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Sensors, Volume 16, Issue 10 (October 2016) – 223 articles

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4480 KiB  
Article
Geometric Calibration and Validation of Kompsat-3A AEISS-A Camera
by Doocheon Seo, Jaehong Oh, Changno Lee, Donghan Lee and Haejin Choi
Sensors 2016, 16(10), 1776; https://doi.org/10.3390/s16101776 - 24 Oct 2016
Cited by 16 | Viewed by 7284
Abstract
Kompsat-3A, which was launched on 25 March 2015, is a sister spacecraft of the Kompsat-3 developed by the Korea Aerospace Research Institute (KARI). Kompsat-3A’s AEISS-A (Advanced Electronic Image Scanning System-A) camera is similar to Kompsat-3’s AEISS but it was designed to provide PAN [...] Read more.
Kompsat-3A, which was launched on 25 March 2015, is a sister spacecraft of the Kompsat-3 developed by the Korea Aerospace Research Institute (KARI). Kompsat-3A’s AEISS-A (Advanced Electronic Image Scanning System-A) camera is similar to Kompsat-3’s AEISS but it was designed to provide PAN (Panchromatic) resolution of 0.55 m, MS (multispectral) resolution of 2.20 m, and TIR (thermal infrared) at 5.5 m resolution. In this paper we present the geometric calibration and validation work of Kompsat-3A that was completed last year. A set of images over the test sites was taken for two months and was utilized for the work. The workflow includes the boresight calibration, CCDs (charge-coupled devices) alignment and focal length determination, the merge of two CCD lines, and the band-to-band registration. Then, the positional accuracies without any GCPs (ground control points) were validated for hundreds of test sites across the world using various image acquisition modes. In addition, we checked the planimetric accuracy by bundle adjustments with GCPs. Full article
(This article belongs to the Special Issue Imaging: Sensors and Technologies)
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2611 KiB  
Article
Optical Fiber Temperature and Torsion Sensor Based on Lyot-Sagnac Interferometer
by Li-Yang Shao, Xinpu Zhang, Haijun He, Zhiyong Zhang, Xihua Zou, Bin Luo, Wei Pan and Lianshan Yan
Sensors 2016, 16(10), 1774; https://doi.org/10.3390/s16101774 - 24 Oct 2016
Cited by 28 | Viewed by 6385
Abstract
An optical fiber temperature and torsion sensor has been proposed by employing the Lyot-Sagnac interferometer, which was composed by inserting two sections of high-birefringence (HiBi) fiber into the Sagnac loop. The two inserted sections of HiBi fiber have different functions; while one section [...] Read more.
An optical fiber temperature and torsion sensor has been proposed by employing the Lyot-Sagnac interferometer, which was composed by inserting two sections of high-birefringence (HiBi) fiber into the Sagnac loop. The two inserted sections of HiBi fiber have different functions; while one section acts as the temperature sensitive region, the other can be used as reference fiber. The temperature and twist sensor based on the proposed interferometer structure have been experimentally demonstrated. The experimental results show that the envelope of the output spectrum will shift with the temperature evolution. The temperature sensitivity is calculated to be −17.99 nm/°C, which is enlarged over 12 times compared to that of the single Sagnac interferometer. Additionally, the fringe visibility of the spectrum will change due to the fiber twist, and the test results reveal that the fringe visibility and twist angle perfectly conform to a Sine relationship over a 360° twist angle. Consequently, simultaneous torsion and temperature measurement could be realized by detecting the envelope shift and fringe visibility of the spectrum. Full article
(This article belongs to the Section Physical Sensors)
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2854 KiB  
Article
Sparse Reconstruction for Micro Defect Detection in Acoustic Micro Imaging
by Yichun Zhang, Tielin Shi, Lei Su, Xiao Wang, Yuan Hong, Kepeng Chen and Guanglan Liao
Sensors 2016, 16(10), 1773; https://doi.org/10.3390/s16101773 - 24 Oct 2016
Cited by 9 | Viewed by 5608
Abstract
Acoustic micro imaging has been proven to be sufficiently sensitive for micro defect detection. In this study, we propose a sparse reconstruction method for acoustic micro imaging. A finite element model with a micro defect is developed to emulate the physical scanning. Then [...] Read more.
Acoustic micro imaging has been proven to be sufficiently sensitive for micro defect detection. In this study, we propose a sparse reconstruction method for acoustic micro imaging. A finite element model with a micro defect is developed to emulate the physical scanning. Then we obtain the point spread function, a blur kernel for sparse reconstruction. We reconstruct deblurred images from the oversampled C-scan images based on l1-norm regularization, which can enhance the signal-to-noise ratio and improve the accuracy of micro defect detection. The method is further verified by experimental data. The results demonstrate that the sparse reconstruction is effective for micro defect detection in acoustic micro imaging. Full article
(This article belongs to the Special Issue Ultrasonic Sensors)
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597 KiB  
Article
SNR Degradation in Undersampled Phase Measurement Systems
by David Salido-Monzú, Francisco J. Meca-Meca, Ernesto Martín-Gorostiza and José L. Lázaro-Galilea
Sensors 2016, 16(10), 1772; https://doi.org/10.3390/s16101772 - 24 Oct 2016
Cited by 10 | Viewed by 4965
Abstract
A wide range of measuring applications rely on phase estimation on sinusoidal signals. These systems, where the estimation is mainly implemented in the digital domain, can generally benefit from the use of undersampling to reduce the digitizer and subsequent digital processing requirements. This [...] Read more.
A wide range of measuring applications rely on phase estimation on sinusoidal signals. These systems, where the estimation is mainly implemented in the digital domain, can generally benefit from the use of undersampling to reduce the digitizer and subsequent digital processing requirements. This may be crucial when the application characteristics necessarily imply a simple and inexpensive sensor. However, practical limitations related to the phase stability of the band-pass filter prior digitization establish restrictions to the reduction of noise bandwidth. Due to this, the undersampling intensity is practically defined by noise aliasing, taking into account the amount of signal-to-noise ratio (SNR) reduction caused by it considering the application accuracy requirements. This work analyzes the relationship between undersampling frequency and SNR reduction, conditioned by the stability requirements of the filter that defines the noise bandwidth before digitization. The effect of undersampling is quantified in a practical situation where phase differences are measured by in-phase and quadrature (I/Q) demodulation for an infrared ranging application. Full article
(This article belongs to the Section Physical Sensors)
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2326 KiB  
Article
Development of an FBG Sensor Array for Multi-Impact Source Localization on CFRP Structures
by Mingshun Jiang, Yaozhang Sai, Xiangyi Geng, Qingmei Sui, Xiaohui Liu and Lei Jia
Sensors 2016, 16(10), 1770; https://doi.org/10.3390/s16101770 - 24 Oct 2016
Cited by 8 | Viewed by 4664
Abstract
We proposed and studied an impact detection system based on a fiber Bragg grating (FBG) sensor array and multiple signal classification (MUSIC) algorithm to determine the location and the number of low velocity impacts on a carbon fiber-reinforced polymer (CFRP) plate. A FBG [...] Read more.
