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Sensors, Volume 17, Issue 1 (January 2017)

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Cover Story Autonomous driving sets a disruptive paradigm of mobility which relies on different technological [...] Read more.
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Editorial

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Open AccessEditorial Acknowledgement to Reviewers of Sensors in 2016
Sensors 2017, 17(1), 128; doi:10.3390/s17010128
Received: 9 January 2017 / Revised: 9 January 2017 / Accepted: 10 January 2017 / Published: 10 January 2017
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Abstract
The editors of Sensors would like to express their sincere gratitude to the following reviewers for assessing manuscripts in 2016.[...] Full article

Research

Jump to: Editorial, Review, Other

Open AccessArticle A Unified Framework for Street-View Panorama Stitching
Sensors 2017, 17(1), 1; doi:10.3390/s17010001
Received: 8 September 2016 / Revised: 30 November 2016 / Accepted: 15 December 2016 / Published: 22 December 2016
Cited by 2 | PDF Full-text (33857 KB) | HTML Full-text | XML Full-text
Abstract
In this paper, we propose a unified framework to generate a pleasant and high-quality street-view panorama by stitching multiple panoramic images captured from the cameras mounted on the mobile platform. Our proposed framework is comprised of four major steps: image warping, color correction,
[...] Read more.
In this paper, we propose a unified framework to generate a pleasant and high-quality street-view panorama by stitching multiple panoramic images captured from the cameras mounted on the mobile platform. Our proposed framework is comprised of four major steps: image warping, color correction, optimal seam line detection and image blending. Since the input images are captured without a precisely common projection center from the scenes with the depth differences with respect to the cameras to different extents, such images cannot be precisely aligned in geometry. Therefore, an efficient image warping method based on the dense optical flow field is proposed to greatly suppress the influence of large geometric misalignment at first. Then, to lessen the influence of photometric inconsistencies caused by the illumination variations and different exposure settings, we propose an efficient color correction algorithm via matching extreme points of histograms to greatly decrease color differences between warped images. After that, the optimal seam lines between adjacent input images are detected via the graph cut energy minimization framework. At last, the Laplacian pyramid blending algorithm is applied to further eliminate the stitching artifacts along the optimal seam lines. Experimental results on a large set of challenging street-view panoramic images captured form the real world illustrate that the proposed system is capable of creating high-quality panoramas. Full article
(This article belongs to the Section Remote Sensors)
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Open AccessArticle Graphene-Based Long-Period Fiber Grating Surface Plasmon Resonance Sensor for High-Sensitivity Gas Sensing
Sensors 2017, 17(1), 2; doi:10.3390/s17010002
Received: 25 October 2016 / Revised: 7 December 2016 / Accepted: 12 December 2016 / Published: 22 December 2016
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Abstract
A graphene-based long-period fiber grating (LPFG) surface plasmon resonance (SPR) sensor is proposed. A monolayer of graphene is coated onto the Ag film surface of the LPFG SPR sensor, which increases the intensity of the evanescent field on the surface of the fiber
[...] Read more.
A graphene-based long-period fiber grating (LPFG) surface plasmon resonance (SPR) sensor is proposed. A monolayer of graphene is coated onto the Ag film surface of the LPFG SPR sensor, which increases the intensity of the evanescent field on the surface of the fiber and thereby enhances the interaction between the SPR wave and molecules. Such features significantly improve the sensitivity of the sensor. The experimental results demonstrate that the sensitivity of the graphene-based LPFG SPR sensor can reach 0.344 nm%−1 for methane, which is improved 2.96 and 1.31 times with respect to the traditional LPFG sensor and Ag-coated LPFG SPR sensor, respectively. Meanwhile, the graphene-based LPFG SPR sensor exhibits excellent response characteristics and repeatability. Such a SPR sensing scheme offers a promising platform to achieve high sensitivity for gas-sensing applications. Full article
(This article belongs to the Section Physical Sensors)
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Open AccessArticle Measurement and Geometric Modelling of Human Spine Posture for Medical Rehabilitation Purposes Using a Wearable Monitoring System Based on Inertial Sensors
Sensors 2017, 17(1), 0003; doi:10.3390/s17010003
Received: 27 September 2016 / Revised: 28 November 2016 / Accepted: 11 December 2016 / Published: 22 December 2016
Cited by 1 | PDF Full-text (14429 KB) | HTML Full-text | XML Full-text
Abstract
This paper presents a mathematical model that can be used to virtually reconstruct the posture of the human spine. By using orientation angles from a wearable monitoring system based on inertial sensors, the model calculates and represents the curvature of the spine. Several
[...] Read more.
This paper presents a mathematical model that can be used to virtually reconstruct the posture of the human spine. By using orientation angles from a wearable monitoring system based on inertial sensors, the model calculates and represents the curvature of the spine. Several hypotheses are taken into consideration to increase the model precision. An estimation of the postures that can be calculated is also presented. A non-invasive solution to identify the human back shape can help reducing the time needed for medical rehabilitation sessions. Moreover, it prevents future problems caused by poor posture. Full article
(This article belongs to the Special Issue Body Worn Behavior Sensing)
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Open AccessArticle Effects of Operating Temperature on Droplet Casting of Flexible Polymer/Multi-Walled Carbon Nanotube Composite Gas Sensors
Sensors 2017, 17(1), 4; doi:10.3390/s17010004
Received: 29 November 2016 / Revised: 16 December 2016 / Accepted: 17 December 2016 / Published: 22 December 2016
Cited by 2 | PDF Full-text (4910 KB) | HTML Full-text | XML Full-text
Abstract
This study examined the performance of a flexible polymer/multi-walled carbon nanotube (MWCNT) composite sensor array as a function of operating temperature. The response magnitudes of a cost-effective flexible gas sensor array equipped with a heater were measured with respect to five different operating
[...] Read more.
This study examined the performance of a flexible polymer/multi-walled carbon nanotube (MWCNT) composite sensor array as a function of operating temperature. The response magnitudes of a cost-effective flexible gas sensor array equipped with a heater were measured with respect to five different operating temperatures (room temperature, 40 °C, 50 °C, 60 °C, and 70 °C) via impedance spectrum measurement and sensing response experiments. The selected polymers that were droplet cast to coat a MWCNT conductive layer to form two-layer polymer/MWCNT composite sensing films included ethyl cellulose (EC), polyethylene oxide (PEO), and polyvinylpyrrolidone (PVP). Electrical characterization of impedance, sensing response magnitude, and scanning electron microscope (SEM) morphology of each type of polymer/MWCNT composite film was performed at different operating temperatures. With respect to ethanol, the response magnitude of the sensor decreased with increasing operating temperatures. The results indicated that the higher operating temperature could reduce the response and influence the sensitivity of the polymer/MWCNT gas sensor array. The morphology of polymer/MWCNT composite films revealed that there were changes in the porous film after volatile organic compound (VOC) testing. Full article
(This article belongs to the Special Issue Gas Nanosensors)
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Open AccessArticle Selection of Shear Horizontal Wave Transducers for Robotic Nondestructive Inspection in Harsh Environments
Sensors 2017, 17(1), 5; doi:10.3390/s17010005
Received: 31 October 2016 / Revised: 13 December 2016 / Accepted: 19 December 2016 / Published: 22 December 2016
Cited by 1 | PDF Full-text (11735 KB) | HTML Full-text | XML Full-text
Abstract
Harsh environments and confined spaces require that nondestructive inspections be conducted with robotic systems. Ultrasonic guided waves are well suited for robotic systems because they can provide efficient volumetric coverage when inspecting for various types of damage, including cracks and corrosion. Shear horizontal
[...] Read more.
Harsh environments and confined spaces require that nondestructive inspections be conducted with robotic systems. Ultrasonic guided waves are well suited for robotic systems because they can provide efficient volumetric coverage when inspecting for various types of damage, including cracks and corrosion. Shear horizontal guided waves are especially well suited for robotic inspection because they are sensitive to cracks oriented perpendicular or parallel to the wave propagation direction and can be generated with electromagnetic acoustic transducers (EMATs) and magnetostrictive transducers (MSTs). Both types of transducers are investigated for crack detection in a stainless steel plate. The MSTs require the robot to apply a compressive normal force that creates frictional force coupling. However, the coupling is observed to be very dependent upon surface roughness and surface debris. The EMATs are coupled through the Lorentz force and are thus noncontact, although they depend on the lift off between transducer and substrate. After comparing advantages and disadvantages of each transducer for robotic inspection the EMATs are selected for application to canisters that store used nuclear fuel. Full article
(This article belongs to the Special Issue Ultrasonic Sensors)
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Open AccessArticle Cross View Gait Recognition Using Joint-Direct Linear Discriminant Analysis
Sensors 2017, 17(1), 6; doi:10.3390/s17010006
Received: 2 November 2016 / Revised: 20 December 2016 / Accepted: 20 December 2016 / Published: 22 December 2016
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Abstract
This paper proposes a view-invariant gait recognition framework that employs a unique view invariant model that profits from the dimensionality reduction provided by Direct Linear Discriminant Analysis (DLDA). The framework, which employs gait energy images (GEIs), creates a single joint model that accurately
[...] Read more.
This paper proposes a view-invariant gait recognition framework that employs a unique view invariant model that profits from the dimensionality reduction provided by Direct Linear Discriminant Analysis (DLDA). The framework, which employs gait energy images (GEIs), creates a single joint model that accurately classifies GEIs captured at different angles. Moreover, the proposed framework also helps to reduce the under-sampling problem (USP) that usually appears when the number of training samples is much smaller than the dimension of the feature space. Evaluation experiments compare the proposed framework’s computational complexity and recognition accuracy against those of other view-invariant methods. Results show improvements in both computational complexity and recognition accuracy. Full article
(This article belongs to the Section Physical Sensors)
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Open AccessArticle Characteristics of the Fiber Laser Sensor System Based on Etched-Bragg Grating Sensing Probe for Determination of the Low Nitrate Concentration in Water
Sensors 2017, 17(1), 7; doi:10.3390/s17010007
Received: 18 October 2016 / Revised: 29 November 2016 / Accepted: 20 December 2016 / Published: 22 December 2016
Cited by 2 | PDF Full-text (2373 KB) | HTML Full-text | XML Full-text
Abstract
The necessity of environmental protection has stimulated the development of many kinds of methods allowing the determination of different pollutants in the natural environment, including methods for determining nitrate in source water. In this paper, the characteristics of an etched fiber Bragg grating
[...] Read more.
The necessity of environmental protection has stimulated the development of many kinds of methods allowing the determination of different pollutants in the natural environment, including methods for determining nitrate in source water. In this paper, the characteristics of an etched fiber Bragg grating (e-FBG) sensing probe—which integrated in fiber laser structure—are studied by numerical simulation and experiment. The proposed sensor is demonstrated for determination of the low nitrate concentration in a water environment. Experimental results show that this sensor could determine nitrate in water samples at a low concentration range of 0–80 ppm with good repeatability, rapid response, and average sensitivity of 3.5 × 10−3 nm/ppm with the detection limit of 3 ppm. The e-FBG sensing probe integrated in fiber laser demonstrates many advantages, such as a high resolution for wavelength shift identification, high optical signal-to-noise ratio (OSNR of 40 dB), narrow bandwidth of 0.02 nm that enhanced accuracy and precision of wavelength peak measurement, and capability for optical remote sensing. The obtained results suggested that the proposed e-FBG sensor has a large potential for the determination of low nitrate concentrations in water in outdoor field work. Full article
(This article belongs to the Section Physical Sensors)
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Open AccessArticle Small UAS-Based Wind Feature Identification System Part 1: Integration and Validation
Sensors 2017, 17(1), 8; doi:10.3390/s17010008
Received: 31 October 2016 / Revised: 17 December 2016 / Accepted: 19 December 2016 / Published: 23 December 2016
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Abstract
This paper presents a system for identification of wind features, such as gusts and wind shear. These are of particular interest in the context of energy-efficient navigation of Small Unmanned Aerial Systems (UAS). The proposed system generates real-time wind vector estimates and a
[...] Read more.
This paper presents a system for identification of wind features, such as gusts and wind shear. These are of particular interest in the context of energy-efficient navigation of Small Unmanned Aerial Systems (UAS). The proposed system generates real-time wind vector estimates and a novel algorithm to generate wind field predictions. Estimations are based on the integration of an off-the-shelf navigation system and airspeed readings in a so-called direct approach. Wind predictions use atmospheric models to characterize the wind field with different statistical analyses. During the prediction stage, the system is able to incorporate, in a big-data approach, wind measurements from previous flights in order to enhance the approximations. Wind estimates are classified and fitted into a Weibull probability density function. A Genetic Algorithm (GA) is utilized to determine the shaping and scale parameters of the distribution, which are employed to determine the most probable wind speed at a certain position. The system uses this information to characterize a wind shear or a discrete gust and also utilizes a Gaussian Process regression to characterize continuous gusts. The knowledge of the wind features is crucial for computing energy-efficient trajectories with low cost and payload. Therefore, the system provides a solution that does not require any additional sensors. The system architecture presents a modular decentralized approach, in which the main parts of the system are separated in modules and the exchange of information is managed by a communication handler to enhance upgradeability and maintainability. Validation is done providing preliminary results of both simulations and Software-In-The-Loop testing. Telemetry data collected from real flights, performed in the Seville Metropolitan Area in Andalusia (Spain), was used for testing. Results show that wind estimation and predictions can be calculated at 1 Hz and a wind map can be updated at 0.4 Hz . Predictions show a convergence time with a 95% confidence interval of approximately 30 s . Full article
(This article belongs to the Special Issue UAV-Based Remote Sensing)
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Open AccessArticle Energy and Quality Evaluation for Compressive Sensing of Fetal Electrocardiogram Signals
Sensors 2017, 17(1), 9; doi:10.3390/s17010009
Received: 19 October 2016 / Revised: 12 December 2016 / Accepted: 14 December 2016 / Published: 22 December 2016
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Abstract
This manuscript addresses the problem of non-invasive fetal Electrocardiogram (ECG) signal acquisition with low power/low complexity sensors. A sensor architecture using the Compressive Sensing (CS) paradigm is compared to a standard compression scheme using wavelets in terms of energy consumption vs. reconstruction quality,
[...] Read more.
