model of hysteresis characteristic of the cores is necessary
[...] Read more.
The main part of the magnetic fluxgate sensor is the magnetic core, the hysteresis characteristic of which affects the performance of the sensor. When the fluxgate sensors are modelled for design purposes, an accurate model of hysteresis characteristic of the cores is necessary to achieve good agreement between modelled and experimental data. The Jiles-Atherton model is simple and can reflect the hysteresis properties of the magnetic material precisely, which makes it widely used in hysteresis modelling and simulation of ferromagnetic materials. However, in practice, it is difficult to determine the parameters accurately owing to the sensitivity of the parameters. In this paper, the Biogeography-Based Optimization (BBO) algorithm is applied to identify the Jiles-Atherton model parameters. To enhance the performances of the BBO algorithm such as global search capability, search accuracy and convergence rate, an improved Biogeography-Based Optimization (IBBO) algorithm is put forward by using Arnold map and mutation strategy of Differential Evolution (DE) algorithm. Simulation results show that IBBO algorithm is superior to Genetic Algorithm (GA), Particle Swarm Optimization (PSO) algorithm, Differential Evolution algorithm and BBO algorithm in identification accuracy and convergence rate. The IBBO algorithm is applied to identify Jiles-Atherton model parameters of selected permalloy. The simulation hysteresis loop is in high agreement with experimental data. Using permalloy as core of fluxgate probe, the simulation output is consistent with experimental output. The IBBO algorithm can identify the parameters of Jiles-Atherton model accurately, which provides a basis for the precise analysis and design of instruments and equipment with magnetic core. Full article
(This article belongs to the Section Physical Sensors)
Open AccessArticle On Curating Multimodal Sensory Data for Health and Wellness Platforms
Sensors 2016, 16(7), 980; doi:10.3390/s16070980
Received: 4 February 2016 / Revised: 14 June 2016 / Accepted: 21 June 2016 / Published: 27 June 2016
Cited by 6 | PDF Full-text (6307 KB) | HTML Full-text | XML Full-text
Abstract
In recent years, the focus of healthcare and wellness technologies has shown a significant shift towards personal vital signs devices. The technology has evolved from smartphone-based wellness applications to fitness bands and smartwatches. The novelty of these devices is the accumulation of activity
[...] Read more.
In recent years, the focus of healthcare and wellness technologies has shown a significant shift towards personal vital signs devices. The technology has evolved from smartphone-based wellness applications to fitness bands and smartwatches. The novelty of these devices is the accumulation of activity data as their users go about their daily life routine. However, these implementations are device specific and lack the ability to incorporate multimodal data sources. Data accumulated in their usage does not offer rich contextual information that is adequate for providing a holistic view of a user’s lifelog. As a result, making decisions and generating recommendations based on this data are single dimensional. In this paper, we present our Data Curation Framework (DCF) which is device independent and accumulates a user’s sensory data from multimodal data sources in real time. DCF curates the context of this accumulated data over the user’s lifelog. DCF provides rule-based anomaly detection over this context-rich lifelog in real time. To provide computation and persistence over the large volume of sensory data, DCF utilizes the distributed and ubiquitous environment of the cloud platform. DCF has been evaluated for its performance, correctness, ability to detect complex anomalies, and management support for a large volume of sensory data. Full article
(This article belongs to the collection Sensors for Globalized Healthy Living and Wellbeing)
Open AccessArticle An Efficient Bayesian Approach to Exploit the Context of Object-Action Interaction for Object Recognition
Sensors 2016, 16(7), 981; doi:10.3390/s16070981
Received: 8 March 2016 / Revised: 22 May 2016 / Accepted: 23 June 2016 / Published: 25 June 2016
PDF Full-text (4977 KB) | HTML Full-text | XML Full-text
Abstract
This research features object recognition that exploits the context of object-action interaction to enhance the recognition performance. Since objects have specific usages, and human actions corresponding to these usages can be associated with these objects, human actions can provide effective information for object
[...] Read more.
This research features object recognition that exploits the context of object-action interaction to enhance the recognition performance. Since objects have specific usages, and human actions corresponding to these usages can be associated with these objects, human actions can provide effective information for object recognition. When objects from different categories have similar appearances, the human action associated with each object can be very effective in resolving ambiguities related to recognizing these objects. We propose an efficient method that integrates human interaction with objects into a form of object recognition. We represent human actions by concatenating poselet vectors computed from key frames and learn the probabilities of objects and actions using random forest and multi-class AdaBoost algorithms. Our experimental results show that poselet representation of human actions is quite effective in integrating human action information into object recognition. Full article
(This article belongs to the Section Physical Sensors)
Open AccessArticle Object Occlusion Detection Using Automatic Camera Calibration for a Wide-Area Video Surveillance System
Sensors 2016, 16(7), 982; doi:10.3390/s16070982
Received: 3 May 2016 / Revised: 16 June 2016 / Accepted: 23 June 2016 / Published: 25 June 2016
Cited by 1 | PDF Full-text (24948 KB) | HTML Full-text | XML Full-text
Abstract
This paper presents an object occlusion detection algorithm using object depth information that is estimated by automatic camera calibration. The object occlusion problem is a major factor to degrade the performance of object tracking and recognition. To detect an object occlusion, the proposed
[...] Read more.
This paper presents an object occlusion detection algorithm using object depth information that is estimated by automatic camera calibration. The object occlusion problem is a major factor to degrade the performance of object tracking and recognition. To detect an object occlusion, the proposed algorithm consists of three steps: (i) automatic camera calibration using both moving objects and a background structure; (ii) object depth estimation; and (iii) detection of occluded regions. The proposed algorithm estimates the depth of the object without extra sensors but with a generic red, green and blue (RGB) camera. As a result, the proposed algorithm can be applied to improve the performance of object tracking and object recognition algorithms for video surveillance systems. Full article
(This article belongs to the Special Issue Imaging: Sensors and Technologies) Printed Edition available
Open AccessArticle Design of Miniaturized Dual-Band Microstrip Antenna for WLAN Application
Sensors 2016, 16(7), 983; doi:10.3390/s16070983
Received: 9 April 2016 / Revised: 14 June 2016 / Accepted: 22 June 2016 / Published: 27 June 2016
Cited by 4 | PDF Full-text (1085 KB) | HTML Full-text | XML Full-text
Abstract
Wireless local area network (WLAN) is a technology that combines computer network with wireless communication technology. The 2.4 GHz and 5 GHz frequency bands in the Industrial Scientific Medical (ISM) band can be used in the WLAN environment. Because of the development of
[...] Read more.
Wireless local area network (WLAN) is a technology that combines computer network with wireless communication technology. The 2.4 GHz and 5 GHz frequency bands in the Industrial Scientific Medical (ISM) band can be used in the WLAN environment. Because of the development of wireless communication technology and the use of the frequency bands without the need for authorization, the application of WLAN is becoming more and more extensive. As the key part of the WLAN system, the antenna must also be adapted to the development of WLAN communication technology. This paper designs two new dual-frequency microstrip antennas with the use of electromagnetic simulation software—High Frequency Structure Simulator (HFSS). The two antennas adopt ordinary FR4 material as a dielectric substrate, with the advantages of low cost and small size. The first antenna adopts microstrip line feeding, and the antenna radiation patch is composed of a folded T-shaped radiating dipole which reduces the antenna size, and two symmetrical rectangular patches located on both sides of the T-shaped radiating patch. The second antenna is a microstrip patch antenna fed by coaxial line, and the size of the antenna is diminished by opening a stepped groove on the two edges of the patch and a folded slot inside the patch. Simulation experiments prove that the two designed antennas have a higher gain and a favourable transmission characteristic in the working frequency range, which is in accordance with the requirements of WLAN communication. Full article
Open AccessArticle A MAC Protocol to Support Monitoring of Underwater Spaces
Sensors 2016, 16(7), 984; doi:10.3390/s16070984
Received: 27 April 2016 / Revised: 28 May 2016 / Accepted: 3 June 2016 / Published: 27 June 2016
Cited by 2 | PDF Full-text (1011 KB) | HTML Full-text | XML Full-text
Abstract
Underwater sensor networks are becoming an important field of research, because of their everyday increasing application scope. Examples of their application areas are environmental and pollution monitoring (mainly oil spills), oceanographic data collection, support for submarine geolocalization, ocean sampling and early tsunamis alert.
[...] Read more.
Underwater sensor networks are becoming an important field of research, because of their everyday increasing application scope. Examples of their application areas are environmental and pollution monitoring (mainly oil spills), oceanographic data collection, support for submarine geolocalization, ocean sampling and early tsunamis alert. The challenge of performing underwater communications is well known, provided that radio signals are useless in this medium, and a wired solution is too expensive. Therefore, the sensors in these networks transmit their information using acoustic signals that propagate well under water. This data transmission type not only brings an opportunity, but also several challenges to the implementation of these networks, e.g., in terms of energy consumption, data transmission and signal interference. In order to help advance the knowledge in the design and implementation of these networks for monitoring underwater spaces, this paper proposes a MAC protocol for acoustic communications between the nodes, based on a self-organized time division multiple access mechanism. The proposal was evaluated using simulations of a real monitoring scenario, and the obtained results are highly encouraging. Full article
(This article belongs to the Special Issue Selected Papers from UCAmI, IWAAL and AmIHEALTH 2015)
Figures

Open AccessArticle Time and Energy Efficient Relay Transmission for Multi-Hop Wireless Sensor Networks
Sensors 2016, 16(7), 985; doi:10.3390/s16070985
Received: 5 March 2016 / Revised: 20 June 2016 / Accepted: 23 June 2016 / Published: 27 June 2016
Cited by 1 | PDF Full-text (10243 KB) | HTML Full-text | XML Full-text
Abstract
The IEEE 802.15.4 standard is widely recognized as one of the most successful enabling technologies for short range low rate wireless communications and it is used in IoT applications. It covers all the details related to the MAC and PHY layers of the
[...] Read more.
The IEEE 802.15.4 standard is widely recognized as one of the most successful enabling technologies for short range low rate wireless communications and it is used in IoT applications. It covers all the details related to the MAC and PHY layers of the IoT protocol stack. Due to the nature of IoT, the wireless sensor networks are autonomously self-organized networks without infrastructure support. One of the issues in IoT is the network scalability. To address this issue, it is necessary to support the multi-hop topology. The IEEE 802.15.4 network can support a star, peer-to-peer, or cluster-tree topology. One of the IEEE 802.15.4 topologies suited for the high predictability of performance guarantees and energy efficient behavior is a cluster-tree topology where sensor nodes can switch off their transceivers and go into a sleep state to save energy. However, the IEEE 802.15.4 cluster-tree topology may not be able to provide sufficient bandwidth for the increased traffic load and the additional information may not be delivered successfully. The common drawback of the existing approaches is that they do not address the poor bandwidth utilization problem in IEEE 802.15.4 cluster-tree networks, so it is difficult to increase the network performance. Therefore, to solve this problem in this paper we study a relay transmission protocol based on the standard protocol in the IEEE 802.15.4 MAC. In the proposed scheme, the coordinators can relay data frames to their parent devices or their children devices without contention and can provide bandwidth for the increased traffic load or the number of devices. We also evaluate the performance of the proposed scheme through simulation. The simulation results demonstrate that the proposed scheme can improve the reliability, the end-to-end delay, and the energy consumption. Full article
(This article belongs to the Section Sensor Networks)
Open AccessArticle A Flexible Optical pH Sensor Based on Polysulfone Membranes Coated with pH-Responsive Polyaniline Nanofibers
Sensors 2016, 16(7), 986; doi:10.3390/s16070986
Received: 9 March 2016 / Revised: 29 May 2016 / Accepted: 14 June 2016 / Published: 27 June 2016
Cited by 2 | PDF Full-text (4610 KB) | HTML Full-text | XML Full-text
Abstract
A new optical pH sensor based on polysulfone (PSU) and polyaniline (PANI) was developed. A transparent and flexible PSU membrane was employed as a support. The electrically conductive and pH-responsive PANI was deposited onto the membrane surface by in situ chemical oxidative polymerization
[...] Read more.
A new optical pH sensor based on polysulfone (PSU) and polyaniline (PANI) was developed. A transparent and flexible PSU membrane was employed as a support. The electrically conductive and pH-responsive PANI was deposited onto the membrane surface by in situ chemical oxidative polymerization (COP). The absorption spectra of the PANI-coated PSU membranes exhibited sensitivity to pH changes in the range of 4–12, which allowed for designing a dual wavelength pH optical sensor. The performance of the membranes was assessed by measuring their response starting from high pH and going down to low pH, and vice versa. It was found that it is necessary to precondition the sensor layers before each measurement due to the slight hysteresis observed during forward and backward pH titrations. PSU membranes with polyaniline coating thicknesses in the range of ≈100–200 nm exhibited fast response times of <4 s, which are attributed to the porous, rough and nanofibrillar morphology of the polyaniline coating. The fabricated pH sensor was characterized by a sigmoidal response (R2 = 0.997) which allows for pH determination over a wide dynamic range. All membranes were stable for a period of more than six months when stored in 1 M HCl solution. The reproducibility of the fabricated optical pH sensors was found to be <0.02 absorption units after one month storage in 1 M HCl solution. The performance of the optical pH sensor was tested and the obtained pH values were compared with the results obtained using a pH meter device. Full article
Figures

Open AccessArticle Link Investigation of IEEE 802.15.4 Wireless Sensor Networks in Forests
Sensors 2016, 16(7), 987; doi:10.3390/s16070987
Received: 9 March 2016 / Revised: 6 June 2016 / Accepted: 9 June 2016 / Published: 27 June 2016
PDF Full-text (3964 KB) | HTML Full-text | XML Full-text
Abstract
Wireless sensor networks are expected to automatically monitor the ecological evolution and wildlife habits in forests. Low-power links (transceivers) are often adopted in wireless sensor network applications, in order to save the precious sensor energy and then achieve long-term, unattended monitoring. Recent research
[...] Read more.
Wireless sensor networks are expected to automatically monitor the ecological evolution and wildlife habits in forests. Low-power links (transceivers) are often adopted in wireless sensor network applications, in order to save the precious sensor energy and then achieve long-term, unattended monitoring. Recent research has presented some performance characteristics of such low-power wireless links under laboratory or outdoor scenarios with less obstacles, and they have found that low-power wireless links are unreliable and prone to be affected by the target environment. However, there is still less understanding about how well the low-power wireless link performs in real-world forests and to what extent the complex in-forest surrounding environments affect the link performances. In this paper, we empirically evaluate the low-power links of wireless sensors in three typical different forest environments. Our experiment investigates the performance of the link layer compatible with the IEEE 802.15.4 standard and analyzes the variation patterns of the packet reception ratio (PRR), the received signal strength indicator (RSSI) and the link quality indicator (LQI) under diverse experimental settings. Some observations of this study are inconsistent with or even contradict prior results that are achieved in open fields or relatively clean environments and thus, provide new insights both into effectively evaluating the low-power wireless links and into efficiently deploying wireless sensor network systems in forest environments. Full article
(This article belongs to the Section Sensor Networks)
Open AccessArticle A Bandwidth-Efficient Dissemination Scheme of Non-Safety Information in Urban VANETs
Sensors 2016, 16(7), 988; doi:10.3390/s16070988
Received: 28 April 2016 / Revised: 21 June 2016 / Accepted: 22 June 2016 / Published: 27 June 2016
PDF Full-text (814 KB) | HTML Full-text | XML Full-text
Abstract
The recent release of standards for vehicular communications will hasten the development of smart cities in the following years. Many applications for vehicular networks, such as blocked road warnings or advertising, will require multi-hop dissemination of information to all vehicles in a region
[...] Read more.
The recent release of standards for vehicular communications will hasten the development of smart cities in the following years. Many applications for vehicular networks, such as blocked road warnings or advertising, will require multi-hop dissemination of information to all vehicles in a region of interest. However, these networks present special features and difficulties that may require special measures. The dissemination of information may cause broadcast storms. Urban scenarios are especially sensitive to broadcast storms because of the high density of vehicles in downtown areas. They also present numerous crossroads and signal blocking due to buildings, which make dissemination more difficult than in open, almost straight interurban roadways. In this article, we discuss several options to avoid the broadcast storm problem while trying to achieve the maximum coverage of the region of interest. Specifically, we evaluate through simulations different ways to detect and take advantage of intersections and a strategy based on store-carry-forward to overcome short disconnections between groups of vehicles. Our conclusions are varied, and we propose two different solutions, depending on the requirements of the application. Full article
(This article belongs to the Special Issue Selected Papers from UCAmI, IWAAL and AmIHEALTH 2015)
Open AccessArticle Planar Laser-Based QEPAS Trace Gas Sensor
Sensors 2016, 16(7), 989; doi:10.3390/s16070989
Received: 17 April 2016 / Revised: 22 June 2016 / Accepted: 23 June 2016 / Published: 28 June 2016
PDF Full-text (2331 KB) | HTML Full-text | XML Full-text
Abstract
A novel quartz enhanced photoacoustic spectroscopy (QEPAS) trace gas detection scheme is reported in this paper. A cylindrical lens was employed for near-infrared laser focusing. The laser beam was shaped as a planar line laser between the gap of the quartz tuning fork
[...] Read more.
A novel quartz enhanced photoacoustic spectroscopy (QEPAS) trace gas detection scheme is reported in this paper. A cylindrical lens was employed for near-infrared laser focusing. The laser beam was shaped as a planar line laser between the gap of the quartz tuning fork (QTF) prongs. Compared with a spherical lens-based QEPAS sensor, the cylindrical lens-based QEPAS sensor has the advantages of easier laser beam alignment and a reduction of stringent stability requirements. Therefore, the reported approach is useful in long-term and continuous sensor operation. Full article
(This article belongs to the Special Issue Infrared and THz Sensing and Imaging)
Open AccessArticle A Three-Dimensional Shape-Based Force and Stiffness-Sensing Platform for Tendon-Driven Catheters
Sensors 2016, 16(7), 990; doi:10.3390/s16070990
Received: 22 February 2016 / Revised: 29 April 2016 / Accepted: 24 May 2016 / Published: 28 June 2016
PDF Full-text (3916 KB) | HTML Full-text | XML Full-text
Abstract
This paper presents an efficient shape-based three-axial force and stiffness estimator for active catheters commonly implemented in cardiac ablation. The force-sensing capability provides important feedback for catheterization procedures including real-time control and catheter steering in autonomous navigation systems. The proposed platform is based
[...] Read more.
This paper presents an efficient shape-based three-axial force and stiffness estimator for active catheters commonly implemented in cardiac ablation. The force-sensing capability provides important feedback for catheterization procedures including real-time control and catheter steering in autonomous navigation systems. The proposed platform is based on the introduced accurate and computationally efficient Cosserat rod model for tendon-driven catheters. The proposed nonlinear Kalman filter formulation for contact force estimation along with the developed catheter model provides a real-time force observer robust to nonlinearities and noise covariance uncertainties. Furthermore, the proposed platform enables stiffness estimation in addition to tip contact force sensing in different operational circumstances. The approach incorporates pose measurements which can be achieved using currently developed pose-sensing systems or imaging techniques. The method makes the approach compatible with the range of forces applied in clinical applications. The simulation and experimental results verify the viability of the introduced force and stiffness-sensing technique. Full article
(This article belongs to the Section Physical Sensors)
Open AccessArticle Development of Torque Sensor with High Sensitivity for Joint of Robot Manipulator Using 4-Bar Linkage Shape
Sensors 2016, 16(7), 991; doi:10.3390/s16070991
Received: 29 March 2016 / Revised: 7 June 2016 / Accepted: 14 June 2016 / Published: 1 July 2016
Cited by 3 | PDF Full-text (5588 KB) | HTML Full-text | XML Full-text
Abstract
The torque sensor is used to measure the joint torque of a robot manipulator. Previous research showed that the sensitivity and the stiffness of torque sensors have trade-off characteristics. Stiffness has to be sacrificed to increase the sensitivity of the sensor. In this
[...] Read more.
The torque sensor is used to measure the joint torque of a robot manipulator. Previous research showed that the sensitivity and the stiffness of torque sensors have trade-off characteristics. Stiffness has to be sacrificed to increase the sensitivity of the sensor. In this research, a new torque sensor with high sensitivity (TSHS) is proposed in order to resolve this problem. The key idea of the TSHS comes from its 4-bar linkage shape in which the angular displacement of a short link is larger than that of a long link. The sensitivity of the torque sensor with a 4-bar link shape is improved without decreasing stiffness. Optimization techniques are applied to maximize the sensitivity of the sensor. An actual TSHS is constructed to verify the validity of the proposed mechanism. Experimental results show that the sensitivity of TSHS can be increased 3.5 times without sacrificing stiffness. Full article
Open AccessArticle An Efficient Interactive Model for On-Demand Sensing-As-A-Servicesof Sensor-Cloud
Sensors 2016, 16(7), 992; doi:10.3390/s16070992
Received: 9 May 2016 / Revised: 17 June 2016 / Accepted: 17 June 2016 / Published: 28 June 2016
Cited by 4 | PDF Full-text (899 KB) | HTML Full-text | XML Full-text
Abstract
This paper proposes an efficient interactive model for the sensor-cloud to enable the sensor-cloud to efficiently provide on-demand sensing services for multiple applications with different requirements at the same time. The interactive model is designed for both the cloud and sensor nodes to
[...] Read more.
This paper proposes an efficient interactive model for the sensor-cloud to enable the sensor-cloud to efficiently provide on-demand sensing services for multiple applications with different requirements at the same time. The interactive model is designed for both the cloud and sensor nodes to optimize the resource consumption of physical sensors, as well as the bandwidth consumption of sensing traffic. In the model, the sensor-cloud plays a key role in aggregating application requests to minimize the workloads required for constrained physical nodes while guaranteeing that the requirements of all applications are satisfied. Physical sensor nodes perform their sensing under the guidance of the sensor-cloud. Based on the interactions with the sensor-cloud, physical sensor nodes adapt their scheduling accordingly to minimize their energy consumption. Comprehensive experimental results show that our proposed system achieves a significant improvement in terms of the energy consumption of physical sensors, the bandwidth consumption from the sink node to the sensor-cloud, the packet delivery latency, reliability and scalability, compared to current approaches. Based on the obtained results, we discuss the economical benefits and how the proposed system enables a win-win model in the sensor-cloud. Full article
(This article belongs to the Special Issue Intelligent Internet of Things (IoT) Networks)
Figures

Open AccessArticle Spectral Characterization of a Prototype SFA Camera for Joint Visible and NIR Acquisition
Sensors 2016, 16(7), 993; doi:10.3390/s16070993
Received: 2 May 2016 / Revised: 2 June 2016 / Accepted: 16 June 2016 / Published: 28 June 2016
Cited by 9 | PDF Full-text (7005 KB) | HTML Full-text | XML Full-text | Supplementary Files
Abstract
Multispectral acquisition improves machine vision since it permits capturing more information on object surface properties than color imaging. The concept of spectral filter arrays has been developed recently and allows multispectral single shot acquisition with a compact camera design. Due to filter manufacturing
[...] Read more.
Multispectral acquisition improves machine vision since it permits capturing more information on object surface properties than color imaging. The concept of spectral filter arrays has been developed recently and allows multispectral single shot acquisition with a compact camera design. Due to filter manufacturing difficulties, there was, up to recently, no system available for a large span of spectrum, i.e., visible and Near Infra-Red acquisition. This article presents the achievement of a prototype of camera that captures seven visible and one near infra-red bands on the same sensor chip. A calibration is proposed to characterize the sensor, and images are captured. Data are provided as supplementary material for further analysis and simulations. This opens a new range of applications in security, robotics, automotive and medical fields. Full article
(This article belongs to the Special Issue Infrared and THz Sensing and Imaging)
Figures

Open AccessArticle Strategic Decision-Making Learning from Label Distributions: An Approach for Facial Age Estimation
Sensors 2016, 16(7), 994; doi:10.3390/s16070994
Received: 8 April 2016 / Revised: 20 June 2016 / Accepted: 21 June 2016 / Published: 28 June 2016
Cited by 1 | PDF Full-text (1694 KB) | HTML Full-text | XML Full-text
Abstract
Nowadays, label distribution learning is among the state-of-the-art methodologies in facial age estimation. It takes the age of each facial image instance as a label distribution with a series of age labels rather than the single chronological age label that is commonly used.
[...] Read more.
Nowadays, label distribution learning is among the state-of-the-art methodologies in facial age estimation. It takes the age of each facial image instance as a label distribution with a series of age labels rather than the single chronological age label that is commonly used. However, this methodology is deficient in its simple decision-making criterion: the final predicted age is only selected at the one with maximum description degree. In many cases, different age labels may have very similar description degrees. Consequently, blindly deciding the estimated age by virtue of the highest description degree would miss or neglect other valuable age labels that may contribute a lot to the final predicted age. In this paper, we propose a strategic decision-making label distribution learning algorithm (SDM-LDL) with a series of strategies specialized for different types of age label distribution. Experimental results from the most popular aging face database, FG-NET, show the superiority and validity of all the proposed strategic decision-making learning algorithms over the existing label distribution learning and other single-label learning algorithms for facial age estimation. The inner properties of SDM-LDL are further explored with more advantages. Full article
(This article belongs to the Section Physical Sensors)
Open AccessArticle High-Precision Hysteresis Sensing of the Quartz Crystal Inductance-to-Frequency Converter
Sensors 2016, 16(7), 995; doi:10.3390/s16070995
Received: 29 April 2016 / Revised: 17 June 2016 / Accepted: 18 June 2016 / Published: 28 June 2016
Cited by 2 | PDF Full-text (4020 KB) | HTML Full-text | XML Full-text
Abstract
A new method for the automated measurement of the hysteresis of the temperature-compensated inductance-to-frequency converter with a single quartz crystal is proposed. The new idea behind this method is a converter with two programmable analog switches enabling the automated measurement of the converter
[...] Read more.
A new method for the automated measurement of the hysteresis of the temperature-compensated inductance-to-frequency converter with a single quartz crystal is proposed. The new idea behind this method is a converter with two programmable analog switches enabling the automated measurement of the converter hysteresis, as well as the temperature compensation of the quartz crystal and any other circuit element. Also used is the programmable timing control device that allows the selection of different oscillating frequencies. In the proposed programmable method two different inductances connected in series to the quartz crystal are switched in a short time sequence, compensating the crystal’s natural temperature characteristics (in the temperature range between 0 and 50 °C). The procedure allows for the measurement of the converter hysteresis at various values of capacitance connected in parallel with the quartz crystal for the converter sensitivity setting at selected inductance. It, furthermore, enables the measurement of hysteresis at various values of inductance at selected parallel capacitance (sensitivity) connected to the quartz crystal. The article shows that the proposed hysteresis measurement of the converter, which converts the inductance in the range between 95 and 100 μH to a frequency in the range between 1 and 200 kHz, has only 7 × 10−13 frequency instability (during the temperature change between 0 and 50 °C) with a maximum 1 × 10−11 hysteresis frequency difference. Full article
(This article belongs to the Special Issue Resonator Sensors)
Figures

