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Sensors, Volume 16, Issue 8 (August 2016) – 188 articles

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6761 KiB  
Article
Monitoring of Grouting Compactness in a Post-Tensioning Tendon Duct Using Piezoceramic Transducers
by Tianyong Jiang, Qingzhao Kong, Wenxi Wang, Linsheng Huo and Gangbing Song
Sensors 2016, 16(8), 1343; https://doi.org/10.3390/s16081343 - 22 Aug 2016
Cited by 78 | Viewed by 9670
Abstract
A post-tensioning tendon duct filled with grout can effectively prevent corrosion of the reinforcement, maintain bonding behavior between the reinforcement and concrete, and enhance the load bearing capacity of concrete structures. In practice, grouting of the post-tensioning tendon ducts always causes quality problems, [...] Read more.
A post-tensioning tendon duct filled with grout can effectively prevent corrosion of the reinforcement, maintain bonding behavior between the reinforcement and concrete, and enhance the load bearing capacity of concrete structures. In practice, grouting of the post-tensioning tendon ducts always causes quality problems, which may reduce structural integrity and service life, and even cause accidents. However, monitoring of the grouting compactness is still a challenge due to the invisibility of the grout in the duct during the grouting process. This paper presents a stress wave-based active sensing approach using piezoceramic transducers to monitor the grouting compactness in real time. A segment of a commercial tendon duct was used as research object in this study. One lead zirconate titanate (PZT) piezoceramic transducer with marble protection, called a smart aggregate (SA), was bonded on the tendon and installed in the tendon duct. Two PZT patch sensors were mounted on the top outside surface of the duct, and one PZT patch sensor was bonded on the bottom outside surface of the tendon duct. In the active sensing approach, the SA was used as an actuator to generate a stress wave and the PZT sensors were utilized to detect the wave response. Cement or grout in the duct functions as a wave conduit, which can propagate the stress wave. If the cement or grout is not fully filled in the tendon duct, the top PZT sensors cannot receive much stress wave energy. The experimental procedures simulated four stages during the grout pouring process, which includes empty status, half grouting, 90% grouting, and full grouting of the duct. Experimental results show that the bottom PZT sensor can detect the signal when the grout level increases towards 50%, when a conduit between the SA and PZT sensor is formed. The top PZT sensors cannot receive any signal until the grout process is completely finished. The wavelet packet-based energy analysis was adopted in this research to compute the total signal energy received by PZT sensors. Experimental results show that the energy levels of the PZT sensors can reflect the degree of grouting compactness in the duct. The proposed method has the potential to be implemented to monitor the tendon duct grouting compactness of the reinforced concrete structures with post tensioning. Full article
(This article belongs to the Special Issue Ultrasonic Sensors)
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2370 KiB  
Article
Recognition of Daily Gestures with Wearable Inertial Rings and Bracelets
by Alessandra Moschetti, Laura Fiorini, Dario Esposito, Paolo Dario and Filippo Cavallo
Sensors 2016, 16(8), 1341; https://doi.org/10.3390/s16081341 - 22 Aug 2016
Cited by 64 | Viewed by 8587
Abstract
Recognition of activities of daily living plays an important role in monitoring elderly people and helping caregivers in controlling and detecting changes in daily behaviors. Thanks to the miniaturization and low cost of Microelectromechanical systems (MEMs), in particular of Inertial Measurement Units, in [...] Read more.
Recognition of activities of daily living plays an important role in monitoring elderly people and helping caregivers in controlling and detecting changes in daily behaviors. Thanks to the miniaturization and low cost of Microelectromechanical systems (MEMs), in particular of Inertial Measurement Units, in recent years body-worn activity recognition has gained popularity. In this context, the proposed work aims to recognize nine different gestures involved in daily activities using hand and wrist wearable sensors. Additionally, the analysis was carried out also considering different combinations of wearable sensors, in order to find the best combination in terms of unobtrusiveness and recognition accuracy. In order to achieve the proposed goals, an extensive experimentation was performed in a realistic environment. Twenty users were asked to perform the selected gestures and then the data were off-line analyzed to extract significant features. In order to corroborate the analysis, the classification problem was treated using two different and commonly used supervised machine learning techniques, namely Decision Tree and Support Vector Machine, analyzing both personal model and Leave-One-Subject-Out cross validation. The results obtained from this analysis show that the proposed system is able to recognize the proposed gestures with an accuracy of 89.01% in the Leave-One-Subject-Out cross validation and are therefore promising for further investigation in real life scenarios. Full article
(This article belongs to the Special Issue Advances on Data Transmission and Analysis for Wearable Sensors Systems)
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5954 KiB  
Article
A Dielectric-Filled Waveguide Antenna Element for 3D Imaging Radar in High Temperature and Excessive Dust Conditions
by Ding Xu, Zhiping Li, Xianzhong Chen, Zhengpeng Wang and Jianhua Wu
Sensors 2016, 16(8), 1339; https://doi.org/10.3390/s16081339 - 22 Aug 2016
Cited by 9 | Viewed by 8797
Abstract
Three-dimensional information of the burden surface in high temperature and excessive dust industrial conditions has been previously hard to obtain. This paper presents a novel microstrip-fed dielectric-filled waveguide antenna element which is resistant to dust and high temperatures. A novel microstrip-to-dielectric-loaded waveguide transition [...] Read more.
Three-dimensional information of the burden surface in high temperature and excessive dust industrial conditions has been previously hard to obtain. This paper presents a novel microstrip-fed dielectric-filled waveguide antenna element which is resistant to dust and high temperatures. A novel microstrip-to-dielectric-loaded waveguide transition was developed. A cylinder and cuboid composite structure was employed at the terminal of the antenna element, which improved the return loss performance and reduced the size. The proposed antenna element was easily integrated into a T-shape multiple-input multiple-output (MIMO) imaging radar system and tested in both the laboratory environment and real blast furnace environment. The measurement results show that the proposed antenna element works very well in industrial 3D imaging radar. Full article
(This article belongs to the Special Issue Advanced Technologies and Techniques for Microwave and Wireless Sensors)
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1478 KiB  
Article
Virtualized MME Design for IoT Support in 5G Systems
by Pilar Andres-Maldonado, Pablo Ameigeiras, Jonathan Prados-Garzon, Juan Jose Ramos-Munoz and Juan Manuel Lopez-Soler
Sensors 2016, 16(8), 1338; https://doi.org/10.3390/s16081338 - 22 Aug 2016
Cited by 11 | Viewed by 6893
Abstract
Cellular systems are recently being considered an option to provide support to the Internet of Things (IoT). To enable this support, the 3rd Generation Partnership Project (3GPP) has introduced new procedures specifically targeted for cellular IoT. With one of these procedures, the transmissions [...] Read more.