We proposed and studied an impact detection system based on a fiber Bragg grating (FBG) sensor array and multiple signal classification (MUSIC) algorithm to determine the location and the number of low velocity impacts on a carbon fiber-reinforced polymer (CFRP) plate. A FBG linear array, consisting of seven FBG sensors, was used for detecting the ultrasonic signals from impacts. The edge-filter method was employed for signal demodulation. Shannon wavelet transform was used to extract narrow band signals from the impacts. The Gerschgorin disc theorem was used for estimating the number of impacts. We used the MUSIC algorithm to obtain the coordinates of multi-impacts. The impact detection system was tested on a 500 mm × 500 mm × 1.5 mm CFRP plate. The results show that the maximum error and average error of the multi-impacts’ localization are 9.2 mm and 7.4 mm, respectively. Full article
(This article belongs to the Section Physical Sensors)
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5466 KiB  
Article
GNSS Spoofing Network Monitoring Based on Differential Pseudorange
by Zhenjun Zhang and Xingqun Zhan
Sensors 2016, 16(10), 1771; https://doi.org/10.3390/s16101771 - 23 Oct 2016
Cited by 19 | Viewed by 6066
Abstract
Spoofing is becoming a serious threat to various Global Navigation Satellite System (GNSS) applications, especially for those that require high reliability and security such as power grid synchronization and applications related to first responders and aviation safety. Most current works on anti-spoofing focus [...] Read more.
Spoofing is becoming a serious threat to various Global Navigation Satellite System (GNSS) applications, especially for those that require high reliability and security such as power grid synchronization and applications related to first responders and aviation safety. Most current works on anti-spoofing focus on spoofing detection from the individual receiver side, which identifies spoofing when it is under an attack. This paper proposes a novel spoofing network monitoring (SNM) mechanism aiming to reveal the presence of spoofing within an area. Consisting of several receivers and one central processing component, it keeps detecting spoofing even when the network is not attacked. The mechanism is based on the different time difference of arrival (TDOA) properties between spoofing and authentic signals. Normally, TDOAs of spoofing signals from a common spoofer are identical while those of authentic signals from diverse directions are dispersed. The TDOA is measured as the differential pseudorange to carrier frequency ratio (DPF). In a spoofing case, the DPFs include those of both authentic and spoofing signals, among which the DPFs of authentic are dispersed while those of spoofing are almost overlapped. An algorithm is proposed to search for the DPFs that are within a pre-defined small range, and an alarm will be raised if several DPFs are found within such range. The proposed SNM methodology is validated by simulations and a partial field trial. Results show 99.99% detection and 0.01% false alarm probabilities are achieved. The SNM has the potential to be adopted in various applications such as (1) alerting dedicated users when spoofing is occurring, which could significantly shorten the receiver side spoofing cost; (2) in combination with GNSS performance monitoring systems, such as the Continuous Operating Reference System (CORS) and GNSS Availability, Accuracy, Reliability anD Integrity Assessment for Timing and Navigation (GAARDIAN) System, to provide more reliable monitoring services. Full article
(This article belongs to the Special Issue Advances in Multi-Sensor Information Fusion: Theory and Applications)
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4984 KiB  
Article
Underwater Communications for Video Surveillance Systems at 2.4 GHz
by Sandra Sendra, Jaime Lloret, Jose Miguel Jimenez and Joel J.P.C. Rodrigues
Sensors 2016, 16(10), 1769; https://doi.org/10.3390/s16101769 - 23 Oct 2016
Cited by 16 | Viewed by 7155
Abstract
Video surveillance is needed to control many activities performed in underwater environments. The use of wired media can be a problem since the material specially designed for underwater environments is very expensive. In order to transmit the images and videos wirelessly under water, [...] Read more.
Video surveillance is needed to control many activities performed in underwater environments. The use of wired media can be a problem since the material specially designed for underwater environments is very expensive. In order to transmit the images and videos wirelessly under water, three main technologies can be used: acoustic waves, which do not provide high bandwidth, optical signals, although the effect of light dispersion in water severely penalizes the transmitted signals and therefore, despite offering high transfer rates, the maximum distance is very small, and electromagnetic (EM) waves, which can provide enough bandwidth for video delivery. In the cases where the distance between transmitter and receiver is short, the use of EM waves would be an interesting option since they provide high enough data transfer rates to transmit videos with high resolution. This paper presents a practical study of the behavior of EM waves at 2.4 GHz in freshwater underwater environments. First, we discuss the minimum requirements of a network to allow video delivery. From these results, we measure the maximum distance between nodes and the round trip time (RTT) value depending on several parameters such as data transfer rate, signal modulations, working frequency, and water temperature. The results are statistically analyzed to determine their relation. Finally, the EM waves’ behavior is modeled by a set of equations. The results show that there are some combinations of working frequency, modulation, transfer rate and temperature that offer better results than others. Our work shows that short communication distances with high data transfer rates is feasible. Full article
(This article belongs to the Special Issue Underwater Sensor Nodes and Underwater Sensor Networks)
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5933 KiB  
Article
An Improved Map-Matching Technique Based on the Fréchet Distance Approach for Pedestrian Navigation Services
by Yoonsik Bang, Jiyoung Kim and Kiyun Yu
Sensors 2016, 16(10), 1768; https://doi.org/10.3390/s16101768 - 22 Oct 2016
Cited by 22 | Viewed by 7571
Abstract
Wearable and smartphone technology innovations have propelled the growth of Pedestrian Navigation Services (PNS). PNS need a map-matching process to project a user’s locations onto maps. Many map-matching techniques have been developed for vehicle navigation services. These techniques are inappropriate for PNS because [...] Read more.
