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Sensors, Volume 17, Issue 11 (November 2017)

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Cover Story (view full-size image) Zhang and Or report a small-scale, standalone, and high-performance magnetoelectric (ME) transverse [...] Read more.
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Open AccessArticle Low Computational-Cost Footprint Deformities Diagnosis Sensor through Angles, Dimensions Analysis and Image Processing Techniques
Sensors 2017, 17(11), 2700; https://doi.org/10.3390/s17112700
Received: 19 October 2017 / Revised: 9 November 2017 / Accepted: 14 November 2017 / Published: 22 November 2017
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Abstract
Manual measurements of foot anthropometry can lead to errors since this task involves the experience of the specialist who performs them, resulting in different subjective measures from the same footprint. Moreover, some of the diagnoses that are given to classify a footprint deformity
[...] Read more.
Manual measurements of foot anthropometry can lead to errors since this task involves the experience of the specialist who performs them, resulting in different subjective measures from the same footprint. Moreover, some of the diagnoses that are given to classify a footprint deformity are based on a qualitative interpretation by the physician; there is no quantitative interpretation of the footprint. The importance of providing a correct and accurate diagnosis lies in the need to ensure that an appropriate treatment is provided for the improvement of the patient without risking his or her health. Therefore, this article presents a smart sensor that integrates the capture of the footprint, a low computational-cost analysis of the image and the interpretation of the results through a quantitative evaluation. The smart sensor implemented required the use of a camera (Logitech C920) connected to a Raspberry Pi 3, where a graphical interface was made for the capture and processing of the image, and it was adapted to a podoscope conventionally used by specialists such as orthopedist, physiotherapists and podiatrists. The footprint diagnosis smart sensor (FPDSS) has proven to be robust to different types of deformity, precise, sensitive and correlated in 0.99 with the measurements from the digitalized image of the ink mat. Full article
(This article belongs to the Special Issue Biomedical Sensors and Systems 2017)
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Open AccessArticle Pedestrian Detection with Semantic Regions of Interest
Sensors 2017, 17(11), 2699; https://doi.org/10.3390/s17112699
Received: 1 October 2017 / Revised: 16 November 2017 / Accepted: 16 November 2017 / Published: 22 November 2017
Cited by 1 | PDF Full-text (9872 KB) | HTML Full-text | XML Full-text
Abstract
For many pedestrian detectors, background vs. foreground errors heavily influence the detection quality. Our main contribution is to design semantic regions of interest that extract the foreground target roughly to reduce the background vs. foreground errors of detectors. First, we generate a pedestrian
[...] Read more.
For many pedestrian detectors, background vs. foreground errors heavily influence the detection quality. Our main contribution is to design semantic regions of interest that extract the foreground target roughly to reduce the background vs. foreground errors of detectors. First, we generate a pedestrian heat map from the input image with a full convolutional neural network trained on the Caltech Pedestrian Dataset. Next, semantic regions of interest are extracted from the heat map by morphological image processing. Finally, the semantic regions of interest divide the whole image into foreground and background to assist the decision-making of detectors. We test our approach on the Caltech Pedestrian Detection Benchmark. With the help of our semantic regions of interest, the effects of the detectors have varying degrees of improvement. The best one exceeds the state-of-the-art. Full article
(This article belongs to the Section Physical Sensors)
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Open AccessArticle Markerless Knee Joint Position Measurement Using Depth Data during Stair Walking
Sensors 2017, 17(11), 2698; https://doi.org/10.3390/s17112698
Received: 4 September 2017 / Revised: 28 October 2017 / Accepted: 21 November 2017 / Published: 22 November 2017
Cited by 1 | PDF Full-text (4889 KB) | HTML Full-text | XML Full-text
Abstract
Climbing and descending stairs are demanding daily activities, and the monitoring of them may reveal the presence of musculoskeletal diseases at an early stage. A markerless system is needed to monitor such stair walking activity without mentally or physically disturbing the subject. Microsoft
[...] Read more.