Open AccessArticle Microsoft Kinect Visual and Depth Sensors for Breathing and Heart Rate Analysis
Sensors 2016, 16(7), 996; doi:10.3390/s16070996
Received: 18 April 2016 / Revised: 18 June 2016 / Accepted: 22 June 2016 / Published: 28 June 2016
Cited by 8 | PDF Full-text (1645 KB) | HTML Full-text | XML Full-text
Abstract
This paper is devoted to a new method of using Microsoft (MS) Kinect sensors for non-contact monitoring of breathing and heart rate estimation to detect possible medical and neurological disorders. Video sequences of facial features and thorax movements are recorded by MS Kinect
[...] Read more.
This paper is devoted to a new method of using Microsoft (MS) Kinect sensors for non-contact monitoring of breathing and heart rate estimation to detect possible medical and neurological disorders. Video sequences of facial features and thorax movements are recorded by MS Kinect image, depth and infrared sensors to enable their time analysis in selected regions of interest. The proposed methodology includes the use of computational methods and functional transforms for data selection, as well as their denoising, spectral analysis and visualization, in order to determine specific biomedical features. The results that were obtained verify the correspondence between the evaluation of the breathing frequency that was obtained from the image and infrared data of the mouth area and from the thorax movement that was recorded by the depth sensor. Spectral analysis of the time evolution of the mouth area video frames was also used for heart rate estimation. Results estimated from the image and infrared data of the mouth area were compared with those obtained by contact measurements by Garmin sensors (www.garmin.com). The study proves that simple image and depth sensors can be used to efficiently record biomedical multidimensional data with sufficient accuracy to detect selected biomedical features using specific methods of computational intelligence. The achieved accuracy for non-contact detection of breathing rate was 0.26% and the accuracy of heart rate estimation was 1.47% for the infrared sensor. The following results show how video frames with depth data can be used to differentiate different kinds of breathing. The proposed method enables us to obtain and analyse data for diagnostic purposes in the home environment or during physical activities, enabling efficient human–machine interaction. Full article
(This article belongs to the Special Issue Non-Contact Sensing)
Figures

Open AccessArticle Microcantilever Displacement Measurement Using a Mechanically Modulated Optical Feedback Interferometer
Sensors 2016, 16(7), 997; doi:10.3390/s16070997
Received: 28 April 2016 / Revised: 23 June 2016 / Accepted: 24 June 2016 / Published: 29 June 2016
PDF Full-text (8676 KB) | HTML Full-text | XML Full-text
Abstract
Microcantilever motion detection is a useful tool for the characterization of the physical, chemical and biological properties of materials. In the past, different approaches have been proposed and tested to enhance the behavior, size and simplicity of microcantilever motion detectors. In this paper,
[...] Read more.
Microcantilever motion detection is a useful tool for the characterization of the physical, chemical and biological properties of materials. In the past, different approaches have been proposed and tested to enhance the behavior, size and simplicity of microcantilever motion detectors. In this paper, a new approach to measure microcantilever motion with nanometric resolution is presented. The proposed approach is based on the concept of mechanically-modulated optical feedback interferometry, a technique that has shown displacement measurement capabilities well within the nanometric scale and that, due to its size, compactness and low cost, may be a suitable choice for measuring nanometric motions in cantilever-like sensors. It will be shown that the sensor, in its current state of development, is capable of following a cantilever sinusoidal trajectory at different sets of frequencies ranging up to 200 Hz and peak to peak amplitudes up to λ / 2 with experimental resolutions in the λ / 100 range. Full article
(This article belongs to the Special Issue SPR, WGM & Nano-Sensors: Advantages and Prospects)
Figures

Open AccessArticle Quality-Related Monitoring and Grading of Granulated Products by Weibull-Distribution Modeling of Visual Images with Semi-Supervised Learning
Sensors 2016, 16(7), 998; doi:10.3390/s16070998
Received: 20 April 2016 / Revised: 14 June 2016 / Accepted: 23 June 2016 / Published: 29 June 2016
PDF Full-text (5133 KB) | HTML Full-text | XML Full-text
Abstract
The topic of online product quality inspection (OPQI) with smart visual sensors is attracting increasing interest in both the academic and industrial communities on account of the natural connection between the visual appearance of products with their underlying qualities. Visual images captured from
[...] Read more.
The topic of online product quality inspection (OPQI) with smart visual sensors is attracting increasing interest in both the academic and industrial communities on account of the natural connection between the visual appearance of products with their underlying qualities. Visual images captured from granulated products (GPs), e.g., cereal products, fabric textiles, are comprised of a large number of independent particles or stochastically stacking locally homogeneous fragments, whose analysis and understanding remains challenging. A method of image statistical modeling-based OPQI for GP quality grading and monitoring by a Weibull distribution(WD) model with a semi-supervised learning classifier is presented. WD-model parameters (WD-MPs) of GP images’ spatial structures, obtained with omnidirectional Gaussian derivative filtering (OGDF), which were demonstrated theoretically to obey a specific WD model of integral form, were extracted as the visual features. Then, a co-training-style semi-supervised classifier algorithm, named COSC-Boosting, was exploited for semi-supervised GP quality grading, by integrating two independent classifiers with complementary nature in the face of scarce labeled samples. Effectiveness of the proposed OPQI method was verified and compared in the field of automated rice quality grading with commonly-used methods and showed superior performance, which lays a foundation for the quality control of GP on assembly lines. Full article
(This article belongs to the Special Issue Sensors for Agriculture)
Open AccessArticle A 75-ps Gated CMOS Image Sensor with Low Parasitic Light Sensitivity
Sensors 2016, 16(7), 999; doi:10.3390/s16070999
Received: 3 April 2016 / Revised: 19 June 2016 / Accepted: 22 June 2016 / Published: 29 June 2016
PDF Full-text (2408 KB) | HTML Full-text | XML Full-text
Abstract
In this study, a 40 × 48 pixel global shutter complementary metal-oxide-semiconductor (CMOS) image sensor with an adjustable shutter time as low as 75 ps was implemented using a 0.5-μm mixed-signal CMOS process. The implementation consisted of a continuous contact ring around each
[...] Read more.
In this study, a 40 × 48 pixel global shutter complementary metal-oxide-semiconductor (CMOS) image sensor with an adjustable shutter time as low as 75 ps was implemented using a 0.5-μm mixed-signal CMOS process. The implementation consisted of a continuous contact ring around each p+/n-well photodiode in the pixel array in order to apply sufficient light shielding. The parasitic light sensitivity of the in-pixel storage node was measured to be 1/8.5 × 107 when illuminated by a 405-nm diode laser and 1/1.4 × 104 when illuminated by a 650-nm diode laser. The pixel pitch was 24 μm, the size of the square p+/n-well photodiode in each pixel was 7 μm per side, the measured random readout noise was 217 e rms, and the measured dynamic range of the pixel of the designed chip was 5500:1. The type of gated CMOS image sensor (CIS) that is proposed here can be used in ultra-fast framing cameras to observe non-repeatable fast-evolving phenomena. Full article
(This article belongs to the Special Issue Imaging: Sensors and Technologies) Printed Edition available
Open AccessArticle Robust Control for the Segway with Unknown Control Coefficient and Model Uncertainties
Sensors 2016, 16(7), 1000; doi:10.3390/s16071000
Received: 28 March 2016 / Revised: 10 June 2016 / Accepted: 23 June 2016 / Published: 29 June 2016
Cited by 2 | PDF Full-text (1032 KB) | HTML Full-text | XML Full-text
Abstract
The Segway, which is a popular vehicle nowadays, is an uncertain nonlinear system and has an unknown time-varying control coefficient. Thus, we should consider the unknown time-varying control coefficient and model uncertainties to design the controller. Motivated by this observation, we propose a
[...] Read more.
The Segway, which is a popular vehicle nowadays, is an uncertain nonlinear system and has an unknown time-varying control coefficient. Thus, we should consider the unknown time-varying control coefficient and model uncertainties to design the controller. Motivated by this observation, we propose a robust control for the Segway with unknown control coefficient and model uncertainties. To deal with the time-varying unknown control coefficient, we employ the Nussbaum gain technique. We introduce an auxiliary variable to solve the underactuated problem. Due to the prescribed performance control technique, the proposed controller does not require the adaptive technique, neural network, and fuzzy logic to compensate the uncertainties. Therefore, it can be simple. From the Lyapunov stability theory, we prove that all signals in the closed-loop system are bounded. Finally, we provide the simulation results to demonstrate the effectiveness of the proposed control scheme. Full article
Open AccessArticle Silica-gel Particles Loaded with an Ionic Liquid for Separation of Zr(IV) Prior to Its Determination by ICP-OES
Sensors 2016, 16(7), 1001; doi:10.3390/s16071001
Received: 10 April 2016 / Revised: 29 May 2016 / Accepted: 3 June 2016 / Published: 29 June 2016
PDF Full-text (7017 KB) | HTML Full-text | XML Full-text
Abstract
A new ionic liquid loaded silica gel amine (SG-APTMS-N,N-EPANTf2) was developed, as an adsorptive material, for selective adsorption and determination of zirconium, Zr(IV), without the need for a chelating intermediate. Based on a selectivity study, the SG-APTMS-N,N-EPANTf2 phase showed a
[...] Read more.
A new ionic liquid loaded silica gel amine (SG-APTMS-N,N-EPANTf2) was developed, as an adsorptive material, for selective adsorption and determination of zirconium, Zr(IV), without the need for a chelating intermediate. Based on a selectivity study, the SG-APTMS-N,N-EPANTf2 phase showed a perfect selectivity towards Zr(IV) at pH 4 as compared to other metallic ions, including gold [Au(III)], copper [Cu(II)], cobalt [Co(II)], chromium [Cr(III)], lead [Pb(II)], selenium [Se(IV)] and mercury [Hg(II)] ions. The influence of pH, Zr(IV) concentration, contact time and interfering ions on SG-APTMS-N,N-EPANTf2 uptake for Zr(IV) was evaluated. The presence of incorporated donor atoms in newly synthesized SG-APTMS-N,N-EPANTf2 phase played a significant role in enhancing its uptake capacity of Zr(IV) by 78.64% in contrast to silica gel (activated). The equilibrium and kinetic information of Zr(IV) adsorption onto SG-APTMS-N,N-EPANTf2 were best expressed by Langmuir and pseudo second-order kinetic models, respectively. General co-existing cations did not interfere with the extraction and detection of Zr(IV). Finally, the analytical efficiency of the newly developed method was also confirmed by implementing it for the determination of Zr(IV) in several water samples. Full article
(This article belongs to the Special Issue Ionic Liquids)
Figures

Open AccessArticle Quantum Random Number Generation Using a Quanta Image Sensor
Sensors 2016, 16(7), 1002; doi:10.3390/s16071002
Received: 6 April 2016 / Revised: 13 June 2016 / Accepted: 23 June 2016 / Published: 29 June 2016
Cited by 1 | PDF Full-text (1260 KB) | HTML Full-text | XML Full-text
Abstract
A new quantum random number generation method is proposed. The method is based on the randomness of the photon emission process and the single photon counting capability of the Quanta Image Sensor (QIS). It has the potential to generate high-quality random numbers with
[...] Read more.
A new quantum random number generation method is proposed. The method is based on the randomness of the photon emission process and the single photon counting capability of the Quanta Image Sensor (QIS). It has the potential to generate high-quality random numbers with remarkable data output rate. In this paper, the principle of photon statistics and theory of entropy are discussed. Sample data were collected with QIS jot device, and its randomness quality was analyzed. The randomness assessment method and results are discussed. Full article
(This article belongs to the Special Issue Photon-Counting Image Sensors) Printed Edition available
Figures

Open AccessArticle Amperometric Non-Enzymatic Hydrogen Peroxide Sensor Based on Aligned Zinc Oxide Nanorods
Sensors 2016, 16(7), 1004; doi:10.3390/s16071004
Received: 28 April 2016 / Revised: 14 June 2016 / Accepted: 15 June 2016 / Published: 29 June 2016
Cited by 4 | PDF Full-text (962 KB) | HTML Full-text | XML Full-text
Abstract
Zinc oxide (ZnO) nanorods (NRs) have been synthesized via the hydrothermal process. The NRs were grown over a conductive glass substrate. A non-enzymatic electrochemical sensor for hydrogen peroxide (H2O2), based on the prepared ZnO NRs, was examined through the
[...] Read more.
Zinc oxide (ZnO) nanorods (NRs) have been synthesized via the hydrothermal process. The NRs were grown over a conductive glass substrate. A non-enzymatic electrochemical sensor for hydrogen peroxide (H2O2), based on the prepared ZnO NRs, was examined through the use of current-voltage measurements. The measured currents, as a function of H2O2 concentrations ranging from 10 μM to 700 μM, revealed two distinct behaviours and good performance, with a lower detection limit (LOD) of 42 μM for the low range of H2O2 concentrations (first region), and a LOD of 143.5 μM for the higher range of H2O2 concentrations (second region). The prepared ZnO NRs show excellent electrocatalytic activity. This enables a measurable and stable output current. The results were correlated with the oxidation process of the H2O2 and revealed a good performance for the ZnO NR non-enzymatic H2O2 sensor. Full article
(This article belongs to the Special Issue Amperometric Biosensors)
Figures

Open AccessArticle Photon-Counting Arrays for Time-Resolved Imaging
Sensors 2016, 16(7), 1005; doi:10.3390/s16071005
Received: 18 February 2016 / Revised: 24 May 2016 / Accepted: 16 June 2016 / Published: 29 June 2016
Cited by 3 | PDF Full-text (9302 KB) | HTML Full-text | XML Full-text
Abstract
The paper presents a camera comprising 512 × 128 pixels capable of single-photon detection and gating with a maximum frame rate of 156 kfps. The photon capture is performed through a gated single-photon avalanche diode that generates a digital pulse upon photon detection
[...] Read more.
The paper presents a camera comprising 512 × 128 pixels capable of single-photon detection and gating with a maximum frame rate of 156 kfps. The photon capture is performed through a gated single-photon avalanche diode that generates a digital pulse upon photon detection and through a digital one-bit counter. Gray levels are obtained through multiple counting and accumulation, while time-resolved imaging is achieved through a 4-ns gating window controlled with subnanosecond accuracy by a field-programmable gate array. The sensor, which is equipped with microlenses to enhance its effective fill factor, was electro-optically characterized in terms of sensitivity and uniformity. Several examples of capture of fast events are shown to demonstrate the suitability of the approach. Full article
(This article belongs to the Special Issue Photon-Counting Image Sensors) Printed Edition available
Figures

Open AccessArticle A Proof-of-Concept for Semantically Interoperable Federation of IoT Experimentation Facilities
Sensors 2016, 16(7), 1006; doi:10.3390/s16071006
Received: 29 April 2016 / Revised: 10 June 2016 / Accepted: 23 June 2016 / Published: 29 June 2016
Cited by 5 | PDF Full-text (5137 KB) | HTML Full-text | XML Full-text
Abstract
The Internet-of-Things (IoT) is unanimously identified as one of the main pillars of future smart scenarios. The potential of IoT technologies and deployments has been already demonstrated in a number of different application areas, including transport, energy, safety and healthcare. However, despite the
[...] Read more.
The Internet-of-Things (IoT) is unanimously identified as one of the main pillars of future smart scenarios. The potential of IoT technologies and deployments has been already demonstrated in a number of different application areas, including transport, energy, safety and healthcare. However, despite the growing number of IoT deployments, the majority of IoT applications tend to be self-contained, thereby forming application silos. A lightweight data centric integration and combination of these silos presents several challenges that still need to be addressed. Indeed, the ability to combine and synthesize data streams and services from diverse IoT platforms and testbeds, holds the promise to increase the potentiality of smart applications in terms of size, scope and targeted business context. In this article, a proof-of-concept implementation that federates two different IoT experimentation facilities by means of semantic-based technologies will be described. The specification and design of the implemented system and information models will be described together with the practical details of the developments carried out and its integration with the existing IoT platforms supporting the aforementioned testbeds. Overall, the system described in this paper demonstrates that it is possible to open new horizons in the development of IoT applications and experiments at a global scale, that transcend the (silo) boundaries of individual deployments, based on the semantic interconnection and interoperability of diverse IoT platforms and testbeds. Full article
(This article belongs to the Special Issue Data in the IoT: from Sensing to Meaning)
Open AccessArticle Development of a Calibration Strip for Immunochromatographic Assay Detection Systems
Sensors 2016, 16(7), 1007; doi:10.3390/s16071007
Received: 16 May 2016 / Revised: 14 June 2016 / Accepted: 21 June 2016 / Published: 29 June 2016
PDF Full-text (2785 KB) | HTML Full-text | XML Full-text
Abstract
With many benefits and applications, immunochromatographic (ICG) assay detection systems have been reported on a great deal. However, the existing research mainly focuses on increasing the dynamic detection range or application fields. Calibration of the detection system, which has a great influence on
[...] Read more.
With many benefits and applications, immunochromatographic (ICG) assay detection systems have been reported on a great deal. However, the existing research mainly focuses on increasing the dynamic detection range or application fields. Calibration of the detection system, which has a great influence on the detection accuracy, has not been addressed properly. In this context, this work develops a calibration strip for ICG assay photoelectric detection systems. An image of the test strip is captured by an image acquisition device, followed by performing a fuzzy c-means (FCM) clustering algorithm and maximin-distance algorithm for image segmentation. Additionally, experiments are conducted to find the best characteristic quantity. By analyzing the linear coefficient, an average value of hue (H) at 14 min is chosen as the characteristic quantity and the empirical formula between H and optical density (OD) value is established. Therefore, H, saturation (S), and value (V) are calculated by a number of selected OD values. Then, H, S, and V values are transferred to the RGB color space and a high-resolution printer is used to print the strip images on cellulose nitrate membranes. Finally, verification of the printed calibration strips is conducted by analyzing the linear correlation between OD and the spectral reflectance, which shows a good linear correlation (R2 = 98.78%). Full article
(This article belongs to the Special Issue Point-of-Care Biosensors)
Open AccessArticle An Enhanced Technique for Ultrasonic Flow Metering Featuring Very Low Jitter and Offset
Sensors 2016, 16(7), 1008; doi:10.3390/s16071008
Received: 15 April 2016 / Revised: 14 June 2016 / Accepted: 24 June 2016 / Published: 29 June 2016
Cited by 2 | PDF Full-text (3100 KB) | HTML Full-text | XML Full-text
Abstract
This paper proposes a new, improved method for water flow metering. It applies to a transit time ultrasonic flow meter device. In principle, the flow of a given liquid in a pipe is obtained by measuring the transit times of an ultrasonic wave
[...] Read more.
This paper proposes a new, improved method for water flow metering. It applies to a transit time ultrasonic flow meter device. In principle, the flow of a given liquid in a pipe is obtained by measuring the transit times of an ultrasonic wave in the upstream and downstream directions. The difference between these times is, in theory, linearly proportional to the liquid flow velocity. However, the fainter the flow is, the smaller the transit time difference (TTD) is. This difference can be as low as a few picoseconds, which gives rise to many technical difficulties in measuring such a small time difference with a given accuracy. The proposed method relies on measuring the TTD indirectly by computing the phase difference between the steady-state parts of the received signals in the upstream and downstream directions and by using a least-square-sine-fitting technique. This reduces the effect of the jitter noise and the offset, which limit measurement precision at very low flow velocity. The obtained measurement results illustrate the robustness of the proposed method, as we measure the TTD at no-flow conditions, with a precision as low as 10 ps peak-to-peak and a TTD offset of zero, within a temperature range from room temperature to 80 °C. This allows us to reach a smaller minimum detectable flow when compared with previous techniques. The proposed method exhibits a better trade-off between measurement accuracy and system complexity. It can be completely integrated in an ASIC (application specific integrated circuit) or incorporated in a CPU- or micro-controller-based system. Full article
(This article belongs to the Section Physical Sensors)
Open AccessArticle An Energy-Efficient Game-Theory-Based Spectrum Decision Scheme for Cognitive Radio Sensor Networks
Sensors 2016, 16(7), 1009; doi:10.3390/s16071009
Received: 25 March 2016 / Revised: 17 June 2016 / Accepted: 25 June 2016 / Published: 30 June 2016
Cited by 2 | PDF Full-text (3568 KB) | HTML Full-text | XML Full-text
Abstract
A cognitive radio sensor network (CRSN) is a wireless sensor network in which sensor nodes are equipped with cognitive radio. In this paper, we propose an energy-efficient game-theory-based spectrum decision (EGSD) scheme for CRSNs to prolong the network lifetime. Note that energy efficiency
[...] Read more.
A cognitive radio sensor network (CRSN) is a wireless sensor network in which sensor nodes are equipped with cognitive radio. In this paper, we propose an energy-efficient game-theory-based spectrum decision (EGSD) scheme for CRSNs to prolong the network lifetime. Note that energy efficiency is the most important design consideration in CRSNs because it determines the network lifetime. The central part of the EGSD scheme consists of two spectrum selection algorithms: random selection and game-theory-based selection. The EGSD scheme also includes a clustering algorithm, spectrum characterization with a Markov chain, and cluster member coordination. Our performance study shows that EGSD outperforms the existing popular framework in terms of network lifetime and coordination overhead. Full article
(This article belongs to the Section Sensor Networks)
Open AccessArticle Robust Behavior Recognition in Intelligent Surveillance Environments
Sensors 2016, 16(7), 1010; doi:10.3390/s16071010
Received: 16 May 2016 / Revised: 17 June 2016 / Accepted: 25 June 2016 / Published: 30 June 2016
Cited by 3 | PDF Full-text (7055 KB) | HTML Full-text | XML Full-text
Abstract
Intelligent surveillance systems have been studied by many researchers. These systems should be operated in both daytime and nighttime, but objects are invisible in images captured by visible light camera during the night. Therefore, near infrared (NIR) cameras, thermal cameras (based on medium-wavelength
[...] Read more.
Intelligent surveillance systems have been studied by many researchers. These systems should be operated in both daytime and nighttime, but objects are invisible in images captured by visible light camera during the night. Therefore, near infrared (NIR) cameras, thermal cameras (based on medium-wavelength infrared (MWIR), and long-wavelength infrared (LWIR) light) have been considered for usage during the nighttime as an alternative. Due to the usage during both daytime and nighttime, and the limitation of requiring an additional NIR illuminator (which should illuminate a wide area over a great distance) for NIR cameras during the nighttime, a dual system of visible light and thermal cameras is used in our research, and we propose a new behavior recognition in intelligent surveillance environments. Twelve datasets were compiled by collecting data in various environments, and they were used to obtain experimental results. The recognition accuracy of our method was found to be 97.6%, thereby confirming the ability of our method to outperform previous methods. Full article
(This article belongs to the Section Physical Sensors)
Figures

Open AccessArticle Molecularly Imprinted Polymer Nanoparticles for Formaldehyde Sensing with QCM
Sensors 2016, 16(7), 1011; doi:10.3390/s16071011
Received: 23 March 2016 / Revised: 20 June 2016 / Accepted: 22 June 2016 / Published: 30 June 2016
Cited by 3 | PDF Full-text (1945 KB) | HTML Full-text | XML Full-text
Abstract
Herein, we report on molecularly imprinted polymers (MIPs) for detecting formaldehyde vapors in air streams. A copolymer thin film consisting of styrene, methacrylic acid, and ethylene glycol dimethacrylate on quartz crystal microbalance (QCM) yielded a detection limit of 500 ppb formaldehyde in dry
[...] Read more.
Herein, we report on molecularly imprinted polymers (MIPs) for detecting formaldehyde vapors in air streams. A copolymer thin film consisting of styrene, methacrylic acid, and ethylene glycol dimethacrylate on quartz crystal microbalance (QCM) yielded a detection limit of 500 ppb formaldehyde in dry air. Surprisingly, these MIPs showed specific behavior when tested against a range of volatile organic compounds (VOCs), such as acetaldehyde, methanol, formic acid, and dichloromethane. Despite thus being a suitable receptor in principle, the MIPs were not useful for measurements at 50% humidity due to surface saturation by water. This was overcome by introducing primary amino groups into the polymer via allyl amine and by changing the coating morphology from thin film to nanoparticles. This led to the same limit of detection (500 ppb) and selectivity as before, but at the real-life conditions of 50% relative humidity. Full article
Open AccessArticle Classification of Kiwifruit Grades Based on Fruit Shape Using a Single Camera
Sensors 2016, 16(7), 1012; doi:10.3390/s16071012
Received: 17 April 2016 / Revised: 24 June 2016 / Accepted: 28 June 2016 / Published: 30 June 2016
PDF Full-text (1610 KB) | HTML Full-text | XML Full-text
Abstract
This study aims to demonstrate the feasibility for classifying kiwifruit into shape grades by adding a single camera to current Chinese sorting lines equipped with weight sensors. Image processing methods are employed to calculate fruit length, maximum diameter of the equatorial section, and
[...] Read more.
This study aims to demonstrate the feasibility for classifying kiwifruit into shape grades by adding a single camera to current Chinese sorting lines equipped with weight sensors. Image processing methods are employed to calculate fruit length, maximum diameter of the equatorial section, and projected area. A stepwise multiple linear regression method is applied to select significant variables for predicting minimum diameter of the equatorial section and volume and to establish corresponding estimation models. Results show that length, maximum diameter of the equatorial section and weight are selected to predict the minimum diameter of the equatorial section, with the coefficient of determination of only 0.82 when compared to manual measurements. Weight and length are then selected to estimate the volume, which is in good agreement with the measured one with the coefficient of determination of 0.98. Fruit classification based on the estimated minimum diameter of the equatorial section achieves a low success rate of 84.6%, which is significantly improved using a linear combination of the length/maximum diameter of the equatorial section and projected area/length ratios, reaching 98.3%. Thus, it is possible for Chinese kiwifruit sorting lines to reach international standards of grading kiwifruit on fruit shape classification by adding a single camera. Full article
(This article belongs to the Special Issue Sensors for Agriculture)
Open AccessArticle An Improved Simulated Annealing Technique for Enhanced Mobility in Smart Cities
Sensors 2016, 16(7), 1013; doi:10.3390/s16071013
Received: 24 April 2016 / Revised: 23 June 2016 / Accepted: 24 June 2016 / Published: 30 June 2016
PDF Full-text (4387 KB) | HTML Full-text | XML Full-text
Abstract
Vehicular traffic congestion is a significant problem that arises in many cities. This is due to the increasing number of vehicles that are driving on city roads of limited capacity. The vehicular congestion significantly impacts travel distance, travel time, fuel consumption and air
[...] Read more.
Vehicular traffic congestion is a significant problem that arises in many cities. This is due to the increasing number of vehicles that are driving on city roads of limited capacity. The vehicular congestion significantly impacts travel distance, travel time, fuel consumption and air pollution. Avoidance of traffic congestion and providing drivers with optimal paths are not trivial tasks. The key contribution of this work consists of the developed approach for dynamic calculation of optimal traffic routes. Two attributes (the average travel speed of the traffic and the roads’ length) are utilized by the proposed method to find the optimal paths. The average travel speed values can be obtained from the sensors deployed in smart cities and communicated to vehicles via the Internet of Vehicles and roadside communication units. The performance of the proposed algorithm is compared to three other algorithms: the simulated annealing weighted sum, the simulated annealing technique for order preference by similarity to the ideal solution and the Dijkstra algorithm. The weighted sum and technique for order preference by similarity to the ideal solution methods are used to formulate different attributes in the simulated annealing cost function. According to the Sheffield scenario, simulation results show that the improved simulated annealing technique for order preference by similarity to the ideal solution method improves the traffic performance in the presence of congestion by an overall average of 19.22% in terms of travel time, fuel consumption and CO2 emissions as compared to other algorithms; also, similar performance patterns were achieved for the Birmingham test scenario. Full article
(This article belongs to the Special Issue Smart City: Vision and Reality)
Open AccessArticle Joint Parameter Estimation for the Two-Wave with Diffuse Power Fading Model
Sensors 2016, 16(7), 1014; doi:10.3390/s16071014
Received: 14 April 2016 / Revised: 23 June 2016 / Accepted: 25 June 2016 / Published: 30 June 2016
PDF Full-text (950 KB) | HTML Full-text | XML Full-text
Abstract
Wireless sensor networks deployed within metallic cavities are known to suffer from a very severe fading, even in strong line-of-sight propagation conditions. This behavior is well-captured by the Two-Wave with Diffuse Power (TWDP) fading distribution, which shows great fit to field measurements in
[...] Read more.
Wireless sensor networks deployed within metallic cavities are known to suffer from a very severe fading, even in strong line-of-sight propagation conditions. This behavior is well-captured by the Two-Wave with Diffuse Power (TWDP) fading distribution, which shows great fit to field measurements in such scenarios. In this paper, we address the joint estimation of the parameters K and Δ that characterize the TWDP fading model, based on the observation of the received signal envelope. We use a moment-based approach to derive closed-form expressions for the estimators of K and Δ, as well as closed-form expressions for their asymptotic variance. Results show that the estimation error is close to the Cramer-Rao lower bound for a wide range of values of the parameters K and Δ. The performance degradation due to a finite number of observations is also analyzed. Full article
(This article belongs to the Section Sensor Networks)
Open AccessArticle Development of a Nafion/MWCNT-SPCE-Based Portable Sensor for the Voltammetric Analysis of the Anti-Tuberculosis Drug Ethambutol
Sensors 2016, 16(7), 1015; doi:10.3390/s16071015
Received: 17 May 2016 / Revised: 22 June 2016 / Accepted: 27 June 2016 / Published: 30 June 2016
Cited by 2 | PDF Full-text (4825 KB) | HTML Full-text | XML Full-text
Abstract
Herein we describe the development, characterization and application of an electrochemical sensor based on the use of Nafion/MWCNT-modified screen-printed carbon electrodes (SPCEs) for the voltammetric detection of the anti-tuberculosis (anti-TB) drug ethambutol (ETB). The electrochemical behaviour of the drug at the surface of
[...] Read more.
Herein we describe the development, characterization and application of an electrochemical sensor based on the use of Nafion/MWCNT-modified screen-printed carbon electrodes (SPCEs) for the voltammetric detection of the anti-tuberculosis (anti-TB) drug ethambutol (ETB). The electrochemical behaviour of the drug at the surface of the developed Nafion/MWCNT-SPCEs was studied through cyclic voltammetry (CV) and square wave voltammetry (SWV) techniques. Electrochemical impedance spectroscopy (EIS) and scanning electron microscopy (SEM) were employed to characterize the modified surface of the electrodes. Results showed that, compared to both unmodified and MWCNTs-modified SPCEs, negatively charged Nafion/MWCNT-SPCEs remarkably enhanced the electrochemical sensitivity and selectivity for ETB due to the synergistic effect of the electrostatic interaction between cationic ETB molecules and negatively charged Nafion polymer and the inherent electrocatalytic properties of both MWCNTs and Nafion. Nafion/MWCNT-SPCEs provided excellent biocompatibility, good electrical conductivity, low electrochemical interferences and a high signal-to-noise ratio, providing excellent performance towards ETB quantification in microvolumes of human urine and human blood serum samples. The outcomes of this paper confirm that the Nafion/MWCNT-SPCE-based device could be a potential candidate for the development of a low-cost, yet reliable and efficient electrochemical portable sensor for the low-level detection of this antimycobacterial drug in biological samples. Full article
(This article belongs to the Section Chemical Sensors)
Figures