Wearable and smartphone technology innovations have propelled the growth of Pedestrian Navigation Services (PNS). PNS need a map-matching process to project a user’s locations onto maps. Many map-matching techniques have been developed for vehicle navigation services. These techniques are inappropriate for PNS because pedestrians move, stop, and turn in different ways compared to vehicles. In addition, the base map data for pedestrians are more complicated than for vehicles. This article proposes a new map-matching method for locating Global Positioning System (GPS) trajectories of pedestrians onto road network datasets. The theory underlying this approach is based on the Fréchet distance, one of the measures of geometric similarity between two curves. The Fréchet distance approach can provide reasonable matching results because two linear trajectories are parameterized with the time variable. Then we improved the method to be adaptive to the positional error of the GPS signal. We used an adaptation coefficient to adjust the search range for every input signal, based on the assumption of auto-correlation between consecutive GPS points. To reduce errors in matching, the reliability index was evaluated in real time for each match. To test the proposed map-matching method, we applied it to GPS trajectories of pedestrians and the road network data. We then assessed the performance by comparing the results with reference datasets. Our proposed method performed better with test data when compared to a conventional map-matching technique for vehicles. Full article
(This article belongs to the Section Physical Sensors)
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2274 KiB  
Article
A Nanoporous Alumina Membrane Based Electrochemical Biosensor for Histamine Determination with Biofunctionalized Magnetic Nanoparticles Concentration and Signal Amplification
by Weiwei Ye, Yifan Xu, Lihao Zheng, Yu Zhang, Mo Yang and Peilong Sun
Sensors 2016, 16(10), 1767; https://doi.org/10.3390/s16101767 - 22 Oct 2016
Cited by 39 | Viewed by 7602
Abstract
Histamine is an indicator of food quality and indispensable in the efficient functioning of various physiological systems. Rapid and sensitive determination of histamine is urgently needed in food analysis and clinical diagnostics. Traditional histamine detection methods require qualified personnel, need complex operation processes, [...] Read more.
Histamine is an indicator of food quality and indispensable in the efficient functioning of various physiological systems. Rapid and sensitive determination of histamine is urgently needed in food analysis and clinical diagnostics. Traditional histamine detection methods require qualified personnel, need complex operation processes, and are time-consuming. In this study, a biofunctionalized nanoporous alumina membrane based electrochemical biosensor with magnetic nanoparticles (MNPs) concentration and signal amplification was developed for histamine determination. Nanoporous alumina membranes were modified by anti-histamine antibody and integrated into polydimethylsiloxane (PDMS) chambers. The specific antibody modified MNPs were used to concentrate histamine from samples and transferred to the antibody modified nanoporous membrane. The MNPs conjugated to histamine were captured in the nanopores via specific reaction between histamine and anti-histamine antibody, resulting in a blocking effect that was amplified by MNPs in the nanopores. The blockage signals could be measured by electrochemical impedance spectroscopy across the nanoporous alumina membrane. The sensing platform had great sensitivity and the limit of detection (LOD) reached as low as 3 nM. This biosensor could be successfully applied for histamine determination in saury that was stored in frozen conditions for different hours, presenting a potentially novel, sensitive, and specific sensing system for food quality assessment and safety support. Full article
(This article belongs to the Special Issue Nanobiosensors in Food Industry)
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5264 KiB  
Article
Plantar Pressure Detection with Fiber Bragg Gratings Sensing System
by Tsair-Chun Liang, Jhe-Jhun Lin and Lan-Yuen Guo
Sensors 2016, 16(10), 1766; https://doi.org/10.3390/s16101766 - 22 Oct 2016
Cited by 37 | Viewed by 10028
Abstract
In this paper, a novel fiber-optic sensing system based on fiber Bragg gratings (FBGs) to measure foot plantar pressure is proposed. This study first explores the Pedar-X insole foot pressure types of the adult-size chart and then defines six measurement areas to effectively [...] Read more.
In this paper, a novel fiber-optic sensing system based on fiber Bragg gratings (FBGs) to measure foot plantar pressure is proposed. This study first explores the Pedar-X insole foot pressure types of the adult-size chart and then defines six measurement areas to effectively identify four foot types: neutral foot, cavus foot, supinated foot and flat foot. The plantar pressure signals are detected by only six FBGs, which are embedded in silicone rubber. The performance of the fiber optic sensing is examined and compared with a digital pressure plate of i-Step P1000 with 1024 barometric sensors. In the experiment, there are 11 participants with different foot types to participate in the test. The Pearson correlation coefficient, which is determined from the measured results of the homemade fiber-optic plantar pressure system and i-Step P1000 plantar pressure plate, reaches up to 0.671 (p < 0.01). According to the measured results from the plantar pressure data, the proposed fiber optic sensing system can successfully identify the four different foot types. Measurements of this study have demonstrated the feasibility of the proposed system so that it can be an alternative for plantar pressure detection systems. Full article
(This article belongs to the Special Issue Applications of Advanced Materials on Microelectronic and Optical Sensors)
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6345 KiB  
Article
Experimental Study on Damage Detection in Timber Specimens Based on an Electromechanical Impedance Technique and RMSD-Based Mahalanobis Distance
by Dansheng Wang, Qinghua Wang, Hao Wang and Hongping Zhu
Sensors 2016, 16(10), 1765; https://doi.org/10.3390/s16101765 - 22 Oct 2016
Cited by 53 | Viewed by 5242
Abstract
In the electromechanical impedance (EMI) method, the PZT patch performs the functions of both sensor and exciter. Due to the high frequency actuation and non-model based characteristics, the EMI method can be utilized to detect incipient structural damage. In recent years EMI techniques [...] Read more.
In the electromechanical impedance (EMI) method, the PZT patch performs the functions of both sensor and exciter. Due to the high frequency actuation and non-model based characteristics, the EMI method can be utilized to detect incipient structural damage. In recent years EMI techniques have been widely applied to monitor the health status of concrete and steel materials, however, studies on application to timber are limited. This paper will explore the feasibility of using the EMI technique for damage detection in timber specimens. In addition, the conventional damage index, namely root mean square deviation (RMSD) is employed to evaluate the level of damage. On that basis, a new damage index, Mahalanobis distance based on RMSD, is proposed to evaluate the damage severity of timber specimens. Experimental studies are implemented to detect notch and hole damage in the timber specimens. Experimental results verify the availability and robustness of the proposed damage index and its superiority over the RMSD indexes. Full article
(This article belongs to the Section Physical Sensors)
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3634 KiB  
Article
In-Field, In Situ, and In Vivo 3-Dimensional Elemental Mapping for Plant Tissue and Soil Analysis Using Laser-Induced Breakdown Spectroscopy
by Chunjiang Zhao, Daming Dong, Xiaofan Du and Wengang Zheng
Sensors 2016, 16(10), 1764; https://doi.org/10.3390/s16101764 - 22 Oct 2016
Cited by 20 | Viewed by 6780
Abstract
Sensing and mapping element distributions in plant tissues and its growth environment has great significance for understanding the uptake, transport, and accumulation of nutrients and harmful elements in plants, as well as for understanding interactions between plants and the environment. In this study, [...] Read more.