Climbing and descending stairs are demanding daily activities, and the monitoring of them may reveal the presence of musculoskeletal diseases at an early stage. A markerless system is needed to monitor such stair walking activity without mentally or physically disturbing the subject. Microsoft Kinect v2 has been used for gait monitoring, as it provides a markerless skeleton tracking function. However, few studies have used this device for stair walking monitoring, and the accuracy of its skeleton tracking function during stair walking has not been evaluated. Moreover, skeleton tracking is not likely to be suitable for estimating body joints during stair walking, as the form of the body is different from what it is when it walks on level surfaces. In this study, a new method of estimating the 3D position of the knee joint was devised that uses the depth data of Kinect v2. The accuracy of this method was compared with that of the skeleton tracking function of Kinect v2 by simultaneously measuring subjects with a 3D motion capture system. The depth data method was found to be more accurate than skeleton tracking. The mean error of the 3D Euclidian distance of the depth data method was 43.2 ± 27.5 mm, while that of the skeleton tracking was 50.4 ± 23.9 mm. This method indicates the possibility of stair walking monitoring for the early discovery of musculoskeletal diseases. Full article
(This article belongs to the Section Physical Sensors)
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Open AccessArticle Optimal Pricing and Power Allocation for Collaborative Jamming with Full Channel Knowledge in Wireless Sensor Networks
Sensors 2017, 17(11), 2697; https://doi.org/10.3390/s17112697
Received: 18 October 2017 / Revised: 16 November 2017 / Accepted: 19 November 2017 / Published: 22 November 2017
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Abstract
This paper presents a price-searching model in which a source node (Alice) seeks friendly jammers that prevent eavesdroppers (Eves) from snooping legitimate communications by generating interference or noise. Unlike existing models, the distributed jammers also have data to send to their respective destinations
[...] Read more.
This paper presents a price-searching model in which a source node (Alice) seeks friendly jammers that prevent eavesdroppers (Eves) from snooping legitimate communications by generating interference or noise. Unlike existing models, the distributed jammers also have data to send to their respective destinations and are allowed to access Alice’s channel if it can transmit sufficient jamming power, which is referred to as collaborative jamming in this paper. For the power used to deliver its own signal, the jammer should pay Alice. The price of the jammers’ signal power is set by Alice and provides a tradeoff between the signal and the jamming power. This paper presents, in closed-form, an optimal price that maximizes Alice’s benefit and the corresponding optimal power allocation from a jammers’ perspective by assuming that the network-wide channel knowledge is shared by Alice and jammers. For a multiple-jammer scenario where Alice hardly has the channel knowledge, this paper provides a distributed and interactive price-searching procedure that geometrically converges to an optimal price and shows that Alice by a greedy selection policy achieves certain diversity gain, which increases log-linearly as the number of (potential) jammers grows. Various numerical examples are presented to illustrate the behavior of the proposed model. Full article
(This article belongs to the Special Issue Sensor Networks for Collaborative and Secure Internet of Things)
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Open AccessArticle An Optical Interferometric Triaxial Displacement Sensor for Structural Health Monitoring: Characterization of Sliding and Debonding for a Delamination Process
Sensors 2017, 17(11), 2696; https://doi.org/10.3390/s17112696
Received: 30 October 2017 / Revised: 12 November 2017 / Accepted: 21 November 2017 / Published: 22 November 2017
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Abstract
This paper presents an extrinsic Fabry–Perot interferometer-based optical fiber sensor (EFPI) for measuring three-dimensional (3D) displacements, including interfacial sliding and debonding during delamination. The idea employs three spatially arranged EFPIs as the sensing elements. In our sensor, the three EFPIs are formed by
[...] Read more.
This paper presents an extrinsic Fabry–Perot interferometer-based optical fiber sensor (EFPI) for measuring three-dimensional (3D) displacements, including interfacial sliding and debonding during delamination. The idea employs three spatially arranged EFPIs as the sensing elements. In our sensor, the three EFPIs are formed by three endfaces of three optical fibers and their corresponding inclined mirrors. Two coincident roof-like metallic structures are used to support the three fibers and the three mirrors, respectively. Our sensor was calibrated and then used to monitor interfacial sliding and debonding between a long square brick of mortar and its support structure (i.e., a steel base plate) during the drying/curing process. This robust and easy-to-manufacture triaxial EFPI-based 3D displacement sensor has great potential in structural health monitoring, the construction industry, oil well monitoring, and geotechnology. Full article
(This article belongs to the Section Physical Sensors)
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Open AccessArticle A Novel 3D Pedestrian Navigation Method for a Multiple Sensors-Based Foot-Mounted Inertial System
Sensors 2017, 17(11), 2695; https://doi.org/10.3390/s17112695
Received: 19 September 2017 / Revised: 3 November 2017 / Accepted: 17 November 2017 / Published: 22 November 2017
Cited by 1 | PDF Full-text (13720 KB) | HTML Full-text | XML Full-text
Abstract
In this paper, we present a novel method for 3D pedestrian navigation of foot-mounted inertial systems by integrating a MEMS-IMU, barometer, and permanent magnet. Zero-velocity update (ZUPT) is a well-known algorithm to eliminate the accumulated error of foot-mounted inertial systems. However, the ZUPT
[...] Read more.