Open AccessArticle Field Measurement-Based System Identification and Dynamic Response Prediction of a Unique MIT Building
Sensors 2016, 16(7), 1016; doi:10.3390/s16071016
Received: 26 April 2016 / Revised: 25 June 2016 / Accepted: 28 June 2016 / Published: 1 July 2016
Cited by 3 | PDF Full-text (9685 KB) | HTML Full-text | XML Full-text
Abstract
Tall buildings are ubiquitous in major cities and house the homes and workplaces of many individuals. However, relatively few studies have been carried out to study the dynamic characteristics of tall buildings based on field measurements. In this paper, the dynamic behavior of
[...] Read more.
Tall buildings are ubiquitous in major cities and house the homes and workplaces of many individuals. However, relatively few studies have been carried out to study the dynamic characteristics of tall buildings based on field measurements. In this paper, the dynamic behavior of the Green Building, a unique 21-story tall structure located on the campus of the Massachusetts Institute of Technology (MIT, Cambridge, MA, USA), was characterized and modeled as a simplified lumped-mass beam model (SLMM), using data from a network of accelerometers. The accelerometer network was used to record structural responses due to ambient vibrations, blast loading, and the October 16th 2012 earthquake near Hollis Center (ME, USA). Spectral and signal coherence analysis of the collected data was used to identify natural frequencies, modes, foundation rocking behavior, and structural asymmetries. A relation between foundation rocking and structural natural frequencies was also found. Natural frequencies and structural acceleration from the field measurements were compared with those predicted by the SLMM which was updated by inverse solving based on advanced multiobjective optimization methods using the measured structural responses and found to have good agreement. Full article
(This article belongs to the Section Physical Sensors)
Open AccessArticle Parameter Estimation of a Ground Moving Target Using Image Sharpness Optimization
Sensors 2016, 16(7), 1017; doi:10.3390/s16071017
Received: 13 April 2016 / Revised: 16 June 2016 / Accepted: 25 June 2016 / Published: 30 June 2016
PDF Full-text (1896 KB) | HTML Full-text | XML Full-text
Abstract
Motion parameter estimation of a ground moving target is an important issue in synthetic aperture radar ground moving target indication (SAR-GMTI) which has significant applications for civilian and military. The SAR image of a moving target may be displaced and defocused due to
[...] Read more.
Motion parameter estimation of a ground moving target is an important issue in synthetic aperture radar ground moving target indication (SAR-GMTI) which has significant applications for civilian and military. The SAR image of a moving target may be displaced and defocused due to the radial and along-track velocity components, respectively. The sharpness cost function presents a measure of the degree of focus of the image. In this work, a new ground moving target parameter estimation algorithm based on the sharpness optimization criterion is proposed. The relationships between the quadratic phase errors and the target’s velocity components are derived. Using two-dimensional searching of the sharpness cost function, we can obtain the velocity components of the target and the focused target image simultaneously. The proposed moving target parameter estimation method and image sharpness metrics are analyzed in detail. Finally, numerical results illustrate the effective and superior velocity estimation performance of the proposed method when compared to existing algorithms. Full article
(This article belongs to the Section Remote Sensors)
Figures

Open AccessArticle Heterogeneous Multi-Robot System for Mapping Environmental Variables of Greenhouses
Sensors 2016, 16(7), 1018; doi:10.3390/s16071018
Received: 30 May 2016 / Revised: 23 June 2016 / Accepted: 25 June 2016 / Published: 1 July 2016
PDF Full-text (9050 KB) | HTML Full-text | XML Full-text | Supplementary Files
Abstract
The productivity of greenhouses highly depends on the environmental conditions of crops, such as temperature and humidity. The control and monitoring might need large sensor networks, and as a consequence, mobile sensory systems might be a more suitable solution. This paper describes the
[...] Read more.
The productivity of greenhouses highly depends on the environmental conditions of crops, such as temperature and humidity. The control and monitoring might need large sensor networks, and as a consequence, mobile sensory systems might be a more suitable solution. This paper describes the application of a heterogeneous robot team to monitor environmental variables of greenhouses. The multi-robot system includes both ground and aerial vehicles, looking to provide flexibility and improve performance. The multi-robot sensory system measures the temperature, humidity, luminosity and carbon dioxide concentration in the ground and at different heights. Nevertheless, these measurements can be complemented with other ones (e.g., the concentration of various gases or images of crops) without a considerable effort. Additionally, this work addresses some relevant challenges of multi-robot sensory systems, such as the mission planning and task allocation, the guidance, navigation and control of robots in greenhouses and the coordination among ground and aerial vehicles. This work has an eminently practical approach, and therefore, the system has been extensively tested both in simulations and field experiments. Full article
(This article belongs to the Special Issue Robotic Sensory Systems for Environment Protection and Conservation)
Figures

Open AccessArticle A Novel Pre-Processing Technique for Original Feature Matrix of Electronic Nose Based on Supervised Locality Preserving Projections
Sensors 2016, 16(7), 1019; doi:10.3390/s16071019
Received: 12 April 2016 / Revised: 12 June 2016 / Accepted: 20 June 2016 / Published: 30 June 2016
Cited by 1 | PDF Full-text (2425 KB) | HTML Full-text | XML Full-text
Abstract
An electronic nose (E-nose) consisting of 14 metal oxide gas sensors and one electronic chemical gas sensor has been constructed to identify four different classes of wound infection. However, the classification results of the E-nose are not ideal if the original feature matrix
[...] Read more.
An electronic nose (E-nose) consisting of 14 metal oxide gas sensors and one electronic chemical gas sensor has been constructed to identify four different classes of wound infection. However, the classification results of the E-nose are not ideal if the original feature matrix containing the maximum steady-state response value of sensors is processed by the classifier directly, so a novel pre-processing technique based on supervised locality preserving projections (SLPP) is proposed in this paper to process the original feature matrix before it is put into the classifier to improve the performance of the E-nose. SLPP is good at finding and keeping the nonlinear structure of data; furthermore, it can provide an explicit mapping expression which is unreachable by the traditional manifold learning methods. Additionally, some effective optimization methods are found by us to optimize the parameters of SLPP and the classifier. Experimental results prove that the classification accuracy of support vector machine (SVM combined with the data pre-processed by SLPP outperforms other considered methods. All results make it clear that SLPP has a better performance in processing the original feature matrix of the E-nose. Full article
(This article belongs to the Special Issue E-noses: Sensors and Applications)
Open AccessArticle Sequential Total Variation Denoising for the Extraction of Fetal ECG from Single-Channel Maternal Abdominal ECG
Sensors 2016, 16(7), 1020; doi:10.3390/s16071020
Received: 27 April 2016 / Revised: 24 June 2016 / Accepted: 29 June 2016 / Published: 1 July 2016
Cited by 5 | PDF Full-text (5012 KB) | HTML Full-text | XML Full-text
Abstract
Fetal heart rate (FHR) is an important determinant of fetal health. Cardiotocography (CTG) is widely used for measuring the FHR in the clinical field. However, fetal movement and blood flow through the maternal blood vessels can critically influence Doppler ultrasound signals. Moreover, CTG
[...] Read more.
Fetal heart rate (FHR) is an important determinant of fetal health. Cardiotocography (CTG) is widely used for measuring the FHR in the clinical field. However, fetal movement and blood flow through the maternal blood vessels can critically influence Doppler ultrasound signals. Moreover, CTG is not suitable for long-term monitoring. Therefore, researchers have been developing algorithms to estimate the FHR using electrocardiograms (ECGs) from the abdomen of pregnant women. However, separating the weak fetal ECG signal from the abdominal ECG signal is a challenging problem. In this paper, we propose a method for estimating the FHR using sequential total variation denoising and compare its performance with that of other single-channel fetal ECG extraction methods via simulation using the Fetal ECG Synthetic Database (FECGSYNDB). Moreover, we used real data from PhysioNet fetal ECG databases for the evaluation of the algorithm performance. The R-peak detection rate is calculated to evaluate the performance of our algorithm. Our approach could not only separate the fetal ECG signals from the abdominal ECG signals but also accurately estimate the FHR. Full article
(This article belongs to the Special Issue Noninvasive Biomedical Sensors)
Open AccessArticle A Distributed Learning Method for ℓ 1 -Regularized Kernel Machine over Wireless Sensor Networks
Sensors 2016, 16(7), 1021; doi:10.3390/s16071021
Received: 14 March 2016 / Revised: 23 June 2016 / Accepted: 24 June 2016 / Published: 1 July 2016
PDF Full-text (880 KB) | HTML Full-text | XML Full-text
Abstract
In wireless sensor networks, centralized learning methods have very high communication costs and energy consumption. These are caused by the need to transmit scattered training examples from various sensor nodes to the central fusion center where a classifier or a regression machine is
[...] Read more.
In wireless sensor networks, centralized learning methods have very high communication costs and energy consumption. These are caused by the need to transmit scattered training examples from various sensor nodes to the central fusion center where a classifier or a regression machine is trained. To reduce the communication cost, a distributed learning method for a kernel machine that incorporates 1 norm regularization ( 1 -regularized) is investigated, and a novel distributed learning algorithm for the 1 -regularized kernel minimum mean squared error (KMSE) machine is proposed. The proposed algorithm relies on in-network processing and a collaboration that transmits the sparse model only between single-hop neighboring nodes. This paper evaluates the proposed algorithm with respect to the prediction accuracy, the sparse rate of model, the communication cost and the number of iterations on synthetic and real datasets. The simulation results show that the proposed algorithm can obtain approximately the same prediction accuracy as that obtained by the batch learning method. Moreover, it is significantly superior in terms of the sparse rate of model and communication cost, and it can converge with fewer iterations. Finally, an experiment conducted on a wireless sensor network (WSN) test platform further shows the advantages of the proposed algorithm with respect to communication cost. Full article
(This article belongs to the Special Issue Advances in Multi-Sensor Information Fusion: Theory and Applications)
Open AccessArticle Collaboration-Centred Cities through Urban Apps Based on Open and User-Generated Data
Sensors 2016, 16(7), 1022; doi:10.3390/s16071022
Received: 28 April 2016 / Revised: 24 June 2016 / Accepted: 26 June 2016 / Published: 1 July 2016
Cited by 3 | PDF Full-text (5035 KB) | HTML Full-text | XML Full-text
Abstract
This paper describes the IES Cities platform conceived to streamline the development of urban apps that combine heterogeneous datasets provided by diverse entities, namely, government, citizens, sensor infrastructure and other information data sources. This work pursues the challenge of achieving effective citizen collaboration
[...] Read more.
This paper describes the IES Cities platform conceived to streamline the development of urban apps that combine heterogeneous datasets provided by diverse entities, namely, government, citizens, sensor infrastructure and other information data sources. This work pursues the challenge of achieving effective citizen collaboration by empowering them to prosume urban data across time. Particularly, this paper focuses on the query mapper; a key component of the IES Cities platform devised to democratize the development of open data-based mobile urban apps. This component allows developers not only to use available data, but also to contribute to existing datasets with the execution of SQL sentences. In addition, the component allows developers to create ad hoc storages for their applications, publishable as new datasets accessible by other consumers. As multiple users could be contributing and using a dataset, our solution also provides a data level permission mechanism to control how the platform manages the access to its datasets. We have evaluated the advantages brought forward by IES Cities from the developers’ perspective by describing an exemplary urban app created on top of it. In addition, we include an evaluation of the main functionalities of the query mapper. Full article
(This article belongs to the Special Issue Selected Papers from UCAmI, IWAAL and AmIHEALTH 2015)
Figures

Open AccessArticle Content-Based Multi-Channel Network Coding Algorithm in the Millimeter-Wave Sensor Network
Sensors 2016, 16(7), 1023; doi:10.3390/s16071023
Received: 27 April 2016 / Revised: 25 June 2016 / Accepted: 28 June 2016 / Published: 1 July 2016
PDF Full-text (932 KB) | HTML Full-text | XML Full-text
Abstract
With the development of wireless technology, the widespread use of 5G is already an irreversible trend, and millimeter-wave sensor networks are becoming more and more common. However, due to the high degree of complexity and bandwidth bottlenecks, the millimeter-wave sensor network still faces
[...] Read more.
With the development of wireless technology, the widespread use of 5G is already an irreversible trend, and millimeter-wave sensor networks are becoming more and more common. However, due to the high degree of complexity and bandwidth bottlenecks, the millimeter-wave sensor network still faces numerous problems. In this paper, we propose a novel content-based multi-channel network coding algorithm, which uses the functions of data fusion, multi-channel and network coding to improve the data transmission; the algorithm is referred to as content-based multi-channel network coding (CMNC). The CMNC algorithm provides a fusion-driven model based on the Dempster-Shafer (D-S) evidence theory to classify the sensor nodes into different classes according to the data content. By using the result of the classification, the CMNC algorithm also provides the channel assignment strategy and uses network coding to further improve the quality of data transmission in the millimeter-wave sensor network. Extensive simulations are carried out and compared to other methods. Our simulation results show that the proposed CMNC algorithm can effectively improve the quality of data transmission and has better performance than the compared methods. Full article
(This article belongs to the Special Issue Millimeter Wave Wireless Communications and Networks)
Open AccessArticle Single-Use Disposable Electrochemical Label-Free Immunosensor for Detection of Glycated Hemoglobin (HbA1c) Using Differential Pulse Voltammetry (DPV)
Sensors 2016, 16(7), 1024; doi:10.3390/s16071024
Received: 3 June 2016 / Revised: 26 June 2016 / Accepted: 28 June 2016 / Published: 1 July 2016
Cited by 7 | PDF Full-text (2914 KB) | HTML Full-text | XML Full-text
Abstract
A single-use disposable in vitro electrochemical immunosensor for the detection of HbA1c in undiluted human serum using differential pulse voltammetry (DPV) was developed. A three-electrode configuration electrochemical biosensor consisted of 10-nm-thin gold film working and counter electrodes and a thick-film printed Ag/AgCl reference
[...] Read more.
A single-use disposable in vitro electrochemical immunosensor for the detection of HbA1c in undiluted human serum using differential pulse voltammetry (DPV) was developed. A three-electrode configuration electrochemical biosensor consisted of 10-nm-thin gold film working and counter electrodes and a thick-film printed Ag/AgCl reference electrode was fabricated on a polyethylene terephthalate (PET) substrate. Micro-fabrication techniques including sputtering vapor deposition and thick-film printing were used to fabricate the biosensor. This was a roll-to-roll cost-effective manufacturing process making the single-use disposable in vitro HbA1c biosensor a reality. Self-assembled monolayers of 3-Mercaptopropionic acid (MPA) were employed to covalently immobilize anti-HbA1c on the surface of gold electrodes. Electrochemical impedance spectroscopy (EIS) and X-ray photoelectron spectroscopy (XPS) confirmed the excellent coverage of MPA-SAM and the upward orientation of carboxylic groups. The hindering effect of HbA1c on the ferricyanide/ferrocyanide electron transfer reaction was exploited as the HbA1c detection mechanism. The biosensor showed a linear range of 7.5–20 µg/mL of HbA1c in 0.1 M PBS. Using undiluted human serum as the test medium, the biosensor presented an excellent linear behavior (R2 = 0.999) in the range of 0.1–0.25 mg/mL of HbA1c. The potential application of this biosensor for in vitro measurement of HbA1c for diabetic management was demonstrated. Full article
(This article belongs to the Special Issue Sensors for Glycoproteins and Glycated Proteins)
Figures

Open AccessArticle Design of Diaphragm and Coil for Stable Performance of an Eddy Current Type Pressure Sensor
Sensors 2016, 16(7), 1025; doi:10.3390/s16071025
Received: 7 April 2016 / Revised: 21 June 2016 / Accepted: 22 June 2016 / Published: 1 July 2016
Cited by 1 | PDF Full-text (7164 KB) | HTML Full-text | XML Full-text
Abstract
The aim of this work was to develop an eddy current type pressure sensor and investigate its fundamental characteristics affected by the mechanical and electrical design parameters of sensor. The sensor has two key components, i.e., diaphragm and coil. On the condition that
[...] Read more.
The aim of this work was to develop an eddy current type pressure sensor and investigate its fundamental characteristics affected by the mechanical and electrical design parameters of sensor. The sensor has two key components, i.e., diaphragm and coil. On the condition that the outer diameter of sensor is 10 mm, two key parts should be designed so as to keep a good linearity and sensitivity. Experiments showed that aluminum is the best target material for eddy current detection. A round-grooved diaphragm is suggested in order to measure more precisely its deflection caused by applied pressures. The design parameters of a round-grooved diaphragm can be selected depending on the measuring requirements. A developed pressure sensor with diaphragm of t = 0.2 mm and w = 1.05 mm was verified to measure pressure up to 10 MPa with very good linearity and errors of less than 0.16%. Full article
(This article belongs to the Section Physical Sensors)
Open AccessArticle The Integration of the Image Sensor with a 3-DOF Pneumatic Parallel Manipulator
Sensors 2016, 16(7), 1026; doi:10.3390/s16071026
Received: 6 April 2016 / Revised: 24 June 2016 / Accepted: 28 June 2016 / Published: 1 July 2016
PDF Full-text (10872 KB) | HTML Full-text | XML Full-text
Abstract
The study aims to integrate the image sensor for a three-axial pneumatic parallel manipulator which can pick and place objects automatically by the feature information of the image processed through the SURF algorithm. The SURF algorithm is adopted for defining and matching the
[...] Read more.
The study aims to integrate the image sensor for a three-axial pneumatic parallel manipulator which can pick and place objects automatically by the feature information of the image processed through the SURF algorithm. The SURF algorithm is adopted for defining and matching the features of a target object and an object database. In order to accurately mark the center of target and strengthen the feature matching results, the random sample and consensus method (RANSAC) is utilized. The ASUS Xtion Pro Live depth camera which can directly estimate the 3-D location of the target point is used in this study. A set of coordinate estimation calibrations is developed for enhancing the accuracy of target location estimation. This study also presents hand gesture recognition exploiting skin detection and noise elimination to determine the active finger count for input signals of the parallel manipulator. The end-effector of the parallel manipulator can be manipulated to the desired poses according to the measured finger count. Finally, the proposed methods are successfully to achieve the feature recognition and pick and place of the target object. Full article
(This article belongs to the Special Issue Advanced Robotics and Mechatronics Devices)
Figures

Open AccessArticle LEA Detection and Tracking Method for Color-Independent Visual-MIMO
Sensors 2016, 16(7), 1027; doi:10.3390/s16071027
Received: 28 February 2016 / Revised: 6 June 2016 / Accepted: 27 June 2016 / Published: 2 July 2016
Cited by 2 | PDF Full-text (4711 KB) | HTML Full-text | XML Full-text | Supplementary Files
Abstract
Communication performance in the color-independent visual-multiple input multiple output (visual-MIMO) technique is deteriorated by light emitting array (LEA) detection and tracking errors in the received image because the image sensor included in the camera must be used as the receiver in the visual-MIMO
[...] Read more.
Communication performance in the color-independent visual-multiple input multiple output (visual-MIMO) technique is deteriorated by light emitting array (LEA) detection and tracking errors in the received image because the image sensor included in the camera must be used as the receiver in the visual-MIMO system. In this paper, in order to improve detection reliability, we first set up the color-space-based region of interest (ROI) in which an LEA is likely to be placed, and then use the Harris corner detection method. Next, we use Kalman filtering for robust tracking by predicting the most probable location of the LEA when the relative position between the camera and the LEA varies. In the last step of our proposed method, the perspective projection is used to correct the distorted image, which can improve the symbol decision accuracy. Finally, through numerical simulation, we show the possibility of robust detection and tracking of the LEA, which results in a symbol error rate (SER) performance improvement. Full article
Open AccessArticle On the Use of a Signal Quality Index Applying at Tracking Stage Level to Assist the RAIM System of a GNSS Receiver
Sensors 2016, 16(7), 1029; doi:10.3390/s16071029
Received: 6 May 2016 / Revised: 23 June 2016 / Accepted: 27 June 2016 / Published: 2 July 2016
Cited by 1 | PDF Full-text (4650 KB) | HTML Full-text | XML Full-text
Abstract
In this work, a novel signal processing method is proposed to assist the Receiver Autonomous Integrity Monitoring (RAIM) module used in a receiver of Global Navigation Satellite Systems (GNSS) to improve the integrity of the estimated position. The proposed technique represents an evolution
[...] Read more.
In this work, a novel signal processing method is proposed to assist the Receiver Autonomous Integrity Monitoring (RAIM) module used in a receiver of Global Navigation Satellite Systems (GNSS) to improve the integrity of the estimated position. The proposed technique represents an evolution of the Multipath Distance Detector (MPDD), thanks to the introduction of a Signal Quality Index (SQI), which is both a metric able to evaluate the goodness of the signal, and a parameter used to improve the performance of the RAIM modules. Simulation results show the effectiveness of the proposed method. Full article
(This article belongs to the Section Remote Sensors)
Open AccessArticle Exchange Bias Tuning for Magnetoresistive Sensors by Inclusion of Non-Magnetic Impurities
Sensors 2016, 16(7), 1030; doi:10.3390/s16071030
Received: 20 April 2016 / Revised: 20 June 2016 / Accepted: 28 June 2016 / Published: 4 July 2016
Cited by 3 | PDF Full-text (2319 KB) | HTML Full-text | XML Full-text
Abstract
The fine control of the exchange coupling strength and blocking temperature ofexchange bias systems is an important requirement for the development of magnetoresistive sensors with two pinned electrodes. In this paper, we successfully tune these parameters in top- and bottom-pinned systems, comprising 5
[...] Read more.
The fine control of the exchange coupling strength and blocking temperature ofexchange bias systems is an important requirement for the development of magnetoresistive sensors with two pinned electrodes. In this paper, we successfully tune these parameters in top- and bottom-pinned systems, comprising 5 nm thick Co40Fe40B20 and 6.5 nm thick Ir22Mn78 films. By inserting Ru impurities at different concentrations in the Ir22Mn78 layer, blocking temperatures ranging from 220 °C to 100 °C and exchange bias fields from 200 Oe to 60 Oe are obtained. This method is then applied to the fabrication of sensors based on magnetic tunneling junctions consisting of a pinned synthetic antiferromagnet reference layer and a top-pinned sensing layer. This work paves the way towards the development of new sensors with finely tuned magnetic anisotropies. Full article
(This article belongs to the Special Issue Magnetoresistive Sensors under Extreme Conditions)
Open AccessArticle A Channelization-Based DOA Estimation Method for Wideband Signals
Sensors 2016, 16(7), 1031; doi:10.3390/s16071031
Received: 4 May 2016 / Revised: 12 June 2016 / Accepted: 28 June 2016 / Published: 4 July 2016
PDF Full-text (5293 KB) | HTML Full-text | XML Full-text
Abstract
In this paper, we propose a novel direction of arrival (DOA) estimation method for wideband signals with sensor arrays. The proposed method splits the wideband array output into multiple frequency sub-channels and estimates the signal parameters using a digital channelization receiver. Based on
[...] Read more.
In this paper, we propose a novel direction of arrival (DOA) estimation method for wideband signals with sensor arrays. The proposed method splits the wideband array output into multiple frequency sub-channels and estimates the signal parameters using a digital channelization receiver. Based on the output sub-channels, a channelization-based incoherent signal subspace method (Channelization-ISM) and a channelization-based test of orthogonality of projected subspaces method (Channelization-TOPS) are proposed. Channelization-ISM applies narrowband signal subspace methods on each sub-channel independently. Then the arithmetic mean or geometric mean of the estimated DOAs from each sub-channel gives the final result. Channelization-TOPS measures the orthogonality between the signal and the noise subspaces of the output sub-channels to estimate DOAs. The proposed channelization-based method isolates signals in different bandwidths reasonably and improves the output SNR. It outperforms the conventional ISM and TOPS methods on estimation accuracy and dynamic range, especially in real environments. Besides, the parallel processing architecture makes it easy to implement on hardware. A wideband digital array radar (DAR) using direct wideband radio frequency (RF) digitization is presented. Experiments carried out in a microwave anechoic chamber with the wideband DAR are presented to demonstrate the performance. The results verify the effectiveness of the proposed method. Full article
(This article belongs to the Section Physical Sensors)
Open AccessArticle Design of Helical Capacitance Sensor for Holdup Measurement in Two-Phase Stratified Flow: A Sinusoidal Function Approach
Sensors 2016, 16(7), 1032; doi:10.3390/s16071032
Received: 3 June 2016 / Revised: 30 June 2016 / Accepted: 30 June 2016 / Published: 4 July 2016
Cited by 3 | PDF Full-text (4580 KB) | HTML Full-text | XML Full-text | Supplementary Files
Abstract
A 360° twisted helical capacitance sensor was developed for holdup measurement in horizontal two-phase stratified flow. Instead of suppressing nonlinear response, the sensor was optimized in such a way that a ‘sine-like’ function was displayed on top of the linear function. This concept
[...] Read more.
A 360° twisted helical capacitance sensor was developed for holdup measurement in horizontal two-phase stratified flow. Instead of suppressing nonlinear response, the sensor was optimized in such a way that a ‘sine-like’ function was displayed on top of the linear function. This concept of design had been implemented and verified in both software and hardware. A good agreement was achieved between the finite element model of proposed design and the approximation model (pure sinusoidal function), with a maximum difference of ±1.2%. In addition, the design parameters of the sensor were analysed and investigated. It was found that the error in symmetry of the sinusoidal function could be minimized by adjusting the pitch of helix. The experiments of air-water and oil-water stratified flows were carried out and validated the sinusoidal relationship with a maximum difference of ±1.2% and ±1.3% for the range of water holdup from 0.15 to 0.85. The proposed design concept therefore may pose a promising alternative for the optimization of capacitance sensor design. Full article
(This article belongs to the Section Physical Sensors)
Figures