Sensing and mapping element distributions in plant tissues and its growth environment has great significance for understanding the uptake, transport, and accumulation of nutrients and harmful elements in plants, as well as for understanding interactions between plants and the environment. In this study, we developed a 3-dimensional elemental mapping system based on laser-induced breakdown spectroscopy that can be deployed in- field to directly measure the distribution of multiple elements in living plants as well as in the soil. Mapping is performed by a fast scanning laser, which ablates a micro volume of a sample to form a plasma. The presence and concentration of specific elements are calculated using the atomic, ionic, and molecular spectral characteristics of the plasma emission spectra. Furthermore, we mapped the pesticide residues in maize leaves after spraying to demonstrate the capacity of this method for trace elemental mapping. We also used the system to quantitatively detect the element concentrations in soil, which can be used to further understand the element transport between plants and soil. We demonstrate that this method has great potential for elemental mapping in plant tissues and soil with the advantages of 3-dimensional and multi-elemental mapping, in situ and in vivo measurement, flexible use, and low cost. Full article
(This article belongs to the Special Issue Sensors for Environmental Monitoring 2016)
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3772 KiB  
Article
A Portable Farmland Information Collection System with Multiple Sensors
by Jianfeng Zhang, Jinyang Hu, Lvwen Huang, Zhiyong Zhang and Yimian Ma
Sensors 2016, 16(10), 1762; https://doi.org/10.3390/s16101762 - 22 Oct 2016
Cited by 16 | Viewed by 7361
Abstract
Precision agriculture is the trend of modern agriculture, and it is also one of the important ways to realize the sustainable development of agriculture. In order to meet the production requirements of precision agriculture—efficient use of agricultural resources, and improving the crop yields [...] Read more.
Precision agriculture is the trend of modern agriculture, and it is also one of the important ways to realize the sustainable development of agriculture. In order to meet the production requirements of precision agriculture—efficient use of agricultural resources, and improving the crop yields and quality—some necessary field information in crop growth environment needs to be collected and monitored. In this paper, a farmland information collection system is developed, which includes a portable farmland information collection device based on STM32 (a 32-bit comprehensive range of microcontrollers based on ARM Crotex-M3), a remote server and a mobile phone APP. The device realizes the function of portable and mobile collecting of multiple parameters farmland information, such as chlorophyll content of crop leaves, air temperature, air humidity, and light intensity. UM220-III (Unicore Communication Inc., Beijing, China) is used to realize the positioning based on BDS/GPS (BeiDou Navigation Satellite System, BDS/Global Positioning System, GPS) dual-mode navigation and positioning system, and the CDMA (Code Division Multiple Access, CDMA) wireless communication module is adopted to realize the real-time remote transmission. The portable multi-function farmland information collection system is real-time, accurate, and easy to use to collect farmland information and multiple information parameters of crops. Full article
(This article belongs to the Special Issue Sensors for Agriculture)
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8538 KiB  
Article
A Comparative Study of the Application of Fluorescence Excitation-Emission Matrices Combined with Parallel Factor Analysis and Nonnegative Matrix Factorization in the Analysis of Zn Complexation by Humic Acids
by Patrycja Boguta, Piotr M. Pieczywek and Zofia Sokołowska
Sensors 2016, 16(10), 1760; https://doi.org/10.3390/s16101760 - 22 Oct 2016
Cited by 20 | Viewed by 6415
Abstract
The main aim of this study was the application of excitation-emission fluorescence matrices (EEMs) combined with two decomposition methods: parallel factor analysis (PARAFAC) and nonnegative matrix factorization (NMF) to study the interaction mechanisms between humic acids (HAs) and Zn(II) over a wide concentration [...] Read more.
The main aim of this study was the application of excitation-emission fluorescence matrices (EEMs) combined with two decomposition methods: parallel factor analysis (PARAFAC) and nonnegative matrix factorization (NMF) to study the interaction mechanisms between humic acids (HAs) and Zn(II) over a wide concentration range (0–50 mg·dm−3). The influence of HA properties on Zn(II) complexation was also investigated. Stability constants, quenching degree and complexation capacity were estimated for binding sites found in raw EEM, EEM-PARAFAC and EEM-NMF data using mathematical models. A combination of EEM fluorescence analysis with one of the proposed decomposition methods enabled separation of overlapping binding sites and yielded more accurate calculations of the binding parameters. PARAFAC and NMF processing allowed finding binding sites invisible in a few raw EEM datasets as well as finding totally new maxima attributed to structures of the lowest humification. Decomposed data showed an increase in Zn complexation with an increase in humification, aromaticity and molecular weight of HAs. EEM-PARAFAC analysis also revealed that the most stable compounds were formed by structures containing the highest amounts of nitrogen. The content of oxygen-functional groups did not influence the binding parameters, mainly due to fact of higher competition of metal cation with protons. EEM spectra coupled with NMF and especially PARAFAC processing gave more adequate assessments of interactions as compared to raw EEM data and should be especially recommended for modeling of complexation processes where the fluorescence intensities (FI) changes are weak or where the processes are interfered with by the presence of other fluorophores. Full article
(This article belongs to the Section Chemical Sensors)
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7853 KiB  
Article
Achievement of High-Response Organic Field-Effect Transistor NO2 Sensor by Using the Synergistic Effect of ZnO/PMMA Hybrid Dielectric and CuPc/Pentacene Heterojunction
by Shijiao Han, Jiang Cheng, Huidong Fan, Junsheng Yu and Lu Li
Sensors 2016, 16(10), 1763; https://doi.org/10.3390/s16101763 - 21 Oct 2016
Cited by 15 | Viewed by 7953
Abstract
High-response organic field-effect transistor (OFET)-based NO2 sensors were fabricated using the synergistic effect the synergistic effect of zinc oxide/poly(methyl methacrylate) (ZnO/PMMA) hybrid dielectric and CuPc/Pentacene heterojunction. Compared with the OFET sensors without synergistic effect, the fabricated OFET sensors showed a remarkable shift [...] Read more.