In this paper, we present a novel method for 3D pedestrian navigation of foot-mounted inertial systems by integrating a MEMS-IMU, barometer, and permanent magnet. Zero-velocity update (ZUPT) is a well-known algorithm to eliminate the accumulated error of foot-mounted inertial systems. However, the ZUPT stance phase detector using acceleration and angular rate is threshold-based, which may cause incorrect stance phase estimation in the running gait pattern. A permanent magnet-based ZUPT detector is introduced to solve this problem. Peaks extracted from the magnetic field strength waveform are mid-stances of stance phases. A model of peak-peak information and stance phase duration is developed to have a quantitative calculation method of stance phase duration in different movement patterns. Height estimation using barometer is susceptible to the environment. A height difference information aided barometer (HDIB) algorithm integrating MEMS-IMU and barometer is raised to have a better height estimation. The first stage of HDIB is to distinguish level ground/upstairs/downstairs and the second stage is to calculate height using reference atmospheric pressure obtained from the first stage. At last, a ZUPT-based adaptive average window length algorithm (ZUPT-AAWL) is proposed to calculate the true total travelled distance to have a more accurate percentage error (TTDE). This proposed method is verified via multiple experiments. Numerical results show that TTDE ranges from 0.32% to 1.04% in both walking and running gait patterns, and the height estimation error is from 0 m to 2.35 m. Full article
(This article belongs to the Section Physical Sensors)
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Open AccessArticle A Collaboration-Oriented M2M Messaging Mechanism for the Collaborative Automation between Machines in Future Industrial Networks
Sensors 2017, 17(11), 2694; https://doi.org/10.3390/s17112694
Received: 10 September 2017 / Revised: 9 November 2017 / Accepted: 13 November 2017 / Published: 22 November 2017
Cited by 1 | PDF Full-text (2726 KB) | HTML Full-text | XML Full-text
Abstract
Machine-to-machine (M2M) communication is a key enabling technology for industrial internet of things (IIoT)-empowered industrial networks, where machines communicate with one another for collaborative automation and intelligent optimisation. This new industrial computing paradigm features high-quality connectivity, ubiquitous messaging, and interoperable interactions between machines.
[...] Read more.
Machine-to-machine (M2M) communication is a key enabling technology for industrial internet of things (IIoT)-empowered industrial networks, where machines communicate with one another for collaborative automation and intelligent optimisation. This new industrial computing paradigm features high-quality connectivity, ubiquitous messaging, and interoperable interactions between machines. However, manufacturing IIoT applications have specificities that distinguish them from many other internet of things (IoT) scenarios in machine communications. By highlighting the key requirements and the major technical gaps of M2M in industrial applications, this article describes a collaboration-oriented M2M (CoM2M) messaging mechanism focusing on flexible connectivity and discovery, ubiquitous messaging, and semantic interoperability that are well suited for the production line-scale interoperability of manufacturing applications. The designs toward machine collaboration and data interoperability at both the communication and semantic level are presented. Then, the application scenarios of the presented methods are illustrated with a proof-of-concept implementation in the PicknPack food packaging line. Eventually, the advantages and some potential issues are discussed based on the PicknPack practice. Full article
(This article belongs to the Special Issue Smart Industrial Wireless Sensor Networks)
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Open AccessArticle Comparison of Benchtop Fourier-Transform (FT) and Portable Grating Scanning Spectrometers for Determination of Total Soluble Solid Contents in Single Grape Berry (Vitis vinifera L.) and Calibration Transfer
Sensors 2017, 17(11), 2693; https://doi.org/10.3390/s17112693
Received: 5 November 2017 / Revised: 16 November 2017 / Accepted: 17 November 2017 / Published: 22 November 2017
Cited by 3 | PDF Full-text (1782 KB) | HTML Full-text | XML Full-text
Abstract
Near-infrared (NIR) spectroscopy was applied for the determination of total soluble solid contents (SSC) of single Ruby Seedless grape berries using both benchtop Fourier transform (VECTOR 22/N) and portable grating scanning (SupNIR-1500) spectrometers in this study. The results showed that the best SSC
[...] Read more.