This manuscript addresses the problem of non-invasive fetal Electrocardiogram (ECG) signal acquisition with low power/low complexity sensors. A sensor architecture using the Compressive Sensing (CS) paradigm is compared to a standard compression scheme using wavelets in terms of energy consumption vs. reconstruction quality, and, more importantly, vs. performance of fetal heart beat detection in the reconstructed signals. We show in this paper that a CS scheme based on reconstruction with an over-complete dictionary has similar reconstruction quality to one based on wavelet compression. We also consider, as a more important figure of merit, the accuracy of fetal beat detection after reconstruction as a function of the sensor power consumption. Experimental results with an actual implementation in a commercial device show that CS allows significant reduction of energy consumption in the sensor node, and that the detection performance is comparable to that obtained from original signals for compression ratios up to about 75%. Full article
(This article belongs to the Special Issue Wearable Biomedical Sensors)
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Open AccessArticle Object-Based Paddy Rice Mapping Using HJ-1A/B Data and Temporal Features Extracted from Time Series MODIS NDVI Data
Sensors 2017, 17(1), 10; doi:10.3390/s17010010
Received: 27 October 2016 / Revised: 13 December 2016 / Accepted: 19 December 2016 / Published: 22 December 2016
Cited by 1 | PDF Full-text (12877 KB) | HTML Full-text | XML Full-text
Abstract
Accurate and timely mapping of paddy rice is vital for food security and environmental sustainability. This study evaluates the utility of temporal features extracted from coarse resolution data for object-based paddy rice classification of fine resolution data. The coarse resolution vegetation index data
[...] Read more.
Accurate and timely mapping of paddy rice is vital for food security and environmental sustainability. This study evaluates the utility of temporal features extracted from coarse resolution data for object-based paddy rice classification of fine resolution data. The coarse resolution vegetation index data is first fused with the fine resolution data to generate the time series fine resolution data. Temporal features are extracted from the fused data and added with the multi-spectral data to improve the classification accuracy. Temporal features provided the crop growth information, while multi-spectral data provided the pattern variation of paddy rice. The achieved overall classification accuracy and kappa coefficient were 84.37% and 0.68, respectively. The results indicate that the use of temporal features improved the overall classification accuracy of a single-date multi-spectral image by 18.75% from 65.62% to 84.37%. The minimum sensitivity (MS) of the paddy rice classification has also been improved. The comparison showed that the mapped paddy area was analogous to the agricultural statistics at the district level. This work also highlighted the importance of feature selection to achieve higher classification accuracies. These results demonstrate the potential of the combined use of temporal and spectral features for accurate paddy rice classification. Full article
(This article belongs to the Special Issue Sensors and Smart Sensing of Agricultural Land Systems)
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Open AccessArticle A Multi-Sensor Fusion MAV State Estimation from Long-Range Stereo, IMU, GPS and Barometric Sensors
Sensors 2017, 17(1), 11; doi:10.3390/s17010011
Received: 1 October 2016 / Revised: 10 December 2016 / Accepted: 16 December 2016 / Published: 22 December 2016
Cited by 1 | PDF Full-text (3300 KB) | HTML Full-text | XML Full-text | Supplementary Files
Abstract
State estimation is the most critical capability for MAV (Micro-Aerial Vehicle) localization, autonomous obstacle avoidance, robust flight control and 3D environmental mapping. There are three main challenges for MAV state estimation: (1) it can deal with aggressive 6 DOF (Degree Of Freedom) motion;
[...] Read more.
State estimation is the most critical capability for MAV (Micro-Aerial Vehicle) localization, autonomous obstacle avoidance, robust flight control and 3D environmental mapping. There are three main challenges for MAV state estimation: (1) it can deal with aggressive 6 DOF (Degree Of Freedom) motion; (2) it should be robust to intermittent GPS (Global Positioning System) (even GPS-denied) situations; (3) it should work well both for low- and high-altitude flight. In this paper, we present a state estimation technique by fusing long-range stereo visual odometry, GPS, barometric and IMU (Inertial Measurement Unit) measurements. The new estimation system has two main parts, a stochastic cloning EKF (Extended Kalman Filter) estimator that loosely fuses both absolute state measurements (GPS, barometer) and the relative state measurements (IMU, visual odometry), and is derived and discussed in detail. A long-range stereo visual odometry is proposed for high-altitude MAV odometry calculation by using both multi-view stereo triangulation and a multi-view stereo inverse depth filter. The odometry takes the EKF information (IMU integral) for robust camera pose tracking and image feature matching, and the stereo odometry output serves as the relative measurements for the update of the state estimation. Experimental results on a benchmark dataset and our real flight dataset show the effectiveness of the proposed state estimation system, especially for the aggressive, intermittent GPS and high-altitude MAV flight. Full article
(This article belongs to the Special Issue Vision-Based Sensors in Field Robotics)
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Open AccessArticle An Efficient Wireless Recharging Mechanism for Achieving Perpetual Lifetime of Wireless Sensor Networks
Sensors 2017, 17(1), 13; doi:10.3390/s17010013
Received: 3 October 2016 / Revised: 30 November 2016 / Accepted: 15 December 2016 / Published: 23 December 2016
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Abstract
Energy recharging has received much attention in recent years. Several recharging mechanisms were proposed for achieving perpetual lifetime of a given Wireless Sensor Network (WSN). However, most of them require a mobile recharger to visit each sensor and then perform the recharging task,
[...] Read more.
Energy recharging has received much attention in recent years. Several recharging mechanisms were proposed for achieving perpetual lifetime of a given Wireless Sensor Network (WSN). However, most of them require a mobile recharger to visit each sensor and then perform the recharging task, which increases the length of the recharging path. Another common weakness of these works is the requirement for the mobile recharger to stop at the location of each sensor. As a result, it is impossible for recharger to move with a constant speed, leading to inefficient movement. To improve the recharging efficiency, this paper takes “recharging while moving” into consideration when constructing the recharging path. We propose a Recharging Path Construction (RPC) mechanism, which enables the mobile recharger to recharge all sensors using a constant speed, aiming to minimize the length of recharging path and improve the recharging efficiency while achieving the requirement of perpetual network lifetime of a given WSN. Performance studies reveal that the proposed RPC outperforms existing proposals in terms of path length and energy utilization index, as well as visiting cycle. Full article
(This article belongs to the Section Sensor Networks)
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Open AccessArticle Finite Element Analysis of Single Cell Stiffness Measurements Using PZT-Integrated Buckling Nanoneedles
Sensors 2017, 17(1), 14; doi:10.3390/s17010014
Received: 3 September 2016 / Revised: 26 October 2016 / Accepted: 15 November 2016 / Published: 23 December 2016
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Abstract
This paper proposes a new technique for real-time single cell stiffness measurement using lead zirconate titanate (PZT)-integrated buckling nanoneedles. The PZT and the buckling part of the nanoneedle have been modelled and validated using the ABAQUS software. The two parts are integrated together
[...] Read more.
This paper proposes a new technique for real-time single cell stiffness measurement using lead zirconate titanate (PZT)-integrated buckling nanoneedles. The PZT and the buckling part of the nanoneedle have been modelled and validated using the ABAQUS software. The two parts are integrated together to function as a single unit. After calibration, the stiffness, Young’s modulus, Poisson’s ratio and sensitivity of the PZT-integrated buckling nanoneedle have been determined to be 0.7100 N·m−1, 123.4700 GPa, 0.3000 and 0.0693 V·m·N−1, respectively. Three Saccharomyces cerevisiae cells have been modelled and validated based on compression tests. The average global stiffness and Young’s modulus of the cells are determined to be 10.8867 ± 0.0094 N·m−1 and 110.7033 ± 0.0081 MPa, respectively. The nanoneedle and the cell have been assembled to measure the local stiffness of the single Saccharomyces cerevisiae cells The local stiffness, Young’s modulus and PZT output voltage of the three different size Saccharomyces cerevisiae have been determined at different environmental conditions. We investigated that, at low temperature the stiffness value is low to adapt to the change in the environmental condition. As a result, Saccharomyces cerevisiae becomes vulnerable to viral and bacterial attacks. Therefore, the proposed technique will serve as a quick and accurate process to diagnose diseases at early stage in a cell for effective treatment. Full article
(This article belongs to the Section Biosensors)
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Open AccessArticle High Performance CMOS Light Detector with Dark Current Suppression in Variable-Temperature Systems
Sensors 2017, 17(1), 15; doi:10.3390/s17010015
Received: 26 September 2016 / Revised: 5 December 2016 / Accepted: 9 December 2016 / Published: 23 December 2016
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Abstract
This paper presents a dark current suppression technique for a light detector in a variable-temperature system. The light detector architecture comprises a photodiode for sensing the ambient light, a dark current diode for conducting dark current suppression, and a current subtractor that is
[...] Read more.
This paper presents a dark current suppression technique for a light detector in a variable-temperature system. The light detector architecture comprises a photodiode for sensing the ambient light, a dark current diode for conducting dark current suppression, and a current subtractor that is embedded in the current amplifier with enhanced dark current cancellation. The measured dark current of the proposed light detector is lower than that of the epichlorohydrin photoresistor or cadmium sulphide photoresistor. This is advantageous in variable-temperature systems, especially for those with many infrared light-emitting diodes. Experimental results indicate that the maximum dark current of the proposed current amplifier is approximately 135 nA at 125 °C, a near zero dark current is achieved at temperatures lower than 50 °C, and dark current and temperature exhibit an exponential relation at temperatures higher than 50 °C. The dark current of the proposed light detector is lower than 9.23 nA and the linearity is approximately 1.15 μA/lux at an external resistance RSS = 10 kΩ and environmental temperatures from 25 °C to 85 °C. Full article
(This article belongs to the Section Physical Sensors)
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Open AccessArticle A Circuit-Based Neural Network with Hybrid Learning of Backpropagation and Random Weight Change Algorithms
Sensors 2017, 17(1), 16; doi:10.3390/s17010016
Received: 29 September 2016 / Revised: 9 December 2016 / Accepted: 19 December 2016 / Published: 23 December 2016
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Abstract
A hybrid learning method of a software-based backpropagation learning and a hardware-based RWC learning is proposed for the development of circuit-based neural networks. The backpropagation is known as one of the most efficient learning algorithms. A weak point is that its hardware implementation
[...] Read more.
A hybrid learning method of a software-based backpropagation learning and a hardware-based RWC learning is proposed for the development of circuit-based neural networks. The backpropagation is known as one of the most efficient learning algorithms. A weak point is that its hardware implementation is extremely difficult. The RWC algorithm, which is very easy to implement with respect to its hardware circuits, takes too many iterations for learning. The proposed learning algorithm is a hybrid one of these two. The main learning is performed with a software version of the BP algorithm, firstly, and then, learned weights are transplanted on a hardware version of a neural circuit. At the time of the weight transplantation, a significant amount of output error would occur due to the characteristic difference between the software and the hardware. In the proposed method, such error is reduced via a complementary learning of the RWC algorithm, which is implemented in a simple hardware. The usefulness of the proposed hybrid learning system is verified via simulations upon several classical learning problems. Full article
(This article belongs to the Section Sensor Networks)
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Open AccessArticle Nanostructured Tip-Shaped Biosensors: Application of Six Sigma Approach for Enhanced Manufacturing
Sensors 2017, 17(1), 17; doi:10.3390/s17010017
Received: 30 September 2016 / Revised: 10 December 2016 / Accepted: 20 December 2016 / Published: 23 December 2016
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Abstract
Nanostructured tip-shaped biosensors have drawn attention for biomolecule detection as they are promising for highly sensitive and specific detection of a target analyte. Using a nanostructured tip, the sensitivity is increased to identify individual molecules because of the high aspect ratio structure. Various
[...] Read more.
Nanostructured tip-shaped biosensors have drawn attention for biomolecule detection as they are promising for highly sensitive and specific detection of a target analyte. Using a nanostructured tip, the sensitivity is increased to identify individual molecules because of the high aspect ratio structure. Various detection methods, such as electrochemistry, fluorescence microcopy, and Raman spectroscopy, have been attempted to enhance the sensitivity and the specificity. Due to the confined path of electrons, electrochemical measurement using a nanotip enables the detection of single molecules. When an electric field is combined with capillary action and fluid flow, target molecules can be effectively concentrated onto a nanotip surface for detection. To enhance the concentration efficacy, a dendritic nanotip rather than a single tip could be used to detect target analytes, such as nanoparticles, cells, and DNA. However, reproducible fabrication with relation to specific detection remains a challenge due to the instability of a manufacturing method, resulting in inconsistent shape. In this paper, nanostructured biosensors are reviewed with our experimental results using dendritic nanotips for sequence specific detection of DNA. By the aid of the Six Sigma approach, the fabrication yield of dendritic nanotips increases from 20.0% to 86.6%. Using the nanotips, DNA is concentrated and detected in a sequence specific way with the detection limit equivalent to 1000 CFU/mL. The pros and cons of a nanotip biosensor are evaluated in conjunction with future prospects. Full article
(This article belongs to the Special Issue Nanobiosensing for Sensors)
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Open AccessArticle A Machine Learning Approach to Pedestrian Detection for Autonomous Vehicles Using High-Definition 3D Range Data
Sensors 2017, 17(1), 18; doi:10.3390/s17010018
Received: 31 October 2016 / Revised: 11 December 2016 / Accepted: 15 December 2016 / Published: 23 December 2016
Cited by 3 | PDF Full-text (12514 KB) | HTML Full-text | XML Full-text
Abstract
This article describes an automated sensor-based system to detect pedestrians in an autonomous vehicle application. Although the vehicle is equipped with a broad set of sensors, the article focuses on the processing of the information generated by a Velodyne HDL-64E LIDAR sensor. The
[...] Read more.
This article describes an automated sensor-based system to detect pedestrians in an autonomous vehicle application. Although the vehicle is equipped with a broad set of sensors, the article focuses on the processing of the information generated by a Velodyne HDL-64E LIDAR sensor. The cloud of points generated by the sensor (more than 1 million points per revolution) is processed to detect pedestrians, by selecting cubic shapes and applying machine vision and machine learning algorithms to the XY, XZ, and YZ projections of the points contained in the cube. The work relates an exhaustive analysis of the performance of three different machine learning algorithms: k-Nearest Neighbours (kNN), Naïve Bayes classifier (NBC), and Support Vector Machine (SVM). These algorithms have been trained with 1931 samples. The final performance of the method, measured a real traffic scenery, which contained 16 pedestrians and 469 samples of non-pedestrians, shows sensitivity (81.2%), accuracy (96.2%) and specificity (96.8%). Full article
(This article belongs to the Special Issue Sensors for Autonomous Road Vehicles)
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Open AccessArticle A Formal Methodology to Design and Deploy Dependable Wireless Sensor Networks
Sensors 2017, 17(1), 19; doi:10.3390/s17010019
Received: 10 August 2016 / Revised: 9 December 2016 / Accepted: 14 December 2016 / Published: 23 December 2016
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Abstract
Wireless Sensor Networks (WSNs) are being increasingly adopted in critical applications, where verifying the correct operation of sensor nodes is a major concern. Undesired events may undermine the mission of the WSNs. Hence, their effects need to be properly assessed before deployment, to
[...] Read more.