High-response organic field-effect transistor (OFET)-based NO2 sensors were fabricated using the synergistic effect the synergistic effect of zinc oxide/poly(methyl methacrylate) (ZnO/PMMA) hybrid dielectric and CuPc/Pentacene heterojunction. Compared with the OFET sensors without synergistic effect, the fabricated OFET sensors showed a remarkable shift of saturation current, field-effect mobility and threshold voltage when exposed to various concentrations of NO2 analyte. Moreover, after being stored in atmosphere for 30 days, the variation of saturation current increased more than 10 folds at 0.5 ppm NO2. By analyzing the electrical characteristics, and the morphologies of organic semiconductor films of the OFET-based sensors, the performance enhancement was ascribed to the synergistic effect of the dielectric and organic semiconductor. The ZnO nanoparticles on PMMA dielectric surface decreased the grain size of pentacene formed on hybrid dielectric, facilitating the diffusion of CuPc molecules into the grain boundary of pentacene and the approach towards the conducting channel of OFET. Hence, NO2 molecules could interact with CuPc and ZnO nanoparticles at the interface of dielectric and organic semiconductor. Our results provided a promising strategy for the design of high performance OFET-based NO2 sensors in future electronic nose and environment monitoring. Full article
(This article belongs to the Special Issue Gas Nanosensors)
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2723 KiB  
Review
Printable Electrochemical Biosensors: A Focus on Screen-Printed Electrodes and Their Application
by Keiichiro Yamanaka, Mun’delanji C. Vestergaard and Eiichi Tamiya
Sensors 2016, 16(10), 1761; https://doi.org/10.3390/s16101761 - 21 Oct 2016
Cited by 139 | Viewed by 13084
Abstract
In this review we present electrochemical biosensor developments, focusing on screen-printed electrodes (SPEs) and their applications. In particular, we discuss how SPEs enable simple integration, and the portability needed for on-field applications. First, we briefly discuss the general concept of biosensors and quickly [...] Read more.
In this review we present electrochemical biosensor developments, focusing on screen-printed electrodes (SPEs) and their applications. In particular, we discuss how SPEs enable simple integration, and the portability needed for on-field applications. First, we briefly discuss the general concept of biosensors and quickly move on to electrochemical biosensors. Drawing from research undertaken in this area, we cover the development of electrochemical DNA biosensors in great detail. Through specific examples, we describe the fabrication and surface modification of printed electrodes for sensitive and selective detection of targeted DNA sequences, as well as integration with reverse transcription-polymerase chain reaction (RT-PCR). For a more rounded approach, we also touch on electrochemical immunosensors and enzyme-based biosensors. Last, we present some electrochemical devices specifically developed for use with SPEs, including USB-powered compact mini potentiostat. The coupling demonstrates the practical use of printable electrode technologies for application at point-of-use. Although tremendous advances have indeed been made in this area, a few challenges remain. One of the main challenges is application of these technologies for on-field analysis, which involves complicated sample matrices. Full article
(This article belongs to the Special Issue Point-of-Care Biosensors)
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5262 KiB  
Article
A Fiber Bragg Grating-Based Monitoring System for Roof Safety Control in Underground Coal Mining
by Yiming Zhao, Nong Zhang and Guangyao Si
Sensors 2016, 16(10), 1759; https://doi.org/10.3390/s16101759 - 21 Oct 2016
Cited by 58 | Viewed by 7385
Abstract
Monitoring of roof activity is a primary measure adopted in the prevention of roof collapse accidents and functions to optimize and support the design of roadways in underground coalmines. However, traditional monitoring measures, such as using mechanical extensometers or electronic gauges, either require [...] Read more.
Monitoring of roof activity is a primary measure adopted in the prevention of roof collapse accidents and functions to optimize and support the design of roadways in underground coalmines. However, traditional monitoring measures, such as using mechanical extensometers or electronic gauges, either require arduous underground labor or cannot function properly in the harsh underground environment. Therefore, in this paper, in order to break through this technological barrier, a novel monitoring system for roof safety control in underground coal mining, using fiber Bragg grating (FBG) material as a perceived element and transmission medium, has been developed. Compared with traditional monitoring equipment, the developed, novel monitoring system has the advantages of providing accurate, reliable, and continuous online monitoring of roof activities in underground coal mining. This is expected to further enable the prevention of catastrophic roof collapse accidents. The system has been successfully implemented at a deep hazardous roadway in Zhuji Coal Mine, China. Monitoring results from the study site have demonstrated the advantages of FBG-based sensors over traditional monitoring approaches. The dynamic impacts of progressive face advance on roof displacement and stress have been accurately captured by the novel roadway roof activity and safety monitoring system, which provided essential references for roadway support and design of the mine. Full article
(This article belongs to the Section Physical Sensors)
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3299 KiB  
Article
Moving Object Detection Using Scanning Camera on a High-Precision Intelligent Holder
by Shuoyang Chen, Tingfa Xu, Daqun Li, Jizhou Zhang and Shenwang Jiang
Sensors 2016, 16(10), 1758; https://doi.org/10.3390/s16101758 - 21 Oct 2016
Cited by 13 | Viewed by 11020
Abstract
During the process of moving object detection in an intelligent visual surveillance system, a scenario with complex background is sure to appear. The traditional methods, such as “frame difference” and “optical flow”, may not able to deal with the problem very well. In [...] Read more.
During the process of moving object detection in an intelligent visual surveillance system, a scenario with complex background is sure to appear. The traditional methods, such as “frame difference” and “optical flow”, may not able to deal with the problem very well. In such scenarios, we use a modified algorithm to do the background modeling work. In this paper, we use edge detection to get an edge difference image just to enhance the ability of resistance illumination variation. Then we use a “multi-block temporal-analyzing LBP (Local Binary Pattern)” algorithm to do the segmentation. In the end, a connected component is used to locate the object. We also produce a hardware platform, the core of which consists of the DSP (Digital Signal Processor) and FPGA (Field Programmable Gate Array) platforms and the high-precision intelligent holder. Full article
(This article belongs to the Section Physical Sensors)
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1044 KiB  
Communication
First Results of a Detection Sensor for the Monitoring of Laying Hens Reared in a Commercial Organic Egg Production Farm Based on the Use of Infrared Technology
by Mauro Zaninelli, Veronica Redaelli, Erica Tirloni, Cristian Bernardi, Vittorio Dell’Orto and Giovanni Savoini
Sensors 2016, 16(10), 1757; https://doi.org/10.3390/s16101757 - 21 Oct 2016
Cited by 20 | Viewed by 5210
Abstract
The development of a monitoring system to identify the presence of laying hens, in a closed room of a free-range commercial organic egg production farm, was the aim of this study. This monitoring system was based on the infrared (IR) technology and had, [...] Read more.