Near-infrared (NIR) spectroscopy was applied for the determination of total soluble solid contents (SSC) of single Ruby Seedless grape berries using both benchtop Fourier transform (VECTOR 22/N) and portable grating scanning (SupNIR-1500) spectrometers in this study. The results showed that the best SSC prediction was obtained by VECTOR 22/N in the range of 12,000 to 4000 cm−1 (833–2500 nm) for Ruby Seedless with determination coefficient of prediction (Rp2) of 0.918, root mean squares error of prediction (RMSEP) of 0.758% based on least squares support vector machine (LS-SVM). Calibration transfer was conducted on the same spectral range of two instruments (1000–1800 nm) based on the LS-SVM model. By conducting Kennard-Stone (KS) to divide sample sets, selecting the optimal number of standardization samples and applying Passing-Bablok regression to choose the optimal instrument as the master instrument, a modified calibration transfer method between two spectrometers was developed. When 45 samples were selected for the standardization set, the linear interpolation-piecewise direct standardization (linear interpolation-PDS) performed well for calibration transfer with Rp2 of 0.857 and RMSEP of 1.099% in the spectral region of 1000–1800 nm. And it was proved that re-calculating the standardization samples into master model could improve the performance of calibration transfer in this study. This work indicated that NIR could be used as a rapid and non-destructive method for SSC prediction, and provided a feasibility to solve the transfer difficulty between totally different NIR spectrometers. Full article
(This article belongs to the Special Issue Signal and Information Processing in Chemical Sensing)
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Open AccessArticle An Orientation Sensor-Based Head Tracking System for Driver Behaviour Monitoring
Sensors 2017, 17(11), 2692; https://doi.org/10.3390/s17112692
Received: 16 October 2017 / Revised: 17 November 2017 / Accepted: 18 November 2017 / Published: 22 November 2017
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Abstract
Although at present legislation does not allow drivers in a Level 3 autonomous vehicle to engage in a secondary task, there may become a time when it does. Monitoring the behaviour of drivers engaging in various non-driving activities (NDAs) is crucial to decide
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Although at present legislation does not allow drivers in a Level 3 autonomous vehicle to engage in a secondary task, there may become a time when it does. Monitoring the behaviour of drivers engaging in various non-driving activities (NDAs) is crucial to decide how well the driver will be able to take over control of the vehicle. One limitation of the commonly used face-based head tracking system, using cameras, is that sufficient features of the face must be visible, which limits the detectable angle of head movement and thereby measurable NDAs, unless multiple cameras are used. This paper proposes a novel orientation sensor based head tracking system that includes twin devices, one of which measures the movement of the vehicle while the other measures the absolute movement of the head. Measurement error in the shaking and nodding axes were less than 0.4°, while error in the rolling axis was less than 2°. Comparison with a camera-based system, through in-house tests and on-road tests, showed that the main advantage of the proposed system is the ability to detect angles larger than 20° in the shaking and nodding axes. Finally, a case study demonstrated that the measurement of the shaking and nodding angles, produced from the proposed system, can effectively characterise the drivers’ behaviour while engaged in the NDAs of chatting to a passenger and playing on a smartphone. Full article
(This article belongs to the Special Issue Sensors for Transportation)
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Open AccessArticle Dielectrophoretic Separation of Live and Dead Monocytes Using 3D Carbon-Electrodes
Sensors 2017, 17(11), 2691; https://doi.org/10.3390/s17112691
Received: 19 October 2017 / Revised: 7 November 2017 / Accepted: 13 November 2017 / Published: 22 November 2017
Cited by 1 | PDF Full-text (797 KB) | HTML Full-text | XML Full-text | Supplementary Files
Abstract
Blood has been the most reliable body fluid commonly used for the diagnosis of diseases. Although there have been promising investigations for the development of novel lab-on-a-chip devices to utilize other body fluids such as urine and sweat samples in diagnosis, their stability
[...] Read more.