Cellular systems are recently being considered an option to provide support to the Internet of Things (IoT). To enable this support, the 3rd Generation Partnership Project (3GPP) has introduced new procedures specifically targeted for cellular IoT. With one of these procedures, the transmissions of small and infrequent data packets from/to the devices are encapsulated in signaling messages and sent through the control plane. However, these transmissions from/to a massive number of devices may imply a major increase of the processing load on the control plane entities of the network and in particular on the Mobility Management Entity (MME). In this paper, we propose two designs of an MME based on Network Function Virtualization (NFV) that aim at facilitating the IoT support. The first proposed design partially separates the processing resources dedicated to each traffic class. The second design includes traffic shaping to control the traffic of each class. We consider three classes: Mobile Broadband (MBB), low latency Machine to Machine communications (lM2M) and delay-tolerant M2M communications. Our proposals enable reducing the processing resources and, therefore, the cost. Additionally, results show that the proposed designs lessen the impact between classes, so they ease the compliance of the delay requirements of MBB and lM2M communications. Full article
(This article belongs to the Special Issue Intelligent Internet of Things (IoT) Networks)
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Article
Factors Influencing Continuous Breath Signal in Intubated and Mechanically-Ventilated Intensive Care Unit Patients Measured by an Electronic Nose
by Jan Hendrik Leopold, Ameen Abu-Hanna, Camilla Colombo, Peter J. Sterk, Marcus J. Schultz and Lieuwe D. J. Bos
Sensors 2016, 16(8), 1337; https://doi.org/10.3390/s16081337 - 22 Aug 2016
Cited by 5 | Viewed by 5086
Abstract
Introduction: Continuous breath analysis by electronic nose (eNose) technology in the intensive care unit (ICU) may be useful in monitoring (patho) physiological changes. However, the application of breath monitoring in a non-controlled clinical setting introduces noise into the data. We hypothesized that the [...] Read more.
Introduction: Continuous breath analysis by electronic nose (eNose) technology in the intensive care unit (ICU) may be useful in monitoring (patho) physiological changes. However, the application of breath monitoring in a non-controlled clinical setting introduces noise into the data. We hypothesized that the sensor signal is influenced by: (1) humidity in the side-stream; (2) patient-ventilator disconnections and the nebulization of medication; and (3) changes in ventilator settings and the amount of exhaled CO2. We aimed to explore whether the aforementioned factors introduce noise into the signal, and discuss several approaches to reduce this noise. Methods: Study in mechanically-ventilated ICU patients. Exhaled breath was monitored using a continuous eNose with metal oxide sensors. Linear (mixed) models were used to study hypothesized associations. Results: In total, 1251 h of eNose data were collected. First, the initial 15 min of the signal was discarded. There was a negative association between humidity and Sensor 1 (Fixed-effect β: −0.05 ± 0.002) and a positive association with Sensors 2–4 (Fixed-effect β: 0.12 ± 0.001); the signal was corrected for this noise. Outliers were most likely due to noise and therefore removed. Sensor values were positively associated with end-tidal CO2, tidal volume and the pressure variables. The signal was corrected for changes in these ventilator variables after which the associations disappeared. Conclusion: Variations in humidity, ventilator disconnections, nebulization of medication and changes of ventilator settings indeed influenced exhaled breath signals measured in ventilated patients by continuous eNose analysis. We discussed several approaches to reduce the effects of these noise inducing variables. Full article
(This article belongs to the Special Issue Olfactory and Gustatory Sensors)
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Article
Fault Diagnosis Strategies for SOFC-Based Power Generation Plants
by Paola Costamagna, Andrea De Giorgi, Alberto Gotelli, Loredana Magistri, Gabriele Moser, Emanuele Sciaccaluga and Andrea Trucco
Sensors 2016, 16(8), 1336; https://doi.org/10.3390/s16081336 - 22 Aug 2016
Cited by 21 | Viewed by 6520
Abstract
The success of distributed power generation by plants based on solid oxide fuel cells (SOFCs) is hindered by reliability problems that can be mitigated through an effective fault detection and isolation (FDI) system. However, the numerous operating conditions under which such plants can [...] Read more.
The success of distributed power generation by plants based on solid oxide fuel cells (SOFCs) is hindered by reliability problems that can be mitigated through an effective fault detection and isolation (FDI) system. However, the numerous operating conditions under which such plants can operate and the random size of the possible faults make identifying damaged plant components starting from the physical variables measured in the plant very difficult. In this context, we assess two classical FDI strategies (model-based with fault signature matrix and data-driven with statistical classification) and the combination of them. For this assessment, a quantitative model of the SOFC-based plant, which is able to simulate regular and faulty conditions, is used. Moreover, a hybrid approach based on the random forest (RF) classification method is introduced to address the discrimination of regular and faulty situations due to its practical advantages. Working with a common dataset, the FDI performances obtained using the aforementioned strategies, with different sets of monitored variables, are observed and compared. We conclude that the hybrid FDI strategy, realized by combining a model-based scheme with a statistical classifier, outperforms the other strategies. In addition, the inclusion of two physical variables that should be measured inside the SOFCs can significantly improve the FDI performance, despite the actual difficulty in performing such measurements. Full article
(This article belongs to the Section Physical Sensors)
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11106 KiB  
Article
Measurement Matrix Optimization and Mismatch Problem Compensation for DLSLA 3-D SAR Cross-Track Reconstruction
by Qian Bao, Chenglong Jiang, Yun Lin, Weixian Tan, Zhirui Wang and Wen Hong
Sensors 2016, 16(8), 1333; https://doi.org/10.3390/s16081333 - 22 Aug 2016
Cited by 10 | Viewed by 5337
Abstract
With a short linear array configured in the cross-track direction, downward looking sparse linear array three-dimensional synthetic aperture radar (DLSLA 3-D SAR) can obtain the 3-D image of an imaging scene. To improve the cross-track resolution, sparse recovery methods have been investigated in [...] Read more.