Wireless Sensor Networks (WSNs) are being increasingly adopted in critical applications, where verifying the correct operation of sensor nodes is a major concern. Undesired events may undermine the mission of the WSNs. Hence, their effects need to be properly assessed before deployment, to obtain a good level of expected performance; and during the operation, in order to avoid dangerous unexpected results. In this paper, we propose a methodology that aims at assessing and improving the dependability level of WSNs by means of an event-based formal verification technique. The methodology includes a process to guide designers towards the realization of a dependable WSN and a tool (“ADVISES”) to simplify its adoption. The tool is applicable to homogeneous WSNs with static routing topologies. It allows the automatic generation of formal specifications used to check correctness properties and evaluate dependability metrics at design time and at runtime for WSNs where an acceptable percentage of faults can be defined. During the runtime, we can check the behavior of the WSN accordingly to the results obtained at design time and we can detect sudden and unexpected failures, in order to trigger recovery procedures. The effectiveness of the methodology is shown in the context of two case studies, as proof-of-concept, aiming to illustrate how the tool is helpful to drive design choices and to check the correctness properties of the WSN at runtime. Although the method scales up to very large WSNs, the applicability of the methodology may be compromised by the state space explosion of the reasoning model, which must be faced by partitioning large topologies into sub-topologies. Full article
(This article belongs to the Section Sensor Networks)
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Open AccessArticle Simultaneous Moisture Content and Mass Flow Measurements in Wood Chip Flows Using Coupled Dielectric and Impact Sensors
Sensors 2017, 17(1), 20; doi:10.3390/s17010020
Received: 30 October 2016 / Revised: 16 December 2016 / Accepted: 20 December 2016 / Published: 23 December 2016
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Abstract
An 8-electrode capacitance tomography (ECT) sensor was built and used to measure moisture content (MC) and mass flow of pine chip flows. The device was capable of directly measuring total water quantity in a sample but was sensitive to both dry matter and
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An 8-electrode capacitance tomography (ECT) sensor was built and used to measure moisture content (MC) and mass flow of pine chip flows. The device was capable of directly measuring total water quantity in a sample but was sensitive to both dry matter and moisture, and therefore required a second measurement of mass flow to calculate MC. Two means of calculating the mass flow were used: the first being an impact sensor to measure total mass flow, and the second a volumetric approach based on measuring total area occupied by wood in images generated using the capacitance sensor’s tomographic mode. Tests were made on 109 groups of wood chips ranging in moisture content from 14% to 120% (dry basis) and wet weight of 280 to 1100 g. Sixty groups were randomly selected as a calibration set, and the remaining were used for validation of the sensor’s performance. For the combined capacitance/force transducer system, root mean square errors of prediction (RMSEP) for wet mass flow and moisture content were 13.42% and 16.61%, respectively. RMSEP using the combined volumetric mass flow/capacitance sensor for dry mass flow and moisture content were 22.89% and 24.16%, respectively. Either of the approaches was concluded to be feasible for prediction of moisture content in pine chip flows, but combining the impact and capacitance sensors was easier to implement. In situations where flows could not be impeded, however, the tomographic approach would likely be more useful. Full article
(This article belongs to the collection Sensors in Agriculture and Forestry)
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Open AccessArticle A Novel Controller Design for the Next Generation Space Electrostatic Accelerometer Based on Disturbance Observation and Rejection
Sensors 2017, 17(1), 21; doi:10.3390/s17010021
Received: 1 November 2016 / Revised: 12 December 2016 / Accepted: 20 December 2016 / Published: 23 December 2016
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Abstract
The state-of-the-art accelerometer technology has been widely applied in space missions. The performance of the next generation accelerometer in future geodesic satellites is pushed to 8×1013m/s2/Hz1/2, which is
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The state-of-the-art accelerometer technology has been widely applied in space missions. The performance of the next generation accelerometer in future geodesic satellites is pushed to 8 × 10 13 m / s 2 / H z 1 / 2 , which is close to the hardware fundamental limit. According to the instrument noise budget, the geodesic test mass must be kept in the center of the accelerometer within the bounds of 56 pm / Hz 1 / 2 by the feedback controller. The unprecedented control requirements and necessity for the integration of calibration functions calls for a new type of control scheme with more flexibility and robustness. A novel digital controller design for the next generation electrostatic accelerometers based on disturbance observation and rejection with the well-studied Embedded Model Control (EMC) methodology is presented. The parameters are optimized automatically using a non-smooth optimization toolbox and setting a weighted H-infinity norm as the target. The precise frequency performance requirement of the accelerometer is well met during the batch auto-tuning, and a series of controllers for multiple working modes is generated. Simulation results show that the novel controller could obtain not only better disturbance rejection performance than the traditional Proportional Integral Derivative (PID) controllers, but also new instrument functions, including: easier tuning procedure, separation of measurement and control bandwidth and smooth control parameter switching. Full article
(This article belongs to the Section Physical Sensors)
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Open AccessArticle Robust Functionalization of Large Microelectrode Arrays by Using Pulsed Potentiostatic Deposition
Sensors 2017, 17(1), 22; doi:10.3390/s17010022
Received: 31 October 2016 / Revised: 13 December 2016 / Accepted: 21 December 2016 / Published: 23 December 2016
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Abstract
Surface modification of microelectrodes is a central step in the development of microsensors and microsensor arrays. Here, we present an electrodeposition scheme based on voltage pulses. Key features of this method are uniformity in the deposited electrode coatings, flexibility in the overall deposition
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Surface modification of microelectrodes is a central step in the development of microsensors and microsensor arrays. Here, we present an electrodeposition scheme based on voltage pulses. Key features of this method are uniformity in the deposited electrode coatings, flexibility in the overall deposition area, i.e., the sizes and number of the electrodes to be coated, and precise control of the surface texture. Deposition and characterization of four different materials are demonstrated, including layers of high-surface-area platinum, gold, conducting polymer poly(ethylenedioxythiophene), also known as PEDOT, and the non-conducting polymer poly(phenylenediamine), also known as PPD. The depositions were conducted using a fully integrated complementary metal-oxide-semiconductor (CMOS) chip with an array of 1024 microelectrodes. The pulsed potentiostatic deposition scheme is particularly suitable for functionalization of individual electrodes or electrode subsets of large integrated microelectrode arrays: the required deposition waveforms are readily available in an integrated system, the same deposition parameters can be used to functionalize the surface of either single electrodes or large arrays of thousands of electrodes, and the deposition method proved to be robust and reproducible for all materials tested. Full article
(This article belongs to the Special Issue Integrated Sensor Arrays and Array Signal Processing)
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Open AccessArticle Experimental Investigations of a Precision Sensor for an Automatic Weapons Stabilizer System
Sensors 2017, 17(1), 23; doi:10.3390/s17010023
Received: 2 September 2016 / Revised: 21 November 2016 / Accepted: 13 December 2016 / Published: 24 December 2016
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Abstract
This paper presents the results of experimental investigations of a precision sensor for an automatic weapons stabilizer system. It also describes the experimental equipment used and the structure of the developed sensor. A weapons stabilizer is designed for automatic guidance of an armament
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This paper presents the results of experimental investigations of a precision sensor for an automatic weapons stabilizer system. It also describes the experimental equipment used and the structure of the developed sensor. A weapons stabilizer is designed for automatic guidance of an armament unit in the horizontal and vertical planes when firing at ground and air targets that are quickly maneuvering, and at lower speeds when firing anti-tank missiles, as well as the bypass of construction elements by the armament unit, and the automatic tracking of moving targets when interacting with a fire control system. The results of experimental investigations have shown that the error of the precision sensor developed on the basis of a piezoelectric element is 6 × 10−10 m/s2 under quasi-static conditions, and ~10−5 m/s2 for mobile use. This paper defines metrological and calibration properties of the developed sensor. Full article
(This article belongs to the Section Physical Sensors)
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Open AccessArticle Optical Gas Sensing of Ammonia and Amines Based on Protonated Porphyrin/TiO2 Composite Thin Films
Sensors 2017, 17(1), 24; doi:10.3390/s17010024
Received: 15 November 2016 / Revised: 14 December 2016 / Accepted: 20 December 2016 / Published: 23 December 2016
Cited by 1 | PDF Full-text (3638 KB) | HTML Full-text | XML Full-text | Supplementary Files
Abstract
Open porous and transparent microcolumnar structures of TiO2 prepared by physical vapour deposition in glancing angle configuration (GLAD-PVD) have been used as host matrices for two different fluorescent cationic porphyrins, 5-(N-methyl 4-pyridyl)-10,15,20-triphenyl porphine chloride (MMPyP) and meso-tetra (N-methyl
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Open porous and transparent microcolumnar structures of TiO2 prepared by physical vapour deposition in glancing angle configuration (GLAD-PVD) have been used as host matrices for two different fluorescent cationic porphyrins, 5-(N-methyl 4-pyridyl)-10,15,20-triphenyl porphine chloride (MMPyP) and meso-tetra (N-methyl 4-pyridyl) porphine tetrachloride (TMPyP). The porphyrins have been anchored by electrostatic interactions to the microcolumns by self-assembly through the dip-coating method. These porphyrin/TiO2 composites have been used as gas sensors for ammonia and amines through previous protonation of the porphyrin with HCl followed by subsequent exposure to the basic analyte. UV–vis absorption, emission, and time-resolved spectroscopies have been used to confirm the protonation–deprotonation of the two porphyrins and to follow their spectral changes in the presence of the analytes. The monocationic porphyrin has been found to be more sensible (up to 10 times) than its tetracationic counterpart. This result has been attributed to the different anchoring arrangements of the two porphyrins to the TiO2 surface and their different states of aggregation within the film. Finally, there was an observed decrease of the emission fluorescence intensity in consecutive cycles of exposure and recovery due to the formation of ammonium chloride inside the film. Full article
(This article belongs to the Section Chemical Sensors)
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Open AccessArticle Compound Event Barrier Coverage in Wireless Sensor Networks under Multi-Constraint Conditions
Sensors 2017, 17(1), 25; doi:10.3390/s17010025
Received: 2 November 2016 / Revised: 12 December 2016 / Accepted: 20 December 2016 / Published: 24 December 2016
Cited by 2 | PDF Full-text (1277 KB) | HTML Full-text | XML Full-text
Abstract
It is important to monitor compound event by barrier coverage issues in wireless sensor networks (WSNs). Compound event barrier coverage (CEBC) is a novel coverage problem. Unlike traditional ones, the data of compound event barrier coverage comes from different types of sensors. It
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It is important to monitor compound event by barrier coverage issues in wireless sensor networks (WSNs). Compound event barrier coverage (CEBC) is a novel coverage problem. Unlike traditional ones, the data of compound event barrier coverage comes from different types of sensors. It will be subject to multiple constraints under complex conditions in real-world applications. The main objective of this paper is to design an efficient algorithm for complex conditions that can combine the compound event confidence. Moreover, a multiplier method based on an active-set strategy (ASMP) is proposed to optimize the multiple constraints in compound event barrier coverage. The algorithm can calculate the coverage ratio efficiently and allocate the sensor resources reasonably in compound event barrier coverage. The proposed algorithm can simplify complex problems to reduce the computational load of the network and improve the network efficiency. The simulation results demonstrate that the proposed algorithm is more effective and efficient than existing methods, especially in the allocation of sensor resources. Full article
(This article belongs to the Special Issue Sensors for Home Automation and Security)
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Open AccessArticle Change Analysis in Structural Laser Scanning Point Clouds: The Baseline Method
Sensors 2017, 17(1), 26; doi:10.3390/s17010026
Received: 13 August 2016 / Revised: 6 December 2016 / Accepted: 16 December 2016 / Published: 24 December 2016
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Abstract
A method is introduced for detecting changes from point clouds that avoids registration. For many applications, changes are detected between two scans of the same scene obtained at different times. Traditionally, these scans are aligned to a common coordinate system having the disadvantage
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A method is introduced for detecting changes from point clouds that avoids registration. For many applications, changes are detected between two scans of the same scene obtained at different times. Traditionally, these scans are aligned to a common coordinate system having the disadvantage that this registration step introduces additional errors. In addition, registration requires stable targets or features. To avoid these issues, we propose a change detection method based on so-called baselines. Baselines connect feature points within one scan. To analyze changes, baselines connecting corresponding points in two scans are compared. As feature points either targets or virtual points corresponding to some reconstructable feature in the scene are used. The new method is implemented on two scans sampling a masonry laboratory building before and after seismic testing, that resulted in damages in the order of several centimeters. The centres of the bricks of the laboratory building are automatically extracted to serve as virtual points. Baselines connecting virtual points and/or target points are extracted and compared with respect to a suitable structural coordinate system. Changes detected from the baseline analysis are compared to a traditional cloud to cloud change analysis demonstrating the potential of the new method for structural analysis. Full article
(This article belongs to the Section Remote Sensors)
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Open AccessArticle Node Redeployment Algorithm Based on Stratified Connected Tree for Underwater Sensor Networks
Sensors 2017, 17(1), 27; doi:10.3390/s17010027
Received: 16 August 2016 / Revised: 19 December 2016 / Accepted: 20 December 2016 / Published: 24 December 2016
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Abstract
During the underwater sensor networks (UWSNs) operation, node drift with water environment causes network topology changes. Periodic node location examination and adjustment are needed to maintain good network monitoring quality as long as possible. In this paper, a node redeployment algorithm based on