The development of a monitoring system to identify the presence of laying hens, in a closed room of a free-range commercial organic egg production farm, was the aim of this study. This monitoring system was based on the infrared (IR) technology and had, as final target, a possible reduction of atmospheric ammonia levels and bacterial load. Tests were carried out for three weeks and involved 7 ISA (Institut de Sélection Animale) brown laying hens. The first 5 days was used to set up the detection sensor, while the other 15 days were used to evaluate the accuracy of the resulting monitoring system, in terms of sensitivity and specificity. The setup procedure included the evaluation of different color background (CB) thresholds, used to discriminate the information contents of the thermographic images. At the end of this procedure, a CB threshold equal to an increase of 3 °C from the floor temperature was chosen, and a cutoff level of 196 colored pixels was identified as the threshold to use to classify a positive case. The results of field tests showed that the developed monitoring system reached a fine detection accuracy (sensitivity = 97.9% and specificity = 94.9%) and the IR technology proved to be a possible solution for the development of a detection sensor necessary to reach the scope of this study. Full article
(This article belongs to the Section Physical Sensors)
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8776 KiB  
Article
A Novel Gradient Vector Flow Snake Model Based on Convex Function for Infrared Image Segmentation
by Rui Zhang, Shiping Zhu and Qin Zhou
Sensors 2016, 16(10), 1756; https://doi.org/10.3390/s16101756 - 21 Oct 2016
Cited by 21 | Viewed by 7230
Abstract
Infrared image segmentation is a challenging topic because infrared images are characterized by high noise, low contrast, and weak edges. Active contour models, especially gradient vector flow, have several advantages in terms of infrared image segmentation. However, the GVF (Gradient Vector Flow) model [...] Read more.
Infrared image segmentation is a challenging topic because infrared images are characterized by high noise, low contrast, and weak edges. Active contour models, especially gradient vector flow, have several advantages in terms of infrared image segmentation. However, the GVF (Gradient Vector Flow) model also has some drawbacks including a dilemma between noise smoothing and weak edge protection, which decrease the effect of infrared image segmentation significantly. In order to solve this problem, we propose a novel generalized gradient vector flow snakes model combining GGVF (Generic Gradient Vector Flow) and NBGVF (Normally Biased Gradient Vector Flow) models. We also adopt a new type of coefficients setting in the form of convex function to improve the ability of protecting weak edges while smoothing noises. Experimental results and comparisons against other methods indicate that our proposed snakes model owns better ability in terms of infrared image segmentation than other snakes models. Full article
(This article belongs to the Special Issue Infrared and THz Sensing and Imaging)
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18231 KiB  
Article
Fine-Scale Population Estimation by 3D Reconstruction of Urban Residential Buildings
by Shixin Wang, Ye Tian, Yi Zhou, Wenliang Liu and Chenxi Lin
Sensors 2016, 16(10), 1755; https://doi.org/10.3390/s16101755 - 21 Oct 2016
Cited by 31 | Viewed by 6555
Abstract
Fine-scale population estimation is essential in emergency response and epidemiological applications as well as urban planning and management. However, representing populations in heterogeneous urban regions with a finer resolution is a challenge. This study aims to obtain fine-scale population distribution based on 3D [...] Read more.
Fine-scale population estimation is essential in emergency response and epidemiological applications as well as urban planning and management. However, representing populations in heterogeneous urban regions with a finer resolution is a challenge. This study aims to obtain fine-scale population distribution based on 3D reconstruction of urban residential buildings with morphological operations using optical high-resolution (HR) images from the Chinese No. 3 Resources Satellite (ZY-3). Specifically, the research area was first divided into three categories when dasymetric mapping was taken into consideration. The results demonstrate that the morphological building index (MBI) yielded better results than built-up presence index (PanTex) in building detection, and the morphological shadow index (MSI) outperformed color invariant indices (CIIT) in shadow extraction and height retrieval. Building extraction and height retrieval were then combined to reconstruct 3D models and to estimate population. Final results show that this approach is effective in fine-scale population estimation, with a mean relative error of 16.46% and an overall Relative Total Absolute Error (RATE) of 0.158. This study gives significant insights into fine-scale population estimation in complicated urban landscapes, when detailed 3D information of buildings is unavailable. Full article
(This article belongs to the Special Issue Urban Remote Sensing: Monitoring, Synthesis and Modeling in the Urban Environment)
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2239 KiB  
Article
Underwater Sensor Network Redeployment Algorithm Based on Wolf Search
by Peng Jiang, Yang Feng and Feng Wu
Sensors 2016, 16(10), 1754; https://doi.org/10.3390/s16101754 - 21 Oct 2016
Cited by 17 | Viewed by 5295
Abstract
This study addresses the optimization of node redeployment coverage in underwater wireless sensor networks. Given that nodes could easily become invalid under a poor environment and the large scale of underwater wireless sensor networks, an underwater sensor network redeployment algorithm was developed based [...] Read more.
This study addresses the optimization of node redeployment coverage in underwater wireless sensor networks. Given that nodes could easily become invalid under a poor environment and the large scale of underwater wireless sensor networks, an underwater sensor network redeployment algorithm was developed based on wolf search. This study is to apply the wolf search algorithm combined with crowded degree control in the deployment of underwater wireless sensor networks. The proposed algorithm uses nodes to ensure coverage of the events, and it avoids the prematurity of the nodes. The algorithm has good coverage effects. In addition, considering that obstacles exist in the underwater environment, nodes are prevented from being invalid by imitating the mechanism of avoiding predators. Thus, the energy consumption of the network is reduced. Comparative analysis shows that the algorithm is simple and effective in wireless sensor network deployment. Compared with the optimized artificial fish swarm algorithm, the proposed algorithm exhibits advantages in network coverage, energy conservation, and obstacle avoidance. Full article
(This article belongs to the Special Issue Sensing Technologies for Autonomy and Cooperation in Underwater Networked Robot Systems)
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8806 KiB  
Article
Design and Implementation of Foot-Mounted Inertial Sensor Based Wearable Electronic Device for Game Play Application
by Qifan Zhou, Hai Zhang, Zahra Lari, Zhenbo Liu and Naser El-Sheimy
Sensors 2016, 16(10), 1752; https://doi.org/10.3390/s16101752 - 21 Oct 2016
Cited by 19 | Viewed by 7371
Abstract
Wearable electronic devices have experienced increasing development with the advances in the semiconductor industry and have received more attention during the last decades. This paper presents the development and implementation of a novel inertial sensor-based foot-mounted wearable electronic device for a brand new [...] Read more.