With a short linear array configured in the cross-track direction, downward looking sparse linear array three-dimensional synthetic aperture radar (DLSLA 3-D SAR) can obtain the 3-D image of an imaging scene. To improve the cross-track resolution, sparse recovery methods have been investigated in recent years. In the compressive sensing (CS) framework, the reconstruction performance depends on the property of measurement matrix. This paper concerns the technique to optimize the measurement matrix and deal with the mismatch problem of measurement matrix caused by the off-grid scatterers. In the model of cross-track reconstruction, the measurement matrix is mainly affected by the configuration of antenna phase centers (APC), thus, two mutual coherence based criteria are proposed to optimize the configuration of APCs. On the other hand, to compensate the mismatch problem of the measurement matrix, the sparse Bayesian inference based method is introduced into the cross-track reconstruction by jointly estimate the scatterers and the off-grid error. Experiments demonstrate the performance of the proposed APCs’ configuration schemes and the proposed cross-track reconstruction method. Full article
(This article belongs to the Special Issue Synthetic Aperture Radars: Models, Algorithms, Techniques and Tools for Data Exploitation)
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4249 KiB  
Article
Global Navigation Satellite System Multipath Mitigation Using a Wave-Absorbing Shield
by Haiyan Yang, Xuhai Yang, Baoqi Sun and Hang Su
Sensors 2016, 16(8), 1332; https://doi.org/10.3390/s16081332 - 22 Aug 2016
Cited by 10 | Viewed by 5672
Abstract
Code multipath is an unmanaged error source in precise global navigation satellite system (GNSS) observation processing that limits GNSS positioning accuracy. A new technique for mitigating multipath by installing a wave-absorbing shield is presented in this paper. The wave-absorbing shield was designed according [...] Read more.
Code multipath is an unmanaged error source in precise global navigation satellite system (GNSS) observation processing that limits GNSS positioning accuracy. A new technique for mitigating multipath by installing a wave-absorbing shield is presented in this paper. The wave-absorbing shield was designed according to a GNSS requirement of received signals and collected measurements to achieve good performance. The wave-absorbing shield was installed at the KUN1 and SHA1 sites of the international GNSS Monitoring and Assessment System (iGMAS). Code and carrier phase measurements of three constellations were collected on the dates of the respective installations plus and minus one week. Experiments were performed in which the multipath of the measurements obtained at different elevations was mitigated to different extents after applying the wave-absorbing shield. The results of an analysis and comparison show that the multipath was mitigated by approximately 17%–36% on all available frequencies of BeiDou Navigation Satellite System (BDS), Global Positioning System (GPS), and Global Navigation Satellite System (GLONASS) satellites. The three-dimensional accuracies of BDS, GPS, and GLONASS single-point positioning (SPP) were, respectively, improved by 1.07, 0.63 and 0.49 m for the KUN1 site, and by 0.72, 0.79 and 0.73 m for the SHA1 site. Results indicate that the multipath of the original observations was mitigated by using the wave-absorbing shield. Full article
(This article belongs to the Section Remote Sensors)
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2694 KiB  
Article
Subsea Cable Tracking by Autonomous Underwater Vehicle with Magnetic Sensing Guidance
by Xianbo Xiang, Caoyang Yu, Zemin Niu and Qin Zhang
Sensors 2016, 16(8), 1335; https://doi.org/10.3390/s16081335 - 20 Aug 2016
Cited by 107 | Viewed by 10499
Abstract
The changes of the seabed environment caused by a natural disaster or human activities dramatically affect the life span of the subsea buried cable. It is essential to track the cable route in order to inspect the condition of the buried cable and [...] Read more.
The changes of the seabed environment caused by a natural disaster or human activities dramatically affect the life span of the subsea buried cable. It is essential to track the cable route in order to inspect the condition of the buried cable and protect its surviving seabed environment. The magnetic sensor is instrumental in guiding the remotely-operated vehicle (ROV) to track and inspect the buried cable underseas. In this paper, a novel framework integrating the underwater cable localization method with the magnetic guidance and control algorithm is proposed, in order to enable the automatic cable tracking by a three-degrees-of-freedom (3-DOF) under-actuated autonomous underwater vehicle (AUV) without human beings in the loop. The work relies on the passive magnetic sensing method to localize the subsea cable by using two tri-axial magnetometers, and a new analytic formulation is presented to compute the heading deviation, horizontal offset and buried depth of the cable. With the magnetic localization, the cable tracking and inspection mission is elaborately constructed as a straight-line path following control problem in the horizontal plane. A dedicated magnetic line-of-sight (LOS) guidance is built based on the relative geometric relationship between the vehicle and the cable, and the feedback linearizing technique is adopted to design a simplified cable tracking controller considering the side-slip effects, such that the under-actuated vehicle is able to move towards the subsea cable and then inspect its buried environment, which further guides the environmental protection of the cable by setting prohibited fishing/anchoring zones and increasing the buried depth. Finally, numerical simulation results show the effectiveness of the proposed magnetic guidance and control algorithm on the envisioned subsea cable tracking and the potential protection of the seabed environment along the cable route. Full article
(This article belongs to the Special Issue Robotic Sensory Systems for Environment Protection and Conservation)
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24767 KiB  
Article
Clustering and Beamforming for Efficient Communication in Wireless Sensor Networks
by Francisco Porcel-Rodríguez, Juan Valenzuela-Valdés, Pablo Padilla, Francisco Luna-Valero, Rafael Luque-Baena and Miguel Ángel López-Gordo
Sensors 2016, 16(8), 1334; https://doi.org/10.3390/s16081334 - 20 Aug 2016
Cited by 9 | Viewed by 5920
Abstract
Energy efficiency is a critical issue for wireless sensor networks (WSNs) as sensor nodes have limited power availability. In order to address this issue, this paper tries to maximize the power efficiency in WSNs by means of the evaluation of WSN node networks [...] Read more.