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During the underwater sensor networks (UWSNs) operation, node drift with water environment causes network topology changes. Periodic node location examination and adjustment are needed to maintain good network monitoring quality as long as possible. In this paper, a node redeployment algorithm based on stratified connected tree for UWSNs is proposed. At every network adjustment moment, self-examination and adjustment on node locations are performed firstly. If a node is outside the monitored space, it returns to the last location recorded in its memory along straight line. Later, the network topology is stratified into a connected tree that takes the sink node as the root node by broadcasting ready information level by level, which can improve the network connectivity rate. Finally, with synthetically considering network coverage and connectivity rates, and node movement distance, the sink node performs centralized optimization on locations of leaf nodes in the stratified connected tree. Simulation results show that the proposed redeployment algorithm can not only keep the number of nodes in the monitored space as much as possible and maintain good network coverage and connectivity rates during network operation, but also reduce node movement distance during node redeployment and prolong the network lifetime. Full article
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Open AccessArticle Reverse Engineering and Security Evaluation of Commercial Tags for RFID-Based IoT Applications
Sensors 2017, 17(1), 28; doi:10.3390/s17010028
Received: 20 October 2016 / Revised: 28 November 2016 / Accepted: 20 December 2016 / Published: 24 December 2016
Cited by 6 | PDF Full-text (12174 KB) | HTML Full-text | XML Full-text
Abstract
The Internet of Things (IoT) is a distributed system of physical objects that requires the seamless integration of hardware (e.g., sensors, actuators, electronics) and network communications in order to collect and exchange data. IoT smart objects need to be somehow identified to determine
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The Internet of Things (IoT) is a distributed system of physical objects that requires the seamless integration of hardware (e.g., sensors, actuators, electronics) and network communications in order to collect and exchange data. IoT smart objects need to be somehow identified to determine the origin of the data and to automatically detect the elements around us. One of the best positioned technologies to perform identification is RFID (Radio Frequency Identification), which in the last years has gained a lot of popularity in applications like access control, payment cards or logistics. Despite its popularity, RFID security has not been properly handled in numerous applications. To foster security in such applications, this article includes three main contributions. First, in order to establish the basics, a detailed review of the most common flaws found in RFID-based IoT systems is provided, including the latest attacks described in the literature. Second, a novel methodology that eases the detection and mitigation of such flaws is presented. Third, the latest RFID security tools are analyzed and the methodology proposed is applied through one of them (Proxmark 3) to validate it. Thus, the methodology is tested in different scenarios where tags are commonly used for identification. In such systems it was possible to clone transponders, extract information, and even emulate both tags and readers. Therefore, it is shown that the methodology proposed is useful for auditing security and reverse engineering RFID communications in IoT applications. It must be noted that, although this paper is aimed at fostering RFID communications security in IoT applications, the methodology can be applied to any RFID communications protocol. Full article
(This article belongs to the Special Issue New Generation Sensors Enabling and Fostering IoT)
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Open AccessArticle A Visual Analytics Approach for Station-Based Air Quality Data
Sensors 2017, 17(1), 30; doi:10.3390/s17010030
Received: 29 September 2016 / Revised: 2 December 2016 / Accepted: 12 December 2016 / Published: 24 December 2016
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Abstract
With the deployment of multi-modality and large-scale sensor networks for monitoring air quality, we are now able to collect large and multi-dimensional spatio-temporal datasets. For these sensed data, we present a comprehensive visual analysis approach for air quality analysis. This approach integrates several
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With the deployment of multi-modality and large-scale sensor networks for monitoring air quality, we are now able to collect large and multi-dimensional spatio-temporal datasets. For these sensed data, we present a comprehensive visual analysis approach for air quality analysis. This approach integrates several visual methods, such as map-based views, calendar views, and trends views, to assist the analysis. Among those visual methods, map-based visual methods are used to display the locations of interest, and the calendar and the trends views are used to discover the linear and periodical patterns. The system also provides various interaction tools to combine the map-based visualization, trends view, calendar view and multi-dimensional view. In addition, we propose a self-adaptive calendar-based controller that can flexibly adapt the changes of data size and granularity in trends view. Such a visual analytics system would facilitate big-data analysis in real applications, especially for decision making support. Full article
(This article belongs to the Special Issue Big Data and Cloud Computing for Sensor Networks)
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Open AccessArticle A Canopy Density Model for Planar Orchard Target Detection Based on Ultrasonic Sensors
Sensors 2017, 17(1), 31; doi:10.3390/s17010031
Received: 30 October 2016 / Revised: 18 December 2016 / Accepted: 21 December 2016 / Published: 24 December 2016
Cited by 1 | PDF Full-text (4732 KB) | HTML Full-text | XML Full-text | Supplementary Files
Abstract
Orchard target-oriented variable rate spraying is an effective method to reduce pesticide drift and excessive residues. To accomplish this task, the orchard targets’ characteristic information is needed to control liquid flow rate and airflow rate. One of the most important characteristics is the
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Orchard target-oriented variable rate spraying is an effective method to reduce pesticide drift and excessive residues. To accomplish this task, the orchard targets’ characteristic information is needed to control liquid flow rate and airflow rate. One of the most important characteristics is the canopy density. In order to establish the canopy density model for a planar orchard target which is indispensable for canopy density calculation, a target density detection testing system was developed based on an ultrasonic sensor. A time-domain energy analysis method was employed to analyze the ultrasonic signal. Orthogonal regression central composite experiments were designed and conducted using man-made canopies of known density with three or four layers of leaves. Two model equations were obtained, of which the model for the canopies with four layers was found to be the most reliable. A verification test was conducted with different layers at the same density values and detecting distances. The test results showed that the relative errors of model density values and actual values of five, four, three and two layers of leaves were acceptable, while the maximum relative errors were 17.68%, 25.64%, 21.33% and 29.92%, respectively. It also suggested the model equation with four layers had a good applicability with different layers which increased with adjacent layers. Full article
(This article belongs to the Special Issue Ultrasonic Sensors)
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Open AccessArticle Network Allocation Vector (NAV) Optimization for Underwater Handshaking-Based Protocols
Sensors 2017, 17(1), 32; doi:10.3390/s17010032
Received: 6 October 2016 / Revised: 14 December 2016 / Accepted: 15 December 2016 / Published: 24 December 2016
Cited by 1 | PDF Full-text (2540 KB) | HTML Full-text | XML Full-text
Abstract
In this paper, we obtained the optimized network allocation vector (NAV) for underwater handshaking-based protocols, as inefficient determination of the NAV leads to unnecessarily long silent periods. We propose a scheme which determines the NAV by taking into account all possible propagation delays:
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In this paper, we obtained the optimized network allocation vector (NAV) for underwater handshaking-based protocols, as inefficient determination of the NAV leads to unnecessarily long silent periods. We propose a scheme which determines the NAV by taking into account all possible propagation delays: propagation delay between a source and a destination; propagation delay between a source and the neighbors; and propagation delay between a destination and the neighbors. Such an approach effectively allows the NAV to be determined precisely equal to duration of a busy channel, and the silent period can be set commensurate to that duration. This allows for improvements in the performance of handshaking-based protocols, such as the carrier sense multiple access/collision avoidance (CSMA/CA) protocol, in terms of throughput and fairness. To evaluate the performance of the proposed scheme, performance comparisons were carried out through simulations with prior NAV setting methods. The simulation results show that the proposed scheme outperforms the other schemes in terms of throughput and fairness. Full article
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Open AccessArticle Real-Time Multi-Target Localization from Unmanned Aerial Vehicles
Sensors 2017, 17(1), 33; doi:10.3390/s17010033
Received: 3 September 2016 / Revised: 14 December 2016 / Accepted: 19 December 2016 / Published: 25 December 2016
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Abstract
In order to improve the reconnaissance efficiency of unmanned aerial vehicle (UAV) electro-optical stabilized imaging systems, a real-time multi-target localization scheme based on an UAV electro-optical stabilized imaging system is proposed. First, a target location model is studied. Then, the geodetic coordinates of
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In order to improve the reconnaissance efficiency of unmanned aerial vehicle (UAV) electro-optical stabilized imaging systems, a real-time multi-target localization scheme based on an UAV electro-optical stabilized imaging system is proposed. First, a target location model is studied. Then, the geodetic coordinates of multi-targets are calculated using the homogeneous coordinate transformation. On the basis of this, two methods which can improve the accuracy of the multi-target localization are proposed: (1) the real-time zoom lens distortion correction method; (2) a recursive least squares (RLS) filtering method based on UAV dead reckoning. The multi-target localization error model is established using Monte Carlo theory. In an actual flight, the UAV flight altitude is 1140 m. The multi-target localization results are within the range of allowable error. After we use a lens distortion correction method in a single image, the circular error probability (CEP) of the multi-target localization is reduced by 7%, and 50 targets can be located at the same time. The RLS algorithm can adaptively estimate the location data based on multiple images. Compared with multi-target localization based on a single image, CEP of the multi-target localization using RLS is reduced by 25%. The proposed method can be implemented on a small circuit board to operate in real time. This research is expected to significantly benefit small UAVs which need multi-target geo-location functions. Full article
(This article belongs to the Special Issue UAV-Based Remote Sensing)
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Open AccessArticle Organophosphorous Pesticide Detection in Olive Oil by Using a Miniaturized, Easy-to-Use, and Cost-Effective Biosensor Combined with QuEChERS for Sample Clean-Up
Sensors 2017, 17(1), 34; doi:10.3390/s17010034
Received: 4 November 2016 / Revised: 13 December 2016 / Accepted: 20 December 2016 / Published: 24 December 2016
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Abstract
Herein, we report a portable electrochemical biosensor based on butyrylcholinesterase (BChE) immobilized on carbon black (CB)-modified screen-printed electrodes (SPEs) for the detection of organophosphorous pesticides in olive oil. The BChE/CB-SPE biosensor was developed to detect paraoxon in standard solutions as well as in
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Herein, we report a portable electrochemical biosensor based on butyrylcholinesterase (BChE) immobilized on carbon black (CB)-modified screen-printed electrodes (SPEs) for the detection of organophosphorous pesticides in olive oil. The BChE/CB-SPE biosensor was developed to detect paraoxon in standard solutions as well as in olive oil samples previously treated with the QuEChERS method to extract pesticides from the whole fatty matrix. The biosensor shows a linear concentration range of between 20 and 100 ppb for paraoxon both in standard solutions (phosphate buffer 0.05 M) and in olive oil extracts, with a detection limit of 6 ppb in olive oil extract, corresponding to 10% of inhibition. The accuracy of this biosensor in olive oil samples was assessed with olive oil spiked with paraoxon, obtaining satisfactory recovery values. Full article
(This article belongs to the Special Issue Recent Advances in Biosensors Based Screen Printed Platforms)
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Open AccessArticle A Cu2+-Selective Probe Based on Phenanthro-Imidazole Derivative
Sensors 2017, 17(1), 35; doi:10.3390/s17010035
Received: 21 October 2016 / Revised: 20 December 2016 / Accepted: 21 December 2016 / Published: 24 December 2016
Cited by 1 | PDF Full-text (823 KB) | HTML Full-text | XML Full-text | Supplementary Files
Abstract
A novel fluorescent Probe 1, based on phenanthro-imidazole has been developed as an efficient chemosensor for the trace detection of copper ions (Cu2+). Probe 1 demonstrated sensitive fluorescence quenching upon binding with Cu2+ through 1:1 stoichiometric chelation. The detection
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A novel fluorescent Probe 1, based on phenanthro-imidazole has been developed as an efficient chemosensor for the trace detection of copper ions (Cu2+). Probe 1 demonstrated sensitive fluorescence quenching upon binding with Cu2+ through 1:1 stoichiometric chelation. The detection limit for Cu2+ ions was projected through linear quenching fitting to be as low as 2.77 × 10−8 M (or 1.77 ppb). The sensing response was highly selective towards Cu2+ with minimal influence from other common metal ions, facilitating the practical application of Probe 1 in trace detection. Full article
(This article belongs to the Special Issue Colorimetric and Fluorescent Sensor)
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Open AccessArticle An Indoor Positioning System Based on Wearables for Ambient-Assisted Living
Sensors 2017, 17(1), 36; doi:10.3390/s17010036
Received: 18 November 2016 / Revised: 21 December 2016 / Accepted: 21 December 2016 / Published: 25 December 2016
Cited by 3 | PDF Full-text (1518 KB) | HTML Full-text | XML Full-text
Abstract
The urban population is growing at such a rate that by 2050 it is estimated that 84% of the world’s population will live in cities, with flats being the most common living place. Moreover, WiFi technology is present in most developed country urban
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The urban population is growing at such a rate that by 2050 it is estimated that 84% of the world’s population will live in cities, with flats being the most common living place. Moreover, WiFi technology is present in most developed country urban areas, with a quick growth in developing countries. New Ambient-Assisted Living applications will be developed in the near future having user positioning as ground technology: elderly tele-care, energy consumption, security and the like are strongly based on indoor positioning information. We present an Indoor Positioning System for wearable devices based on WiFi fingerprinting. Smart-watch wearable devices are used to acquire the WiFi strength signals of the surrounding Wireless Access Points used to build an ensemble of Machine Learning classification algorithms. Once built, the ensemble algorithm is used to locate a user based on the WiFi strength signals provided by the wearable device. Experimental results for five different urban flats are reported, showing that the system is robust and reliable enough for locating a user at room level into his/her home. Another interesting characteristic of the presented system is that it does not require deployment of any infrastructure, and it is unobtrusive, the only device required for it to work is a smart-watch. Full article
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Open AccessArticle Enhancement of Fluorescence-Based Sandwich Immunoassay Using Multilayered Microplates Modified with Plasma-Polymerized Films
Sensors 2017, 17(1), 37; doi:10.3390/s17010037
Received: 29 November 2016 / Revised: 21 December 2016 / Accepted: 22 December 2016 / Published: 25 December 2016
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Abstract
A functional modification of the surface of a 96-well microplate coupled with a thin layer deposition technique is demonstrated for enhanced fluorescence-based sandwich immunoassays. The plasma polymerization technique enabling the deposition of organic thin films was employed for the modification of the well