Open AccessArticle A Novel Wearable Sensor-Based Human Activity Recognition Approach Using Artificial Hydrocarbon Networks
Sensors 2016, 16(7), 1033; doi:10.3390/s16071033
Received: 31 March 2016 / Revised: 22 June 2016 / Accepted: 24 June 2016 / Published: 5 July 2016
Cited by 4 | PDF Full-text (658 KB) | HTML Full-text | XML Full-text
Abstract
Human activity recognition has gained more interest in several research communities given that understanding user activities and behavior helps to deliver proactive and personalized services. There are many examples of health systems improved by human activity recognition. Nevertheless, the human activity recognition classification
[...] Read more.
Human activity recognition has gained more interest in several research communities given that understanding user activities and behavior helps to deliver proactive and personalized services. There are many examples of health systems improved by human activity recognition. Nevertheless, the human activity recognition classification process is not an easy task. Different types of noise in wearable sensors data frequently hamper the human activity recognition classification process. In order to develop a successful activity recognition system, it is necessary to use stable and robust machine learning techniques capable of dealing with noisy data. In this paper, we presented the artificial hydrocarbon networks (AHN) technique to the human activity recognition community. Our artificial hydrocarbon networks novel approach is suitable for physical activity recognition, noise tolerance of corrupted data sensors and robust in terms of different issues on data sensors. We proved that the AHN classifier is very competitive for physical activity recognition and is very robust in comparison with other well-known machine learning methods. Full article
(This article belongs to the Special Issue Selected Papers from UCAmI, IWAAL and AmIHEALTH 2015)
Figures

Open AccessArticle Multi-Sensor Integration to Map Odor Distribution for the Detection of Chemical Sources
Sensors 2016, 16(7), 1034; doi:10.3390/s16071034
Received: 14 March 2016 / Revised: 24 May 2016 / Accepted: 25 May 2016 / Published: 4 July 2016
Cited by 1 | PDF Full-text (5384 KB) | HTML Full-text | XML Full-text
Abstract
This paper addresses the problem of mapping odor distribution derived from a chemical source using multi-sensor integration and reasoning system design. Odor localization is the problem of finding the source of an odor or other volatile chemical. Most localization methods require a mobile
[...] Read more.
This paper addresses the problem of mapping odor distribution derived from a chemical source using multi-sensor integration and reasoning system design. Odor localization is the problem of finding the source of an odor or other volatile chemical. Most localization methods require a mobile vehicle to follow an odor plume along its entire path, which is time consuming and may be especially difficult in a cluttered environment. To solve both of the above challenges, this paper proposes a novel algorithm that combines data from odor and anemometer sensors, and combine sensors’ data at different positions. Initially, a multi-sensor integration method, together with the path of airflow was used to map the pattern of odor particle movement. Then, more sensors are introduced at specific regions to determine the probable location of the odor source. Finally, the results of odor source location simulation and a real experiment are presented. Full article
(This article belongs to the Special Issue Advances in Multi-Sensor Information Fusion: Theory and Applications)
Open AccessArticle Policy 2.0 Platform for Mobile Sensing and Incentivized Targeted Shifts in Mobility Behavior
Sensors 2016, 16(7), 1035; doi:10.3390/s16071035
Received: 4 April 2016 / Revised: 20 June 2016 / Accepted: 29 June 2016 / Published: 5 July 2016
Cited by 5 | PDF Full-text (3508 KB) | HTML Full-text | XML Full-text
Abstract
Sustainable mobility and smart mobility management play important roles in achieving smart cities’ goals. In this context we investigate the role of smartphones as mobility behavior sensors and evaluate the responsivity of different attitudinal profiles towards personalized route suggestion incentives delivered via mobile
[...] Read more.
Sustainable mobility and smart mobility management play important roles in achieving smart cities’ goals. In this context we investigate the role of smartphones as mobility behavior sensors and evaluate the responsivity of different attitudinal profiles towards personalized route suggestion incentives delivered via mobile phones. The empirical results are based on mobile sensed data collected from more than 3400 people’s real life over a period of six months. The findings show which user profiles are most likely to accept such incentives and how likely they are to result in more sustainable mode choices. In addition we provide insights into tendencies towards accepting more sustainable route options for different trip purposes and illustrate smart city platform potential (for collection of mobility behavior data and delivery of incentives) as a tool for development of personalized mobility management campaigns and policies. Full article
(This article belongs to the Special Issue Smart City: Vision and Reality)
Open AccessArticle A Reliable TTP-Based Infrastructure with Low Sensor Resource Consumption for the Smart Home Multi-Platform
Sensors 2016, 16(7), 1036; doi:10.3390/s16071036
Received: 11 May 2016 / Revised: 22 June 2016 / Accepted: 25 June 2016 / Published: 5 July 2016
Cited by 4 | PDF Full-text (1572 KB) | HTML Full-text | XML Full-text
Abstract
With the ICT technology making great progress in the smart home environment, the ubiquitous environment is rapidly emerging all over the world, but problems are also increasing proportionally to the rapid growth of the smart home market such as multiplatform heterogeneity and new
[...] Read more.
With the ICT technology making great progress in the smart home environment, the ubiquitous environment is rapidly emerging all over the world, but problems are also increasing proportionally to the rapid growth of the smart home market such as multiplatform heterogeneity and new security threats. In addition, the smart home sensors have so low computing resources that they cannot process complicated computation tasks, which is required to create a proper security environment. A service provider also faces overhead in processing data from a rapidly increasing number of sensors. This paper aimed to propose a scheme to build infrastructure in which communication entities can securely authenticate and design security channel with physically unclonable PUFs and the TTP that smart home communication entities can rely on. In addition, we analyze and evaluate the proposed scheme for security and performance and prove that it can build secure channels with low resources. Finally, we expect that the proposed scheme can be helpful for secure communication with low resources in future smart home multiplatforms. Full article
(This article belongs to the Special Issue Advances on Resources Management for Multi-Platform Infrastructures)
Open AccessArticle Autonomous Quality Control of Joint Orientation Measured with Inertial Sensors
Sensors 2016, 16(7), 1037; doi:10.3390/s16071037
Received: 18 April 2016 / Revised: 29 June 2016 / Accepted: 29 June 2016 / Published: 5 July 2016
Cited by 3 | PDF Full-text (2911 KB) | HTML Full-text | XML Full-text
Abstract
Clinical mobility assessment is traditionally performed in laboratories using complex and expensive equipment. The low accessibility to such equipment, combined with the emerging trend to assess mobility in a free-living environment, creates a need for body-worn sensors (e.g., inertial measurement units—IMUs) that are
[...] Read more.
Clinical mobility assessment is traditionally performed in laboratories using complex and expensive equipment. The low accessibility to such equipment, combined with the emerging trend to assess mobility in a free-living environment, creates a need for body-worn sensors (e.g., inertial measurement units—IMUs) that are capable of measuring the complexity in motor performance using meaningful measurements, such as joint orientation. However, accuracy of joint orientation estimates using IMUs may be affected by environment, the joint tracked, type of motion performed and velocity. This study investigates a quality control (QC) process to assess the quality of orientation data based on features extracted from the raw inertial sensors’ signals. Joint orientation (trunk, hip, knee, ankle) of twenty participants was acquired by an optical motion capture system and IMUs during a variety of tasks (sit, sit-to-stand transition, walking, turning) performed under varying conditions (speed, environment). An artificial neural network was used to classify good and bad sequences of joint orientation with a sensitivity and a specificity above 83%. This study confirms the possibility to perform QC on IMU joint orientation data based on raw signal features. This innovative QC approach may be of particular interest in a big data context, such as for remote-monitoring of patients’ mobility. Full article
(This article belongs to the Section Physical Sensors)
Open AccessArticle Developing a Penetrometer-Based Mapping System for Visualizing Silage Bulk Density from the Bunker Silo Face
Sensors 2016, 16(7), 1038; doi:10.3390/s16071038
Received: 25 April 2016 / Revised: 19 June 2016 / Accepted: 1 July 2016 / Published: 5 July 2016
PDF Full-text (12001 KB) | HTML Full-text | XML Full-text
Abstract
For silage production, high bulk density (BD) is critical to minimize aerobic deterioration facilitated by oxygen intrusion. To precisely assess packing quality for bunker silos, there is a desire to visualize the BD distribution within the silage. In this study, a penetrometer-based mapping
[...] Read more.
For silage production, high bulk density (BD) is critical to minimize aerobic deterioration facilitated by oxygen intrusion. To precisely assess packing quality for bunker silos, there is a desire to visualize the BD distribution within the silage. In this study, a penetrometer-based mapping system was developed. The data processing included filtering of the penetration friction component (PFC) out of the penetration resistance (PR), transfer of the corrected penetration resistance (PRc) to BD, incorporation of Kriged interpolation for data expansion and map generation. The experiment was conducted in a maize bunker silo (width: 8 m, middle height: 3 m). The BD distributions near the bunker silo face were represented using two map groups, one related to horizontal- and the other to vertical-density distribution patterns. We also presented a comparison between the map-based BD results and core sampling data. Agreement between the two measurement approaches (RMSE = 19.175 kg·m−3) demonstrates that the developed penetrometer mapping system may be beneficial for rapid assessment of aerobic deterioration potential in bunker silos. Full article
(This article belongs to the Special Issue Sensors for Agriculture)
Open AccessArticle Filtering Based Adaptive Visual Odometry Sensor Framework Robust to Blurred Images
Sensors 2016, 16(7), 1040; doi:10.3390/s16071040
Received: 28 March 2016 / Revised: 18 June 2016 / Accepted: 28 June 2016 / Published: 5 July 2016
Cited by 1 | PDF Full-text (4320 KB) | HTML Full-text | XML Full-text
Abstract
Visual odometry (VO) estimation from blurred image is a challenging problem in practical robot applications, and the blurred images will severely reduce the estimation accuracy of the VO. In this paper, we address the problem of visual odometry estimation from blurred images, and
[...] Read more.
Visual odometry (VO) estimation from blurred image is a challenging problem in practical robot applications, and the blurred images will severely reduce the estimation accuracy of the VO. In this paper, we address the problem of visual odometry estimation from blurred images, and present an adaptive visual odometry estimation framework robust to blurred images. Our approach employs an objective measure of images, named small image gradient distribution (SIGD), to evaluate the blurring degree of the image, then an adaptive blurred image classification algorithm is proposed to recognize the blurred images, finally we propose an anti-blurred key-frame selection algorithm to enable the VO robust to blurred images. We also carried out varied comparable experiments to evaluate the performance of the VO algorithms with our anti-blur framework under varied blurred images, and the experimental results show that our approach can achieve superior performance comparing to the state-of-the-art methods under the condition with blurred images while not increasing too much computation cost to the original VO algorithms. Full article
(This article belongs to the Special Issue Vision-Based Sensors in Field Robotics)
Open AccessArticle An MEF-Based Localization Algorithm against Outliers in Wireless Sensor Networks
Sensors 2016, 16(7), 1041; doi:10.3390/s16071041
Received: 31 March 2016 / Revised: 19 June 2016 / Accepted: 26 June 2016 / Published: 7 July 2016
Cited by 1 | PDF Full-text (4536 KB) | HTML Full-text | XML Full-text
Abstract
Precise localization has attracted considerable interest in Wireless Sensor Networks (WSNs) localization systems. Due to the internal or external disturbance, the existence of the outliers, including both the distance outliers and the anchor outliers, severely decreases the localization accuracy. In order to eliminate
[...] Read more.
Precise localization has attracted considerable interest in Wireless Sensor Networks (WSNs) localization systems. Due to the internal or external disturbance, the existence of the outliers, including both the distance outliers and the anchor outliers, severely decreases the localization accuracy. In order to eliminate both kinds of outliers simultaneously, an outlier detection method is proposed based on the maximum entropy principle and fuzzy set theory. Since not all the outliers can be detected in the detection process, the Maximum Entropy Function (MEF) method is utilized to tolerate the errors and calculate the optimal estimated locations of unknown nodes. Simulation results demonstrate that the proposed localization method remains stable while the outliers vary. Moreover, the localization accuracy is highly improved by wisely rejecting outliers. Full article
(This article belongs to the Section Sensor Networks)
Open AccessArticle Design of Flow Systems for Improved Networking and Reduced Noise in Biomolecular Signal Processing in Biocomputing and Biosensing Applications
Sensors 2016, 16(7), 1042; doi:10.3390/s16071042
Received: 26 April 2016 / Revised: 21 June 2016 / Accepted: 24 June 2016 / Published: 5 July 2016
Cited by 3 | PDF Full-text (2555 KB) | HTML Full-text | XML Full-text | Supplementary Files
Abstract
We consider flow systems that have been utilized for small-scale biomolecular computing and digital signal processing in binary-operating biosensors. Signal measurement is optimized by designing a flow-reversal cuvette and analyzing the experimental data to theoretically extract the pulse shape, as well as reveal
[...] Read more.
We consider flow systems that have been utilized for small-scale biomolecular computing and digital signal processing in binary-operating biosensors. Signal measurement is optimized by designing a flow-reversal cuvette and analyzing the experimental data to theoretically extract the pulse shape, as well as reveal the level of noise it possesses. Noise reduction is then carried out numerically. We conclude that this can be accomplished physically via the addition of properly designed well-mixing flow-reversal cell(s) as an integral part of the flow system. This approach should enable improved networking capabilities and potentially not only digital but analog signal-processing in such systems. Possible applications in complex biocomputing networks and various sense-and-act systems are discussed. Full article
(This article belongs to the Section Biosensors)
Figures

Open AccessArticle Node Detection and Internode Length Estimation of Tomato Seedlings Based on Image Analysis and Machine Learning
Sensors 2016, 16(7), 1044; doi:10.3390/s16071044
Received: 16 April 2016 / Revised: 27 June 2016 / Accepted: 1 July 2016 / Published: 7 July 2016
Cited by 1 | PDF Full-text (1125 KB) | HTML Full-text | XML Full-text
Abstract
Seedling vigor in tomatoes determines the quality and growth of fruits and total plant productivity. It is well known that the salient effects of environmental stresses appear on the internode length; the length between adjoining main stem node (henceforth called node). In this
[...] Read more.
Seedling vigor in tomatoes determines the quality and growth of fruits and total plant productivity. It is well known that the salient effects of environmental stresses appear on the internode length; the length between adjoining main stem node (henceforth called node). In this study, we develop a method for internode length estimation using image processing technology. The proposed method consists of three steps: node detection, node order estimation, and internode length estimation. This method has two main advantages: (i) as it uses machine learning approaches for node detection, it does not require adjustment of threshold values even though seedlings are imaged under varying timings and lighting conditions with complex backgrounds; and (ii) as it uses affinity propagation for node order estimation, it can be applied to seedlings with different numbers of nodes without prior provision of the node number as a parameter. Our node detection results show that the proposed method can detect 72% of the 358 nodes in time-series imaging of three seedlings (recall = 0.72, precision = 0.78). In particular, the application of a general object recognition approach, Bag of Visual Words (BoVWs), enabled the elimination of many false positives on leaves occurring in the image segmentation based on pixel color, significantly improving the precision. The internode length estimation results had a relative error of below 15.4%. These results demonstrate that our method has the ability to evaluate the vigor of tomato seedlings quickly and accurately. Full article
(This article belongs to the Special Issue Sensors for Agriculture)
Figures

Open AccessArticle Flexible Piezoelectric Energy Harvesting from Mouse Click Motions
Sensors 2016, 16(7), 1045; doi:10.3390/s16071045
Received: 8 June 2016 / Accepted: 4 July 2016 / Published: 6 July 2016
Cited by 6 | PDF Full-text (635 KB) | HTML Full-text | XML Full-text
Abstract
In this paper, we study energy harvesting from the mouse click motions of a robot finger and a human index finger using a piezoelectric material. The feasibility of energy harvesting from mouse click motions is experimentally and theoretically assessed. The fingers wear a
[...] Read more.
In this paper, we study energy harvesting from the mouse click motions of a robot finger and a human index finger using a piezoelectric material. The feasibility of energy harvesting from mouse click motions is experimentally and theoretically assessed. The fingers wear a glove with a pocket for including the piezoelectric material. We model the energy harvesting system through the inverse kinematic framework of parallel joints in a finger and the electromechanical coupling equations of the piezoelectric material. The model is validated through energy harvesting experiments in the robot and human fingers with the systematically varying load resistance. We find that energy harvesting is maximized at the matched load resistance to the impedance of the piezoelectric material, and the harvested energy level is tens of nJ. Full article
(This article belongs to the Special Issue Advanced Robotics and Mechatronics Devices)
Open AccessArticle Microwave Imaging under Oblique Illumination
Sensors 2016, 16(7), 1046; doi:10.3390/s16071046
Received: 7 May 2016 / Accepted: 5 July 2016 / Published: 6 July 2016
PDF Full-text (5432 KB) | HTML Full-text | XML Full-text
Abstract
Microwave imaging based on inverse scattering problem has been attracting many interests in the microwave society. Among some major technical challenges, the ill-posed, multi-dimensional inversion algorithm and the complicated measurement setup are critical ones that prevent it from practical applications. In this paper,
[...] Read more.
Microwave imaging based on inverse scattering problem has been attracting many interests in the microwave society. Among some major technical challenges, the ill-posed, multi-dimensional inversion algorithm and the complicated measurement setup are critical ones that prevent it from practical applications. In this paper, we experimentally investigate the performance of the subspace-based optimization method (SOM) for two-dimensional objects when it was applied to a setup designed for oblique incidence. Analytical, simulation, and experimental results show that, for 2D objects, neglecting the cross-polarization scattering will not cause a notable loss of information. Our method can be potentially used in practical imaging applications for 2D-like objects, such as human limbs. Full article
(This article belongs to the Special Issue Non-Contact Sensing)
Figures

Open AccessArticle Rule-Based vs. Behavior-Based Self-Deployment for Mobile Wireless Sensor Networks
Sensors 2016, 16(7), 1047; doi:10.3390/s16071047
Received: 28 April 2016 / Revised: 13 June 2016 / Accepted: 5 July 2016 / Published: 7 July 2016
Cited by 3 | PDF Full-text (7091 KB) | HTML Full-text | XML Full-text
Abstract
In mobile wireless sensor networks (MWSN), nodes are allowed to move autonomously for deployment. This process is meant: (i) to achieve good coverage; and (ii) to distribute the communication load as homogeneously as possible. Rather than optimizing deployment, reactive algorithms are based on
[...] Read more.
In mobile wireless sensor networks (MWSN), nodes are allowed to move autonomously for deployment. This process is meant: (i) to achieve good coverage; and (ii) to distribute the communication load as homogeneously as possible. Rather than optimizing deployment, reactive algorithms are based on a set of rules or behaviors, so nodes can determine when to move. This paper presents an experimental evaluation of both reactive deployment approaches: rule-based and behavior-based ones. Specifically, we compare a backbone dispersion algorithm with a social potential fields algorithm. Most tests are done under simulation for a large number of nodes in environments with and without obstacles. Results are validated using a small robot network in the real world. Our results show that behavior-based deployment tends to provide better coverage and communication balance, especially for a large number of nodes in areas with obstacles. Full article
(This article belongs to the Special Issue Selected Papers from UCAmI, IWAAL and AmIHEALTH 2015)
Open AccessArticle A Cyber-Physical System for Girder Hoisting Monitoring Based on Smartphones
Sensors 2016, 16(7), 1048; doi:10.3390/s16071048
Received: 18 May 2016 / Revised: 23 June 2016 / Accepted: 4 July 2016 / Published: 7 July 2016
Cited by 5 | PDF Full-text (14953 KB) | HTML Full-text | XML Full-text
Abstract
Offshore design and construction is much more difficult than land-based design and construction, particularly due to hoisting operations. Real-time monitoring of the orientation and movement of a hoisted structure is thus required for operators’ safety. In recent years, rapid development of the smart-phone
[...] Read more.
Offshore design and construction is much more difficult than land-based design and construction, particularly due to hoisting operations. Real-time monitoring of the orientation and movement of a hoisted structure is thus required for operators’ safety. In recent years, rapid development of the smart-phone commercial market has offered the possibility that everyone can carry a mini personal computer that is integrated with sensors, an operating system and communication system that can act as an effective aid for cyber-physical systems (CPS) research. In this paper, a CPS for hoisting monitoring using smartphones was proposed, including a phone collector, a controller and a server. This system uses smartphones equipped with internal sensors to obtain girder movement information, which will be uploaded to a server, then returned to controller users. An alarming system will be provided on the controller phone once the returned data exceeds a threshold. The proposed monitoring system is used to monitor the movement and orientation of a girder during hoisting on a cross-sea bridge in real time. The results show the convenience and feasibility of the proposed system. Full article
(This article belongs to the Special Issue New Paradigms in Cyber-Physical Social Sensing)
Figures

Open AccessArticle A Framework for the Development of Context-Adaptable User Interfaces for Ubiquitous Computing Systems
Sensors 2016, 16(7), 1049; doi:10.3390/s16071049
Received: 29 April 2016 / Revised: 28 June 2016 / Accepted: 30 June 2016 / Published: 7 July 2016
PDF Full-text (3581 KB) | HTML Full-text | XML Full-text
Abstract
This paper addresses the problem of developing user interfaces for Ubiquitous Computing (UC) and Ambient Intelligence (AmI) systems. These kind of systems are expected to provide a natural user experience, considering interaction modalities adapted to the user abilities and preferences and using whatever
[...] Read more.
This paper addresses the problem of developing user interfaces for Ubiquitous Computing (UC) and Ambient Intelligence (AmI) systems. These kind of systems are expected to provide a natural user experience, considering interaction modalities adapted to the user abilities and preferences and using whatever interaction devices are present in the environment. These interaction devices are not necessarily known at design time. The task is quite complicated due to the variety of devices and technologies, and the diversity of scenarios, and it usually burdens the developer with the need to create many different UIs in order to consider the foreseeable user-environment combinations. Here, we propose an UI abstraction framework for UC and AmI systems that effectively improves the portability of those systems between different environments and for different users. It allows developers to design and implement a single UI capable of being deployed with different devices and modalities regardless the physical location. Full article
(This article belongs to the Special Issue Selected Papers from UCAmI, IWAAL and AmIHEALTH 2015)
Open AccessArticle Multiplexed Simultaneous High Sensitivity Sensors with High-Order Mode Based on the Integration of Photonic Crystal 1 × 3 Beam Splitter and Three Different Single-Slot PCNCs
Sensors 2016, 16(7), 1050; doi:10.3390/s16071050
Received: 1 April 2016 / Revised: 27 June 2016 / Accepted: 6 July 2016 / Published: 7 July 2016
Cited by 2 | PDF Full-text (4093 KB) | HTML Full-text | XML Full-text
Abstract
We simulated an efficient method for the sensor array of high-sensitivity single-slot photonic crystal nanobeam cavities (PCNCs) on a silicon platform. With the combination of a well-designed photonic crystal waveguide (PhCW) filter and an elaborate single-slot PCNC, a specific high-order resonant mode was
[...] Read more.
We simulated an efficient method for the sensor array of high-sensitivity single-slot photonic crystal nanobeam cavities (PCNCs) on a silicon platform. With the combination of a well-designed photonic crystal waveguide (PhCW) filter and an elaborate single-slot PCNC, a specific high-order resonant mode was filtered for sensing. A 1 × 3 beam splitter carefully established was implemented to split channels and integrate three sensors to realize microarrays. By applying the three-dimensional finite-difference-time-domain (3D-FDTD) method, the sensitivities calculated were S1 = 492 nm/RIU, S2 = 244 nm/RIU, and S3 = 552 nm/RIU, respectively. To the best of our knowledge, this is the first multiplexing design in which each sensor cite features such a high sensitivity simultaneously. Full article
(This article belongs to the Special Issue Label-Free Optical Biosensors)
Open AccessArticle First Eigenmode Transmission by High Efficient CSI Estimation for Multiuser Massive MIMO Using Millimeter Wave Bands
Sensors 2016, 16(7), 1051; doi:10.3390/s16071051
Received: 7 May 2016 / Revised: 4 July 2016 / Accepted: 5 July 2016 / Published: 8 July 2016
Cited by 1 | PDF Full-text (4278 KB) | HTML Full-text | XML Full-text
Abstract
Drastic improvements in transmission rate and system capacity are required towards 5th generation mobile communications (5G). One promising approach, utilizing the millimeter wave band for its rich spectrum resources, suffers area coverage shortfalls due to its large propagation loss. Fortunately, massive multiple-input multiple-output
[...] Read more.
Drastic improvements in transmission rate and system capacity are required towards 5th generation mobile communications (5G). One promising approach, utilizing the millimeter wave band for its rich spectrum resources, suffers area coverage shortfalls due to its large propagation loss. Fortunately, massive multiple-input multiple-output (MIMO) can offset this shortfall as well as offer high order spatial multiplexing gain. Multiuser MIMO is also effective in further enhancing system capacity by multiplexing spatially de-correlated users. However, the transmission performance of multiuser MIMO is strongly degraded by channel time variation, which causes inter-user interference since null steering must be performed at the transmitter. This paper first addresses the effectiveness of multiuser massive MIMO transmission that exploits the first eigenmode for each user. In Line-of-Sight (LoS) dominant channel environments, the first eigenmode is chiefly formed by the LoS component, which is highly correlated with user movement. Therefore, the first eigenmode provided by a large antenna array can improve the robustness against the channel time variation. In addition, we propose a simplified beamforming scheme based on high efficient channel state information (CSI) estimation that extracts the LoS component. We also show that this approximate beamforming can achieve throughput performance comparable to that of the rigorous first eigenmode transmission. Our proposed multiuser massive MIMO scheme can open the door for practical millimeter wave communication with enhanced system capacity. Full article
(This article belongs to the Special Issue Millimeter Wave Wireless Communications and Networks)
Open AccessArticle Capacitive Sensing for Non-Invasive Breathing and Heart Monitoring in Non-Restrained, Non-Sedated Laboratory Mice
Sensors 2016, 16(7), 1052; doi:10.3390/s16071052
Received: 24 May 2016 / Revised: 28 June 2016 / Accepted: 4 July 2016 / Published: 7 July 2016
Cited by 1 | PDF Full-text (5799 KB) | HTML Full-text | XML Full-text
Abstract
Animal testing plays a vital role in biomedical research. Stress reduction is important for improving research results and increasing the welfare and the quality of life of laboratory animals. To estimate stress we believe it is of great importance to develop non-invasive techniques
[...] Read more.
Animal testing plays a vital role in biomedical research. Stress reduction is important for improving research results and increasing the welfare and the quality of life of laboratory animals. To estimate stress we believe it is of great importance to develop non-invasive techniques for monitoring physiological signals during the transport of laboratory animals, thereby allowing the gathering of information on the transport conditions, and, eventually, the improvement of these conditions. Here, we study the suitability of commercially available electric potential integrated circuit (EPIC) sensors, using both contact and contactless techniques, for monitoring the heart rate and breathing rate of non-restrained, non-sedated laboratory mice. The design has been tested under different scenarios with the aim of checking the plausibility of performing contactless capture of mouse heart activity (ideally with an electrocardiogram). First experimental results are shown. Full article
(This article belongs to the Special Issue Noninvasive Biomedical Sensors)
Figures