Energy efficiency is a critical issue for wireless sensor networks (WSNs) as sensor nodes have limited power availability. In order to address this issue, this paper tries to maximize the power efficiency in WSNs by means of the evaluation of WSN node networks and their performance when both clustering and antenna beamforming techniques are applied. In this work, four different scenarios are defined, each one considering different numbers of sensors: 50, 20, 10, five, and two nodes per scenario, and each scenario is randomly generated thirty times in order to statistically validate the results. For each experiment, two different target directions for transmission are taken into consideration in the optimization process (φ = 0° and θ = 45°; φ = 45°, and θ = 45°). Each scenario is evaluated for two different types of antennas, an ideal isotropic antenna and a conventional dipole one. In this set of experiments two types of WSN are evaluated: in the first one, all of the sensors have the same amount of power for communications purposes; in the second one, each sensor has a different amount of power for its communications purposes. The analyzed cases in this document are focused on 2D surface and 3D space for the node location. To the authors’ knowledge, this is the first time that beamforming and clustering are simultaneously applied to increase the network lifetime in WSNs. Full article
(This article belongs to the Special Issue Advanced Algorithms for Mobile Sensing: from Wireless Sensor Networks to Mobile Crowd Sensing)
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Article
Mounted Smartphones as Measurement and Control Platforms for Motor-Based Laboratory Test-Beds
by Jared A. Frank, Anthony Brill and Vikram Kapila
Sensors 2016, 16(8), 1331; https://doi.org/10.3390/s16081331 - 20 Aug 2016
Cited by 3 | Viewed by 6349
Abstract
Laboratory education in science and engineering often entails the use of test-beds equipped with costly peripherals for sensing, acquisition, storage, processing, and control of physical behavior. However, costly peripherals are no longer necessary to obtain precise measurements and achieve stable feedback control of [...] Read more.
Laboratory education in science and engineering often entails the use of test-beds equipped with costly peripherals for sensing, acquisition, storage, processing, and control of physical behavior. However, costly peripherals are no longer necessary to obtain precise measurements and achieve stable feedback control of test-beds. With smartphones performing diverse sensing and processing tasks, this study examines the feasibility of mounting smartphones directly to test-beds to exploit their embedded hardware and software in the measurement and control of the test-beds. This approach is a first step towards replacing laboratory-grade peripherals with more compact and affordable smartphone-based platforms, whose interactive user interfaces can engender wider participation and engagement from learners. Demonstrative cases are presented in which the sensing, computation, control, and user interaction with three motor-based test-beds are handled by a mounted smartphone. Results of experiments and simulations are used to validate the feasibility of mounted smartphones as measurement and feedback control platforms for motor-based laboratory test-beds, report the measurement precision and closed-loop performance achieved with such platforms, and address challenges in the development of platforms to maintain system stability. Full article
(This article belongs to the Special Issue Advanced Robotics and Mechatronics Devices)
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Article
Channel Measurement and Modeling for 5G Urban Microcellular Scenarios
by Michael Peter, Richard J. Weiler, Barış Göktepe, Wilhelm Keusgen and Kei Sakaguchi
Sensors 2016, 16(8), 1330; https://doi.org/10.3390/s16081330 - 20 Aug 2016
Cited by 15 | Viewed by 7004
Abstract
In order to support the development of channel models for higher frequency bands, multiple urban microcellular measurement campaigns have been carried out in Berlin, Germany, at 60 and 10 GHz. In this paper, the collected data is uniformly analyzed with focus on the [...] Read more.
In order to support the development of channel models for higher frequency bands, multiple urban microcellular measurement campaigns have been carried out in Berlin, Germany, at 60 and 10 GHz. In this paper, the collected data is uniformly analyzed with focus on the path loss (PL) and the delay spread (DS). It reveals that the ground reflection has a dominant impact on the fading behavior. For line-of-sight conditions, the PL exponents are close to free space propagation at 60 GHz, but slightly smaller (1.62) for the street canyon at 10 GHz. The DS shows a clear dependence on the scenario (median values between 16 and 38 ns) and a strong distance dependence for the open square and the wide street canyon. The dependence is less distinct for the narrow street canyon with residential buildings. This behavior is consistent with complementary ray tracing simulations, though the simplified model tends to overestimate the DS. Full article
(This article belongs to the Special Issue Millimeter Wave Wireless Communications and Networks)
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Article
Recognizing the Operating Hand and the Hand-Changing Process for User Interface Adjustment on Smartphones
by Hansong Guo, He Huang, Liusheng Huang and Yu-E Sun
Sensors 2016, 16(8), 1314; https://doi.org/10.3390/s16081314 - 20 Aug 2016
Cited by 6 | Viewed by 5943
Abstract
As the size of smartphone touchscreens has become larger and larger in recent years, operability with a single hand is getting worse, especially for female users. We envision that user experience can be significantly improved if smartphones are able to recognize the current [...] Read more.