Blood has been the most reliable body fluid commonly used for the diagnosis of diseases. Although there have been promising investigations for the development of novel lab-on-a-chip devices to utilize other body fluids such as urine and sweat samples in diagnosis, their stability remains a problem that limits the reliability and accuracy of readouts. Hence, accurate and quantitative separation and characterization of blood cells are still crucial. The first step in achieving high-resolution characteristics for specific cell subpopulations from the whole blood is the isolation of pure cell populations from a mixture of cell suspensions. Second, live cells need to be purified from dead cells; otherwise, dead cells might introduce biases in the measurements. In addition, the separation and characterization methods being used must preserve the genetic and phenotypic properties of the cells. Among the characterization and separation approaches, dielectrophoresis (DEP) is one of the oldest and most efficient label-free quantification methods, which directly purifies and characterizes cells using their intrinsic, physical properties. In this study, we present the dielectrophoretic separation and characterization of live and dead monocytes using 3D carbon-electrodes. Our approach successfully removed the dead monocytes while preserving the viability of the live monocytes. Therefore, when blood analyses and disease diagnosis are performed with enriched, live monocyte populations, this approach will reduce the dead-cell contamination risk and achieve more reliable and accurate test results. Full article
(This article belongs to the Special Issue Bio-MEMS for Precision Medicine)
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Open AccessArticle Development and Validation of an On-Line Water Toxicity Sensor with Immobilized Luminescent Bacteria for On-Line Surface Water Monitoring
Sensors 2017, 17(11), 2682; https://doi.org/10.3390/s17112682
Received: 17 October 2017 / Revised: 14 November 2017 / Accepted: 14 November 2017 / Published: 22 November 2017
PDF Full-text (2649 KB) | HTML Full-text | XML Full-text | Supplementary Files
Abstract
Surface water used for drinking water production is frequently monitored in The Netherlands using whole organism biomonitors, with for example Daphnia magna or Dreissena mussels, which respond to changes in the water quality. However, not all human-relevant toxic compounds can be detected by
[...] Read more.
Surface water used for drinking water production is frequently monitored in The Netherlands using whole organism biomonitors, with for example Daphnia magna or Dreissena mussels, which respond to changes in the water quality. However, not all human-relevant toxic compounds can be detected by these biomonitors. Therefore, a new on-line biosensor has been developed, containing immobilized genetically modified bacteria, which respond to genotoxicity in the water by emitting luminescence. The performance of this sensor was tested under laboratory conditions, as well as under field conditions at a monitoring station along the river Meuse in The Netherlands. The sensor was robust and easy to clean, with inert materials, temperature control and nutrient feed for the reporter organisms. The bacteria were immobilized in sol-gel on either an optical fiber or a glass slide and then continuously exposed to water. Since the glass slide was more sensitive and robust, only this setup was used in the field. The sensor responded to spikes of genotoxic compounds in the water with a minimal detectable concentration of 0.01 mg/L mitomycin C in the laboratory and 0.1 mg/L mitomycin C in the field. With further optimization, which should include a reduction in daily maintenance, the sensor has the potential to become a useful addition to the currently available biomonitors. Full article
(This article belongs to the Special Issue Sensors for Toxic and Pathogen Detection)
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Open AccessArticle Target Tracking with Sensor Navigation Using Coupled RSS and AoA Measurements
Sensors 2017, 17(11), 2690; https://doi.org/10.3390/s17112690
Received: 20 October 2017 / Revised: 10 November 2017 / Accepted: 16 November 2017 / Published: 21 November 2017
Cited by 2 | PDF Full-text (1143 KB) | HTML Full-text | XML Full-text
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This work addresses the problem of tracking a signal-emitting mobile target in wireless sensor networks (WSNs) with navigated mobile sensors. The sensors are properly equipped to acquire received signal strength (RSS) and angle of arrival (AoA) measurements from the received signal, while the
[...] Read more.
This work addresses the problem of tracking a signal-emitting mobile target in wireless sensor networks (WSNs) with navigated mobile sensors. The sensors are properly equipped to acquire received signal strength (RSS) and angle of arrival (AoA) measurements from the received signal, while the target transmit power is assumed not known. We start by showing how to linearize the highly non-linear measurement model. Then, by employing a Bayesian approach, we combine the linearized observation model with prior knowledge extracted from the state transition model. Based on the maximum a posteriori (MAP) principle and the Kalman filtering (KF) framework, we propose new MAP and KF algorithms, respectively. We also propose a simple and efficient mobile sensor navigation procedure, which allows us to further enhance the estimation accuracy of our algorithms with a reduced number of sensors. Model flaws, which result in imperfect knowledge about the path loss exponent (PLE) and the true mobile sensors’ locations, are taken into consideration. We have carried out an extensive simulation study, and our results confirm the superiority of the proposed algorithms, as well as the effectiveness of the proposed navigation routine. Full article
(This article belongs to the Section Physical Sensors)
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Open AccessReview Selectivity/Specificity Improvement Strategies in Surface-Enhanced Raman Spectroscopy Analysis
Sensors 2017, 17(11), 2689; https://doi.org/10.3390/s17112689
Received: 28 September 2017 / Revised: 31 October 2017 / Accepted: 12 November 2017 / Published: 21 November 2017
Cited by 3 | PDF Full-text (32795 KB) | HTML Full-text | XML Full-text
Abstract
Surface-enhanced Raman spectroscopy (SERS) is a powerful technique for the discrimination, identification, and potential quantification of certain compounds/organisms. However, its real application is challenging due to the multiple interference from the complicated detection matrix. Therefore, selective/specific detection is crucial for the real application
[...] Read more.