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A functional modification of the surface of a 96-well microplate coupled with a thin layer deposition technique is demonstrated for enhanced fluorescence-based sandwich immunoassays. The plasma polymerization technique enabling the deposition of organic thin films was employed for the modification of the well surface of a microplate. A silver layer and a plasma-polymerized film were consecutively deposited on the microplate as a metal mirror and the optical interference layer, respectively. When Cy3-labeled antibody was applied to the wells of the resulting multilayered microplate without any immobilization step, greatly enhanced fluorescence was observed compared with that obtained with the unmodified one. The same effect could be also exhibited for an immunoassay targeting antigen directly adsorbed on the multilayered microplate. Furthermore, a sandwich immunoassay for the detection of interleukin 2 (IL-2) was performed with the multilayered microplates, resulting in specific and 88-fold–enhanced fluorescence detection. Full article
(This article belongs to the Special Issue Colorimetric and Fluorescent Sensor)
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Open AccessArticle Fiber-Optic Fabry-Pérot Interferometers for Axial Force Sensing on the Tip of a Needle
Sensors 2017, 17(1), 38; doi:10.3390/s17010038
Received: 11 November 2016 / Revised: 20 December 2016 / Accepted: 21 December 2016 / Published: 26 December 2016
PDF Full-text (6587 KB) | HTML Full-text | XML Full-text
Abstract
A range of complex percutaneous procedures, such as biopsy or regional anesthesia, rely heavily on accurate needle insertion. Small variations in the mechanical properties of the pierced tissue can however cause deviations from the projected needle path and can thus result in inaccurate
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A range of complex percutaneous procedures, such as biopsy or regional anesthesia, rely heavily on accurate needle insertion. Small variations in the mechanical properties of the pierced tissue can however cause deviations from the projected needle path and can thus result in inaccurate placement of the needle. Navigation of a rigid needle towards the target tissue is traditionally based on the surgeons capacity to interpret small variations in the needle insertion force. A more accurate measurement of these small force variations enables improvement in needle targeting, can potentially aid in enhancing force feedback in robotic needle placement and can provide valuable information on tissue-tool interaction. In this study we investigated several concepts for the design of a force sensor based on a fiber-optic Fabry-Pérot interferometer to measure needle-tissue interaction forces on the tip of a 18 G needle, where special attention was given to concepts for a sensor with (1), an intrinsic low cross-sensitivity to temperature and (2), elementary design and fabrication. Three concepts, using either a quartz capillary, an Invar capillary or a thin polyimide film as the force sensitive element were prototyped and subjected to both static and dynamic testing. The force transducer based on a quartz capillary presented the lowest cross-sensitivity to temperature ( 12 m N / C) and good accuracy (maximum measurement error of 65 m N /10 N ) in a measurement of static forces. However, limited strength of the sensor is expected to prevent usage of the quartz capillary in small diameter needles. The concepts for a sensor based on an Invar capillary or a thin polyimide film proved a higher cross-sensitivity to temperature ( 50 m N / C and 220 m N / C, respectively) and higher maximum measurement error (350 m N /10 N , 800 m N /10 N ), comparable to those of FBG-based sensors reported in literature, but are likely to be more suitable for integration in very small biopsy needles. Full article
(This article belongs to the Section Physical Sensors)
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Open AccessArticle Threshold-Based Random Charging Scheme for Decentralized PEV Charging Operation in a Smart Grid
Sensors 2017, 17(1), 39; doi:10.3390/s17010039
Received: 22 September 2016 / Revised: 15 December 2016 / Accepted: 20 December 2016 / Published: 26 December 2016
PDF Full-text (1423 KB) | HTML Full-text | XML Full-text
Abstract
Smart grids have been introduced to replace conventional power distribution systems without real time monitoring for accommodating the future market penetration of plug-in electric vehicles (PEVs). When a large number of PEVs require simultaneous battery charging, charging coordination techniques have become one of
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Smart grids have been introduced to replace conventional power distribution systems without real time monitoring for accommodating the future market penetration of plug-in electric vehicles (PEVs). When a large number of PEVs require simultaneous battery charging, charging coordination techniques have become one of the most critical factors to optimize the PEV charging performance and the conventional distribution system. In this case, considerable computational complexity of a central controller and exchange of real time information among PEVs may occur. To alleviate these problems, a novel threshold-based random charging (TBRC) operation for a decentralized charging system is proposed. Using PEV charging thresholds and random access rates, the PEVs themselves can participate in the charging requests. As PEVs with a high battery state do not transmit the charging requests to the central controller, the complexity of the central controller decreases due to the reduction of the charging requests. In addition, both the charging threshold and the random access rate are statistically calculated based on the average of supply power of the PEV charging system that do not require a real time update. By using the proposed TBRC with a tolerable PEV charging degradation, a 51% reduction of the PEV charging requests is achieved. Full article
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Open AccessArticle A Measurement Method for Large Parts Combining with Feature Compression Extraction and Directed Edge-Point Criterion
Sensors 2017, 17(1), 40; doi:10.3390/s17010040
Received: 20 July 2016 / Revised: 9 December 2016 / Accepted: 13 December 2016 / Published: 26 December 2016
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Abstract
High-accuracy surface measurement of large aviation parts is a significant guarantee of aircraft assembly with high quality. The result of boundary measurement is a significant parameter for aviation-part measurement. This paper proposes a measurement method for accurately measuring the surface and boundary of
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High-accuracy surface measurement of large aviation parts is a significant guarantee of aircraft assembly with high quality. The result of boundary measurement is a significant parameter for aviation-part measurement. This paper proposes a measurement method for accurately measuring the surface and boundary of aviation part with feature compression extraction and directed edge-point criterion. To improve the measurement accuracy of both the surface and boundary of large parts, extraction method of global boundary and feature analysis of local stripe are combined. The center feature of laser stripe is obtained with high accuracy and less calculation using a sub-pixel centroid extraction method based on compress processing. This method consists of a compressing process of images and judgment criterion of laser stripe centers. An edge-point extraction method based on directed arc-length criterion is proposed to obtain accurate boundary. Finally, a high-precision reconstruction of aerospace part is achieved. Experiments are performed both in a laboratory and an industrial field. The physical measurements validate that the mean distance deviation of the proposed method is 0.47 mm. The results of the field experimentation show the validity of the proposed method. Full article
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Open AccessArticle Multi-User Identification-Based Eye-Tracking Algorithm Using Position Estimation
Sensors 2017, 17(1), 41; doi:10.3390/s17010041
Received: 13 December 2016 / Revised: 22 December 2016 / Accepted: 23 December 2016 / Published: 27 December 2016
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Abstract
This paper proposes a new multi-user eye-tracking algorithm using position estimation. Conventional eye-tracking algorithms are typically suitable only for a single user, and thereby cannot be used for a multi-user system. Even though they can be used to track the eyes of multiple
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This paper proposes a new multi-user eye-tracking algorithm using position estimation. Conventional eye-tracking algorithms are typically suitable only for a single user, and thereby cannot be used for a multi-user system. Even though they can be used to track the eyes of multiple users, their detection accuracy is low and they cannot identify multiple users individually. The proposed algorithm solves these problems and enhances the detection accuracy. Specifically, the proposed algorithm adopts a classifier to detect faces for the red, green, and blue (RGB) and depth images. Then, it calculates features based on the histogram of the oriented gradient for the detected facial region to identify multiple users, and selects the template that best matches the users from a pre-determined face database. Finally, the proposed algorithm extracts the final eye positions based on anatomical proportions. Simulation results show that the proposed algorithm improved the average F1 score by up to 0.490, compared with benchmark algorithms. Full article
(This article belongs to the Special Issue Video Analysis and Tracking Using State-of-the-Art Sensors)
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Open AccessArticle Feasibility Test of a Liquid Film Thickness Sensor on a Flexible Printed Circuit Board Using a Three-Electrode Conductance Method
Sensors 2017, 17(1), 42; doi:10.3390/s17010042
Received: 4 October 2016 / Revised: 19 December 2016 / Accepted: 22 December 2016 / Published: 27 December 2016
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Abstract
Liquid film thickness measurements under temperature-varying conditions in a two-phase flow are of great importance to refining our understanding of two-phase flows. In order to overcome the limitations of the conventional electrical means of measuring the thickness of a liquid film, this study
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Liquid film thickness measurements under temperature-varying conditions in a two-phase flow are of great importance to refining our understanding of two-phase flows. In order to overcome the limitations of the conventional electrical means of measuring the thickness of a liquid film, this study proposes a three-electrode conductance method, with the device fabricated on a flexible printed circuit board (FPCB). The three-electrode conductance method offers the advantage of applicability under conditions with varying temperatures in principle, while the FPCB has the advantage of usability on curved surfaces and in relatively high-temperature conditions in comparison with sensors based on a printed circuit board (PCB). Two types of prototype sensors were fabricated on an FPCB and the feasibility of both was confirmed in a calibration test conducted at different temperatures. With the calibrated sensor, liquid film thickness measurements were conducted via a falling liquid film flow experiment, and the working performance was tested. Full article
(This article belongs to the Special Issue Microfluidic Sensors and Control Devices)
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Open AccessArticle Statistical Modeling of Indirect Paths for UWB Sensors in an Indoor Environment
Sensors 2017, 17(1), 43; doi:10.3390/s17010043
Received: 4 October 2016 / Revised: 3 December 2016 / Accepted: 22 December 2016 / Published: 27 December 2016
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Abstract
In this paper, we present a statistical model of an indirect path generated in an ultra-wideband (UWB) human tracking scenario. When performing moving target detection, an indirect path signal can generate ghost targets that may cause a false alarm. For this purpose, we
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In this paper, we present a statistical model of an indirect path generated in an ultra-wideband (UWB) human tracking scenario. When performing moving target detection, an indirect path signal can generate ghost targets that may cause a false alarm. For this purpose, we performed radar measurements in an indoor environment and established a statistical model of an indirect path based on the measurement data. The proposed model takes the form of a modified Saleh–Valenzuela model, which is used in a UWB channel model. An application example of the proposed model for mitigating false alarms is also presented. Full article
(This article belongs to the Section Physical Sensors)
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Open AccessArticle TPLE: A Reliable Data Delivery Scheme for On-Road WSN Traffic Monitoring
Sensors 2017, 17(1), 44; doi:10.3390/s17010044
Received: 24 October 2016 / Revised: 11 December 2016 / Accepted: 20 December 2016 / Published: 27 December 2016
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Abstract
In an on-road environment, motor-engines severely disturb the wireless link of a sensor node, leading to high package loss rate, high delivery delay, and poor radio communication quality. The existing data delivery mechanisms, such as the ACK-based retransmission mechanism and window-based link quality
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In an on-road environment, motor-engines severely disturb the wireless link of a sensor node, leading to high package loss rate, high delivery delay, and poor radio communication quality. The existing data delivery mechanisms, such as the ACK-based retransmission mechanism and window-based link quality estimation mechanism, could not handle these challenges well. To solve this challenge, we propose a Target-Prediction-based Link quality Estimation scheme (TPLE) to realize high quality data delivery in an on-road environment. To perform on-road link quality estimation, TPLE dynamically calculates the track of a nearby vehicle target and estimates target impact on wireless link. Based on the local estimation of link quality, TPLE schedules radio communication tasks effectively. Simulations indicate that our proposed TPLE scheme produces a 94% data delivery rate, its average retransmission number is around 0.8. Our conducted on-road data delivery experiments also indicated a similar result as the computer simulation. Full article
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Open AccessArticle DEP-On-Go for Simultaneous Sensing of Multiple Heavy Metals Pollutants in Environmental Samples
Sensors 2017, 17(1), 45; doi:10.3390/s17010045
Received: 27 November 2016 / Revised: 21 December 2016 / Accepted: 23 December 2016 / Published: 27 December 2016
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Abstract
We describe a simple and affordable “Disposable electrode printed (DEP)-On-Go” sensing platform for the rapid on-site monitoring of trace heavy metal pollutants in environmental samples for early warning by developing a mobile electrochemical device composed of palm-sized potentiostat and disposable unmodified screen-printed electrode
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We describe a simple and affordable “Disposable electrode printed (DEP)-On-Go” sensing platform for the rapid on-site monitoring of trace heavy metal pollutants in environmental samples for early warning by developing a mobile electrochemical device composed of palm-sized potentiostat and disposable unmodified screen-printed electrode chips. We present the analytical performance of our device for the sensitive detection of major heavy metal ions, namely, mercury, cadmium, lead, arsenic, zinc, and copper with detection limits of 1.5, 2.6, 4.0, 5.0, 14.4, and, 15.5 μg·L−1, respectively. Importantly, the utility of this device is extended to detect multiple heavy metals simultaneously with well-defined voltammograms and similar sensitivity. Finally, “DEP-On-Go” was successfully applied to detect heavy metals in real environmental samples from groundwater, tap water, house dust, soil, and industry-processed rice and noodle foods. We evaluated the efficiency of this system with a linear correlation through inductively coupled plasma mass spectrometry, and the results suggested that this system can be reliable for on-site screening purposes. On-field applications using real samples of groundwater for drinking in the northern parts of India support the easy-to-detect, low-cost (<1 USD), rapid (within 5 min), and reliable detection limit (ppb levels) performance of our device for the on-site detection and monitoring of multiple heavy metals in resource-limited settings. Full article
(This article belongs to the Special Issue Point-of-Care Biosensors)
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Open AccessArticle Sensing Technologies for Autism Spectrum Disorder Screening and Intervention
Sensors 2017, 17(1), 46; doi:10.3390/s17010046
Received: 3 August 2016 / Revised: 15 December 2016 / Accepted: 16 December 2016 / Published: 27 December 2016
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Abstract
This paper reviews the state-of-the-art in sensing technologies that are relevant for Autism Spectrum Disorder (ASD) screening and therapy. This disorder is characterized by difficulties in social communication, social interactions, and repetitive behaviors. It is diagnosed during the first three years of life.