As the size of smartphone touchscreens has become larger and larger in recent years, operability with a single hand is getting worse, especially for female users. We envision that user experience can be significantly improved if smartphones are able to recognize the current operating hand, detect the hand-changing process and then adjust the user interfaces subsequently. In this paper, we proposed, implemented and evaluated two novel systems. The first one leverages the user-generated touchscreen traces to recognize the current operating hand, and the second one utilizes the accelerometer and gyroscope data of all kinds of activities in the user’s daily life to detect the hand-changing process. These two systems are based on two supervised classifiers constructed from a series of refined touchscreen trace, accelerometer and gyroscope features. As opposed to existing solutions that all require users to select the current operating hand or confirm the hand-changing process manually, our systems follow much more convenient and practical methods and allow users to change the operating hand frequently without any harm to the user experience. We conduct extensive experiments on Samsung Galaxy S4 smartphones, and the evaluation results demonstrate that our proposed systems can recognize the current operating hand and detect the hand-changing process with 94.1% and 93.9% precision and 94.1% and 93.7% True Positive Rates (TPR) respectively, when deciding with a single touchscreen trace or accelerometer-gyroscope data segment, and the False Positive Rates (FPR) are as low as 2.6% and 0.7% accordingly. These two systems can either work completely independently and achieve pretty high accuracies or work jointly to further improve the recognition accuracy. Full article
(This article belongs to the Special Issue Advanced Algorithms for Mobile Sensing: from Wireless Sensor Networks to Mobile Crowd Sensing)
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3195 KiB  
Article
A Method to Simultaneously Detect the Current Sensor Fault and Estimate the State of Energy for Batteries in Electric Vehicles
by Jun Xu, Jing Wang, Shiying Li and Binggang Cao
Sensors 2016, 16(8), 1328; https://doi.org/10.3390/s16081328 - 19 Aug 2016
Cited by 53 | Viewed by 6350
Abstract
Recently, State of energy (SOE) has become one of the most fundamental parameters for battery management systems in electric vehicles. However, current information is critical in SOE estimation and current sensor is usually utilized to obtain the latest current information. However, if the [...] Read more.
Recently, State of energy (SOE) has become one of the most fundamental parameters for battery management systems in electric vehicles. However, current information is critical in SOE estimation and current sensor is usually utilized to obtain the latest current information. However, if the current sensor fails, the SOE estimation may be confronted with large error. Therefore, this paper attempts to make the following contributions: Current sensor fault detection and SOE estimation method is realized simultaneously. Through using the proportional integral observer (PIO) based method, the current sensor fault could be accurately estimated. By taking advantage of the accurate estimated current sensor fault, the influence caused by the current sensor fault can be eliminated and compensated. As a result, the results of the SOE estimation will be influenced little by the fault. In addition, the simulation and experimental workbench is established to verify the proposed method. The results indicate that the current sensor fault can be estimated accurately. Simultaneously, the SOE can also be estimated accurately and the estimation error is influenced little by the fault. The maximum SOE estimation error is less than 2%, even though the large current error caused by the current sensor fault still exists. Full article
(This article belongs to the Section Physical Sensors)
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1042 KiB  
Article
The Availability of Space Service for Inter-Satellite Links in Navigation Constellations
by Yinyin Tang, Yueke Wang and Jianyun Chen
Sensors 2016, 16(8), 1327; https://doi.org/10.3390/s16081327 - 19 Aug 2016
Cited by 11 | Viewed by 6154
Abstract
Global navigation satellite systems (GNSS) are widely used in low Earth orbit (LEO) satellite navigation; however, their availability is poor for users in medium Earth orbits (MEO), and high Earth orbits (HEO). With the increasing demand for navigation from MEO and HEO users, [...] Read more.
Global navigation satellite systems (GNSS) are widely used in low Earth orbit (LEO) satellite navigation; however, their availability is poor for users in medium Earth orbits (MEO), and high Earth orbits (HEO). With the increasing demand for navigation from MEO and HEO users, the inadequate coverage of GNSS has emerged. Inter-satellite links (ISLs) are used for ranging and communication between navigation satellites and can also serve space users that are outside the navigation constellation. This paper aims to summarize their application method and analyze their service performance. The mathematical model of visibility is proposed and then the availability of time division ISLs is analyzed based on global grid points. The BeiDou navigation constellation is used as an example for numerical simulation. Simulation results show that the availability can be enhanced by scheduling more satellites and larger beams, while the presence of more users lowers the availability. The availability of navigation signals will be strengthened when combined with the signals from the ISLs. ISLs can improve the space service volume (SSV) of navigation constellations, and are therefore a promising method for navigation in MEO/HEO spacecraft. Full article
(This article belongs to the Section Remote Sensors)
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3844 KiB  
Article
A Microfluidic Approach for Inducing Cell Rotation by Means of Hydrodynamic Forces
by Stefania Torino, Mario Iodice, Ivo Rendina, Giuseppe Coppola and Ethan Schonbrun
Sensors 2016, 16(8), 1326; https://doi.org/10.3390/s16081326 - 19 Aug 2016
Cited by 21 | Viewed by 6842
Abstract
Microfluidic technology allows to realize devices in which cells can be imaged in their three-dimensional shape. However, there are still some limitations in the method, due to the fact that cells follow a straight path while they are flowing in a channel. This [...] Read more.
Microfluidic technology allows to realize devices in which cells can be imaged in their three-dimensional shape. However, there are still some limitations in the method, due to the fact that cells follow a straight path while they are flowing in a channel. This can result in a loss in information, since only one side of the cell will be visible. Our work has started from the consideration that if a cell rotates, it is possible to overcome this problem. Several approaches have been proposed for cell manipulation in microfluidics. In our approach, cells are controlled by only taking advantages of hydrodynamic forces. Two different devices have been designed, realized, and tested. The first device induces cell rotation in a plane that is parallel (in-plane) to the observation plane, while the second one induce rotation in a plane perpendicular (out-of-plane) to the observation plane. Full article
(This article belongs to the Special Issue Biomicrofluidics)
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7344 KiB  
Article
A Hybrid Vehicle Detection Method Based on Viola-Jones and HOG + SVM from UAV Images
by Yongzheng Xu, Guizhen Yu, Yunpeng Wang, Xinkai Wu and Yalong Ma
Sensors 2016, 16(8), 1325; https://doi.org/10.3390/s16081325 - 19 Aug 2016
Cited by 112 | Viewed by 12200
Abstract
A new hybrid vehicle detection scheme which integrates the Viola-Jones (V-J) and linear SVM classifier with HOG feature (HOG + SVM) methods is proposed for vehicle detection from low-altitude unmanned aerial vehicle (UAV) images. As both V-J and HOG + SVM are sensitive [...] Read more.