Open AccessArticle Closed-Loop Lifecycle Management of Service and Product in the Internet of Things: Semantic Framework for Knowledge Integration
Sensors 2016, 16(7), 1053; doi:10.3390/s16071053
Received: 31 March 2016 / Revised: 24 June 2016 / Accepted: 28 June 2016 / Published: 8 July 2016
PDF Full-text (6584 KB) | HTML Full-text | XML Full-text
Abstract
This paper describes our conceptual framework of closed-loop lifecycle information sharing for product-service in the Internet of Things (IoT). The framework is based on the ontology model of product-service and a type of IoT message standard, Open Messaging Interface (O-MI) and Open Data
[...] Read more.
This paper describes our conceptual framework of closed-loop lifecycle information sharing for product-service in the Internet of Things (IoT). The framework is based on the ontology model of product-service and a type of IoT message standard, Open Messaging Interface (O-MI) and Open Data Format (O-DF), which ensures data communication. (1) Background: Based on an existing product lifecycle management (PLM) methodology, we enhanced the ontology model for the purpose of integrating efficiently the product-service ontology model that was newly developed; (2) Methods: The IoT message transfer layer is vertically integrated into a semantic knowledge framework inside which a Semantic Info-Node Agent (SINA) uses the message format as a common protocol of product-service lifecycle data transfer; (3) Results: The product-service ontology model facilitates information retrieval and knowledge extraction during the product lifecycle, while making more information available for the sake of service business creation. The vertical integration of IoT message transfer, encompassing all semantic layers, helps achieve a more flexible and modular approach to knowledge sharing in an IoT environment; (4) Contribution: A semantic data annotation applied to IoT can contribute to enhancing collected data types, which entails a richer knowledge extraction. The ontology-based PLM model enables as well the horizontal integration of heterogeneous PLM data while breaking traditional vertical information silos; (5) Conclusion: The framework was applied to a fictive case study with an electric car service for the purpose of demonstration. For the purpose of demonstrating the feasibility of the approach, the semantic model is implemented in Sesame APIs, which play the role of an Internet-connected Resource Description Framework (RDF) database. Full article
(This article belongs to the Special Issue Identification, Information & Knowledge in the Internet of Things)
Open AccessArticle T-L Plane Abstraction-Based Energy-Efficient Real-Time Scheduling for Multi-Core Wireless Sensors
Sensors 2016, 16(7), 1054; doi:10.3390/s16071054
Received: 4 May 2016 / Revised: 1 July 2016 / Accepted: 4 July 2016 / Published: 8 July 2016
PDF Full-text (2458 KB) | HTML Full-text | XML Full-text
Abstract
Energy efficiency is considered as a critical requirement for wireless sensor networks. As more wireless sensor nodes are equipped with multi-cores, there are emerging needs for energy-efficient real-time scheduling algorithms. The T-L plane-based scheme is known to be an optimal global scheduling technique
[...] Read more.
Energy efficiency is considered as a critical requirement for wireless sensor networks. As more wireless sensor nodes are equipped with multi-cores, there are emerging needs for energy-efficient real-time scheduling algorithms. The T-L plane-based scheme is known to be an optimal global scheduling technique for periodic real-time tasks on multi-cores. Unfortunately, there has been a scarcity of studies on extending T-L plane-based scheduling algorithms to exploit energy-saving techniques. In this paper, we propose a new T-L plane-based algorithm enabling energy-efficient real-time scheduling on multi-core sensor nodes with dynamic power management (DPM). Our approach addresses the overhead of processor mode transitions and reduces fragmentations of the idle time, which are inherent in T-L plane-based algorithms. Our experimental results show the effectiveness of the proposed algorithm compared to other energy-aware scheduling methods on T-L plane abstraction. Full article
(This article belongs to the Section Sensor Networks)
Open AccessArticle Automatic Censoring CFAR Detector Based on Ordered Data Difference for Low-Flying Helicopter Safety
Sensors 2016, 16(7), 1055; doi:10.3390/s16071055
Received: 29 April 2016 / Revised: 22 June 2016 / Accepted: 5 July 2016 / Published: 8 July 2016
PDF Full-text (7034 KB) | HTML Full-text | XML Full-text
Abstract
Being equipped with a millimeter-wave radar allows a low-flying helicopter to sense the surroundings in real time, which significantly increases its safety. However, nonhomogeneous clutter environments, such as a multiple target situation and a clutter edge environment, can dramatically affect the radar signal
[...] Read more.
Being equipped with a millimeter-wave radar allows a low-flying helicopter to sense the surroundings in real time, which significantly increases its safety. However, nonhomogeneous clutter environments, such as a multiple target situation and a clutter edge environment, can dramatically affect the radar signal detection performance. In order to improve the radar signal detection performance in nonhomogeneous clutter environments, this paper proposes a new automatic censored cell averaging CFAR detector. The proposed CFAR detector does not require any prior information about the background environment and uses the hypothesis test of the first-order difference (FOD) result of ordered data to reject the unwanted samples in the reference window. After censoring the unwanted ranked cells, the remaining samples are combined to form an estimate of the background power level, thus getting better radar signal detection performance. The simulation results show that the FOD-CFAR detector provides low loss CFAR performance in a homogeneous environment and also performs robustly in nonhomogeneous environments. Furthermore, the measured results of a low-flying helicopter validate the basic performance of the proposed method. Full article
(This article belongs to the Section Remote Sensors)
Open AccessArticle Design and Analysis of a New Hair Sensor for Multi-Physical Signal Measurement
Sensors 2016, 16(7), 1056; doi:10.3390/s16071056
Received: 28 April 2016 / Revised: 17 June 2016 / Accepted: 20 June 2016 / Published: 8 July 2016
PDF Full-text (8132 KB) | HTML Full-text | XML Full-text
Abstract
A new hair sensor for multi-physical signal measurements, including acceleration, angular velocity and air flow, is presented in this paper. The entire structure consists of a hair post, a torsional frame and a resonant signal transducer. The hair post is utilized to sense
[...] Read more.
A new hair sensor for multi-physical signal measurements, including acceleration, angular velocity and air flow, is presented in this paper. The entire structure consists of a hair post, a torsional frame and a resonant signal transducer. The hair post is utilized to sense and deliver the physical signals of the acceleration and the air flow rate. The physical signals are converted into frequency signals by the resonant transducer. The structure is optimized through finite element analysis. The simulation results demonstrate that the hair sensor has a frequency of 240 Hz in the first mode for the acceleration or the air flow sense, 3115 Hz in the third and fourth modes for the resonant conversion, and 3467 Hz in the fifth and sixth modes for the angular velocity transformation, respectively. All the above frequencies present in a reasonable modal distribution and are separated from interference modes. The input-output analysis of the new hair sensor demonstrates that the scale factor of the acceleration is 12.35 Hz/g, the scale factor of the angular velocity is 0.404 nm/deg/s and the sensitivity of the air flow is 1.075 Hz/(m/s)2, which verifies the multifunction sensitive characteristics of the hair sensor. Besides, the structural optimization of the hair post is used to improve the sensitivity of the air flow rate and the acceleration. The analysis results illustrate that the hollow circular hair post can increase the sensitivity of the air flow and the II-shape hair post can increase the sensitivity of the acceleration. Moreover, the thermal analysis confirms the scheme of the frequency difference for the resonant transducer can prominently eliminate the temperature influences on the measurement accuracy. The air flow analysis indicates that the surface area increase of hair post is significantly beneficial for the efficiency improvement of the signal transmission. In summary, the structure of the new hair sensor is proved to be feasible by comprehensive simulation and analysis. Full article
(This article belongs to the collection Modeling, Testing and Reliability Issues in MEMS Engineering)
Open AccessArticle Tightly Coupled Integration of GPS Ambiguity Fixed Precise Point Positioning and MEMS-INS through a Troposphere-Constrained Adaptive Kalman Filter
Sensors 2016, 16(7), 1057; doi:10.3390/s16071057
Received: 17 April 2016 / Revised: 12 June 2016 / Accepted: 5 July 2016 / Published: 8 July 2016
Cited by 3 | PDF Full-text (4847 KB) | HTML Full-text | XML Full-text
Abstract
Precise Point Positioning (PPP) makes use of the undifferenced pseudorange and carrier phase measurements with ionospheric-free (IF) combinations to achieve centimeter-level positioning accuracy. Conventionally, the IF ambiguities are estimated as float values. To improve the PPP positioning accuracy and shorten the convergence time,
[...] Read more.
Precise Point Positioning (PPP) makes use of the undifferenced pseudorange and carrier phase measurements with ionospheric-free (IF) combinations to achieve centimeter-level positioning accuracy. Conventionally, the IF ambiguities are estimated as float values. To improve the PPP positioning accuracy and shorten the convergence time, the integer phase clock model with between-satellites single-difference (BSSD) operation is used to recover the integer property. However, the continuity and availability of stand-alone PPP is largely restricted by the observation environment. The positioning performance will be significantly degraded when GPS operates under challenging environments, if less than five satellites are present. A commonly used approach is integrating a low cost inertial sensor to improve the positioning performance and robustness. In this study, a tightly coupled (TC) algorithm is implemented by integrating PPP with inertial navigation system (INS) using an Extended Kalman filter (EKF). The navigation states, inertial sensor errors and GPS error states are estimated together. The troposphere constrained approach, which utilizes external tropospheric delay as virtual observation, is applied to further improve the ambiguity-fixed height positioning accuracy, and an improved adaptive filtering strategy is implemented to improve the covariance modelling considering the realistic noise effect. A field vehicular test with a geodetic GPS receiver and a low cost inertial sensor was conducted to validate the improvement on positioning performance with the proposed approach. The results show that the positioning accuracy has been improved with inertial aiding. Centimeter-level positioning accuracy is achievable during the test, and the PPP/INS TC integration achieves a fast re-convergence after signal outages. For troposphere constrained solutions, a significant improvement for the height component has been obtained. The overall positioning accuracies of the height component are improved by 30.36%, 16.95% and 24.07% for three different convergence times, i.e., 60, 50 and 30 min, respectively. It shows that the ambiguity-fixed horizontal positioning accuracy has been significantly improved. When compared with the conventional PPP solution, it can be seen that position accuracies are improved by 19.51%, 61.11% and 23.53% for the north, east and height components, respectively, after one hour convergence through the troposphere constraint fixed PPP/INS with adaptive covariance model. Full article
(This article belongs to the Section Remote Sensors)
Figures

Open AccessArticle Hyperspectral Image-Based Night-Time Vehicle Light Detection Using Spectral Normalization and Distance Mapper for Intelligent Headlight Control
Sensors 2016, 16(7), 1058; doi:10.3390/s16071058
Received: 15 April 2016 / Revised: 19 June 2016 / Accepted: 22 June 2016 / Published: 8 July 2016
PDF Full-text (3597 KB) | HTML Full-text | XML Full-text
Abstract
This paper proposes a vehicle light detection method using a hyperspectral camera instead of a Charge-Coupled Device (CCD) or Complementary metal-Oxide-Semiconductor (CMOS) camera for adaptive car headlamp control. To apply Intelligent Headlight Control (IHC), the vehicle headlights need to be detected. Headlights are
[...] Read more.
This paper proposes a vehicle light detection method using a hyperspectral camera instead of a Charge-Coupled Device (CCD) or Complementary metal-Oxide-Semiconductor (CMOS) camera for adaptive car headlamp control. To apply Intelligent Headlight Control (IHC), the vehicle headlights need to be detected. Headlights are comprised from a variety of lighting sources, such as Light Emitting Diodes (LEDs), High-intensity discharge (HID), and halogen lamps. In addition, rear lamps are made of LED and halogen lamp. This paper refers to the recent research in IHC. Some problems exist in the detection of headlights, such as erroneous detection of street lights or sign lights and the reflection plate of ego-car from CCD or CMOS images. To solve these problems, this study uses hyperspectral images because they have hundreds of bands and provide more information than a CCD or CMOS camera. Recent methods to detect headlights used the Spectral Angle Mapper (SAM), Spectral Correlation Mapper (SCM), and Euclidean Distance Mapper (EDM). The experimental results highlight the feasibility of the proposed method in three types of lights (LED, HID, and halogen). Full article
(This article belongs to the Special Issue Non-Contact Sensing)
Open AccessArticle Portable System for Monitoring the Microclimate in the Footwear-Foot Interface
Sensors 2016, 16(7), 1059; doi:10.3390/s16071059
Received: 12 April 2016 / Revised: 28 June 2016 / Accepted: 29 June 2016 / Published: 8 July 2016
PDF Full-text (2641 KB) | HTML Full-text | XML Full-text
Abstract
A new, continuously-monitoring portable device that monitors the diabetic foot has shown to help in reduction of diabetic foot complications. Persons affected by diabetic foot have shown to be particularly sensitive in the plantar surface; this sensitivity coupled with certain ambient conditions may
[...] Read more.
A new, continuously-monitoring portable device that monitors the diabetic foot has shown to help in reduction of diabetic foot complications. Persons affected by diabetic foot have shown to be particularly sensitive in the plantar surface; this sensitivity coupled with certain ambient conditions may cause dry skin. This dry skin leads to the formation of fissures that may eventually result in a foot ulceration and subsequent hospitalization. This new device monitors the micro-climate temperature and humidity areas between the insole and sole of the footwear. The monitoring system consists of an array of ten sensors that take readings of relative humidity within the range of 100% ± 2% and temperature within the range of −40 °C to 123.8 ± 0.3 °C. Continuous data is collected using embedded C software and the recorded data is processed in Matlab. This allows for the display of data; the implementation of the iterative Gauss-Newton algorithm method was used to display an exponential response curve. Therefore, the aim of our system is to obtain feedback data and provide the critical information to various footwear manufacturers. The footwear manufactures will utilize this critical information to design and manufacture diabetic footwear that reduce the risk of ulcers in diabetic feet. Full article
(This article belongs to the Special Issue Smart Sensor Interface Circuits and Systems)
Figures

Open AccessArticle A Novel Strategy to Eliminate the Influence of Water Adsorption on Quartz Surfaces on Piezoelectric Dynamometers
Sensors 2016, 16(7), 1060; doi:10.3390/s16071060
Received: 25 March 2016 / Revised: 24 June 2016 / Accepted: 24 June 2016 / Published: 8 July 2016
PDF Full-text (3567 KB) | HTML Full-text | XML Full-text
Abstract
Piezoelectric dynamometers are out of use in high humidity. Experimental results showed that piezoelectric coefficients measured by the force-induced charges method initially fluctuated in a small range and then was unstable, and they could not be measured at high relative humidity (RH). The
[...] Read more.
Piezoelectric dynamometers are out of use in high humidity. Experimental results showed that piezoelectric coefficients measured by the force-induced charges method initially fluctuated in a small range and then was unstable, and they could not be measured at high relative humidity (RH). The traditional shielding method-insulation paste was not quiet convenient, and it even added the weight of piezoelectric dynamometers. In this paper, a novel strategy that eliminates the influence of water adsorption with quartz surfaces on piezoelectric dynamometers was proposed. First, a water-quartz model was developed to analyze the origin of the RH effect. In the model, water vapor, which was adsorbed by the quartz sheet side surface, was considered. Second, equivalent sheet resistor of the side surface was researched, while the relationship of the three R’s (Roughness, RH, and Resistor) was respectively discussed based on the adsorption mechanism. Finally, fluorination technology was skillfully adapted to each surface of quartz sheets to shield the water vapor. The experiment verified the fluorination strategy and made piezoelectric dynamometers work in high humidity up to 90%RH successfully. The results showed that the presented model above was reasonable. In addition, these observations also drew some useful insights to change the structure of piezoelectric dynamometers and improve the properties. Full article
(This article belongs to the Section Physical Sensors)
Figures

Open AccessArticle An Optical Sensor for Measuring the Position and Slanting Direction of Flat Surfaces
Sensors 2016, 16(7), 1061; doi:10.3390/s16071061
Received: 23 May 2016 / Revised: 4 July 2016 / Accepted: 5 July 2016 / Published: 9 July 2016
PDF Full-text (3367 KB) | HTML Full-text | XML Full-text
Abstract
Automated optical inspection is a very important technique. For this reason, this study proposes an optical non-contact slanting surface measuring system. The essential features of the measurement system are obtained through simulations using the optical design software Zemax. The actual propagation of laser
[...] Read more.
Automated optical inspection is a very important technique. For this reason, this study proposes an optical non-contact slanting surface measuring system. The essential features of the measurement system are obtained through simulations using the optical design software Zemax. The actual propagation of laser beams within the measurement system is traced by using a homogeneous transformation matrix (HTM), the skew-ray tracing method, and a first-order Taylor series expansion. Additionally, a complete mathematical model that describes the variations in light spots on photoelectric sensors and the corresponding changes in the sample orientation and distance was established. Finally, a laboratory prototype system was constructed on an optical bench to verify experimentally the proposed system. This measurement system can simultaneously detect the slanting angles (x, z) in the x and z directions of the sample and the distance (y) between the biconvex lens and the flat sample surface. Full article
(This article belongs to the Special Issue Non-Contact Sensing)
Open AccessArticle Mobile Autonomous Sensing Unit (MASU): A Framework That Supports Distributed Pervasive Data Sensing
Sensors 2016, 16(7), 1062; doi:10.3390/s16071062
Received: 8 May 2016 / Revised: 4 July 2016 / Accepted: 5 July 2016 / Published: 9 July 2016
PDF Full-text (4792 KB) | HTML Full-text | XML Full-text
Abstract
Pervasive data sensing is a major issue that transverses various research areas and application domains. It allows identifying people’s behaviour and patterns without overwhelming the monitored persons. Although there are many pervasive data sensing applications, they are typically focused on addressing specific problems
[...] Read more.
Pervasive data sensing is a major issue that transverses various research areas and application domains. It allows identifying people’s behaviour and patterns without overwhelming the monitored persons. Although there are many pervasive data sensing applications, they are typically focused on addressing specific problems in a single application domain, making them difficult to generalize or reuse. On the other hand, the platforms for supporting pervasive data sensing impose restrictions to the devices and operational environments that make them unsuitable for monitoring loosely-coupled or fully distributed work. In order to help address this challenge this paper present a framework that supports distributed pervasive data sensing in a generic way. Developers can use this framework to facilitate the implementations of their applications, thus reducing complexity and effort in such an activity. The framework was evaluated using simulations and also through an empirical test, and the obtained results indicate that it is useful to support such a sensing activity in loosely-coupled or fully distributed work scenarios. Full article
(This article belongs to the Special Issue Selected Papers from UCAmI, IWAAL and AmIHEALTH 2015)
Figures

Open AccessArticle Source Authentication for Code Dissemination Supporting Dynamic Packet Size in Wireless Sensor Networks
Sensors 2016, 16(7), 1063; doi:10.3390/s16071063
Received: 12 March 2016 / Revised: 26 June 2016 / Accepted: 5 July 2016 / Published: 9 July 2016
Cited by 2 | PDF Full-text (10987 KB) | HTML Full-text | XML Full-text
Abstract
Code dissemination in wireless sensor networks (WSNs) is a procedure for distributing a new code image over the air in order to update programs. Due to the fact that WSNs are mostly deployed in unattended and hostile environments, secure code dissemination ensuring authenticity
[...] Read more.
Code dissemination in wireless sensor networks (WSNs) is a procedure for distributing a new code image over the air in order to update programs. Due to the fact that WSNs are mostly deployed in unattended and hostile environments, secure code dissemination ensuring authenticity and integrity is essential. Recent works on dynamic packet size control in WSNs allow enhancing the energy efficiency of code dissemination by dynamically changing the packet size on the basis of link quality. However, the authentication tokens attached by the base station become useless in the next hop where the packet size can vary according to the link quality of the next hop. In this paper, we propose three source authentication schemes for code dissemination supporting dynamic packet size. Compared to traditional source authentication schemes such as μTESLA and digital signatures, our schemes provide secure source authentication under the environment, where the packet size changes in each hop, with smaller energy consumption. Full article
(This article belongs to the Special Issue Security and Privacy in Sensor Networks)
Open AccessArticle Highly Sensitive Temperature Sensors Based on Fiber-Optic PWM and Capacitance Variation Using Thermochromic Sensing Membrane
Sensors 2016, 16(7), 1064; doi:10.3390/s16071064
Received: 1 June 2016 / Revised: 4 July 2016 / Accepted: 6 July 2016 / Published: 9 July 2016
Cited by 5 | PDF Full-text (3771 KB) | HTML Full-text | XML Full-text
Abstract
In this paper, we propose a temperature/thermal sensor that contains a Rhodamine-B sensing membrane. We applied two different sensing methods, namely, fiber-optic pulse width modulation (PWM) and an interdigitated capacitor (IDC)-based temperature sensor to measure the temperature from 5 °C to 100 °C.
[...] Read more.
In this paper, we propose a temperature/thermal sensor that contains a Rhodamine-B sensing membrane. We applied two different sensing methods, namely, fiber-optic pulse width modulation (PWM) and an interdigitated capacitor (IDC)-based temperature sensor to measure the temperature from 5 °C to 100 °C. To the best of our knowledge, the fiber-optic PWM-based temperature sensor is reported for the first time in this study. The proposed fiber-optic PWM temperature sensor has good sensing ability; its sensitivity is ~3.733 mV/°C. The designed temperature-sensing system offers stable sensing responses over a wide dynamic range, good reproducibility properties with a relative standard deviation (RSD) of ~0.021, and the capacity for a linear sensing response with a correlation coefficient of R2 ≈ 0.992 over a wide sensing range. In our study, we also developed an IDC temperature sensor that is based on the capacitance variation principle as the IDC sensing element is heated. We compared the performance of the proposed temperature-sensing systems with different fiber-optic temperature sensors (which are based on the fiber-optic wavelength shift method, the long grating fiber-optic Sagnac loop, and probe type fiber-optics) in terms of sensitivity, dynamic range, and linearity. We observed that the proposed sensing systems have better sensing performance than the above-mentioned sensing system. Full article
(This article belongs to the Section Biosensors)
Figures

Open AccessCommunication Microchambers with Solid-State Phosphorescent Sensor for Measuring Single Mitochondrial Respiration
Sensors 2016, 16(7), 1065; doi:10.3390/s16071065
Received: 13 May 2016 / Revised: 20 June 2016 / Accepted: 5 July 2016 / Published: 9 July 2016
PDF Full-text (3283 KB) | HTML Full-text | XML Full-text
Abstract
It is now well established that, even within a single cell, multiple copies of the mitochondrial genome may be present (genetic heteroplasmy). It would be interesting to develop techniques to determine if and to what extent this genetic variation results in functional variation
[...] Read more.
It is now well established that, even within a single cell, multiple copies of the mitochondrial genome may be present (genetic heteroplasmy). It would be interesting to develop techniques to determine if and to what extent this genetic variation results in functional variation from one mitochondrion to the next (functional heteroplasmy). Measuring mitochondrial respiration can reveal the organelles’ functional capacity for Adenosine triphosphate (ATP) production and determine mitochondrial damage that may arise from genetic or age related defects. However, available technologies require significant quantities of mitochondria. Here, we develop a technology to assay the respiration of a single mitochondrion. Our “micro-respirometer” consists of micron sized chambers etched out of borofloat glass substrates and coated with an oxygen sensitive phosphorescent dye Pt(II) meso-tetra(pentafluorophenyl)porphine (PtTFPP) mixed with polystyrene. The chambers are sealed with a polydimethylsiloxane layer coated with oxygen impermeable Viton rubber to prevent diffusion of oxygen from the environment. As the mitochondria consume oxygen in the chamber, the phosphorescence signal increases, allowing direct determination of the respiration rate. Experiments with coupled vs. uncoupled mitochondria showed a substantial difference in respiration, confirming the validity of the microchambers as single mitochondrial respirometers. This demonstration could enable future high-throughput assays of mitochondrial respiration and benefit the study of mitochondrial functional heterogeneity, and its role in health and disease. Full article
(This article belongs to the Section Biosensors)
Open AccessArticle Stair-Walking Performance in Adolescents with Intellectual Disabilities
Sensors 2016, 16(7), 1066; doi:10.3390/s16071066
Received: 21 March 2016 / Revised: 1 July 2016 / Accepted: 8 July 2016 / Published: 11 July 2016
Cited by 1 | PDF Full-text (3937 KB) | HTML Full-text | XML Full-text
Abstract
Most individuals with intellectual disabilities (ID) demonstrate problems in learning and movement coordination. Consequently, they usually have difficulties in activities such as standing, walking, and stair climbing. To monitor the physical impairments of these children, regular gross motor evaluation is crucial. Straight-line level
[...] Read more.
Most individuals with intellectual disabilities (ID) demonstrate problems in learning and movement coordination. Consequently, they usually have difficulties in activities such as standing, walking, and stair climbing. To monitor the physical impairments of these children, regular gross motor evaluation is crucial. Straight-line level walking is the most frequently used test of their mobility. However, numerous studies have found that unless the children have multiple disabilities, no significant differences can be found between the children with ID and typically-developed children in this test. Stair climbing presents more challenges than level walking because it is associated with numerous physical factors, including lower extremity strength, cardiopulmonary endurance, vision, balance, and fear of falling. Limited ability in those factors is one of the most vital markers for children with ID. In this paper, we propose a sensor-based approach for measuring stair-walking performance, both upstairs and downstairs, for adolescents with ID. Particularly, we address the problem of sensor calibration to ensure measurement accuracy. In total, 62 participants aged 15 to 21 years, namely 32 typically-developed (TD) adolescents, 20 adolescents with ID, and 10 adolescents with multiple disabilities (MD), participated. The experimental results showed that stair-walking is more sensitive than straight-line level walking in capturing gait characteristics for adolescents with ID. Full article
(This article belongs to the collection Sensors for Globalized Healthy Living and Wellbeing)
Open AccessArticle A Novel Wearable Device for Food Intake and Physical Activity Recognition
Sensors 2016, 16(7), 1067; doi:10.3390/s16071067
Received: 26 May 2016 / Revised: 7 July 2016 / Accepted: 8 July 2016 / Published: 11 July 2016
Cited by 10 | PDF Full-text (1364 KB) | HTML Full-text | XML Full-text
Abstract
Presence of speech and motion artifacts has been shown to impact the performance of wearable sensor systems used for automatic detection of food intake. This work presents a novel wearable device which can detect food intake even when the user is physically active
[...] Read more.
Presence of speech and motion artifacts has been shown to impact the performance of wearable sensor systems used for automatic detection of food intake. This work presents a novel wearable device which can detect food intake even when the user is physically active and/or talking. The device consists of a piezoelectric strain sensor placed on the temporalis muscle, an accelerometer, and a data acquisition module connected to the temple of eyeglasses. Data from 10 participants was collected while they performed activities including quiet sitting, talking, eating while sitting, eating while walking, and walking. Piezoelectric strain sensor and accelerometer signals were divided into non-overlapping epochs of 3 s; four features were computed for each signal. To differentiate between eating and not eating, as well as between sedentary postures and physical activity, two multiclass classification approaches are presented. The first approach used a single classifier with sensor fusion and the second approach used two-stage classification. The best results were achieved when two separate linear support vector machine (SVM) classifiers were trained for food intake and activity detection, and their results were combined using a decision tree (two-stage classification) to determine the final class. This approach resulted in an average F1-score of 99.85% and area under the curve (AUC) of 0.99 for multiclass classification. With its ability to differentiate between food intake and activity level, this device may potentially be used for tracking both energy intake and energy expenditure. Full article
(This article belongs to the Special Issue Wearable Biomedical Sensors)
Open AccessArticle Pansharpening with a Guided Filter Based on Three-Layer Decomposition
Sensors 2016, 16(7), 1068; doi:10.3390/s16071068
Received: 12 May 2016 / Revised: 24 June 2016 / Accepted: 5 July 2016 / Published: 12 July 2016
Cited by 3 | PDF Full-text (8837 KB) | HTML Full-text | XML Full-text
Abstract
State-of-the-art pansharpening methods generally inject the spatial structures of a high spatial resolution (HR) panchromatic (PAN) image into the corresponding low spatial resolution (LR) multispectral (MS) image by an injection model. In this paper, a novel pansharpening method with an edge-preserving guided filter
[...] Read more.
State-of-the-art pansharpening methods generally inject the spatial structures of a high spatial resolution (HR) panchromatic (PAN) image into the corresponding low spatial resolution (LR) multispectral (MS) image by an injection model. In this paper, a novel pansharpening method with an edge-preserving guided filter based on three-layer decomposition is proposed. In the proposed method, the PAN image is decomposed into three layers: A strong edge layer, a detail layer, and a low-frequency layer. The edge layer and detail layer are then injected into the MS image by a proportional injection model. In addition, two new quantitative evaluation indices, including the modified correlation coefficient (MCC) and the modified universal image quality index (MUIQI) are developed. The proposed method was tested and verified by IKONOS, QuickBird, and Gaofen (GF)-1 satellite images, and it was compared with several of state-of-the-art pansharpening methods from both qualitative and quantitative aspects. The experimental results confirm the superiority of the proposed method. Full article
(This article belongs to the Section Remote Sensors)
Figures