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This paper reviews the state-of-the-art in sensing technologies that are relevant for Autism Spectrum Disorder (ASD) screening and therapy. This disorder is characterized by difficulties in social communication, social interactions, and repetitive behaviors. It is diagnosed during the first three years of life. Early and intensive interventions have been shown to improve the developmental trajectory of the affected children. The earlier the diagnosis, the sooner the intervention therapy can begin, thus, making early diagnosis an important research goal. Technological innovations have tremendous potential to assist with early diagnosis and improve intervention programs. The need for careful and methodological evaluation of such emerging technologies becomes important in order to assist not only the therapists and clinicians in their selection of suitable tools, but to also guide the developers of the technologies in improving hardware and software. In this paper, we survey the literatures on sensing technologies for ASD and we categorize them into eye trackers, movement trackers, electrodermal activity monitors, tactile sensors, vocal prosody and speech detectors, and sleep quality assessment devices. We assess their effectiveness and study their limitations. We also examine the challenges faced by this growing field that need to be addressed before these technologies can perform up to their theoretical potential. Full article
(This article belongs to the Special Issue Sensing Technology for Healthcare System)
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Open AccessArticle A Fiber-Optic Interferometric Tri-Component Geophone for Ocean Floor Seismic Monitoring
Sensors 2017, 17(1), 47; doi:10.3390/s17010047
Received: 22 October 2016 / Revised: 7 December 2016 / Accepted: 23 December 2016 / Published: 28 December 2016
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Abstract
For the implementation of an all fiber observation network for submarine seismic monitoring, a tri-component geophone based on Michelson interferometry is proposed and tested. A compliant cylinder-based sensor head is analyzed with finite element method and tested. The operation frequency ranges from 2
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For the implementation of an all fiber observation network for submarine seismic monitoring, a tri-component geophone based on Michelson interferometry is proposed and tested. A compliant cylinder-based sensor head is analyzed with finite element method and tested. The operation frequency ranges from 2 Hz to 150 Hz for acceleration detection, employing a phase generated carrier demodulation scheme, with a responsivity above 50 dB re rad/g for the whole frequency range. The transverse suppression ratio is about 30 dB. The system noise at low frequency originated mainly from the 1/f fluctuation, with an average system noise level −123.55 dB re rad / Hz ranging from 0 Hz to 500 Hz. The minimum detectable acceleration is about 2 ng / Hz , and the dynamic range is above 116 dB. Full article
(This article belongs to the Special Issue Optical Fiber Sensors 2016)
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Open AccessArticle Influence of Individual Differences on the Calculation Method for FBG-Type Blood Pressure Sensors
Sensors 2017, 17(1), 48; doi:10.3390/s17010048
Received: 7 November 2016 / Revised: 19 December 2016 / Accepted: 23 December 2016 / Published: 28 December 2016
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Abstract
In this paper, we propose a blood pressure calculation and associated measurement method that by using a fiber Bragg grating (FBG) sensor. There are several points at which the pulse can be measured on the surface of the human body, and when a
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In this paper, we propose a blood pressure calculation and associated measurement method that by using a fiber Bragg grating (FBG) sensor. There are several points at which the pulse can be measured on the surface of the human body, and when a FBG sensor located at any of these points, the pulse wave signal can be measured. The measured waveform is similar to the acceleration pulse wave. The pulse wave signal changes depending on several factors, including whether or not the individual is healthy and/or elderly. The measured pulse wave signal can be used to calculate the blood pressure using a calibration curve, which is constructed by a partial least squares (PLS) regression analysis using a reference blood pressure and the pulse wave signal. In this paper, we focus on the influence of individual differences from calculated blood pressure based on each calibration curve. In our study, the calculated blood pressure from both the individual and overall calibration curves were compared, and our results show that the calculated blood pressure based on the overall calibration curve had a lower measurement accuracy than that based on an individual calibration curve. We also found that the influence of the individual differences on the calculated blood pressure when using the FBG sensor method were very low. Therefore, the FBG sensor method that we developed for measuring the blood pressure was found to be suitable for use by many people. Full article
(This article belongs to the Special Issue Recent Advances in Fiber Bragg Grating Sensing)
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Open AccessArticle Multi-Objective Sliding Mode Control on Vehicle Cornering Stability with Variable Gear Ratio Actuator-Based Active Front Steering Systems
Sensors 2017, 17(1), 49; doi:10.3390/s17010049
Received: 16 November 2016 / Revised: 13 December 2016 / Accepted: 19 December 2016 / Published: 28 December 2016
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Abstract
Active front steering (AFS) is an emerging technology to improve the vehicle cornering stability by introducing an additional small steering angle to the driver’s input. This paper proposes an AFS system with a variable gear ratio steering (VGRS) actuator which is controlled by
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Active front steering (AFS) is an emerging technology to improve the vehicle cornering stability by introducing an additional small steering angle to the driver’s input. This paper proposes an AFS system with a variable gear ratio steering (VGRS) actuator which is controlled by using the sliding mode control (SMC) strategy to improve the cornering stability of vehicles. In the design of an AFS system, different sensors are considered to measure the vehicle state, and the mechanism of the AFS system is also modelled in detail. Moreover, in order to improve the cornering stability of vehicles, two dependent objectives, namely sideslip angle and yaw rate, are considered together in the design of SMC strategy. By evaluating the cornering performance, Sine with Dwell and accident avoidance tests are conducted, and the simulation results indicate that the proposed SMC strategy is capable of improving the cornering stability of vehicles in practice. Full article
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Open AccessArticle A Fully Transparent Flexible Sensor for Cryogenic Temperatures Based on High Strength Metallurgical Graphene
Sensors 2017, 17(1), 51; doi:10.3390/s17010051
Received: 13 October 2016 / Revised: 28 November 2016 / Accepted: 12 December 2016 / Published: 28 December 2016
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Abstract
Low-temperature electronics operating in below zero temperatures or even below the lower limit of the common −65 to 125 °C temperature range are essential in medical diagnostics, in space exploration and aviation, in processing and storage of food and mainly in scientific research,
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Low-temperature electronics operating in below zero temperatures or even below the lower limit of the common −65 to 125 °C temperature range are essential in medical diagnostics, in space exploration and aviation, in processing and storage of food and mainly in scientific research, like superconducting materials engineering and their applications—superconducting magnets, superconducting energy storage, and magnetic levitation systems. Such electronic devices demand special approach to the materials used in passive elements and sensors. The main goal of this work was the implementation of a fully transparent, flexible cryogenic temperature sensor with graphene structures as sensing element. Electrodes were made of transparent ITO (Indium Tin Oxide) or ITO/Ag/ITO conductive layers by laser ablation and finally encapsulated in a polymer coating. A helium closed-cycle cryostat has been used in measurements of the electrical properties of these graphene-based temperature sensors under cryogenic conditions. The sensors were repeatedly cooled from room temperature to cryogenic temperature. Graphene structures were characterized using Raman spectroscopy. The observation of the resistance changes as a function of temperature indicates the potential use of graphene layers in the construction of temperature sensors. The temperature characteristics of the analyzed graphene sensors exhibit no clear anomalies or strong non-linearity in the entire studied temperature range (as compared to the typical carbon sensor). Full article
(This article belongs to the Special Issue Flexible Electronics and Sensors)
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Open AccessArticle Relative Estimation of Water Content for Flat-Type Inductive-Based Oil Palm Fruit Maturity Sensor
Sensors 2017, 17(1), 52; doi:10.3390/s17010052
Received: 13 July 2016 / Revised: 5 November 2016 / Accepted: 22 November 2016 / Published: 28 December 2016
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Abstract
The paper aims to study the sensor that identifies the maturity of oil palm fruit bunches by using a flat-type inductive concept based on a resonant frequency technique. Conventionally, a human grader is used to inspect the ripeness of the oil palm fresh
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The paper aims to study the sensor that identifies the maturity of oil palm fruit bunches by using a flat-type inductive concept based on a resonant frequency technique. Conventionally, a human grader is used to inspect the ripeness of the oil palm fresh fruit bunch (FFB) which can be inconsistent and inaccurate. There are various new methods that are proposed with the intention to grade the ripeness of the oil palm FFB, but none has taken the inductive concept. In this study, the resonance frequency of the air coil is investigated. Samples of oil palm FFB are tested with frequencies ranging from 20 Hz to 10 MHz and the results obtained show a linear relationship between the graph of the resonance frequency (MHz) against time (Weeks). It is observed that the resonance frequencies obtained for Week 10 (pre-mature) and Week 18 (mature) are around 8.5 MHz and 9.8 MHz, respectively. These results are compared with the percentage of the moisture content. Hence, the inductive method of the oil palm fruit maturity sensor can be used to detect the change in water content for ripeness detection of the oil palm FFB. Full article
(This article belongs to the Special Issue Sensors for Agriculture)
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Open AccessArticle RFID Ownership Transfer with Positive Secrecy Capacity Channels
Sensors 2017, 17(1), 53; doi:10.3390/s17010053
Received: 9 October 2016 / Revised: 20 December 2016 / Accepted: 23 December 2016 / Published: 29 December 2016
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Abstract
RFID ownership transfer protocols (OTPs) transfer tag ownership rights. Recently, there has been considerable interest in such protocols; however, guaranteeing privacy for symmetric-key settings without trusted third parties (TTPs) is a challenge still unresolved. In this paper, we address this issue and show
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RFID ownership transfer protocols (OTPs) transfer tag ownership rights. Recently, there has been considerable interest in such protocols; however, guaranteeing privacy for symmetric-key settings without trusted third parties (TTPs) is a challenge still unresolved. In this paper, we address this issue and show that it can be solved by using channels with positive secrecy capacity. We implement these channels with noisy tags and provide practical values, thus proving that perfect secrecy is theoretically possible. We then define a communication model that captures spatiotemporal events and describe a first example of symmetric-key based OTP that: (i) is formally secure in the proposed communication model and (ii) achieves privacy with a noisy tag wiretap channel without TTPs. Full article
(This article belongs to the Section Sensor Networks)
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Open AccessArticle A Simple Interfacial Platform for Homogeneous Electrochemical Immunoassays Using a Poly(Vinylimidazole)-Modified Electrode
Sensors 2017, 17(1), 54; doi:10.3390/s17010054
Received: 4 November 2016 / Revised: 22 December 2016 / Accepted: 22 December 2016 / Published: 29 December 2016
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Abstract
In this study, a homogeneous method featuring simple, one-step detection was developed to analyze hippuric acid (HA), a major metabolite of toluene. High sensitivity was achieved with the facile immobilization of poly(vinylimidazole) (PVI) on an indium tin oxide (ITO) electrode. Using a previously
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In this study, a homogeneous method featuring simple, one-step detection was developed to analyze hippuric acid (HA), a major metabolite of toluene. High sensitivity was achieved with the facile immobilization of poly(vinylimidazole) (PVI) on an indium tin oxide (ITO) electrode. Using a previously developed approach, pentacyanoferrate was coordinated with pyridyl-N ligands, and the redox-active Fe(II/III) centers were bound to Ni(II) ions on the electrode via electrostatic cyanide bridges. The detection was accomplished by the competitive binding of free HA and pentacyanoferrate-(4-aminomethylpyridine-hippuric acid) (Fe-HA, the electron transfer mediator) to the HA antibody on the Ni(II) ions-modified PVI-ITO (Ni-PVI-ITO) electrode. The electrical and physicochemical characterization of the electrode was carried out by cyclic voltammetry, differential pulse voltammetry, field emission scanning electron microscopy, and X-ray photoelectron spectroscopy. At low mediator concentrations, the electrical signals were proportional to the HA concentration between 0.1 µg/mL and 1.0 mg/mL. The same method may be extended to other small organic molecules. Full article
(This article belongs to the Special Issue Electrochemical Immunosensors)
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Open AccessArticle Honey Bee Colonies Remote Monitoring System
Sensors 2017, 17(1), 55; doi:10.3390/s17010055
Received: 26 November 2016 / Revised: 22 December 2016 / Accepted: 26 December 2016 / Published: 29 December 2016
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Abstract
Bees are very important for terrestrial ecosystems and, above all, for the subsistence of many crops, due to their ability to pollinate flowers. Currently, the honey bee populations are decreasing due to colony collapse disorder (CCD). The reasons for CCD are not fully
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Bees are very important for terrestrial ecosystems and, above all, for the subsistence of many crops, due to their ability to pollinate flowers. Currently, the honey bee populations are decreasing due to colony collapse disorder (CCD). The reasons for CCD are not fully known, and as a result, it is essential to obtain all possible information on the environmental conditions surrounding the beehives. On the other hand, it is important to carry out such information gathering as non-intrusively as possible to avoid modifying the bees’ work conditions and to obtain more reliable data. We designed a wireless-sensor networks meet these requirements. We designed a remote monitoring system (called WBee) based on a hierarchical three-level model formed by the wireless node, a local data server, and a cloud data server. WBee is a low-cost, fully scalable, easily deployable system with regard to the number and types of sensors and the number of hives and their geographical distribution. WBee saves the data in each of the levels if there are failures in communication. In addition, the nodes include a backup battery, which allows for further data acquisition and storage in the event of a power outage. Unlike other systems that monitor a single point of a hive, the system we present monitors and stores the temperature and relative humidity of the beehive in three different spots. Additionally, the hive is continuously weighed on a weighing scale. Real-time weight measurement is an innovation in wireless beehive—monitoring systems. We designed an adaptation board to facilitate the connection of the sensors to the node. Through the Internet, researchers and beekeepers can access the cloud data server to find out the condition of their hives in real time. Full article
(This article belongs to the Special Issue State-of-the-Art Sensors Technology in Spain 2016)
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Open AccessArticle Target Detection over the Diurnal Cycle Using a Multispectral Infrared Sensor
Sensors 2017, 17(1), 56; doi:10.3390/s17010056
Received: 14 September 2016 / Revised: 23 December 2016 / Accepted: 26 December 2016 / Published: 29 December 2016
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Abstract
When detecting a target over the diurnal cycle, a conventional infrared thermal sensor might lose the target due to the thermal crossover, which could happen at any time throughout the day when the infrared image contrast between target and background in a scene
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When detecting a target over the diurnal cycle, a conventional infrared thermal sensor might lose the target due to the thermal crossover, which could happen at any time throughout the day when the infrared image contrast between target and background in a scene is indistinguishable due to the temperature variation. In this paper, the benefits of using a multispectral-based infrared sensor over the diurnal cycle have been shown. Firstly, a brief theoretical analysis on how the thermal crossover influences a conventional thermal sensor, within the conditions where the thermal crossover would happen and why the mid-infrared (3~5 μm) multispectral technology is effective, is presented. Furthermore, the effectiveness of this technology is also described and we describe how the prototype design and multispectral technology is employed to help solve the thermal crossover detection problem. Thirdly, several targets are set up outside and imaged in the field experiment over a 24-h period. The experimental results show that the multispectral infrared imaging system can enhance the contrast of the detected images and effectively solve the failure of the conventional infrared sensor during the diurnal cycle, which is of great significance for infrared surveillance applications. Full article
(This article belongs to the Special Issue Imaging: Sensors and Technologies) Printed Edition available
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Open AccessArticle Design of a Mobile Low-Cost Sensor Network Using Urban Buses for Real-Time Ubiquitous Noise Monitoring
Sensors 2017, 17(1), 57; doi:10.3390/s17010057
Received: 30 September 2016 / Revised: 7 December 2016 / Accepted: 23 December 2016 / Published: 29 December 2016
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Abstract
One of the main priorities of smart cities is improving the quality of life of their inhabitants. Traffic noise is one of the pollutant sources that causes a negative impact on the quality of life of citizens, which is gaining attention among authorities.