A new hybrid vehicle detection scheme which integrates the Viola-Jones (V-J) and linear SVM classifier with HOG feature (HOG + SVM) methods is proposed for vehicle detection from low-altitude unmanned aerial vehicle (UAV) images. As both V-J and HOG + SVM are sensitive to on-road vehicles’ in-plane rotation, the proposed scheme first adopts a roadway orientation adjustment method, which rotates each UAV image to align the roads with the horizontal direction so the original V-J or HOG + SVM method can be directly applied to achieve fast detection and high accuracy. To address the issue of descending detection speed for V-J and HOG + SVM, the proposed scheme further develops an adaptive switching strategy which sophistically integrates V-J and HOG + SVM methods based on their different descending trends of detection speed to improve detection efficiency. A comprehensive evaluation shows that the switching strategy, combined with the road orientation adjustment method, can significantly improve the efficiency and effectiveness of the vehicle detection from UAV images. The results also show that the proposed vehicle detection method is competitive compared with other existing vehicle detection methods. Furthermore, since the proposed vehicle detection method can be performed on videos captured from moving UAV platforms without the need of image registration or additional road database, it has great potentials of field applications. Future research will be focusing on expanding the current method for detecting other transportation modes such as buses, trucks, motors, bicycles, and pedestrians. Full article
(This article belongs to the Special Issue UAV-Based Remote Sensing)
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6577 KiB  
Article
Transportation Modes Classification Using Sensors on Smartphones
by Shih-Hau Fang, Hao-Hsiang Liao, Yu-Xiang Fei, Kai-Hsiang Chen, Jen-Wei Huang, Yu-Ding Lu and Yu Tsao
Sensors 2016, 16(8), 1324; https://doi.org/10.3390/s16081324 - 19 Aug 2016
Cited by 56 | Viewed by 9077
Abstract
This paper investigates the transportation and vehicular modes classification by using big data from smartphone sensors. The three types of sensors used in this paper include the accelerometer, magnetometer, and gyroscope. This study proposes improved features and uses three machine learning algorithms including [...] Read more.
This paper investigates the transportation and vehicular modes classification by using big data from smartphone sensors. The three types of sensors used in this paper include the accelerometer, magnetometer, and gyroscope. This study proposes improved features and uses three machine learning algorithms including decision trees, K-nearest neighbor, and support vector machine to classify the user’s transportation and vehicular modes. In the experiments, we discussed and compared the performance from different perspectives including the accuracy for both modes, the executive time, and the model size. Results show that the proposed features enhance the accuracy, in which the support vector machine provides the best performance in classification accuracy whereas it consumes the largest prediction time. This paper also investigates the vehicle classification mode and compares the results with that of the transportation modes. Full article
(This article belongs to the Special Issue Applications of Advanced Materials on Microelectronic and Optical Sensors)
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574 KiB  
Article
Virtual Wireless Sensor Networks: Adaptive Brain-Inspired Configuration for Internet of Things Applications
by Shinya Toyonaga, Daichi Kominami and Masayuki Murata
Sensors 2016, 16(8), 1323; https://doi.org/10.3390/s16081323 - 19 Aug 2016
Cited by 9 | Viewed by 7102
Abstract
Many researchers are devoting attention to the so-called “Internet of Things” (IoT), and wireless sensor networks (WSNs) are regarded as a critical technology for realizing the communication infrastructure of the future, including the IoT. Against this background, virtualization is a crucial technique for [...] Read more.
Many researchers are devoting attention to the so-called “Internet of Things” (IoT), and wireless sensor networks (WSNs) are regarded as a critical technology for realizing the communication infrastructure of the future, including the IoT. Against this background, virtualization is a crucial technique for the integration of multiple WSNs. Designing virtualized WSNs for actual environments will require further detailed studies. Within the IoT environment, physical networks can undergo dynamic change, and so, many problems exist that could prevent applications from running without interruption when using the existing approaches. In this paper, we show an overall architecture that is suitable for constructing and running virtual wireless sensor network (VWSN) services within a VWSN topology. Our approach provides users with a reliable VWSN network by assigning redundant resources according to each user’s demand and providing a recovery method to incorporate environmental changes. We tested this approach by simulation experiment, with the results showing that the VWSN network is reliable in many cases, although physical deployment of sensor nodes and the modular structure of the VWSN will be quite important to the stability of services within the VWSN topology. Full article
(This article belongs to the Special Issue Intelligent Internet of Things (IoT) Networks)
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4879 KiB  
Article
A Fuzzy Logic Prompting Mechanism Based on Pattern Recognition and Accumulated Activity Effective Index Using a Smartphone Embedded Sensor
by Chung-Tse Liu and Chia-Tai Chan
Sensors 2016, 16(8), 1322; https://doi.org/10.3390/s16081322 - 19 Aug 2016
Cited by 8 | Viewed by 7986
Abstract
Sufficient physical activity can reduce many adverse conditions and contribute to a healthy life. Nevertheless, inactivity is prevalent on an international scale. Improving physical activity is an essential concern for public health. Reminders that help people change their health behaviors are widely applied [...] Read more.
Sufficient physical activity can reduce many adverse conditions and contribute to a healthy life. Nevertheless, inactivity is prevalent on an international scale. Improving physical activity is an essential concern for public health. Reminders that help people change their health behaviors are widely applied in health care services. However, timed-based reminders deliver periodic prompts suffer from flexibility and dependency issues which may decrease prompt effectiveness. We propose a fuzzy logic prompting mechanism, Accumulated Activity Effective Index Reminder (AAEIReminder), based on pattern recognition and activity effective analysis to manage physical activity. AAEIReminder recognizes activity levels using a smartphone-embedded sensor for pattern recognition and analyzing the amount of physical activity in activity effective analysis. AAEIReminder can infer activity situations such as the amount of physical activity and days spent exercising through fuzzy logic, and decides whether a prompt should be delivered to a user. This prompting system was implemented in smartphones and was used in a short-term real-world trial by seventeenth participants for validation. The results demonstrated that the AAEIReminder is feasible. The fuzzy logic prompting mechanism can deliver prompts automatically based on pattern recognition and activity effective analysis. AAEIReminder provides flexibility which may increase the prompts’ efficiency. Full article
(This article belongs to the Special Issue Advances on Data Transmission and Analysis for Wearable Sensors Systems)
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1347 KiB  
Article
Modeling and Analysis of Micro-Spacecraft Attitude Sensing with Gyrowheel
by Xiaokun Liu, Hui Zhao, Yu Yao and Fenghua He
Sensors 2016, 16(8), 1321; https://doi.org/10.3390/s16081321 - 19 Aug 2016
Cited by 24 | Viewed by 5018
Abstract
This paper proposes two kinds of approaches of angular rate sensing for micro-spacecraft with a gyrowheel (GW), which can combine attitude sensing with attitude control into one single device to achieve a compact micro-spacecraft design. In this implementation, during the three-dimensional attitude control [...] Read more.