Open AccessArticle Multi-Section Sensing and Vibrotactile Perception for Walking Guide of Visually Impaired Person
Sensors 2016, 16(7), 1070; doi:10.3390/s16071070
Received: 27 April 2016 / Revised: 24 June 2016 / Accepted: 6 July 2016 / Published: 12 July 2016
Cited by 2 | PDF Full-text (8991 KB) | HTML Full-text | XML Full-text
Abstract
Electronic Travel Aids (ETAs) improve the mobility of visually-impaired persons, but it is not easy to develop an ETA satisfying all the factors needed for reliable object detection, effective notification, and actual usability. In this study, the authors developed an easy-to-use ETA having
[...] Read more.
Electronic Travel Aids (ETAs) improve the mobility of visually-impaired persons, but it is not easy to develop an ETA satisfying all the factors needed for reliable object detection, effective notification, and actual usability. In this study, the authors developed an easy-to-use ETA having the function of reliable object detection and its successful feedback to the user by tactile stimulation. Seven ultrasonic sensors facing in different directions detect obstacles in the walking path, while vibrators in the tactile display stimulate the hand according to the distribution of obstacles. The detection of ground drop-offs activates the electromagnetic brakes linked to the rear wheels. To verify the feasibility of the developed ETA in the outdoor environment, walking tests by blind participants were performed, and the evaluation of safety to ground drop-offs was carried out. From the experiment, the feasibility of the developed ETA was shown to be sufficient if the sensor ranges for hanging obstacle detection is improved and learning time is provided for the ETA. Finally, the light-weight and low cost ETA designed and assembled based on the evaluation of the developed ETA is introduced to show the improvement of portability and usability, and is compared with the previously developed ETAs. Full article
(This article belongs to the Special Issue Sensing Technology for Healthcare System)
Open AccessArticle An Optically-Transparent Aptamer-Based Detection System for Colon Cancer Applications Using Gold Nanoparticles Electrodeposited on Indium Tin Oxide
Sensors 2016, 16(7), 1071; doi:10.3390/s16071071
Received: 24 April 2016 / Revised: 30 June 2016 / Accepted: 6 July 2016 / Published: 12 July 2016
PDF Full-text (2870 KB) | HTML Full-text | XML Full-text
Abstract
In this paper, a label-free aptamer based detection system (apta-DS) was investigated for detecting colon cancer cells. For this purpose, we employed an aptamer specific to colon cancer cells like HCT116 expressing carcinoembryonic antigen (CEA) on their surfaces. Capture aptamers were covalently immobilized
[...] Read more.
In this paper, a label-free aptamer based detection system (apta-DS) was investigated for detecting colon cancer cells. For this purpose, we employed an aptamer specific to colon cancer cells like HCT116 expressing carcinoembryonic antigen (CEA) on their surfaces. Capture aptamers were covalently immobilized on the surface of gold nanoparticles (GNPs) through self-assembly monolayer of 11-mercaptoundecanoic acid (11-MUA) activated with EDC (1-Ethyl-3-[3-dimethylaminopropyl]carbodiimide)/N-hydroxysuccinimide (NHS). The cyclic voltammetry (CV) and chronopotentiometry (CP) methods were used for electrodeposition of GNPs on the surface of indium tin oxide (ITO). In this work, the CV method was also used to demonstrate the conjugation of GNPs and aptamers and identify the cancer cell capturing events. Additionally, Field Emission Scanning Electron Microscopy (FE-SEM) confirmed the deposition of GNPs on ITO and the immobilization of aptamer on the apta-DS. The electrodeposited GNPs played the role of nanoprobes for cancer cell targeting without losing the optical transparency of the ITO substrate. A conventional optical microscope also verified the detection of captured cancer cells. Based on this study’s results relying on electrochemical and optical microscopic methods, the proposed apta-DS is reliable and high sensitive with a LOD equal to 6 cell/mL for colon cancer detection. Full article
(This article belongs to the Special Issue SPR, WGM & Nano-Sensors: Advantages and Prospects)
Open AccessArticle An Overview of Small Unmanned Aerial Vehicles for Air Quality Measurements: Present Applications and Future Prospectives
Sensors 2016, 16(7), 1072; doi:10.3390/s16071072
Received: 21 April 2016 / Revised: 1 July 2016 / Accepted: 5 July 2016 / Published: 12 July 2016
Cited by 16 | PDF Full-text (647 KB) | HTML Full-text | XML Full-text | Supplementary Files
Abstract
Assessment of air quality has been traditionally conducted by ground based monitoring, and more recently by manned aircrafts and satellites. However, performing fast, comprehensive data collection near pollution sources is not always feasible due to the complexity of sites, moving sources or physical
[...] Read more.
Assessment of air quality has been traditionally conducted by ground based monitoring, and more recently by manned aircrafts and satellites. However, performing fast, comprehensive data collection near pollution sources is not always feasible due to the complexity of sites, moving sources or physical barriers. Small Unmanned Aerial Vehicles (UAVs) equipped with different sensors have been introduced for in-situ air quality monitoring, as they can offer new approaches and research opportunities in air pollution and emission monitoring, as well as for studying atmospheric trends, such as climate change, while ensuring urban and industrial air safety. The aims of this review were to: (1) compile information on the use of UAVs for air quality studies; and (2) assess their benefits and range of applications. An extensive literature review was conducted using three bibliographic databases (Scopus, Web of Knowledge, Google Scholar) and a total of 60 papers was found. This relatively small number of papers implies that the field is still in its early stages of development. We concluded that, while the potential of UAVs for air quality research has been established, several challenges still need to be addressed, including: the flight endurance, payload capacity, sensor dimensions/accuracy, and sensitivity. However, the challenges are not simply technological, in fact, policy and regulations, which differ between countries, represent the greatest challenge to facilitating the wider use of UAVs in atmospheric research. Full article
(This article belongs to the Special Issue UAV-Based Remote Sensing)
Figures

Open AccessArticle FOG Random Drift Signal Denoising Based on the Improved AR Model and Modified Sage-Husa Adaptive Kalman Filter
Sensors 2016, 16(7), 1073; doi:10.3390/s16071073
Received: 18 April 2016 / Revised: 7 July 2016 / Accepted: 7 July 2016 / Published: 12 July 2016
Cited by 3 | PDF Full-text (3981 KB) | HTML Full-text | XML Full-text
Abstract
In order to reduce the influence of fiber optic gyroscope (FOG) random drift error on inertial navigation systems, an improved auto regressive (AR) model is put forward in this paper. First, based on real-time observations at each restart of the gyroscope, the model
[...] Read more.
In order to reduce the influence of fiber optic gyroscope (FOG) random drift error on inertial navigation systems, an improved auto regressive (AR) model is put forward in this paper. First, based on real-time observations at each restart of the gyroscope, the model of FOG random drift can be established online. In the improved AR model, the FOG measured signal is employed instead of the zero mean signals. Then, the modified Sage-Husa adaptive Kalman filter (SHAKF) is introduced, which can directly carry out real-time filtering on the FOG signals. Finally, static and dynamic experiments are done to verify the effectiveness. The filtering results are analyzed with Allan variance. The analysis results show that the improved AR model has high fitting accuracy and strong adaptability, and the minimum fitting accuracy of single noise is 93.2%. Based on the improved AR(3) model, the denoising method of SHAKF is more effective than traditional methods, and its effect is better than 30%. The random drift error of FOG is reduced effectively, and the precision of the FOG is improved. Full article
(This article belongs to the Section Physical Sensors)
Figures

Open AccessArticle Structural Parameters Calibration for Binocular Stereo Vision Sensors Using a Double-Sphere Target
Sensors 2016, 16(7), 1074; doi:10.3390/s16071074
Received: 1 April 2016 / Revised: 4 July 2016 / Accepted: 6 July 2016 / Published: 12 July 2016
Cited by 2 | PDF Full-text (10358 KB) | HTML Full-text | XML Full-text
Abstract
Structural parameter calibration for the binocular stereo vision sensor (BSVS) is an important guarantee for high-precision measurements. We propose a method to calibrate the structural parameters of BSVS based on a double-sphere target. The target, consisting of two identical spheres with a known
[...] Read more.
Structural parameter calibration for the binocular stereo vision sensor (BSVS) is an important guarantee for high-precision measurements. We propose a method to calibrate the structural parameters of BSVS based on a double-sphere target. The target, consisting of two identical spheres with a known fixed distance, is freely placed in different positions and orientations. Any three non-collinear sphere centres determine a spatial plane whose normal vector under the two camera-coordinate-frames is obtained by means of an intermediate parallel plane calculated by the image points of sphere centres and the depth-scale factors. Hence, the rotation matrix R is solved. The translation vector T is determined using a linear method derived from the epipolar geometry. Furthermore, R and T are refined by nonlinear optimization. We also provide theoretical analysis on the error propagation related to the positional deviation of the sphere image and an approach to mitigate its effect. Computer simulations are conducted to test the performance of the proposed method with respect to the image noise level, target placement times and the depth-scale factor. Experimental results on real data show that the accuracy of measurement is higher than 0.9‰, with a distance of 800 mm and a view field of 250 × 200 mm2. Full article
(This article belongs to the Section Physical Sensors)
Open AccessArticle Identification of Water Bodies in a Landsat 8 OLI Image Using a J48 Decision Tree
Sensors 2016, 16(7), 1075; doi:10.3390/s16071075
Received: 21 March 2016 / Revised: 4 July 2016 / Accepted: 7 July 2016 / Published: 12 July 2016
Cited by 1 | PDF Full-text (3020 KB) | HTML Full-text | XML Full-text
Abstract
Water bodies are essential to humans and other forms of life. Identification of water bodies can be useful in various ways, including estimation of water availability, demarcation of flooded regions, change detection, and so on. In past decades, Landsat satellite sensors have been
[...] Read more.
Water bodies are essential to humans and other forms of life. Identification of water bodies can be useful in various ways, including estimation of water availability, demarcation of flooded regions, change detection, and so on. In past decades, Landsat satellite sensors have been used for land use classification and water body identification. Due to the introduction of a New Operational Land Imager (OLI) sensor on Landsat 8 with a high spectral resolution and improved signal-to-noise ratio, the quality of imagery sensed by Landsat 8 has improved, enabling better characterization of land cover and increased data size. Therefore, it is necessary to explore the most appropriate and practical water identification methods that take advantage of the improved image quality and use the fewest inputs based on the original OLI bands. The objective of the study is to explore the potential of a J48 decision tree (JDT) in identifying water bodies using reflectance bands from Landsat 8 OLI imagery. J48 is an open-source decision tree. The test site for the study is in the Northern Han River Basin, which is located in Gangwon province, Korea. Training data with individual bands were used to develop the JDT model and later applied to the whole study area. The performance of the model was statistically analysed using the kappa statistic and area under the curve (AUC). The results were compared with five other known water identification methods using a confusion matrix and related statistics. Almost all the methods showed high accuracy, and the JDT was successfully applied to the OLI image using only four bands, where the new additional deep blue band of OLI was found to have the third highest information gain. Thus, the JDT can be a good method for water body identification based on images with improved resolution and increased size. Full article
Figures

Open AccessArticle Exploiting Outage and Error Probability of Cooperative Incremental Relaying in Underwater Wireless Sensor Networks
Sensors 2016, 16(7), 1076; doi:10.3390/s16071076
Received: 18 May 2016 / Revised: 22 June 2016 / Accepted: 1 July 2016 / Published: 12 July 2016
Cited by 2 | PDF Full-text (564 KB) | HTML Full-text | XML Full-text
Abstract
This paper embeds a bi-fold contribution for Underwater Wireless Sensor Networks (UWSNs); performance analysis of incremental relaying in terms of outage and error probability, and based on the analysis proposition of two new cooperative routing protocols. Subject to the first contribution, a three
[...] Read more.
This paper embeds a bi-fold contribution for Underwater Wireless Sensor Networks (UWSNs); performance analysis of incremental relaying in terms of outage and error probability, and based on the analysis proposition of two new cooperative routing protocols. Subject to the first contribution, a three step procedure is carried out; a system model is presented, the number of available relays are determined, and based on cooperative incremental retransmission methodology, closed-form expressions for outage and error probability are derived. Subject to the second contribution, Adaptive Cooperation in Energy (ACE) efficient depth based routing and Enhanced-ACE (E-ACE) are presented. In the proposed model, feedback mechanism indicates success or failure of data transmission. If direct transmission is successful, there is no need for relaying by cooperative relay nodes. In case of failure, all the available relays retransmit the data one by one till the desired signal quality is achieved at destination. Simulation results show that the ACE and E-ACE significantly improves network performance, i.e., throughput, when compared with other incremental relaying protocols like Cooperative Automatic Repeat reQuest (CARQ). E-ACE and ACE achieve 69% and 63% more throughput respectively as compared to CARQ in hard underwater environment. Full article
Open AccessArticle Flow Rates Measurement and Uncertainty Analysis in Multiple-Zone Water-Injection Wells from Fluid Temperature Profiles
Sensors 2016, 16(7), 1077; doi:10.3390/s16071077
Received: 28 March 2016 / Revised: 9 June 2016 / Accepted: 14 June 2016 / Published: 13 July 2016
PDF Full-text (1966 KB) | HTML Full-text | XML Full-text
Abstract
This work is a contribution to the development of flow sensors in the oil and gas industry. It presents a methodology to measure the flow rates into multiple-zone water-injection wells from fluid temperature profiles and estimate the measurement uncertainty. First, a method to
[...] Read more.
This work is a contribution to the development of flow sensors in the oil and gas industry. It presents a methodology to measure the flow rates into multiple-zone water-injection wells from fluid temperature profiles and estimate the measurement uncertainty. First, a method to iteratively calculate the zonal flow rates using the Ramey (exponential) model was described. Next, this model was linearized to perform an uncertainty analysis. Then, a computer program to calculate the injected flow rates from experimental temperature profiles was developed. In the experimental part, a fluid temperature profile from a dual-zone water-injection well located in the Northeast Brazilian region was collected. Thus, calculated and measured flow rates were compared. The results proved that linearization error is negligible for practical purposes and the relative uncertainty increases as the flow rate decreases. The calculated values from both the Ramey and linear models were very close to the measured flow rates, presenting a difference of only 4.58 m³/d and 2.38 m³/d, respectively. Finally, the measurement uncertainties from the Ramey and linear models were equal to 1.22% and 1.40% (for injection zone 1); 10.47% and 9.88% (for injection zone 2). Therefore, the methodology was successfully validated and all objectives of this work were achieved. Full article
(This article belongs to the Section Physical Sensors)
Figures

Open AccessArticle A Robust and Multi-Weighted Approach to Estimating Topographically Correlated Tropospheric Delays in Radar Interferograms
Sensors 2016, 16(7), 1078; doi:10.3390/s16071078
Received: 4 March 2016 / Revised: 16 June 2016 / Accepted: 8 July 2016 / Published: 12 July 2016
Cited by 1 | PDF Full-text (9133 KB) | HTML Full-text | XML Full-text
Abstract
Spatial and temporal variations in the vertical stratification of the troposphere introduce significant propagation delays in interferometric synthetic aperture radar (InSAR) observations. Observations of small amplitude surface deformations and regional subsidence rates are plagued by tropospheric delays, and strongly correlated with topographic height
[...] Read more.
Spatial and temporal variations in the vertical stratification of the troposphere introduce significant propagation delays in interferometric synthetic aperture radar (InSAR) observations. Observations of small amplitude surface deformations and regional subsidence rates are plagued by tropospheric delays, and strongly correlated with topographic height variations. Phase-based tropospheric correction techniques assuming a linear relationship between interferometric phase and topography have been exploited and developed, with mixed success. Producing robust estimates of tropospheric phase delay however plays a critical role in increasing the accuracy of InSAR measurements. Meanwhile, few phase-based correction methods account for the spatially variable tropospheric delay over lager study regions. Here, we present a robust and multi-weighted approach to estimate the correlation between phase and topography that is relatively insensitive to confounding processes such as regional subsidence over larger regions as well as under varying tropospheric conditions. An expanded form of robust least squares is introduced to estimate the spatially variable correlation between phase and topography by splitting the interferograms into multiple blocks. Within each block, correlation is robustly estimated from the band-filtered phase and topography. Phase-elevation ratios are multiply- weighted and extrapolated to each persistent scatter (PS) pixel. We applied the proposed method to Envisat ASAR images over the Southern California area, USA, and found that our method mitigated the atmospheric noise better than the conventional phase-based method. The corrected ground surface deformation agreed better with those measured from GPS. Full article
Figures

Open AccessArticle Improved Fuzzy Logic System to Evaluate Milk Electrical Conductivity Signals from On-Line Sensors to Monitor Dairy Goat Mastitis
Sensors 2016, 16(7), 1079; doi:10.3390/s16071079
Received: 4 May 2016 / Revised: 29 June 2016 / Accepted: 4 July 2016 / Published: 13 July 2016
Cited by 1 | PDF Full-text (813 KB) | HTML Full-text | XML Full-text
Abstract
The aim of this study was to develop and test a new fuzzy logic model for monitoring the udder health status (HS) of goats. The model evaluated, as input variables, the milk electrical conductivity (EC) signal, acquired on-line for each gland by a
[...] Read more.
The aim of this study was to develop and test a new fuzzy logic model for monitoring the udder health status (HS) of goats. The model evaluated, as input variables, the milk electrical conductivity (EC) signal, acquired on-line for each gland by a dedicated sensor, the bandwidth length and the frequency and amplitude of the first main peak of the Fourier frequency spectrum of the recorded milk EC signal. Two foremilk gland samples were collected from eight Saanen goats for six months at morning milking (lactation stages (LS): 0–60 Days In Milking (DIM); 61–120 DIM; 121–180 DIM), for a total of 5592 samples. Bacteriological analyses and somatic cell counts (SCC) were used to define the HS of the glands. With negative bacteriological analyses and SCC < 1,000,000 cells/mL, glands were classified as healthy. When bacteriological analyses were positive or showed a SCC > 1,000,000 cells/mL, glands were classified as not healthy (NH). For each EC signal, an estimated EC value was calculated and a relative deviation was obtained. Furthermore, the Fourier frequency spectrum was evaluated and bandwidth length, frequency and amplitude of the first main peak were identified. Before using these indexes as input variables of the fuzzy logic model a linear mixed-effects model was developed to evaluate the acquired data considering the HS, LS and LS × HS as explanatory variables. Results showed that performance of a fuzzy logic model, in the monitoring of mammary gland HS, could be improved by the use of EC indexes derived from the Fourier frequency spectra of gland milk EC signals recorded by on-line EC sensors. Full article
(This article belongs to the Section Chemical Sensors)
Open AccessArticle Helium Ion Microscope-Assisted Nanomachining of Resonant Nanostrings
Sensors 2016, 16(7), 1080; doi:10.3390/s16071080
Received: 2 May 2016 / Revised: 5 July 2016 / Accepted: 8 July 2016 / Published: 13 July 2016
PDF Full-text (2515 KB) | HTML Full-text | XML Full-text
Abstract
Helium ion microscopy has recently emerged as a potent tool for the in-situ modification and imaging of nanoscale devices. For example; finely focused helium ion beams have been used for the milling of pores in suspended structures. We here report the use of
[...] Read more.
Helium ion microscopy has recently emerged as a potent tool for the in-situ modification and imaging of nanoscale devices. For example; finely focused helium ion beams have been used for the milling of pores in suspended structures. We here report the use of helium ion milling for the post-fabrication modification of nanostrings machined from an amorphous SiCN material. The modification consisted of milling linear arrays of holes along the length of nanostrings. This milling results in a slight decrease of resonant frequency while increasing the surface to volume ratio of the device. The frequency decrease is attributed to a reduction of the effective Young’s modulus of the string, which in turn reduces the tension the string is under. Such experimental observations are supported by the finite element analysis of milled and non-milled strings. Full article
(This article belongs to the Special Issue Resonator Sensors)
Figures