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One of the main priorities of smart cities is improving the quality of life of their inhabitants. Traffic noise is one of the pollutant sources that causes a negative impact on the quality of life of citizens, which is gaining attention among authorities. The European Commission has promoted the Environmental Noise Directive 2002/49/EC (END) to inform citizens and to prevent the harmful effects of noise exposure. The measure of acoustic levels using noise maps is a strategic issue in the END action plan. Noise maps are typically calculated by computing the average noise during one year and updated every five years. Hence, the implementation of dynamic noise mapping systems could lead to short-term plan actions, besides helping to better understand the evolution of noise levels along time. Recently, some projects have started the monitoring of noise levels in urban areas by means of acoustic sensor networks settled in strategic locations across the city, while others have taken advantage of collaborative citizen sensing mobile applications. In this paper, we describe the design of an acoustic low-cost sensor network installed on public buses to measure the traffic noise in the city in real time. Moreover, the challenges that a ubiquitous bus acoustic measurement system entails are enumerated and discussed. Specifically, the analysis takes into account the feature extraction of the audio signal, the identification and separation of the road traffic noise from urban traffic noise, the hardware platform to measure and process the acoustic signal, the connectivity between the several nodes of the acoustic sensor network to store the data and, finally, the noise maps’ generation process. The implementation and evaluation of the proposal in a real-life scenario is left for future work. Full article
(This article belongs to the Special Issue Smart City: Vision and Reality)
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Open AccessArticle Odor-Sensing System to Support Social Participation of People Suffering from Incontinence
Sensors 2017, 17(1), 58; doi:10.3390/s17010058
Received: 4 November 2016 / Revised: 19 December 2016 / Accepted: 23 December 2016 / Published: 29 December 2016
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Abstract
This manuscript describes the design considerations, implementation, and laboratory validation of an odor sensing module whose purpose is to support people that suffer from incontinence. Because of the requirements expressed by the affected end-users the odor sensing unit is realized as a portable
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This manuscript describes the design considerations, implementation, and laboratory validation of an odor sensing module whose purpose is to support people that suffer from incontinence. Because of the requirements expressed by the affected end-users the odor sensing unit is realized as a portable accessory that may be connected to any pre-existing smart device. We have opted for a low-cost, low-power consuming metal oxide based gas detection approach to highlight the viability of developing an inexpensive yet helpful odor recognition technology. The system consists of a hotplate employing, inkjet-printed p-type semiconducting layers of copper(II) oxide, and chromium titanium oxide. Both functional layers are characterized with respect to their gas-sensitive behavior towards humidity, ammonia, methylmercaptan, and dimethylsulfide and we demonstrate detection limits in the parts-per-billion range for the two latter gases. Employing a temperature variation scheme that reads out the layer’s resistivity in a steady-state, we use each sensor chip as a virtual array. With this setup, we demonstrate the feasibility of detecting odors associated with incontinence. Full article
(This article belongs to the Special Issue Olfactory and Gustatory Sensors)
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Open AccessArticle Concept and Development of an Electronic Framework Intended for Electrode and Surrounding Environment Characterization In Vivo
Sensors 2017, 17(1), 59; doi:10.3390/s17010059
Received: 15 October 2016 / Revised: 22 December 2016 / Accepted: 24 December 2016 / Published: 30 December 2016
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Abstract
There has been substantial progress over the last decade towards miniaturizing implantable microelectrodes for use in Active Implantable Medical Devices (AIMD). Compared to the rapid development and complexity of electrode miniaturization, methods to monitor and assess functional integrity and electrical functionality of these
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There has been substantial progress over the last decade towards miniaturizing implantable microelectrodes for use in Active Implantable Medical Devices (AIMD). Compared to the rapid development and complexity of electrode miniaturization, methods to monitor and assess functional integrity and electrical functionality of these electrodes, particularly during long term stimulation, have not progressed to the same extent. Evaluation methods that form the gold standard, such as stimulus pulse testing, cyclic voltammetry and electrochemical impedance spectroscopy, are either still bound to laboratory infrastructure (impractical for long term in vivo experiments) or deliver no comprehensive insight into the material’s behaviour. As there is a lack of cost effective and practical predictive measures to understand long term electrode behaviour in vivo, material investigations need to be performed after explantation of the electrodes. We propose the analysis of the electrode and its environment in situ, to better understand and correlate the effects leading to electrode failure. The derived knowledge shall eventually lead to improved electrode designs, increased electrode functionality and safety in clinical applications. In this paper, the concept, design and prototyping of a sensor framework used to analyse the electrode’s behaviour and to monitor diverse electrode failure mechanisms, even during stimulation pulses, is presented. We focused on the electronic circuitry and data acquisition techniques required for a conceptual multi-sensor system. Functionality of single modules and a prototype framework have been demonstrated, but further work is needed to convert the prototype system into an implantable device. In vitro studies will be conducted first to verify sensor performance and reliability. Full article
(This article belongs to the Special Issue Sensing Technology for Healthcare System)
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Open AccessArticle SCRMS: An RFID and Sensor Web-Enabled Smart Cultural Relics Management System
Sensors 2017, 17(1), 60; doi:10.3390/s17010060
Received: 27 September 2016 / Revised: 7 December 2016 / Accepted: 26 December 2016 / Published: 30 December 2016
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Abstract
Cultural relics represent national or even global resources of inestimable value. How to efficiently manage and preserve these cultural relics is a vitally important issue. To achieve this goal, this study proposed, designed, and implemented an RFID and Sensor Web–enabled smart cultural relics
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Cultural relics represent national or even global resources of inestimable value. How to efficiently manage and preserve these cultural relics is a vitally important issue. To achieve this goal, this study proposed, designed, and implemented an RFID and Sensor Web–enabled smart cultural relics management system (SCRMS). In this system, active photovoltaic subtle energy-powered Radio Frequency Identification (RFID) is used for long-range contactless identification and lifecycle management of cultural relics during their storage and circulation. In addition, different types of ambient sensors are integrated with the RFID tags and deployed around cultural relics to monitor their environmental parameters, helping to ensure that they remain in good condition. An Android-based smart mobile application, as middleware, is used in collaboration with RFID readers to collect information and provide convenient management for the circulation of cultural relics. Moreover, multiple sensing techniques are taken advantage of simultaneously for preservation of cultural relics. The proposed system was successfully applied to a museum in the Yongding District, Fujian Province, China, demonstrating its feasibility and advantages for smart and efficient management and preservation of cultural relics. Full article
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Open AccessArticle In Situ Real-Time Monitoring of Glutamate and Electrophysiology from Cortex to Hippocampus in Mice Based on a Microelectrode Array
Sensors 2017, 17(1), 61; doi:10.3390/s17010061
Received: 30 September 2016 / Revised: 22 December 2016 / Accepted: 26 December 2016 / Published: 30 December 2016
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Abstract
Changes in the structure and function of the hippocampus contribute to epilepsy, schizophrenia and other neurological or mental disorders of the brain. Since the function of the hippocampus depends heavily on the glutamate (Glu) signaling pathways, in situ real-time detection of Glu neurotransmitter
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Changes in the structure and function of the hippocampus contribute to epilepsy, schizophrenia and other neurological or mental disorders of the brain. Since the function of the hippocampus depends heavily on the glutamate (Glu) signaling pathways, in situ real-time detection of Glu neurotransmitter release and electrophysiological signals in hippocampus is of great significance. To achieve the dual-mode detection in mouse hippocampus in vivo, a 16-channel implantable microelectrode array (MEA) was fabricated by micro-electromechanical system (MEMS) technology. Twelve microelectrode sites were modified with platinum black for electrophysiological recording and four sites were modified with glutamate oxidase (GluOx) and 1,3-phenylenediamine (mPD) for selective electrochemical detection of Glu. The MEA was implanted from cortex to hippocampus in mouse brain for in situ real-time monitoring of Glu and electrophysiological signals. It was found that the Glu concentration in hippocampus was roughly 50 μM higher than that in the cortex, and the firing rate of concurrently recorded spikes declined from 6.32 ± 4.35 spikes/s in cortex to 0.09 ± 0.06 spikes/s in hippocampus. The present results demonstrated that the dual-mode MEA probe was capable in neurological detections in vivo with high spatial resolution and dynamical response, which lays the foundation for further pathology studies in the hippocampus of mouse models with nervous or mental disorders. Full article
(This article belongs to the Special Issue Nanobiosensing for Sensors)
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Open AccessArticle Modeling, Fabrication and Testing of a Customizable Micromachined Hotplate for Sensor Applications
Sensors 2017, 17(1), 62; doi:10.3390/s17010062
Received: 31 October 2016 / Revised: 22 December 2016 / Accepted: 26 December 2016 / Published: 30 December 2016
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Abstract
In the sensors field the active sensing material frequently needs a controlled temperature in order to work properly. In microsystems technology, micro-machined hotplates represent a platform consisting of a thin suspended membrane where the sensing material can be deposited, usually integrating electrical stimuli
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In the sensors field the active sensing material frequently needs a controlled temperature in order to work properly. In microsystems technology, micro-machined hotplates represent a platform consisting of a thin suspended membrane where the sensing material can be deposited, usually integrating electrical stimuli and temperature readout. The micro-hotplate ensures a series of advantages such as miniaturized size, fast response, high sensitivity, low power consumption and selectivity for chemical sensing. This work compares the coplanar and the buried approach for the micro-hotplate heaters design with the aim to optimize the fabrication process and to propose a guideline for the choice of the suitable design with respect to the applications. In particular, robust Finite Element Method (FEM) models are set up in order to predict the electrical and thermal behavior of the micro-hotplates. The multiphysics approach used for the simulation allows to match as close as possible the actual device to the predictive model: geometries, materials, physics have been carefully linked to the fabricated devices to obtain the best possible accuracy. The materials involved in the fabrication process are accurately selected in order to improve the yield of the process and the performance of the devices. The fabricated micro-hotplates are able to warm the active region up to 400 °C (with a corresponding power consumption equal to 250 mW @ 400 °C) with a uniform temperature distribution in the buried micro-hotplate and a controlled temperature gradient in the coplanar one. A response time of about 70 ms was obtained on the virtual model, which perfectly agrees with the one measured on the fabricated device. Besides morphological, electrical and thermal characterizations, this work includes reliability tests in static and dynamic modes. Full article
(This article belongs to the collection Modeling, Testing and Reliability Issues in MEMS Engineering)
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Open AccessArticle Integration of Curved D-Type Optical Fiber Sensor with Microfluidic Chip
Sensors 2017, 17(1), 63; doi:10.3390/s17010063
Received: 22 November 2016 / Revised: 16 December 2016 / Accepted: 27 December 2016 / Published: 30 December 2016
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Abstract
A curved D-type optical fiber sensor (OFS) combined with a microfluidic chip is proposed. This OFS, based on surface plasmon resonance (SPR) of the Kretchmann’s configuration, is applied as a biosensor to measure the concentrations of different bio-liquids such as ethanol, methanol, and
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A curved D-type optical fiber sensor (OFS) combined with a microfluidic chip is proposed. This OFS, based on surface plasmon resonance (SPR) of the Kretchmann’s configuration, is applied as a biosensor to measure the concentrations of different bio-liquids such as ethanol, methanol, and glucose solutions. The SPR phenomenon is attained by using the optical fiber to guide the light source to reach the side-polished, gold-coated region. Integrating this OFS with a polymethylmethacrylate (PMMA)-based microfluidic chip, the SPR spectra for liquids with different refractive indices are recorded. Experimentally, the sensitivity of the current biosensor was calculated to be in the order of 10−5 RIU. This microfluidic chip-integrated OFS could be valuable for monitoring subtle changes in biological samples such as blood sugar, allergen, and biomolecular interactions. Full article
(This article belongs to the Section Physical Sensors)
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Open AccessArticle Novel Visual Sensor Coverage and Deployment in Time Aware PTZ Wireless Visual Sensor Networks
Sensors 2017, 17(1), 64; doi:10.3390/s17010064
Received: 11 November 2016 / Revised: 26 December 2016 / Accepted: 28 December 2016 / Published: 30 December 2016
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Abstract
In this paper, we consider the visual sensor deployment algorithm in Pan-Tilt-Zoom (PTZ) Wireless Visual Sensor Networks (WVSNs). With PTZ capability, a sensor’s visual coverage can be extended to reduce the number of visual sensors that need to be deployed. The coverage zone
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In this paper, we consider the visual sensor deployment algorithm in Pan-Tilt-Zoom (PTZ) Wireless Visual Sensor Networks (WVSNs). With PTZ capability, a sensor’s visual coverage can be extended to reduce the number of visual sensors that need to be deployed. The coverage zone of a visual sensor in PTZ WVSN is composed of two regions, a Direct Coverage Region (DCR) and a PTZ Coverage Region (PTZCR). In the PTZCR, a visual sensor needs a mechanical pan-tilt-zoom operation to cover an object. This mechanical operation can take seconds, so the sensor might not be able to adjust the camera in time to capture the visual data. In this paper, for the first time, we study this PTZ time-aware PTZ WVSN deployment problem. We formulate this PTZ time-aware PTZ WVSN deployment problem as an optimization problem where the objective is to minimize the total visual sensor deployment cost so that each area is either covered in the DCR or in the PTZCR while considering the PTZ time constraint. The proposed Time Aware Coverage Zone (TACZ) model successfully captures the PTZ visual sensor coverage in terms of camera focal range, angle span zone coverage and camera PTZ time. Then a novel heuristic, called Time Aware Deployment with PTZ camera (TADPTZ) algorithm, is proposed to solve the problem. From our computational experiments, we found out that TACZ model outperforms the existing M coverage model under all network scenarios. In addition, as compared to the optimal solutions, the TACZ model is scalable and adaptable to the different PTZ time requirements when deploying large PTZ WVSNs. Full article
(This article belongs to the Special Issue Sensors for Home Automation and Security)
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Open AccessArticle A Comparison Study of Classifier Algorithms for Cross-Person Physical Activity Recognition
Sensors 2017, 17(1), 66; doi:10.3390/s17010066
Received: 1 November 2016 / Revised: 20 December 2016 / Accepted: 27 December 2016 / Published: 30 December 2016
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Abstract
Physical activity is widely known to be one of the key elements of a healthy life. The many benefits of physical activity described in the medical literature include weight loss and reductions in the risk factors for chronic diseases. With the recent advances
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Physical activity is widely known to be one of the key elements of a healthy life. The many benefits of physical activity described in the medical literature include weight loss and reductions in the risk factors for chronic diseases. With the recent advances in wearable devices, such as smartwatches or physical activity wristbands, motion tracking sensors are becoming pervasive, which has led to an impressive growth in the amount of physical activity data available and an increasing interest in recognizing which specific activity a user is performing. Moreover, big data and machine learning are now cross-fertilizing each other in an approach called “deep learning”, which consists of massive artificial neural networks able to detect complicated patterns from enormous amounts of input data to learn classification models. This work compares various state-of-the-art classification techniques for automatic cross-person activity recognition under different scenarios that vary widely in how much information is available for analysis. We have incorporated deep learning by using Google’s TensorFlow framework. The data used in this study were acquired from PAMAP2 (Physical Activity Monitoring in the Ageing Population), a publicly available dataset containing physical activity data. To perform cross-person prediction, we used the leave-one-subject-out (LOSO) cross-validation technique. When working with large training sets, the best classifiers obtain very high average accuracies (e.g., 96% using extra randomized trees). However, when the data volume is drastically reduced (where available data are only 0.001% of the continuous data), deep neural networks performed the best, achieving 60% in overall prediction accuracy. We found that even when working with only approximately 22.67% of the full dataset, we can statistically obtain the same results as when working with the full dataset. This finding enables the design of more energy-efficient devices and facilitates cold starts and big data processing of physical activity records. Full article
(This article belongs to the Special Issue Sensing Technology for Healthcare System)
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Open AccessArticle Programmable Low-Power Low-Noise Capacitance to Voltage Converter for MEMS Accelerometers
Sensors 2017, 17(1), 67; doi:10.3390/s17010067
Received: 30 November 2016 / Revised: 16 December 2016 / Accepted: 23 December 2016 / Published: 30 December 2016
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Abstract
In this work, we present a capacitance-to-voltage converter (CVC) for capacitive accelerometers based on microelectromechanical systems (MEMS). Based on a fully-differential transimpedance amplifier (TIA), it features a 34-dB transimpedance gain control and over one decade programmable bandwidth, from 75 kHz to 1.2 MHz.