This paper proposes two kinds of approaches of angular rate sensing for micro-spacecraft with a gyrowheel (GW), which can combine attitude sensing with attitude control into one single device to achieve a compact micro-spacecraft design. In this implementation, during the three-dimensional attitude control torques being produced, two-dimensional spacecraft angular rates can be sensed from the signals of the GW sensors, such as the currents of the torque coils, the tilt angles of the rotor, the motor rotation, etc. This paper focuses on the problems of the angular rate sensing with the GW at large tilt angles of the rotor. For this purpose, a novel real-time linearization approach based on Lyapunov’s linearization theory is proposed, and a GW linearized measurement model at arbitrary tilt angles of the rotor is derived. Furthermore, by representing the two-dimensional rotor tilt angles and tilt control torques as complex quantities and separating the twice periodic terms about the motor spin speed, the linearized measurement model at smaller tilt angles of the rotor is given and simplified. According to the respective characteristics, the application schemes of the two measurement models are analyzed from the engineering perspective. Finally, the simulation results are presented to demonstrate the effectiveness of the proposed strategy. Full article
(This article belongs to the Section Physical Sensors)
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3319 KiB  
Article
Linearized Programming of Memristors for Artificial Neuro-Sensor Signal Processing
by Changju Yang and Hyongsuk Kim
Sensors 2016, 16(8), 1320; https://doi.org/10.3390/s16081320 - 19 Aug 2016
Cited by 2 | Viewed by 7304
Abstract
A linearized programming method of memristor-based neural weights is proposed. Memristor is known as an ideal element to implement a neural synapse due to its embedded functions of analog memory and analog multiplication. Its resistance variation with a voltage input is generally a [...] Read more.
A linearized programming method of memristor-based neural weights is proposed. Memristor is known as an ideal element to implement a neural synapse due to its embedded functions of analog memory and analog multiplication. Its resistance variation with a voltage input is generally a nonlinear function of time. Linearization of memristance variation about time is very important for the easiness of memristor programming. In this paper, a method utilizing an anti-serial architecture for linear programming is proposed. The anti-serial architecture is composed of two memristors with opposite polarities. It linearizes the variation of memristance due to complimentary actions of two memristors. For programming a memristor, additional memristor with opposite polarity is employed. The linearization effect of weight programming of an anti-serial architecture is investigated and memristor bridge synapse which is built with two sets of anti-serial memristor architecture is taken as an application example of the proposed method. Simulations are performed with memristors of both linear drift model and nonlinear model. Full article
(This article belongs to the Section Physical Sensors)
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1314 KiB  
Article
CS2-Collector: A New Approach for Data Collection in Wireless Sensor Networks Based on Two-Dimensional Compressive Sensing
by Yong Wang, Zhuoshi Yang, Jianpei Zhang, Feng Li, Hongkai Wen and Yiran Shen
Sensors 2016, 16(8), 1318; https://doi.org/10.3390/s16081318 - 19 Aug 2016
Cited by 9 | Viewed by 5917
Abstract
In this paper, we consider the problem of reconstructing the temporal and spatial profile of some physical phenomena monitored by large-scale Wireless Sensor Networks (WSNs) in an energy efficient manner. Compressive sensing is one of the popular choices to reduce the energy consumption [...] Read more.
In this paper, we consider the problem of reconstructing the temporal and spatial profile of some physical phenomena monitored by large-scale Wireless Sensor Networks (WSNs) in an energy efficient manner. Compressive sensing is one of the popular choices to reduce the energy consumption of the data collection in WSNs. The existing solutions only consider sparsity of sensors’ data from either temporal or spatial dimensions. In this paper, we propose a novel data collection strategy, CS2-collector, for WSNs based on the theory of Two Dimensional Compressive Sensing (2DCS). It exploits both temporal and spatial sparsity, i.e., 2D-sparsity of WSNs and achieves significant gain on the tradeoff between the compression ratio and reconstruction accuracy as the numerical simulations and evaluations on different types of sensors’ data. More intuitively, with the same given energy budget, CS2-collector provides significantly more accurate reconstruction of the profile of the physical phenomena that are temporal-spatially sparse. Full article
(This article belongs to the Special Issue Enabling the Move from Wireless Sensor Networks to Internet of Things and Cyber-Physical Systems)
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6143 KiB  
Article
Imaging of Metabolic Status in 3D Cultures with an Improved AMPK FRET Biosensor for FLIM
by George Chennell, Robin J. W. Willows, Sean C. Warren, David Carling, Paul M. W. French, Chris Dunsby and Alessandro Sardini
Sensors 2016, 16(8), 1312; https://doi.org/10.3390/s16081312 - 19 Aug 2016
Cited by 12 | Viewed by 8851
Abstract
We describe an approach to non-invasively map spatiotemporal biochemical and physiological changes in 3D cell culture using Forster Resonance Energy Transfer (FRET) biosensors expressed in tumour spheroids. In particular, we present an improved Adenosine Monophosphate (AMP) Activated Protein Kinase (AMPK) FRET biosensor, mTurquoise2 [...] Read more.