Open AccessArticle Discrete Particle Swarm Optimization Routing Protocol for Wireless Sensor Networks with Multiple Mobile Sinks
Sensors 2016, 16(7), 1081; doi:10.3390/s16071081
Received: 4 June 2016 / Revised: 6 July 2016 / Accepted: 8 July 2016 / Published: 14 July 2016
Cited by 2 | PDF Full-text (4636 KB) | HTML Full-text | XML Full-text
Abstract
Mobile sinks can achieve load-balancing and energy-consumption balancing across the wireless sensor networks (WSNs). However, the frequent change of the paths between source nodes and the sinks caused by sink mobility introduces significant overhead in terms of energy and packet delays. To enhance
[...] Read more.
Mobile sinks can achieve load-balancing and energy-consumption balancing across the wireless sensor networks (WSNs). However, the frequent change of the paths between source nodes and the sinks caused by sink mobility introduces significant overhead in terms of energy and packet delays. To enhance network performance of WSNs with mobile sinks (MWSNs), we present an efficient routing strategy, which is formulated as an optimization problem and employs the particle swarm optimization algorithm (PSO) to build the optimal routing paths. However, the conventional PSO is insufficient to solve discrete routing optimization problems. Therefore, a novel greedy discrete particle swarm optimization with memory (GMDPSO) is put forward to address this problem. In the GMDPSO, particle’s position and velocity of traditional PSO are redefined under discrete MWSNs scenario. Particle updating rule is also reconsidered based on the subnetwork topology of MWSNs. Besides, by improving the greedy forwarding routing, a greedy search strategy is designed to drive particles to find a better position quickly. Furthermore, searching history is memorized to accelerate convergence. Simulation results demonstrate that our new protocol significantly improves the robustness and adapts to rapid topological changes with multiple mobile sinks, while efficiently reducing the communication overhead and the energy consumption. Full article
(This article belongs to the Special Issue New Paradigms in Cyber-Physical Social Sensing)
Open AccessArticle Diurnal Variability in Chlorophyll-a, Carotenoids, CDOM and SO42− Intensity of Offshore Seawater Detected by an Underwater Fluorescence-Raman Spectral System
Sensors 2016, 16(7), 1082; doi:10.3390/s16071082
Received: 29 April 2016 / Revised: 15 June 2016 / Accepted: 30 June 2016 / Published: 13 July 2016
Cited by 1 | PDF Full-text (2331 KB) | HTML Full-text | XML Full-text
Abstract
A newly developed integrated fluorescence-Raman spectral system (λex = 532 nm) for detecting Chlorophyll-a (chl-a), Chromophoric Dissolved Organic Matter (CDOM), carotenoids and SO42− in situ was used to successfully investigate the diurnal variability of all above. Simultaneously using the integration
[...] Read more.
A newly developed integrated fluorescence-Raman spectral system (λex = 532 nm) for detecting Chlorophyll-a (chl-a), Chromophoric Dissolved Organic Matter (CDOM), carotenoids and SO42− in situ was used to successfully investigate the diurnal variability of all above. Simultaneously using the integration of fluorescence spectroscopy and Raman spectroscopy techniques provided comprehensive marine information due to the complementarity between the different excitation mechanisms and different selection rules. The investigation took place in offshore seawater of the Yellow Sea (36°05′40′′ N, 120°31′32′′ E) in October 2014. To detect chl-a, CDOM, carotenoids and SO42−, the fluorescence-Raman spectral system was deployed. It was found that troughs of chl-a and CDOM fluorescence signal intensity were observed during high tides, while the signal intensity showed high values with larger fluctuations during ebb-tide. Chl-a and carotenoids were influenced by solar radiation within a day cycle by different detection techniques, as well as displaying similar and synchronous tendency. CDOM fluorescence cause interference to the measurement of SO42−. To avoid such interference, the backup Raman spectroscopy system with λex = 785 nm was employed to detect SO42− concentration on the following day. The results demonstrated that the fluorescence-Raman spectral system has great potential in detection of chl-a, carotenoids, CDOM and SO42− in the ocean. Full article
(This article belongs to the Special Issue Sensors for Environmental Monitoring 2016)
Open AccessArticle Involvement of Acylated Homoserine Lactones (AHLs) of Aeromonas sobria in Spoilage of Refrigerated Turbot (Scophthalmus maximus L.)
Sensors 2016, 16(7), 1083; doi:10.3390/s16071083
Received: 14 May 2016 / Revised: 4 July 2016 / Accepted: 8 July 2016 / Published: 13 July 2016
Cited by 2 | PDF Full-text (3215 KB) | HTML Full-text | XML Full-text
Abstract
One quorum sensing strain was isolated from spoiled turbot. The species was determined by 16S rRNA gene analysis and classical tests, named Aeromonas sobria AS7. Quorum-sensing (QS) signals (N-acyl homoserine lactones (AHLs)) were detected by report strains and their structures were
[...] Read more.
One quorum sensing strain was isolated from spoiled turbot. The species was determined by 16S rRNA gene analysis and classical tests, named Aeromonas sobria AS7. Quorum-sensing (QS) signals (N-acyl homoserine lactones (AHLs)) were detected by report strains and their structures were further determined by GC-MS. The activity changes of AHLs on strain growth stage as well as the influence of different culture conditions on secretion activity of AHLs were studied by the punch method. The result indicated that strain AS7 could induce report strains to produce typical phenotypic response. N-butanoyl-dl-homoserine lactone (C4–HSL), N-hexanoyl-dl-homoserine lactone (C6–HSL), N-octanoyl-dl-homoserine lactone (C8–HSL), N-decanoyl-dl-homoserine lactone (C10–HSL), N-dodecanoyl-dl-homoserine lactone (C12–HSL) could be detected. The activities of AHLs were density-dependent and the max secretion level was at pH 8, sucrose culture, 1% NaCl and 32 h, respectively. The production of siderophore in strain AS7 was regulated by exogenous C8–HSL, rather than C6–HSL. Exogenous C4–HSL and C8–HSL accelerated the growth rate and population density of AS7 in turbot samples under refrigerated storage. However, according to the total viable counts and total volatile basic nitrogen (TVB-N) values of the fish samples, exogenous C6–HSL did not cause spoilage of the turbot fillets. In conclusion, our results suggested that QS was involved in the spoilage of refrigerated turbot. Full article
(This article belongs to the Section Biosensors)
Open AccessArticle Hazardous Traffic Event Detection Using Markov Blanket and Sequential Minimal Optimization (MB-SMO)
Sensors 2016, 16(7), 1084; doi:10.3390/s16071084
Received: 9 April 2016 / Revised: 29 June 2016 / Accepted: 7 July 2016 / Published: 13 July 2016
Cited by 1 | PDF Full-text (6050 KB) | HTML Full-text | XML Full-text
Abstract
The ability to identify hazardous traffic events is already considered as one of the most effective solutions for reducing the occurrence of crashes. Only certain particular hazardous traffic events have been studied in previous studies, which were mainly based on dedicated video stream
[...] Read more.
The ability to identify hazardous traffic events is already considered as one of the most effective solutions for reducing the occurrence of crashes. Only certain particular hazardous traffic events have been studied in previous studies, which were mainly based on dedicated video stream data and GPS data. The objective of this study is twofold: (1) the Markov blanket (MB) algorithm is employed to extract the main factors associated with hazardous traffic events; (2) a model is developed to identify hazardous traffic event using driving characteristics, vehicle trajectory, and vehicle position data. Twenty-two licensed drivers were recruited to carry out a natural driving experiment in Wuhan, China, and multi-sensor information data were collected for different types of traffic events. The results indicated that a vehicle’s speed, the standard deviation of speed, the standard deviation of skin conductance, the standard deviation of brake pressure, turn signal, the acceleration of steering, the standard deviation of acceleration, and the acceleration in Z (G) have significant influences on hazardous traffic events. The sequential minimal optimization (SMO) algorithm was adopted to build the identification model, and the accuracy of prediction was higher than 86%. Moreover, compared with other detection algorithms, the MB-SMO algorithm was ranked best in terms of the prediction accuracy. The conclusions can provide reference evidence for the development of dangerous situation warning products and the design of intelligent vehicles. Full article
(This article belongs to the Section Physical Sensors)
Open AccessArticle Passive UHF RFID Tag for Multispectral Assessment
Sensors 2016, 16(7), 1085; doi:10.3390/s16071085
Received: 18 May 2016 / Revised: 7 July 2016 / Accepted: 11 July 2016 / Published: 14 July 2016
Cited by 3 | PDF Full-text (3436 KB) | HTML Full-text | XML Full-text
Abstract
This work presents the design, fabrication, and characterization of a passive printed radiofrequency identification tag in the ultra-high-frequency band with multiple optical sensing capabilities. This tag includes five photodiodes to cover a wide spectral range from near-infrared to visible and ultraviolet spectral regions.
[...] Read more.
This work presents the design, fabrication, and characterization of a passive printed radiofrequency identification tag in the ultra-high-frequency band with multiple optical sensing capabilities. This tag includes five photodiodes to cover a wide spectral range from near-infrared to visible and ultraviolet spectral regions. The tag antenna and circuit connections have been screen-printed on a flexible polymeric substrate. An ultra-low-power microcontroller-based switch has been included to measure the five magnitudes issuing from the optical sensors, providing a spectral fingerprint of the incident electromagnetic radiation from ultraviolet to infrared, without requiring energy from a battery. The normalization procedure has been designed applying illuminants, and the entire system was tested by measuring cards from a colour chart and sensing fruit ripening. Full article
(This article belongs to the Special Issue Non-Contact Sensing)
Open AccessArticle Comparison of Three Non-Imaging Angle-Diversity Receivers as Input Sensors of Nodes for Indoor Infrared Wireless Sensor Networks: Theory and Simulation
Sensors 2016, 16(7), 1086; doi:10.3390/s16071086
Received: 1 April 2016 / Revised: 5 July 2016 / Accepted: 7 July 2016 / Published: 14 July 2016
Cited by 2 | PDF Full-text (3294 KB) | HTML Full-text | XML Full-text
Abstract
In general, the use of angle-diversity receivers makes it possible to reduce the impact of ambient light noise, path loss and multipath distortion, in part by exploiting the fact that they often receive the desired signal from different directions. Angle-diversity detection can be
[...] Read more.
In general, the use of angle-diversity receivers makes it possible to reduce the impact of ambient light noise, path loss and multipath distortion, in part by exploiting the fact that they often receive the desired signal from different directions. Angle-diversity detection can be performed using a composite receiver with multiple detector elements looking in different directions. These are called non-imaging angle-diversity receivers. In this paper, a comparison of three non-imaging angle-diversity receivers as input sensors of nodes for an indoor infrared (IR) wireless sensor network is presented. The receivers considered are the conventional angle-diversity receiver (CDR), the sectored angle-diversity receiver (SDR), and the self-orienting receiver (SOR), which have been proposed or studied by research groups in Spain. To this end, the effective signal-collection area of the three receivers is modelled and a Monte-Carlo-based ray-tracing algorithm is implemented which allows us to investigate the effect on the signal to noise ratio and main IR channel parameters, such as path loss and rms delay spread, of using the three receivers in conjunction with different combination techniques in IR links operating at low bit rates. Based on the results of the simulations, we show that the use of a conventional angle-diversity receiver in conjunction with the equal-gain combining technique provides the solution with the best signal to noise ratio, the lowest computational capacity and the lowest transmitted power requirements, which comprise the main limitations for sensor nodes in an indoor infrared wireless sensor network. Full article
Open AccessArticle A Depth-Adjustment Deployment Algorithm Based on Two-Dimensional Convex Hull and Spanning Tree for Underwater Wireless Sensor Networks
Sensors 2016, 16(7), 1087; doi:10.3390/s16071087
Received: 30 May 2016 / Revised: 4 July 2016 / Accepted: 9 July 2016 / Published: 14 July 2016
Cited by 3 | PDF Full-text (2391 KB) | HTML Full-text | XML Full-text
Abstract
Most of the existing node depth-adjustment deployment algorithms for underwater wireless sensor networks (UWSNs) just consider how to optimize network coverage and connectivity rate. However, these literatures don’t discuss full network connectivity, while optimization of network energy efficiency and network reliability are vital
[...] Read more.
Most of the existing node depth-adjustment deployment algorithms for underwater wireless sensor networks (UWSNs) just consider how to optimize network coverage and connectivity rate. However, these literatures don’t discuss full network connectivity, while optimization of network energy efficiency and network reliability are vital topics for UWSN deployment. Therefore, in this study, a depth-adjustment deployment algorithm based on two-dimensional (2D) convex hull and spanning tree (NDACS) for UWSNs is proposed. First, the proposed algorithm uses the geometric characteristics of a 2D convex hull and empty circle to find the optimal location of a sleep node and activate it, minimizes the network coverage overlaps of the 2D plane, and then increases the coverage rate until the first layer coverage threshold is reached. Second, the sink node acts as a root node of all active nodes on the 2D convex hull and then forms a small spanning tree gradually. Finally, the depth-adjustment strategy based on time marker is used to achieve the three-dimensional overall network deployment. Compared with existing depth-adjustment deployment algorithms, the simulation results show that the NDACS algorithm can maintain full network connectivity with high network coverage rate, as well as improved network average node degree, thus increasing network reliability. Full article
(This article belongs to the Section Sensor Networks)
Open AccessArticle Valid Probabilistic Predictions for Ginseng with Venn Machines Using Electronic Nose
Sensors 2016, 16(7), 1088; doi:10.3390/s16071088
Received: 18 April 2016 / Revised: 22 June 2016 / Accepted: 22 June 2016 / Published: 13 July 2016
PDF Full-text (2016 KB) | HTML Full-text | XML Full-text
Abstract
In the application of electronic noses (E-noses), probabilistic prediction is a good way to estimate how confident we are about our prediction. In this work, a homemade E-nose system embedded with 16 metal-oxide semi-conductive gas sensors was used to discriminate nine kinds of
[...] Read more.
In the application of electronic noses (E-noses), probabilistic prediction is a good way to estimate how confident we are about our prediction. In this work, a homemade E-nose system embedded with 16 metal-oxide semi-conductive gas sensors was used to discriminate nine kinds of ginsengs of different species or production places. A flexible machine learning framework, Venn machine (VM) was introduced to make probabilistic predictions for each prediction. Three Venn predictors were developed based on three classical probabilistic prediction methods (Platt’s method, Softmax regression and Naive Bayes). Three Venn predictors and three classical probabilistic prediction methods were compared in aspect of classification rate and especially the validity of estimated probability. A best classification rate of 88.57% was achieved with Platt’s method in offline mode, and the classification rate of VM-SVM (Venn machine based on Support Vector Machine) was 86.35%, just 2.22% lower. The validity of Venn predictors performed better than that of corresponding classical probabilistic prediction methods. The validity of VM-SVM was superior to the other methods. The results demonstrated that Venn machine is a flexible tool to make precise and valid probabilistic prediction in the application of E-nose, and VM-SVM achieved the best performance for the probabilistic prediction of ginseng samples. Full article
(This article belongs to the Special Issue E-noses: Sensors and Applications)
Open AccessArticle Ultrasonic Sensing of Plant Water Needs for Agriculture
Sensors 2016, 16(7), 1089; doi:10.3390/s16071089
Received: 31 May 2016 / Revised: 3 July 2016 / Accepted: 8 July 2016 / Published: 14 July 2016
Cited by 1 | PDF Full-text (5901 KB) | HTML Full-text | XML Full-text
Abstract
Fresh water is a key natural resource for food production, sanitation and industrial uses and has a high environmental value. The largest water use worldwide (~70%) corresponds to irrigation in agriculture, where use of water is becoming essential to maintain productivity. Efficient irrigation
[...] Read more.
Fresh water is a key natural resource for food production, sanitation and industrial uses and has a high environmental value. The largest water use worldwide (~70%) corresponds to irrigation in agriculture, where use of water is becoming essential to maintain productivity. Efficient irrigation control largely depends on having access to reliable information about the actual plant water needs. Therefore, fast, portable and non-invasive sensing techniques able to measure water requirements directly on the plant are essential to face the huge challenge posed by the extensive water use in agriculture, the increasing water shortage and the impact of climate change. Non-contact resonant ultrasonic spectroscopy (NC-RUS) in the frequency range 0.1–1.2 MHz has revealed as an efficient and powerful non-destructive, non-invasive and in vivo sensing technique for leaves of different plant species. In particular, NC-RUS allows determining surface mass, thickness and elastic modulus of the leaves. Hence, valuable information can be obtained about water content and turgor pressure. This work analyzes and reviews the main requirements for sensors, electronics, signal processing and data analysis in order to develop a fast, portable, robust and non-invasive NC-RUS system to monitor variations in leaves water content or turgor pressure. A sensing prototype is proposed, described and, as application example, used to study two different species: Vitis vinifera and Coffea arabica, whose leaves present thickness resonances in two different frequency bands (400–900 kHz and 200–400 kHz, respectively), These species are representative of two different climates and are related to two high-added value agricultural products where efficient irrigation management can be critical. Moreover, the technique can also be applied to other species and similar results can be obtained. Full article
(This article belongs to the Special Issue Sensors for Agriculture)
Figures

Open AccessArticle Distributed Task Offloading in Heterogeneous Vehicular Crowd Sensing
Sensors 2016, 16(7), 1090; doi:10.3390/s16071090
Received: 7 March 2016 / Revised: 8 July 2016 / Accepted: 11 July 2016 / Published: 14 July 2016
Cited by 1 | PDF Full-text (514 KB) | HTML Full-text | XML Full-text
Abstract
The ability of road vehicles to efficiently execute different sensing tasks varies because of the heterogeneity in their sensing ability and trajectories. Therefore, the data collection sensing task, which requires tempo-spatial sensing data, becomes a serious problem in vehicular sensing systems, particularly those
[...] Read more.
The ability of road vehicles to efficiently execute different sensing tasks varies because of the heterogeneity in their sensing ability and trajectories. Therefore, the data collection sensing task, which requires tempo-spatial sensing data, becomes a serious problem in vehicular sensing systems, particularly those with limited sensing capabilities. A utility-based sensing task decomposition and offloading algorithm is proposed in this paper. The utility function for a task executed by a certain vehicle is built according to the mobility traces and sensing interfaces of the vehicle, as well as the sensing data type and tempo-spatial coverage requirements of the sensing task. Then, the sensing tasks are decomposed and offloaded to neighboring vehicles according to the utilities of the neighboring vehicles to the decomposed sensing tasks. Real trace-driven simulation shows that the proposed task offloading is able to collect much more comprehensive and uniformly distributed sensing data than other algorithms. Full article
(This article belongs to the Section Sensor Networks)
Open AccessArticle Correcting Spatial Variance of RCM for GEO SAR Imaging Based on Time-Frequency Scaling
Sensors 2016, 16(7), 1091; doi:10.3390/s16071091
Received: 17 May 2016 / Revised: 1 July 2016 / Accepted: 8 July 2016 / Published: 14 July 2016
Cited by 1 | PDF Full-text (6095 KB) | HTML Full-text | XML Full-text
Abstract
Compared with low-Earth orbit synthetic aperture radar (SAR), a geosynchronous (GEO) SAR can have a shorter revisit period and vaster coverage. However, relative motion between this SAR and targets is more complicated, which makes range cell migration (RCM) spatially variant along both range
[...] Read more.
Compared with low-Earth orbit synthetic aperture radar (SAR), a geosynchronous (GEO) SAR can have a shorter revisit period and vaster coverage. However, relative motion between this SAR and targets is more complicated, which makes range cell migration (RCM) spatially variant along both range and azimuth. As a result, efficient and precise imaging becomes difficult. This paper analyzes and models spatial variance for GEO SAR in the time and frequency domains. A novel algorithm for GEO SAR imaging with a resolution of 2 m in both the ground cross-range and range directions is proposed, which is composed of five steps. The first is to eliminate linear azimuth variance through the first azimuth time scaling. The second is to achieve RCM correction and range compression. The third is to correct residual azimuth variance by the second azimuth time-frequency scaling. The fourth and final steps are to accomplish azimuth focusing and correct geometric distortion. The most important innovation of this algorithm is implementation of the time-frequency scaling to correct high-order azimuth variance. As demonstrated by simulation results, this algorithm can accomplish GEO SAR imaging with good and uniform imaging quality over the entire swath. Full article
Open AccessArticle Towards an Improved LAI Collection Protocol via Simulated and Field-Based PAR Sensing
Sensors 2016, 16(7), 1092; doi:10.3390/s16071092
Received: 7 June 2016 / Revised: 5 July 2016 / Accepted: 7 July 2016 / Published: 14 July 2016
PDF Full-text (8032 KB) | HTML Full-text | XML Full-text
Abstract
In support of NASA’s next-generation spectrometer—the Hyperspectral Infrared Imager (HyspIRI)—we are working towards assessing sub-pixel vegetation structure from imaging spectroscopy data. Of particular interest is Leaf Area Index (LAI), which is an informative, yet notoriously challenging parameter to efficiently measure in situ. While
[...] Read more.
In support of NASA’s next-generation spectrometer—the Hyperspectral Infrared Imager (HyspIRI)—we are working towards assessing sub-pixel vegetation structure from imaging spectroscopy data. Of particular interest is Leaf Area Index (LAI), which is an informative, yet notoriously challenging parameter to efficiently measure in situ. While photosynthetically-active radiation (PAR) sensors have been validated for measuring crop LAI, there is limited literature on the efficacy of PAR-based LAI measurement in the forest environment. This study (i) validates PAR-based LAI measurement in forest environments, and (ii) proposes a suitable collection protocol, which balances efficiency with measurement variation, e.g., due to sun flecks and various-sized canopy gaps. A synthetic PAR sensor model was developed in the Digital Imaging and Remote Sensing Image Generation (DIRSIG) model and used to validate LAI measurement based on first-principles and explicitly-known leaf geometry. Simulated collection parameters were adjusted to empirically identify optimal collection protocols. These collection protocols were then validated in the field by correlating PAR-based LAI measurement to the normalized difference vegetation index (NDVI) extracted from the “classic” Airborne Visible Infrared Imaging Spectrometer (AVIRIS-C) data ( R 2 was 0.61). The results indicate that our proposed collecting protocol is suitable for measuring the LAI of sparse forest (LAI < 3–5 ( m 2 / m 2 )). Full article
(This article belongs to the Section Remote Sensors)
Figures

Open AccessArticle A Monitoring Method Based on FBG for Concrete Corrosion Cracking
Sensors 2016, 16(7), 1093; doi:10.3390/s16071093
Received: 11 February 2016 / Revised: 8 June 2016 / Accepted: 1 July 2016 / Published: 14 July 2016
PDF Full-text (2294 KB) | HTML Full-text | XML Full-text
Abstract
Corrosion cracking of reinforced concrete caused by chloride salt is one of the main determinants of structure durability. Monitoring the entire process of concrete corrosion cracking is critical for assessing the remaining life of the structure and determining if maintenance is needed. Fiber
[...] Read more.
Corrosion cracking of reinforced concrete caused by chloride salt is one of the main determinants of structure durability. Monitoring the entire process of concrete corrosion cracking is critical for assessing the remaining life of the structure and determining if maintenance is needed. Fiber Bragg Grating (FBG) sensing technology is extensively developed in photoelectric monitoring technology and has been used on many projects. FBG can detect the quasi-distribution of strain and temperature under corrosive environments, and thus it is suitable for monitoring reinforced concrete cracking. According to the mechanical principle that corrosion expansion is responsible for the reinforced concrete cracking, a package design of reinforced concrete cracking sensors based on FBG was proposed and investigated in this study. The corresponding relationship between the grating wavelength and strain was calibrated by an equal strength beam test. The effectiveness of the proposed method was verified by an electrically accelerated corrosion experiment. The fiber grating sensing technology was able to track the corrosion expansion and corrosion cracking in real time and provided data to inform decision-making for the maintenance and management of the engineering structure. Full article
(This article belongs to the Section Physical Sensors)
Open AccessArticle Time-Resolved Fluorescent Immunochromatography of Aflatoxin B1 in Soybean Sauce: A Rapid and Sensitive Quantitative Analysis
Sensors 2016, 16(7), 1094; doi:10.3390/s16071094
Received: 1 May 2016 / Revised: 8 June 2016 / Accepted: 6 July 2016 / Published: 14 July 2016
Cited by 6 | PDF Full-text (961 KB) | HTML Full-text | XML Full-text
Abstract
Rapid and quantitative sensing of aflatoxin B1 with high sensitivity and specificity has drawn increased attention of studies investigating soybean sauce. A sensitive and rapid quantitative immunochromatographic sensing method was developed for the detection of aflatoxin B1 based on time-resolved fluorescence. It combines
[...] Read more.
Rapid and quantitative sensing of aflatoxin B1 with high sensitivity and specificity has drawn increased attention of studies investigating soybean sauce. A sensitive and rapid quantitative immunochromatographic sensing method was developed for the detection of aflatoxin B1 based on time-resolved fluorescence. It combines the advantages of time-resolved fluorescent sensing and immunochromatography. The dynamic range of a competitive and portable immunoassay was 0.3–10.0 µg·kg−1, with a limit of detection (LOD) of 0.1 µg·kg−1 and recoveries of 87.2%–114.3%, within 10 min. The results showed good correlation (R2 > 0.99) between time-resolved fluorescent immunochromatographic strip test and high performance liquid chromatography (HPLC). Soybean sauce samples analyzed using time-resolved fluorescent immunochromatographic strip test revealed that 64.2% of samples contained aflatoxin B1 at levels ranging from 0.31 to 12.5 µg·kg−1. The strip test is a rapid, sensitive, quantitative, and cost-effective on-site screening technique in food safety analysis. Full article
(This article belongs to the Section Biosensors)
Open AccessArticle Theoretical and Experimental Study on Wide Range Optical Fiber Turbine Flow Sensor
Sensors 2016, 16(7), 1095; doi:10.3390/s16071095
Received: 31 May 2016 / Revised: 8 July 2016 / Accepted: 8 July 2016 / Published: 15 July 2016
PDF Full-text (3856 KB) | HTML Full-text | XML Full-text
Abstract
In this paper, a novel fiber turbine flow sensor was proposed and demonstrated for liquid measurement with optical fiber, using light intensity modulation to measure the turbine rotational speed for converting to flow rate. The double-circle-coaxial (DCC) fiber probe was introduced in frequency
[...] Read more.
In this paper, a novel fiber turbine flow sensor was proposed and demonstrated for liquid measurement with optical fiber, using light intensity modulation to measure the turbine rotational speed for converting to flow rate. The double-circle-coaxial (DCC) fiber probe was introduced in frequency measurement for the first time. Through the divided ratio of two rings light intensity, the interference in light signals acquisition can be eliminated. To predict the characteristics between the output frequency and flow in the nonlinear range, the turbine flow sensor model was built. Via analyzing the characteristics of turbine flow sensor, piecewise linear equations were achieved in expanding the flow measurement range. Furthermore, the experimental verification was tested. The results showed that the flow range ratio of DN20 turbine flow sensor was improved 2.9 times after using piecewise linear in the nonlinear range. Therefore, combining the DCC fiber sensor and piecewise linear method, it can be developed into a strong anti-electromagnetic interference(anti-EMI) and wide range fiber turbine flowmeter. Full article
(This article belongs to the Section Physical Sensors)
Open AccessArticle Sensor Localization from Distance and Orientation Constraints
Sensors 2016, 16(7), 1096; doi:10.3390/s16071096
Received: 13 May 2016 / Revised: 16 June 2016 / Accepted: 9 July 2016 / Published: 15 July 2016
PDF Full-text (2447 KB) | HTML Full-text | XML Full-text | Supplementary Files
Abstract
The sensor localization problem can be formalized using distance and orientation constraints, typically in 3D. Local methods can be used to refine an initial location estimation, but in many cases such estimation is not available and a method able to determine all the
[...] Read more.
The sensor localization problem can be formalized using distance and orientation constraints, typically in 3D. Local methods can be used to refine an initial location estimation, but in many cases such estimation is not available and a method able to determine all the feasible solutions from scratch is necessary. Unfortunately, existing methods able to find all the solutions in distance space can not take into account orientations, or they can only deal with one- or two-dimensional problems and their extension to 3D is troublesome. This paper presents a method that addresses these issues. The proposed approach iteratively projects the problem to decrease its dimension, then reduces the ranges of the variable distances, and back-projects the result to the original dimension, to obtain a tighter approximation of the feasible sensor locations. This paper extends previous works introducing accurate range reduction procedures which effectively integrate the orientation constraints. The mutual localization of a fleet of robots carrying sensors and the position analysis of a sensor moved by a parallel manipulator are used to validate the approach. Full article
(This article belongs to the Section Sensor Networks)
Open AccessArticle Nanomechanical Pyrolytic Carbon Resonators: Novel Fabrication Method and Characterization of Mechanical Properties
Sensors 2016, 16(7), 1097; doi:10.3390/s16071097
Received: 2 May 2016 / Revised: 27 June 2016 / Accepted: 11 July 2016 / Published: 15 July 2016
Cited by 1 | PDF Full-text (1901 KB) | HTML Full-text | XML Full-text
Abstract
Micro- and nanomechanical string resonators, which essentially are highly stressed bridges, are of particular interest for micro- and nanomechanical sensing because they exhibit resonant behavior with exceptionally high quality factors. Here, we fabricated and characterized nanomechanical pyrolytic carbon resonators (strings and cantilevers) obtained
[...] Read more.
Micro- and nanomechanical string resonators, which essentially are highly stressed bridges, are of particular interest for micro- and nanomechanical sensing because they exhibit resonant behavior with exceptionally high quality factors. Here, we fabricated and characterized nanomechanical pyrolytic carbon resonators (strings and cantilevers) obtained through pyrolysis of photoresist precursors. The developed fabrication process consists of only three processing steps: photolithography, dry etching and pyrolysis. Two different fabrication strategies with two different photoresists, namely SU-8 2005 (negative) and AZ 5214e (positive), were compared. The resonant behavior of the pyrolytic resonators was characterized at room temperature and in high vacuum using a laser Doppler vibrometer. The experimental data was used to estimate the Young’s modulus of pyrolytic carbon and the tensile stress in the string resonators. The Young’s moduli were calculated to be 74 ± 8 GPa with SU-8 and 115 ± 8 GPa with AZ 5214e as the precursor. The tensile stress in the string resonators was 33 ± 7 MPa with AZ 5214e as the precursor. The string resonators displayed maximal quality factor values of up to 3000 for 525-µm-long structures. Full article
(This article belongs to the Special Issue Carbon MEMS and NEMS for Sensor Applications)
Open AccessArticle Sensing Urban Patterns with Antenna Mappings: The Case of Santiago, Chile
Sensors 2016, 16(7), 1098; doi:10.3390/s16071098
Received: 5 May 2016 / Revised: 15 June 2016 / Accepted: 4 July 2016 / Published: 15 July 2016
Cited by 2 | PDF Full-text (4514 KB) | HTML Full-text | XML Full-text
Abstract
Mobile data has allowed us to sense urban dynamics at scales and granularities not known before, helping urban planners to cope with urban growth. A frequently used kind of dataset are Call Detail Records (CDR), used by telecommunication operators for billing purposes. Being
[...] Read more.
Mobile data has allowed us to sense urban dynamics at scales and granularities not known before, helping urban planners to cope with urban growth. A frequently used kind of dataset are Call Detail Records (CDR), used by telecommunication operators for billing purposes. Being an already extracted and processed dataset, it is inexpensive and reliable. A common assumption with respect to geography when working with CDR data is that the position of a device is the same as the Base Transceiver Station (BTS) it is connected to. Because the city is divided into a square grid, or by coverage zones approximated by Voronoi tessellations, CDR network events are assigned to corresponding areas according to BTS position. This geolocation may suffer from non negligible error in almost all cases. In this paper we propose “Antenna Virtual Placement” (AVP), a method to geolocate mobile devices according to their connections to BTS, based on decoupling antennas from its corresponding BTS according to its physical configuration (height, downtilt, and azimuth). We use AVP applied to CDR data as input for two different tasks: first, from an individual perspective, what places are meaningful for them? And second, from a global perspective, how to cluster city areas to understand land use using floating population flows? For both tasks we propose methods that complement or improve prior work in the literature. Our proposed methods are simple, yet not trivial, and work with daily CDR data from the biggest telecommunication operator in Chile. We evaluate them in Santiago, the capital of Chile, with data from working days from June 2015. We find that: (1) AVP improves city coverage of CDR data by geolocating devices to more city areas than using standard methods; (2) we find important places (home and work) for a 10% of the sample using just daily information, and recreate the population distribution as well as commuting trips; (3) the daily rhythms of floating population allow to cluster areas of the city, and explain them from a land use perspective by finding signature points of interest from crowdsourced geographical information. These results have implications for the design of applications based on CDR data like recommendation of places and routes, retail store placement, and estimation of transport effects from pollution alerts. Full article
(This article belongs to the Special Issue Selected Papers from UCAmI, IWAAL and AmIHEALTH 2015)
Open AccessArticle Quantitative Determination of Fusarium proliferatum Concentration in Intact Garlic Cloves Using Near-Infrared Spectroscopy
Sensors 2016, 16(7), 1099; doi:10.3390/s16071099
Received: 27 May 2016 / Revised: 11 July 2016 / Accepted: 13 July 2016 / Published: 15 July 2016
PDF Full-text (2713 KB) | HTML Full-text | XML Full-text
Abstract
Fusarium proliferatum is considered to be a pathogen of many economically important plants, including garlic. The objective of this research was to apply near-infrared spectroscopy (NIRS) to rapidly determine fungal concentration in intact garlic cloves, avoiding the laborious and time-consuming procedures of traditional
[...] Read more.
Fusarium proliferatum is considered to be a pathogen of many economically important plants, including garlic. The objective of this research was to apply near-infrared spectroscopy (NIRS) to rapidly determine fungal concentration in intact garlic cloves, avoiding the laborious and time-consuming procedures of traditional assays. Preventive detection of infection before seeding is of great interest for farmers, because it could avoid serious losses of yield during harvesting and storage. Spectra were collected on 95 garlic cloves, divided in five classes of infection (from 1-healthy to 5-very highly infected) in the range of fungal concentration 0.34–7231.15 ppb. Calibration and cross validation models were developed with partial least squares regression (PLSR) on pretreated spectra (standard normal variate, SNV, and derivatives), providing good accuracy in prediction, with a coefficient of determination (R2) of 0.829 and 0.774, respectively, a standard error of calibration (SEC) of 615.17 ppb, and a standard error of cross validation (SECV) of 717.41 ppb. The calibration model was then used to predict fungal concentration in unknown samples, peeled and unpeeled. The results showed that NIRS could be used as a reliable tool to directly detect and quantify F. proliferatum infection in peeled intact garlic cloves, but the presence of the external peel strongly affected the prediction reliability. Full article
(This article belongs to the Section Chemical Sensors)
Open AccessArticle Stochastic Analysis of the Efficiency of a Wireless Power Transfer System Subject to Antenna Variability and Position Uncertainties
Sensors 2016, 16(7), 1100; doi:10.3390/s16071100
Received: 13 May 2016 / Revised: 8 July 2016 / Accepted: 13 July 2016 / Published: 19 July 2016
Cited by 2 | PDF Full-text (1037 KB) | HTML Full-text | XML Full-text
Abstract
The efficiency of a wireless power transfer (WPT) system in the radiative near-field is inevitably affected by the variability in the design parameters of the deployed antennas and by uncertainties in their mutual position. Therefore, we propose a stochastic analysis that combines the
[...] Read more.
The efficiency of a wireless power transfer (WPT) system in the radiative near-field is inevitably affected by the variability in the design parameters of the deployed antennas and by uncertainties in their mutual position. Therefore, we propose a stochastic analysis that combines the generalized polynomial chaos (gPC) theory with an efficient model for the interaction between devices in the radiative near-field. This framework enables us to investigate the impact of random effects on the power transfer efficiency (PTE) of a WPT system. More specifically, the WPT system under study consists of a transmitting horn antenna and a receiving textile antenna operating in the Industrial, Scientific and Medical (ISM) band at 2.45 GHz. First, we model the impact of the textile antenna’s variability on the WPT system. Next, we include the position uncertainties of the antennas in the analysis in order to quantify the overall variations in the PTE. The analysis is carried out by means of polynomial-chaos-based macromodels, whereas a Monte Carlo simulation validates the complete technique. It is shown that the proposed approach is very accurate, more flexible and more efficient than a straightforward Monte Carlo analysis, with demonstrated speedup factors up to 2500. Full article
(This article belongs to the Section Sensor Networks)
Open AccessArticle The Joint Adaptive Kalman Filter (JAKF) for Vehicle Motion State Estimation
Sensors 2016, 16(7), 1103; doi:10.3390/s16071103
Received: 6 May 2016 / Revised: 6 July 2016 / Accepted: 11 July 2016 / Published: 16 July 2016
Cited by 2 | PDF Full-text (9193 KB) | HTML Full-text | XML Full-text
Abstract
This paper proposes a multi-sensory Joint Adaptive Kalman Filter (JAKF) through extending innovation-based adaptive estimation (IAE) to estimate the motion state of the moving vehicles ahead. JAKF views Lidar and Radar data as the source of the local filters, which aims to adaptively
[...] Read more.
This paper proposes a multi-sensory Joint Adaptive Kalman Filter (JAKF) through extending innovation-based adaptive estimation (IAE) to estimate the motion state of the moving vehicles ahead. JAKF views Lidar and Radar data as the source of the local filters, which aims to adaptively adjust the measurement noise variance-covariance (V-C) matrix ‘R’ and the system noise V-C matrix ‘Q’. Then, the global filter uses R to calculate the information allocation factor ‘β’ for data fusion. Finally, the global filter completes optimal data fusion and feeds back to the local filters to improve the measurement accuracy of the local filters. Extensive simulation and experimental results show that the JAKF has better adaptive ability and fault tolerance. JAKF enables one to bridge the gap of the accuracy difference of various sensors to improve the integral filtering effectivity. If any sensor breaks down, the filtered results of JAKF still can maintain a stable convergence rate. Moreover, the JAKF outperforms the conventional Kalman filter (CKF) and the innovation-based adaptive Kalman filter (IAKF) with respect to the accuracy of displacement, velocity, and acceleration, respectively. Full article
(This article belongs to the Special Issue Advances in Multi-Sensor Information Fusion: Theory and Applications)
Figures