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In this work, we present a capacitance-to-voltage converter (CVC) for capacitive accelerometers based on microelectromechanical systems (MEMS). Based on a fully-differential transimpedance amplifier (TIA), it features a 34-dB transimpedance gain control and over one decade programmable bandwidth, from 75 kHz to 1.2 MHz. The TIA is aimed for low-cost low-power capacitive sensor applications. It has been designed in a standard 0.18-μm CMOS technology and its power consumption is only 54 μW. At the maximum transimpedance configuration, the TIA shows an equivalent input noise of 42 fA/ Hz at 50 kHz, which corresponds to 100 μg/ Hz . Full article
(This article belongs to the Special Issue MEMS and Nano-Sensors)
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Open AccessArticle SEALDH-II—An Autonomous, Holistically Controlled, First Principles TDLAS Hygrometer for Field and Airborne Applications: Design–Setup–Accuracy/Stability Stress Test
Sensors 2017, 17(1), 68; doi:10.3390/s17010068
Received: 9 November 2016 / Revised: 11 December 2016 / Accepted: 20 December 2016 / Published: 30 December 2016
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Abstract
Instrument operation in harsh environments often significantly impacts the trust level of measurement data. While commercial instrument manufacturers clearly define the deployment conditions to achieve trustworthy data in typical standard applications, it is frequently unavoidable in scientific field applications to operate instruments outside
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Instrument operation in harsh environments often significantly impacts the trust level of measurement data. While commercial instrument manufacturers clearly define the deployment conditions to achieve trustworthy data in typical standard applications, it is frequently unavoidable in scientific field applications to operate instruments outside these commercial standard application specifications. Scientific instrumentation, however, is employing cutting-edge technology and often highly optimized but also lacks long-term field tests to assess the field vs. laboratory performance. Recently, we developed the Selective Extractive Laser Diode Hygrometer (SEALDH-II), which addresses field and especially airborne applications as well as metrological laboratory validations. SEALDH-II targets reducing deviations between airborne hygrometers (currently up to 20% between the most advanced hygrometers) with a new holistic, internal control and validation concept, which guarantees the transfer of the laboratory performance into a field scenario by capturing more than 80 instrument internal “housekeeping” data to nearly perfectly control SEALDH-II’s health status. SEALDH-II uses a calibration-free, first principles based, direct Tuneable Diode Laser Absorption Spectroscopy (dTDLAS) approach, to cover the entire atmospheric humidity measurement range from about 3 to 40,000 ppmv with a calculated maximum uncertainty of 4.3% ± 3 ppmv. This is achieved not only by innovations in internal instrument monitoring and design, but also by active control algorithms such as a high resolution spectral stabilization. This paper describes the setup, working principles, and instrument stabilization, as well as its precision validation and long-term stress tests in an environmental chamber over an environmental temperature and humidity range of ΔT = 50 K and ΔRH = 80% RH, respectively. Full article
(This article belongs to the Section Physical Sensors)
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Open AccessArticle A Novel Secure IoT-Based Smart Home Automation System Using a Wireless Sensor Network
Sensors 2017, 17(1), 69; doi:10.3390/s17010069
Received: 27 September 2016 / Revised: 13 December 2016 / Accepted: 27 December 2016 / Published: 30 December 2016
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Abstract
Wireless sensor networks (WSNs) provide noteworthy benefits over traditional approaches for several applications, including smart homes, healthcare, environmental monitoring, and homeland security. WSNs are integrated with the Internet Protocol (IP) to develop the Internet of Things (IoT) for connecting everyday life objects to
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Wireless sensor networks (WSNs) provide noteworthy benefits over traditional approaches for several applications, including smart homes, healthcare, environmental monitoring, and homeland security. WSNs are integrated with the Internet Protocol (IP) to develop the Internet of Things (IoT) for connecting everyday life objects to the internet. Hence, major challenges of WSNs include: (i) how to efficiently utilize small size and low-power nodes to implement security during data transmission among several sensor nodes; (ii) how to resolve security issues associated with the harsh and complex environmental conditions during data transmission over a long coverage range. In this study, a secure IoT-based smart home automation system was developed. To facilitate energy-efficient data encryption, a method namely Triangle Based Security Algorithm (TBSA) based on efficient key generation mechanism was proposed. The proposed TBSA in integration of the low power Wi-Fi were included in WSNs with the Internet to develop a novel IoT-based smart home which could provide secure data transmission among several associated sensor nodes in the network over a long converge range. The developed IoT based system has outstanding performance by fulfilling all the necessary security requirements. The experimental results showed that the proposed TBSA algorithm consumed less energy in comparison with some existing methods. Full article
(This article belongs to the Special Issue Sensors for Home Automation and Security)
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Open AccessArticle Line-Based Registration of Panoramic Images and LiDAR Point Clouds for Mobile Mapping
Sensors 2017, 17(1), 70; doi:10.3390/s17010070
Received: 20 October 2016 / Revised: 18 December 2016 / Accepted: 26 December 2016 / Published: 31 December 2016
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Abstract
For multi-sensor integrated systems, such as the mobile mapping system (MMS), data fusion at sensor-level, i.e., the 2D-3D registration between an optical camera and LiDAR, is a prerequisite for higher level fusion and further applications. This paper proposes a line-based registration method for
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For multi-sensor integrated systems, such as the mobile mapping system (MMS), data fusion at sensor-level, i.e., the 2D-3D registration between an optical camera and LiDAR, is a prerequisite for higher level fusion and further applications. This paper proposes a line-based registration method for panoramic images and a LiDAR point cloud collected by a MMS. We first introduce the system configuration and specification, including the coordinate systems of the MMS, the 3D LiDAR scanners, and the two panoramic camera models. We then establish the line-based transformation model for the panoramic camera. Finally, the proposed registration method is evaluated for two types of camera models by visual inspection and quantitative comparison. The results demonstrate that the line-based registration method can significantly improve the alignment of the panoramic image and the LiDAR datasets under either the ideal spherical or the rigorous panoramic camera model, with the latter being more reliable. Full article
(This article belongs to the Section Remote Sensors)
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Open AccessArticle Matched Field Processing Based on Least Squares with a Small Aperture Hydrophone Array
Sensors 2017, 17(1), 71; doi:10.3390/s17010071
Received: 24 November 2016 / Revised: 20 December 2016 / Accepted: 27 December 2016 / Published: 30 December 2016
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Abstract
The receiver hydrophone array is the signal front-end and plays an important role in matched field processing, which usually covers the whole water column from the sea surface to the bottom. Such a large aperture array is very difficult to realize. To solve
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The receiver hydrophone array is the signal front-end and plays an important role in matched field processing, which usually covers the whole water column from the sea surface to the bottom. Such a large aperture array is very difficult to realize. To solve this problem, an approach called matched field processing based on least squares with a small aperture hydrophone array is proposed, which decomposes the received acoustic fields into depth function matrix and amplitudes of the normal modes at the beginning. Then all the mode amplitudes are estimated using the least squares in the sense of minimum norm, and the amplitudes estimated are used to recalculate the received acoustic fields of the small aperture array, which means the recalculated ones contain more environmental information. In the end, lots of numerical experiments with three small aperture arrays are processed in the classical shallow water, and the performance of matched field passive localization is evaluated. The results show that the proposed method can make the recalculated fields contain more acoustic information of the source, and the performance of matched field passive localization with small aperture array is improved, so the proposed algorithm is proved to be effective. Full article
(This article belongs to the Section Physical Sensors)
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Open AccessArticle High-Precision Registration of Point Clouds Based on Sphere Feature Constraints
Sensors 2017, 17(1), 72; doi:10.3390/s17010072
Received: 24 November 2016 / Revised: 22 December 2016 / Accepted: 27 December 2016 / Published: 30 December 2016
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Abstract
Point cloud registration is a key process in multi-view 3D measurements. Its precision affects the measurement precision directly. However, in the case of the point clouds with non-overlapping areas or curvature invariant surface, it is difficult to achieve a high precision. A high
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Point cloud registration is a key process in multi-view 3D measurements. Its precision affects the measurement precision directly. However, in the case of the point clouds with non-overlapping areas or curvature invariant surface, it is difficult to achieve a high precision. A high precision registration method based on sphere feature constraint is presented to overcome the difficulty in the paper. Some known sphere features with constraints are used to construct virtual overlapping areas. The virtual overlapping areas provide more accurate corresponding point pairs and reduce the influence of noise. Then the transformation parameters between the registered point clouds are solved by an optimization method with weight function. In that case, the impact of large noise in point clouds can be reduced and a high precision registration is achieved. Simulation and experiments validate the proposed method. Full article
(This article belongs to the Section Physical Sensors)
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Open AccessArticle Evaluation of Surface Cleaning Procedures in Terms of Gas Sensing Properties of Spray-Deposited CNT Film: Thermal- and O2 Plasma Treatments
Sensors 2017, 17(1), 73; doi:10.3390/s17010073
Received: 17 November 2016 / Revised: 15 December 2016 / Accepted: 22 December 2016 / Published: 30 December 2016
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Abstract
The effect of cleaning the surface of single-walled carbon nanotube (SWNT) networks by thermal and the O2 plasma treatments is presented in terms of NH3 gas sensing characteristics. The goal of this work is to determine the relationship between the physicochemical
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The effect of cleaning the surface of single-walled carbon nanotube (SWNT) networks by thermal and the O2 plasma treatments is presented in terms of NH3 gas sensing characteristics. The goal of this work is to determine the relationship between the physicochemical properties of the cleaned surface (including the chemical composition, crystal structure, hydrophilicity, and impurity content) and the sensitivity of the SWNT network films to NH3 gas. The SWNT networks are spray-deposited on pre-patterned Pt electrodes, and are further functionalized by heating on a programmable hot plate or by O2 plasma treatment in a laboratory-prepared plasma chamber. Cyclic voltammetry was employed to semi-quantitatively evaluate each surface state of various plasma-treated SWNT-based electrodes. The results show that O2 plasma treatment can more effectively modify the SWNT network surface than thermal cleaning, and can provide a better conductive network surface due to the larger number of carbonyl/carboxyl groups, enabling a faster electron transfer rate, even though both the thermal cleaning and the O2 plasma cleaning methods can eliminate the organic solvent residues from the network surface. The NH3 sensors based on the O2 plasma-treated SWNT network exhibit higher sensitivity, shorter response time, and better recovery of the initial resistance than those prepared employing the thermally-cleaned SWNT networks. Full article
(This article belongs to the Special Issue Chemiresistive Sensors)
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Open AccessArticle Estimation of Ground Reaction Forces and Moments During Gait Using Only Inertial Motion Capture
Sensors 2017, 17(1), 75; doi:10.3390/s17010075
Received: 29 September 2016 / Revised: 21 December 2016 / Accepted: 28 December 2016 / Published: 31 December 2016
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Abstract
Ground reaction forces and moments (GRF&M) are important measures used as input in biomechanical analysis to estimate joint kinetics, which often are used to infer information for many musculoskeletal diseases. Their assessment is conventionally achieved using laboratory-based equipment that cannot be applied in
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Ground reaction forces and moments (GRF&M) are important measures used as input in biomechanical analysis to estimate joint kinetics, which often are used to infer information for many musculoskeletal diseases. Their assessment is conventionally achieved using laboratory-based equipment that cannot be applied in daily life monitoring. In this study, we propose a method to predict GRF&M during walking, using exclusively kinematic information from fully-ambulatory inertial motion capture (IMC). From the equations of motion, we derive the total external forces and moments. Then, we solve the indeterminacy problem during double stance using a distribution algorithm based on a smooth transition assumption. The agreement between the IMC-predicted and reference GRF&M was categorized over normal walking speed as excellent for the vertical (ρ = 0.992, rRMSE = 5.3%), anterior (ρ = 0.965, rRMSE = 9.4%) and sagittal (ρ = 0.933, rRMSE = 12.4%) GRF&M components and as strong for the lateral (ρ = 0.862, rRMSE = 13.1%), frontal (ρ = 0.710, rRMSE = 29.6%), and transverse GRF&M (ρ = 0.826, rRMSE = 18.2%). Sensitivity analysis was performed on the effect of the cut-off frequency used in the filtering of the input kinematics, as well as the threshold velocities for the gait event detection algorithm. This study was the first to use only inertial motion capture to estimate 3D GRF&M during gait, providing comparable accuracy with optical motion capture prediction. This approach enables applications that require estimation of the kinetics during walking outside the gait laboratory. Full article
(This article belongs to the Special Issue Body Worn Behavior Sensing)
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Open AccessArticle Evaluating the More Suitable ISM Frequency Band for IoT-Based Smart Grids: A Quantitative Study of 915 MHz vs. 2400 MHz
Sensors 2017, 17(1), 76; doi:10.3390/s17010076
Received: 15 November 2016 / Revised: 19 December 2016 / Accepted: 28 December 2016 / Published: 31 December 2016
PDF Full-text (3875 KB)