Wearable electronic devices have experienced increasing development with the advances in the semiconductor industry and have received more attention during the last decades. This paper presents the development and implementation of a novel inertial sensor-based foot-mounted wearable electronic device for a brand new application: game playing. The main objective of the introduced system is to monitor and identify the human foot stepping direction in real time, and coordinate these motions to control the player operation in games. This proposed system extends the utilized field of currently available wearable devices and introduces a convenient and portable medium to perform exercise in a more compelling way in the near future. This paper provides an overview of the previously-developed system platforms, introduces the main idea behind this novel application, and describes the implemented human foot moving direction identification algorithm. Practical experiment results demonstrate that the proposed system is capable of recognizing five foot motions, jump, step left, step right, step forward, and step backward, and has achieved an over 97% accuracy performance for different users. The functionality of the system for real-time application has also been verified through the practical experiments. Full article
(This article belongs to the Section Physical Sensors)
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7213 KiB  
Article
A Low-Cost Optical Remote Sensing Application for Glacier Deformation Monitoring in an Alpine Environment
by Daniele Giordan, Paolo Allasia, Niccolò Dematteis, Federico Dell’Anese, Marco Vagliasindi and Elena Motta
Sensors 2016, 16(10), 1750; https://doi.org/10.3390/s16101750 - 21 Oct 2016
Cited by 27 | Viewed by 6875
Abstract
In this work, we present the results of a low-cost optical monitoring station designed for monitoring the kinematics of glaciers in an Alpine environment. We developed a complete hardware/software data acquisition and processing chain that automatically acquires, stores and co-registers images. The system [...] Read more.
In this work, we present the results of a low-cost optical monitoring station designed for monitoring the kinematics of glaciers in an Alpine environment. We developed a complete hardware/software data acquisition and processing chain that automatically acquires, stores and co-registers images. The system was installed in September 2013 to monitor the evolution of the Planpincieux glacier, within the open-air laboratory of the Grandes Jorasses, Mont Blanc massif (NW Italy), and collected data with an hourly frequency. The acquisition equipment consists of a high-resolution DSLR camera operating in the visible band. The data are processed with a Pixel Offset algorithm based on normalized cross-correlation, to estimate the deformation of the observed glacier. We propose a method for the pixel-to-metric conversion and present the results of the projection on the mean slope of the glacier. The method performances are compared with measurements obtained by GB-SAR, and exhibit good agreement. The system provides good support for the analysis of the glacier evolution and allows the creation of daily displacement maps. Full article
(This article belongs to the Section Remote Sensors)
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Graphical abstract

1773 KiB  
Article
A Multifunctional Sensor in Ternary Solution Using Canonical Correlations for Variable Links Assessment
by Dan Liu, Qisong Wang, Xin Liu, Ruixin Niu, Yan Zhang and Jinwei Sun
Sensors 2016, 16(10), 1661; https://doi.org/10.3390/s16101661 - 21 Oct 2016
Cited by 4 | Viewed by 5071
Abstract
Accurately measuring the oil content and salt content of crude oil is very important for both estimating oil reserves and predicting the lifetime of an oil well. There are some problems with the current methods such as high cost, low precision, and difficulties [...] Read more.
Accurately measuring the oil content and salt content of crude oil is very important for both estimating oil reserves and predicting the lifetime of an oil well. There are some problems with the current methods such as high cost, low precision, and difficulties in operation. To solve these problems, we present a multifunctional sensor, which applies, respectively, conductivity method and ultrasound method to measure the contents of oil, water, and salt. Based on cross sensitivity theory, these two transducers are ideally integrated for simplifying the structure. A concentration test of ternary solutions is carried out to testify its effectiveness, and then Canonical Correlation Analysis is applied to evaluate the data. From the perspective of statistics, the sensor inputs, for instance, oil concentration, salt concentration, and temperature, are closely related to its outputs including output voltage and time of flight of ultrasound wave, which further identify the correctness of the sensing theory and the feasibility of the integrated design. Combined with reconstruction algorithms, the sensor can realize the content measurement of the solution precisely. The potential development of the proposed sensor and method in the aspect of online test for crude oil is of important reference and practical value. Full article
(This article belongs to the Special Issue Smart Sensor Interface Circuits and Systems)
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3888 KiB  
Article
A Self-Synthesis Approach to Perceptual Learning for Multisensory Fusion in Robotics
by Cristian Axenie, Christoph Richter and Jörg Conradt
Sensors 2016, 16(10), 1751; https://doi.org/10.3390/s16101751 - 20 Oct 2016
Cited by 10 | Viewed by 6822
Abstract
Biological and technical systems operate in a rich multimodal environment. Due to the diversity of incoming sensory streams a system perceives and the variety of motor capabilities a system exhibits there is no single representation and no singular unambiguous interpretation of such a [...] Read more.
Biological and technical systems operate in a rich multimodal environment. Due to the diversity of incoming sensory streams a system perceives and the variety of motor capabilities a system exhibits there is no single representation and no singular unambiguous interpretation of such a complex scene. In this work we propose a novel sensory processing architecture, inspired by the distributed macro-architecture of the mammalian cortex. The underlying computation is performed by a network of computational maps, each representing a different sensory quantity. All the different sensory streams enter the system through multiple parallel channels. The system autonomously associates and combines them into a coherent representation, given incoming observations. These processes are adaptive and involve learning. The proposed framework introduces mechanisms for self-creation and learning of the functional relations between the computational maps, encoding sensorimotor streams, directly from the data. Its intrinsic scalability, parallelisation, and automatic adaptation to unforeseen sensory perturbations make our approach a promising candidate for robust multisensory fusion in robotic systems. We demonstrate this by applying our model to a 3D motion estimation on a quadrotor. Full article
(This article belongs to the Special Issue Advances in Multi-Sensor Information Fusion: Theory and Applications)
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1356 KiB  
Article
Developing Benthic Class Specific, Chlorophyll-a Retrieving Algorithms for Optically-Shallow Water Using SeaWiFS
by Tara Blakey, Assefa Melesse, Michael C. Sukop, Georgio Tachiev, Dean Whitman and Fernando Miralles-Wilhelm
Sensors 2016, 16(10), 1749; https://doi.org/10.3390/s16101749 - 20 Oct 2016
Cited by 7 | Viewed by 4585
Abstract
This study evaluated the ability to improve Sea-Viewing Wide Field-of-View Sensor (SeaWiFS) chl-a retrieval from optically shallow coastal waters by applying algorithms specific to the pixels’ benthic class. The form of the Ocean Color (OC) algorithm was assumed for this study. The operational [...] Read more.