Surface-enhanced Raman spectroscopy (SERS) is a powerful technique for the discrimination, identification, and potential quantification of certain compounds/organisms. However, its real application is challenging due to the multiple interference from the complicated detection matrix. Therefore, selective/specific detection is crucial for the real application of SERS technique. We summarize in this review five selective/specific detection techniques (chemical reaction, antibody, aptamer, molecularly imprinted polymers and microfluidics), which can be applied for the rapid and reliable selective/specific detection when coupled with SERS technique. Full article
(This article belongs to the Special Issue Surface Plasmon Resonance Sensing)
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Open AccessArticle A Similarity Analysis of Audio Signal to Develop a Human Activity Recognition Using Similarity Networks
Sensors 2017, 17(11), 2688; https://doi.org/10.3390/s17112688
Received: 14 September 2017 / Revised: 1 November 2017 / Accepted: 16 November 2017 / Published: 21 November 2017
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Abstract
Human Activity Recognition (HAR) is one of the main subjects of study in the areas of computer vision and machine learning due to the great benefits that can be achieved. Examples of the study areas are: health prevention, security and surveillance, automotive research,
[...] Read more.
Human Activity Recognition (HAR) is one of the main subjects of study in the areas of computer vision and machine learning due to the great benefits that can be achieved. Examples of the study areas are: health prevention, security and surveillance, automotive research, and many others. The proposed approaches are carried out using machine learning techniques and present good results. However, it is difficult to observe how the descriptors of human activities are grouped. In order to obtain a better understanding of the the behavior of descriptors, it is important to improve the abilities to recognize the human activities. This paper proposes a novel approach for the HAR based on acoustic data and similarity networks. In this approach, we were able to characterize the sound of the activities and identify those activities looking for similarity in the sound pattern. We evaluated the similarity of the sounds considering mainly two features: the sound location and the materials that were used. As a result, the materials are a good reference classifying the human activities compared with the location. Full article
(This article belongs to the Section Sensor Networks)
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Open AccessArticle Study and Validation of Eavesdropping Scenarios over a Visible Light Communication Channel
Sensors 2017, 17(11), 2687; https://doi.org/10.3390/s17112687
Received: 3 October 2017 / Revised: 10 November 2017 / Accepted: 17 November 2017 / Published: 21 November 2017
Cited by 1 | PDF Full-text (4084 KB) | HTML Full-text | XML Full-text
Abstract
The security and privacy provided by Visible Light Communication (VLC) technologies is an area that has been slightly addressed due to the misconception that, since light does not go through solid objects like walls, VLC-based communications cannot be eavesdropped on by outside observers.
[...] Read more.
The security and privacy provided by Visible Light Communication (VLC) technologies is an area that has been slightly addressed due to the misconception that, since light does not go through solid objects like walls, VLC-based communications cannot be eavesdropped on by outside observers. As an upcoming technology, VLC is expected to be used in multiple environments were, due to radio frequency RF overuse or limitations, RF solutions cannot or should not be employed. In this work, we study the eavesdropping characteristics of a VLC-based communication. To evaluate these concerns, a two-step process was followed. First, several simulations of a standardly used scenario were run. Later on, experimental tests were performed. Following those tests, the results of the simulations and the experimental tests were analyzed. The results of these simulations and tests seemed to indicate that VLC channels can be eavesdropped on without considerable difficulties. Furthermore, the results showed that sniffing attacks could be performed from areas outside the expected coverage of the VLC infrastructure. Finally, the use of the simulation such as the one implemented in this work to recognize places from which sniffing is possible helps determine the risk for eavesdropping that our VLC-based network has. Full article
(This article belongs to the Special Issue Visible Light Communication Networks)
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