Open AccessArticle Systematic Development of Intelligent Systems for Public Road Transport
Sensors 2016, 16(7), 1104; doi:10.3390/s16071104
Received: 25 April 2016 / Revised: 8 July 2016 / Accepted: 13 July 2016 / Published: 16 July 2016
Cited by 1 | PDF Full-text (3381 KB) | HTML Full-text | XML Full-text
Abstract
This paper presents an architecture model for the development of intelligent systems for public passenger transport by road. The main objective of our proposal is to provide a framework for the systematic development and deployment of telematics systems to improve various aspects of
[...] Read more.
This paper presents an architecture model for the development of intelligent systems for public passenger transport by road. The main objective of our proposal is to provide a framework for the systematic development and deployment of telematics systems to improve various aspects of this type of transport, such as efficiency, accessibility and safety. The architecture model presented herein is based on international standards on intelligent transport system architectures, ubiquitous computing and service-oriented architecture for distributed systems. To illustrate the utility of the model, we also present a use case of a monitoring system for stops on a public passenger road transport network. Full article
(This article belongs to the Special Issue Selected Papers from UCAmI, IWAAL and AmIHEALTH 2015)
Figures

Open AccessArticle Real-Time Detection and Measurement of Eye Features from Color Images
Sensors 2016, 16(7), 1105; doi:10.3390/s16071105
Received: 28 April 2016 / Revised: 13 July 2016 / Accepted: 14 July 2016 / Published: 16 July 2016
PDF Full-text (7785 KB) | HTML Full-text | XML Full-text | Supplementary Files
Abstract
The accurate extraction and measurement of eye features is crucial to a variety of domains, including human-computer interaction, biometry, and medical research. This paper presents a fast and accurate method for extracting multiple features around the eyes: the center of the pupil, the
[...] Read more.
The accurate extraction and measurement of eye features is crucial to a variety of domains, including human-computer interaction, biometry, and medical research. This paper presents a fast and accurate method for extracting multiple features around the eyes: the center of the pupil, the iris radius, and the external shape of the eye. These features are extracted using a multistage algorithm. On the first stage the pupil center is localized using a fast circular symmetry detector and the iris radius is computed using radial gradient projections, and on the second stage the external shape of the eye (of the eyelids) is determined through a Monte Carlo sampling framework based on both color and shape information. Extensive experiments performed on a different dataset demonstrate the effectiveness of our approach. In addition, this work provides eye annotation data for a publicly-available database. Full article
(This article belongs to the Special Issue Non-Contact Sensing)
Figures

Open AccessArticle Influence of Ionic Liquids on the Selectivity of Ion Exchange-Based Polymer Membrane Sensing Layers
Sensors 2016, 16(7), 1106; doi:10.3390/s16071106
Received: 17 May 2016 / Revised: 8 July 2016 / Accepted: 14 July 2016 / Published: 16 July 2016
Cited by 2 | PDF Full-text (1509 KB) | HTML Full-text | XML Full-text | Supplementary Files
Abstract
The applicability of ion exchange membranes is mainly defined by their permselectivity towards specific ions. For instance, the needed selectivity can be sought by modifying some of the components required for the preparation of such membranes. In this study, a new class of
[...] Read more.
The applicability of ion exchange membranes is mainly defined by their permselectivity towards specific ions. For instance, the needed selectivity can be sought by modifying some of the components required for the preparation of such membranes. In this study, a new class of materials –trihexyl(tetradecyl)phosphonium based ionic liquids (ILs) were used to modify the properties of ion exchange membranes. We determined selectivity coefficients for iodide as model ion utilizing six phosphonium-based ILs and compared the selectivity with two classical plasticizers. The dielectric properties of membranes plasticized with ionic liquids and their response characteristics towards ten different anions were investigated using potentiometric and impedance measurements. In this large set of data, deviations of obtained selectivity coefficients from the well-established Hofmeister series were observed on many occasions thus indicating a multitude of applications for these ion-exchanging systems. Full article
(This article belongs to the Special Issue Ionic Liquids)
Open AccessArticle A Likelihood-Based SLIC Superpixel Algorithm for SAR Images Using Generalized Gamma Distribution
Sensors 2016, 16(7), 1107; doi:10.3390/s16071107
Received: 26 March 2016 / Revised: 7 July 2016 / Accepted: 13 July 2016 / Published: 18 July 2016
Cited by 2 | PDF Full-text (6560 KB) | HTML Full-text | XML Full-text
Abstract
The simple linear iterative clustering (SLIC) method is a recently proposed popular superpixel algorithm. However, this method may generate bad superpixels for synthetic aperture radar (SAR) images due to effects of speckle and the large dynamic range of pixel intensity. In this paper,
[...] Read more.
The simple linear iterative clustering (SLIC) method is a recently proposed popular superpixel algorithm. However, this method may generate bad superpixels for synthetic aperture radar (SAR) images due to effects of speckle and the large dynamic range of pixel intensity. In this paper, an improved SLIC algorithm for SAR images is proposed. This algorithm exploits the likelihood information of SAR image pixel clusters. Specifically, a local clustering scheme combining intensity similarity with spatial proximity is proposed. Additionally, for post-processing, a local edge-evolving scheme that combines spatial context and likelihood information is introduced as an alternative to the connected components algorithm. To estimate the likelihood information of SAR image clusters, we incorporated a generalized gamma distribution (GГD). Finally, the superiority of the proposed algorithm was validated using both simulated and real-world SAR images. Full article
Open AccessArticle A Low Collision and High Throughput Data Collection Mechanism for Large-Scale Super Dense Wireless Sensor Networks
Sensors 2016, 16(7), 1108; doi:10.3390/s16071108
Received: 15 June 2016 / Revised: 7 July 2016 / Accepted: 11 July 2016 / Published: 18 July 2016
PDF Full-text (1364 KB) | HTML Full-text | XML Full-text
Abstract
Super dense wireless sensor networks (WSNs) have become popular with the development of Internet of Things (IoT), Machine-to-Machine (M2M) communications and Vehicular-to-Vehicular (V2V) networks. While highly-dense wireless networks provide efficient and sustainable solutions to collect precise environmental information, a new channel access scheme
[...] Read more.
Super dense wireless sensor networks (WSNs) have become popular with the development of Internet of Things (IoT), Machine-to-Machine (M2M) communications and Vehicular-to-Vehicular (V2V) networks. While highly-dense wireless networks provide efficient and sustainable solutions to collect precise environmental information, a new channel access scheme is needed to solve the channel collision problem caused by the large number of competing nodes accessing the channel simultaneously. In this paper, we propose a space-time random access method based on a directional data transmission strategy, by which collisions in the wireless channel are significantly decreased and channel utility efficiency is greatly enhanced. Simulation results show that our proposed method can decrease the packet loss rate to less than 2 % in large scale WSNs and in comparison with other channel access schemes for WSNs, the average network throughput can be doubled. Full article
(This article belongs to the Section Sensor Networks)
Open AccessArticle Kalman Filters in Geotechnical Monitoring of Ground Subsidence Using Data from MEMS Sensors
Sensors 2016, 16(7), 1109; doi:10.3390/s16071109
Received: 25 March 2016 / Revised: 25 May 2016 / Accepted: 1 June 2016 / Published: 19 July 2016
PDF Full-text (3271 KB) | HTML Full-text | XML Full-text
Abstract
The fast development of wireless sensor networks and MEMS make it possible to set up today real-time wireless geotechnical monitoring. To handle interferences and noises from the output data, Kalman filter can be selected as a method to achieve a more realistic estimate
[...] Read more.
The fast development of wireless sensor networks and MEMS make it possible to set up today real-time wireless geotechnical monitoring. To handle interferences and noises from the output data, Kalman filter can be selected as a method to achieve a more realistic estimate of the observations. In this paper, a one-day wireless measurement using accelerometers and inclinometers was deployed on top of a tunnel section under construction in order to monitor ground subsidence. The normal vectors of the sensors were firstly obtained with the help of rotation matrices, and then be projected to the plane of longitudinal section, by which the dip angles over time would be obtained via a trigonometric function. Finally, a centralized Kalman filter was applied to estimate the tilt angles of the sensor nodes based on the data from the embedded accelerometer and the inclinometer. Comparing the results from two sensor nodes deployed away and on the track respectively, the passing of the tunnel boring machine can be identified from unusual performances. Using this method, the ground settlement due to excavation can be measured and a real-time monitoring of ground subsidence can be realized. Full article
(This article belongs to the collection Modeling, Testing and Reliability Issues in MEMS Engineering)
Open AccessArticle A Robust Gradient Based Method for Building Extraction from LiDAR and Photogrammetric Imagery
Sensors 2016, 16(7), 1110; doi:10.3390/s16071110
Received: 20 April 2016 / Revised: 6 July 2016 / Accepted: 14 July 2016 / Published: 19 July 2016
PDF Full-text (8350 KB) | HTML Full-text | XML Full-text
Abstract
Existing automatic building extraction methods are not effective in extracting buildings which are small in size and have transparent roofs. The application of large area threshold prohibits detection of small buildings and the use of ground points in generating the building mask prevents
[...] Read more.
Existing automatic building extraction methods are not effective in extracting buildings which are small in size and have transparent roofs. The application of large area threshold prohibits detection of small buildings and the use of ground points in generating the building mask prevents detection of transparent buildings. In addition, the existing methods use numerous parameters to extract buildings in complex environments, e.g., hilly area and high vegetation. However, the empirical tuning of large number of parameters reduces the robustness of building extraction methods. This paper proposes a novel Gradient-based Building Extraction (GBE) method to address these limitations. The proposed method transforms the Light Detection And Ranging (LiDAR) height information into intensity image without interpolation of point heights and then analyses the gradient information in the image. Generally, building roof planes have a constant height change along the slope of a roof plane whereas trees have a random height change. With such an analysis, buildings of a greater range of sizes with a transparent or opaque roof can be extracted. In addition, a local colour matching approach is introduced as a post-processing stage to eliminate trees. This stage of our proposed method does not require any manual setting and all parameters are set automatically from the data. The other post processing stages including variance, point density and shadow elimination are also applied to verify the extracted buildings, where comparatively fewer empirically set parameters are used. The performance of the proposed GBE method is evaluated on two benchmark data sets by using the object and pixel based metrics (completeness, correctness and quality). Our experimental results show the effectiveness of the proposed method in eliminating trees, extracting buildings of all sizes, and extracting buildings with and without transparent roof. When compared with current state-of-the-art building extraction methods, the proposed method outperforms the existing methods in various evaluation metrics. Full article
(This article belongs to the Section Remote Sensors)
Figures

Open AccessArticle Preservation Mechanism of Chitosan-Based Coating with Cinnamon Oil for Fruits Storage Based on Sensor Data
Sensors 2016, 16(7), 1111; doi:10.3390/s16071111
Received: 15 April 2016 / Revised: 13 July 2016 / Accepted: 14 July 2016 / Published: 18 July 2016
Cited by 1 | PDF Full-text (4792 KB) | HTML Full-text | XML Full-text
Abstract
The chitosan-based coating with antimicrobial agent has been developed recently to control the decay of fruits. However, its fresh keeping and antimicrobial mechanism is still not very clear. The preservation mechanism of chitosan coating with cinnamon oil for fruits storage is investigated in
[...] Read more.
The chitosan-based coating with antimicrobial agent has been developed recently to control the decay of fruits. However, its fresh keeping and antimicrobial mechanism is still not very clear. The preservation mechanism of chitosan coating with cinnamon oil for fruits storage is investigated in this paper. Results in the atomic force microscopy sensor images show that many micropores exist in the chitosan coating film. The roughness of coating film is affected by the concentration of chitosan. The antifungal activity of cinnamon oil should be mainly due to its main consistent trans-cinnamaldehyde, which is proportional to the trans-cinnamaldehyde concentration and improves with increasing the attachment time of oil. The exosmosis ratios of Penicillium citrinum and Aspergillus flavus could be enhanced by increasing the concentration of cinnamon oil. Morphological observation indicates that, compared to the normal cell, the wizened mycelium of A. flavus is observed around the inhibition zone, and the growth of spores is also inhibited. Moreover, the analysis of gas sensors indicate that the chitosan-oil coating could decrease the level of O2 and increase the level of CO2 in the package of cherry fruits, which also control the fruit decay. These results indicate that its preservation mechanism might be partly due to the micropores structure of coating film as a barrier for gas and a carrier for oil, and partly due to the activity of cinnamon oil on the cell disruption. Full article
(This article belongs to the Special Issue Sensors for Agriculture)
Figures

Open AccessArticle Telecommunication Platforms for Transmitting Sensor Data over Communication Networks—State of the Art and Challenges
Sensors 2016, 16(7), 1113; doi:10.3390/s16071113
Received: 22 April 2016 / Revised: 1 July 2016 / Accepted: 4 July 2016 / Published: 19 July 2016
PDF Full-text (4281 KB) | HTML Full-text | XML Full-text
Abstract
The importance of constructing wide-area sensor networks for holistic environmental state evaluation has been demonstrated. A general structure of such a network has been presented with distinction of three segments: local (based on ZigBee, Ethernet and ModBus techniques), core (base on cellular technologies)
[...] Read more.
The importance of constructing wide-area sensor networks for holistic environmental state evaluation has been demonstrated. A general structure of such a network has been presented with distinction of three segments: local (based on ZigBee, Ethernet and ModBus techniques), core (base on cellular technologies) and the storage/application. The implementation of these techniques requires knowledge of their technical limitations and electromagnetic compatibility issues. The former refer to ZigBee performance degradation in multi-hop transmission, whereas the latter are associated with the common electromagnetic spectrum sharing with other existing technologies or with undesired radiated emissions generated by the radio modules of the sensor network. In many cases, it is also necessary to provide a measurement station with autonomous energy source, such as solar. As stems from measurements of the energetic efficiency of these sources, one should apply them with care and perform detailed power budget since their real performance may turn out to be far from expected. This, in turn, may negatively affect—in particular—the operation of chemical sensors implemented in the network as they often require additional heating. Full article
(This article belongs to the Special Issue Data in the IoT: from Sensing to Meaning)
Open AccessArticle Estimation of Electrically-Evoked Knee Torque from Mechanomyography Using Support Vector Regression
Sensors 2016, 16(7), 1115; doi:10.3390/s16071115
Received: 14 March 2016 / Revised: 6 June 2016 / Accepted: 8 June 2016 / Published: 19 July 2016
Cited by 4 | PDF Full-text (1413 KB) | HTML Full-text | XML Full-text
Abstract
The difficulty of real-time muscle force or joint torque estimation during neuromuscular electrical stimulation (NMES) in physical therapy and exercise science has motivated recent research interest in torque estimation from other muscle characteristics. This study investigated the accuracy of a computational intelligence technique
[...] Read more.
The difficulty of real-time muscle force or joint torque estimation during neuromuscular electrical stimulation (NMES) in physical therapy and exercise science has motivated recent research interest in torque estimation from other muscle characteristics. This study investigated the accuracy of a computational intelligence technique for estimating NMES-evoked knee extension torque based on the Mechanomyographic signals (MMG) of contracting muscles that were recorded from eight healthy males. Simulation of the knee torque was modelled via Support Vector Regression (SVR) due to its good generalization ability in related fields. Inputs to the proposed model were MMG amplitude characteristics, the level of electrical stimulation or contraction intensity, and knee angle. Gaussian kernel function, as well as its optimal parameters were identified with the best performance measure and were applied as the SVR kernel function to build an effective knee torque estimation model. To train and test the model, the data were partitioned into training (70%) and testing (30%) subsets, respectively. The SVR estimation accuracy, based on the coefficient of determination (R2) between the actual and the estimated torque values was up to 94% and 89% during the training and testing cases, with root mean square errors (RMSE) of 9.48 and 12.95, respectively. The knee torque estimations obtained using SVR modelling agreed well with the experimental data from an isokinetic dynamometer. These findings support the realization of a closed-loop NMES system for functional tasks using MMG as the feedback signal source and an SVR algorithm for joint torque estimation. Full article
(This article belongs to the Special Issue Sensing Technology for Healthcare System)
Open AccessArticle A New Controller for a Smart Walker Based on Human-Robot Formation
Sensors 2016, 16(7), 1116; doi:10.3390/s16071116
Received: 12 May 2016 / Revised: 24 June 2016 / Accepted: 14 July 2016 / Published: 19 July 2016
Cited by 1 | PDF Full-text (8888 KB) | HTML Full-text | XML Full-text
Abstract
This paper presents the development of a smart walker that uses a formation controller in its displacements. Encoders, a laser range finder and ultrasound are the sensors used in the walker. The control actions are based on the user (human) location, who is
[...] Read more.
This paper presents the development of a smart walker that uses a formation controller in its displacements. Encoders, a laser range finder and ultrasound are the sensors used in the walker. The control actions are based on the user (human) location, who is the actual formation leader. There is neither a sensor attached to the user’s body nor force sensors attached to the arm supports of the walker, and thus, the control algorithm projects the measurements taken from the laser sensor into the user reference and, then, calculates the linear and angular walker’s velocity to keep the formation (distance and angle) in relation to the user. An algorithm was developed to detect the user’s legs, whose distances from the laser sensor provide the information necessary to the controller. The controller was theoretically analyzed regarding its stability, simulated and validated with real users, showing accurate performance in all experiments. In addition, safety rules are used to check both the user and the device conditions, in order to guarantee that the user will not have any risks when using the smart walker. The applicability of this device is for helping people with lower limb mobility impairments. Full article
(This article belongs to the Special Issue Advanced Robotics and Mechatronics Devices)
Open AccessArticle Robust Ground Target Detection by SAR and IR Sensor Fusion Using Adaboost-Based Feature Selection
Sensors 2016, 16(7), 1117; doi:10.3390/s16071117
Received: 9 May 2016 / Revised: 22 June 2016 / Accepted: 13 July 2016 / Published: 19 July 2016
Cited by 4 | PDF Full-text (12975 KB) | HTML Full-text | XML Full-text
Abstract
Long-range ground targets are difficult to detect in a noisy cluttered environment using either synthetic aperture radar (SAR) images or infrared (IR) images. SAR-based detectors can provide a high detection rate with a high false alarm rate to background scatter noise. IR-based approaches
[...] Read more.
Long-range ground targets are difficult to detect in a noisy cluttered environment using either synthetic aperture radar (SAR) images or infrared (IR) images. SAR-based detectors can provide a high detection rate with a high false alarm rate to background scatter noise. IR-based approaches can detect hot targets but are affected strongly by the weather conditions. This paper proposes a novel target detection method by decision-level SAR and IR fusion using an Adaboost-based machine learning scheme to achieve a high detection rate and low false alarm rate. The proposed method consists of individual detection, registration, and fusion architecture. This paper presents a single framework of a SAR and IR target detection method using modified Boolean map visual theory (modBMVT) and feature-selection based fusion. Previous methods applied different algorithms to detect SAR and IR targets because of the different physical image characteristics. One method that is optimized for IR target detection produces unsuccessful results in SAR target detection. This study examined the image characteristics and proposed a unified SAR and IR target detection method by inserting a median local average filter (MLAF, pre-filter) and an asymmetric morphological closing filter (AMCF, post-filter) into the BMVT. The original BMVT was optimized to detect small infrared targets. The proposed modBMVT can remove the thermal and scatter noise by the MLAF and detect extended targets by attaching the AMCF after the BMVT. Heterogeneous SAR and IR images were registered automatically using the proposed RANdom SAmple Region Consensus (RANSARC)-based homography optimization after a brute-force correspondence search using the detected target centers and regions. The final targets were detected by feature-selection based sensor fusion using Adaboost. The proposed method showed good SAR and IR target detection performance through feature selection-based decision fusion on a synthetic database generated by OKTAL-SE. Full article
(This article belongs to the Special Issue Non-Contact Sensing)
Open AccessArticle The Vector Matching Method in Geomagnetic Aiding Navigation
Sensors 2016, 16(7), 1120; doi:10.3390/s16071120
Received: 28 March 2016 / Revised: 9 July 2016 / Accepted: 15 July 2016 / Published: 20 July 2016
Cited by 2 | PDF Full-text (1414 KB) | HTML Full-text | XML Full-text
Abstract
In this paper, a geomagnetic matching navigation method that utilizes the geomagnetic vector is developed, which can greatly improve the matching probability and positioning precision, even when the geomagnetic entropy information in the matching region is small or the geomagnetic contour line’s variety
[...] Read more.
In this paper, a geomagnetic matching navigation method that utilizes the geomagnetic vector is developed, which can greatly improve the matching probability and positioning precision, even when the geomagnetic entropy information in the matching region is small or the geomagnetic contour line’s variety is obscure. The vector iterative closest contour point (VICCP) algorithm that is proposed here has better adaptability with the positioning error characteristics of the inertial navigation system (INS), where the rigid transformation in ordinary ICCP is replaced with affine transformation. In a subsequent step, a geomagnetic vector information fusion algorithm based on Bayesian statistical analysis is introduced into VICCP to improve matching performance further. Simulations based on the actual geomagnetic reference map have been performed for the validation of the proposed algorithm. Full article
(This article belongs to the Special Issue Advances in Multi-Sensor Information Fusion: Theory and Applications)
Open AccessArticle Modeling and Compensating Temperature-Dependent Non-Uniformity Noise in IR Microbolometer Cameras
Sensors 2016, 16(7), 1121; doi:10.3390/s16071121
Received: 30 April 2016 / Revised: 12 July 2016 / Accepted: 13 July 2016 / Published: 19 July 2016
Cited by 3 | PDF Full-text (3560 KB) | HTML Full-text | XML Full-text | Supplementary Files
Abstract
Images rendered by uncooled microbolometer-based infrared (IR) cameras are severely degraded by the spatial non-uniformity (NU) noise. The NU noise imposes a fixed-pattern over the true images, and the intensity of the pattern changes with time due to the temperature instability of such
[...] Read more.
Images rendered by uncooled microbolometer-based infrared (IR) cameras are severely degraded by the spatial non-uniformity (NU) noise. The NU noise imposes a fixed-pattern over the true images, and the intensity of the pattern changes with time due to the temperature instability of such cameras. In this paper, we present a novel model and a compensation algorithm for the spatial NU noise and its temperature-dependent variations. The model separates the NU noise into two components: a constant term, which corresponds to a set of NU parameters determining the spatial structure of the noise, and a dynamic term, which scales linearly with the fluctuations of the temperature surrounding the array of microbolometers. We use a black-body radiator and samples of the temperature surrounding the IR array to offline characterize both the constant and the temperature-dependent NU noise parameters. Next, the temperature-dependent variations are estimated online using both a spatially uniform Hammerstein-Wiener estimator and a pixelwise least mean squares (LMS) estimator. We compensate for the NU noise in IR images from two long-wave IR cameras. Results show an excellent NU correction performance and a root mean square error of less than 0.25 C, when the array’s temperature varies by approximately 15 C. Full article
(This article belongs to the Special Issue Infrared and THz Sensing and Imaging)
Figures

Open AccessArticle Single Photon Counting Performance and Noise Analysis of CMOS SPAD-Based Image Sensors
by