This study evaluated the ability to improve Sea-Viewing Wide Field-of-View Sensor (SeaWiFS) chl-a retrieval from optically shallow coastal waters by applying algorithms specific to the pixels’ benthic class. The form of the Ocean Color (OC) algorithm was assumed for this study. The operational atmospheric correction producing Level 2 SeaWiFS data was retained since the focus of this study was on establishing the benefit from the alternative specification of the bio-optical algorithm. Benthic class was determined through satellite image-based classification methods. Accuracy of the chl-a algorithms evaluated was determined through comparison with coincident in situ measurements of chl-a. The regionally-tuned models that were allowed to vary by benthic class produced more accurate estimates of chl-a than the single, unified regionally-tuned model. Mean absolute percent difference was approximately 70% for the regionally-tuned, benthic class-specific algorithms. Evaluation of the residuals indicated the potential for further improvement to chl-a estimation through finer characterization of benthic environments. Atmospheric correction procedures specialized to coastal environments were recognized as areas for future improvement as these procedures would improve both classification and algorithm tuning. Full article
(This article belongs to the Special Issue Sensors and Sensing in Water Quality Assessment and Monitoring)
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7734 KiB  
Article
A Readout IC Using Two-Step Fastest Signal Identification for Compact Data Acquisition of PET Systems
by Sung-Jin Jung, Seong-Kwan Hong and Oh-Kyong Kwon
Sensors 2016, 16(10), 1748; https://doi.org/10.3390/s16101748 - 20 Oct 2016
Cited by 3 | Viewed by 6718
Abstract
A readout integrated circuit (ROIC) using two-step fastest signal identification (FSI) is proposed to reduce the number of input channels of a data acquisition (DAQ) block with a high-channel reduction ratio. The two-step FSI enables the proposed ROIC to filter out useless input [...] Read more.
A readout integrated circuit (ROIC) using two-step fastest signal identification (FSI) is proposed to reduce the number of input channels of a data acquisition (DAQ) block with a high-channel reduction ratio. The two-step FSI enables the proposed ROIC to filter out useless input signals that arise from scattering and electrical noise without using complex and bulky circuits. In addition, an asynchronous fastest signal identifier and a self-trimmed comparator are proposed to identify the fastest signal without using a high-frequency clock and to reduce misidentification, respectively. The channel reduction ratio of the proposed ROIC is 16:1 and can be extended to 16 × N:1 using N ROICs. To verify the performance of the two-step FSI, the proposed ROIC was implemented into a gamma photon detector module using a Geiger-mode avalanche photodiode with a lutetium-yttrium oxyorthosilicate array. The measured minimum detectable time is 1 ns. The difference of the measured energy and timing resolution between with and without the two-step FSI are 0.8% and 0.2 ns, respectively, which are negligibly small. These measurement results show that the proposed ROIC using the two-step FSI reduces the number of input channels of the DAQ block without sacrificing the performance of the positron emission tomography (PET) systems. Full article
(This article belongs to the Special Issue Smart Sensor Interface Circuits and Systems)
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3291 KiB  
Article
Decoupling Control of Micromachined Spinning-Rotor Gyroscope with Electrostatic Suspension
by Boqian Sun, Shunyue Wang, Haixia Li and Xiaoxia He
Sensors 2016, 16(10), 1747; https://doi.org/10.3390/s16101747 - 20 Oct 2016
Cited by 11 | Viewed by 6380
Abstract
A micromachined gyroscope in which a high-speed spinning rotor is suspended electrostatically in a vacuum cavity usually functions as a dual-axis angular rate sensor. An inherent coupling error between the two sensing axes exists owing to the angular motion of the spinning rotor [...] Read more.
A micromachined gyroscope in which a high-speed spinning rotor is suspended electrostatically in a vacuum cavity usually functions as a dual-axis angular rate sensor. An inherent coupling error between the two sensing axes exists owing to the angular motion of the spinning rotor being controlled by a torque-rebalance loop. In this paper, a decoupling compensation method is proposed and investigated experimentally based on an electrostatically suspended micromachined gyroscope. In order to eliminate the negative spring effect inherent in the gyroscope dynamics, a stiffness compensation scheme was utilized in design of the decoupled rebalance loop to ensure loop stability and increase suspension stiffness. The experimental results show an overall stiffness increase of 30.3% after compensation. A decoupling method comprised of inner- and outer-loop decoupling compensators is proposed to minimize the cross-axis coupling error. The inner-loop decoupling compensator aims to attenuate the angular position coupling. The experimental frequency response shows a position coupling attenuation by 14.36 dB at 1 Hz. Moreover, the cross-axis coupling between the two angular rate output signals can be attenuated theoretically from −56.2 dB down to −102 dB by further appending the outer-loop decoupling compensator. The proposed dual-loop decoupling compensation algorithm could be applied to other dual-axis spinning-rotor gyroscopes with various suspension solutions. Full article
(This article belongs to the Section Physical Sensors)
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3865 KiB  
Article
A Novel Model-Based Driving Behavior Recognition System Using Motion Sensors
by Minglin Wu, Sheng Zhang and Yuhan Dong
Sensors 2016, 16(10), 1746; https://doi.org/10.3390/s16101746 - 20 Oct 2016
Cited by 54 | Viewed by 6862
Abstract
In this article, a novel driving behavior recognition system based on a specific physical model and motion sensory data is developed to promote traffic safety. Based on the theory of rigid body kinematics, we build a specific physical model to reveal the data [...] Read more.
In this article, a novel driving behavior recognition system based on a specific physical model and motion sensory data is developed to promote traffic safety. Based on the theory of rigid body kinematics, we build a specific physical model to reveal the data change rule during the vehicle moving process. In this work, we adopt a nine-axis motion sensor including a three-axis accelerometer, a three-axis gyroscope and a three-axis magnetometer, and apply a Kalman filter for noise elimination and an adaptive time window for data extraction. Based on the feature extraction guided by the built physical model, various classifiers are accomplished to recognize different driving behaviors. Leveraging the system, normal driving behaviors (such as accelerating, braking, lane changing and turning with caution) and aggressive driving behaviors (such as accelerating, braking, lane changing and turning with a sudden) can be classified with a high accuracy of 93.25%. Compared with traditional driving behavior recognition methods using machine learning only, the proposed system possesses a solid theoretical basis, performs better and has good prospects. Full article
(This article belongs to the Section Physical Sensors)
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