We describe an approach to non-invasively map spatiotemporal biochemical and physiological changes in 3D cell culture using Forster Resonance Energy Transfer (FRET) biosensors expressed in tumour spheroids. In particular, we present an improved Adenosine Monophosphate (AMP) Activated Protein Kinase (AMPK) FRET biosensor, mTurquoise2 AMPK Activity Reporter (T2AMPKAR), for fluorescence lifetime imaging (FLIM) readouts that we have evaluated in 2D and 3D cultures. Our results in 2D cell culture indicate that replacing the FRET donor, enhanced Cyan Fluorescent Protein (ECFP), in the original FRET biosensor, AMPK activity reporter (AMPKAR), with mTurquoise2 (mTq2FP), increases the dynamic range of the response to activation of AMPK, as demonstrated using the direct AMPK activator, 991. We demonstrated 3D FLIM of this T2AMPKAR FRET biosensor expressed in tumour spheroids using two-photon excitation. Full article
(This article belongs to the Special Issue FRET Biosensors)
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2843 KiB  
Article
Colour-Based Binary Discrimination of Scarified Quercus robur Acorns under Varying Illumination
by Mirosław Jabłoński, Paweł Tylek, Józef Walczyk, Ryszard Tadeusiewicz and Adam Piłat
Sensors 2016, 16(8), 1319; https://doi.org/10.3390/s16081319 - 18 Aug 2016
Cited by 14 | Viewed by 5418
Abstract
Efforts to predict the germination ability of acorns using their shape, length, diameter and density are reported in the literature. These methods, however, are not efficient enough. As such, a visual assessment of the viability of seeds based on the appearance of cross-sections [...] Read more.
Efforts to predict the germination ability of acorns using their shape, length, diameter and density are reported in the literature. These methods, however, are not efficient enough. As such, a visual assessment of the viability of seeds based on the appearance of cross-sections of seeds following their scarification is used. This procedure is more robust but demands significant effort from experienced employees over a short period of time. In this article an automated method of acorn scarification and assessment has been announced. This type of automation requires the specific setup of a machine vision system and application of image processing algorithms for evaluation of sections of seeds in order to predict their viability. In the stage of the analysis of pathological changes, it is important to point out image features that enable efficient classification of seeds in respect of viability. The article shows the results of the binary separation of seeds into two fractions (healthy or spoiled) using average components of regular red-green-blue and perception-based hue-saturation-value colour space. Analysis of accuracy of discrimination was performed on sections of 400 scarified acorns acquired using two various setups: machine vision camera under uncontrolled varying illumination and commodity high-resolution camera under controlled illumination. The accuracy of automatic classification has been compared with predictions completed by experienced professionals. It has been shown that both automatic and manual methods reach an accuracy level of 84%, assuming that the images of the sections are properly normalised. The achieved recognition ratio was higher when referenced to predictions provided by professionals. Results of discrimination by means of Bayes classifier have been also presented as a reference. Full article
(This article belongs to the Special Issue Sensors for Agriculture)
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13400 KiB  
Article
Estimation of Prestress Force Distribution in Multi-Strand System of Prestressed Concrete Structures Using Field Data Measured by Electromagnetic Sensor
by Keunhee Cho, Jeong-Rae Cho, Sung Tae Kim, Sung Yong Park, Young-Jin Kim and Young-Hwan Park
Sensors 2016, 16(8), 1317; https://doi.org/10.3390/s16081317 - 18 Aug 2016
Cited by 8 | Viewed by 12641
Abstract
The recently developed smart strand can be used to measure the prestress force in the prestressed concrete (PSC) structure from the construction stage to the in-service stage. The higher cost of the smart strand compared to the conventional strand renders it unaffordable to [...] Read more.
The recently developed smart strand can be used to measure the prestress force in the prestressed concrete (PSC) structure from the construction stage to the in-service stage. The higher cost of the smart strand compared to the conventional strand renders it unaffordable to replace all the strands by smart strands, and results in the application of only a limited number of smart strands in the PSC structure. However, the prestress forces developed in the strands of the multi-strand system frequently adopted in PSC structures differ from each other, which means that the prestress force in the multi-strand system cannot be obtained by simple proportional scaling using the measurement of the smart strand. Therefore, this study examines the prestress force distribution in the multi-strand system to find the correlation between the prestress force measured by the smart strand and the prestress force distribution in the multi-strand system. To that goal, the prestress force distribution was measured using electromagnetic sensors for various factors of the multi-strand system adopted on site in the fabrication of actual PSC girders. The results verified the possibility to assume normal distribution for the prestress force distribution per anchor head, and a method computing the mean and standard deviation defining the normal distribution is proposed. This paper presents a meaningful finding by proposing an estimation method of the prestress force based upon field-measured data of the prestress force distribution in the multi-strand system of actual PSC structures. Full article
(This article belongs to the Section Physical Sensors)
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1400 KiB  
Article
Data-Aware Retrodiction for Asynchronous Harmonic Measurement in a Cyber-Physical Energy System
by Youda Liu, Xue Wang, Yanchi Liu and Sujin Cui
Sensors 2016, 16(8), 1316; https://doi.org/10.3390/s16081316 - 18 Aug 2016
Cited by 4 | Viewed by 5454
Abstract
Cyber-physical energy systems provide a networked solution for safety, reliability and efficiency problems in smart grids. On the demand side, the secure and trustworthy energy supply requires real-time supervising and online power quality assessing. Harmonics measurement is necessary in power quality evaluation. However, [...] Read more.
Cyber-physical energy systems provide a networked solution for safety, reliability and efficiency problems in smart grids. On the demand side, the secure and trustworthy energy supply requires real-time supervising and online power quality assessing. Harmonics measurement is necessary in power quality evaluation. However, under the large-scale distributed metering architecture, harmonic measurement faces the out-of-sequence measurement (OOSM) problem, which is the result of latencies in sensing or the communication process and brings deviations in data fusion. This paper depicts a distributed measurement network for large-scale asynchronous harmonic analysis and exploits a nonlinear autoregressive model with exogenous inputs (NARX) network to reorder the out-of-sequence measuring data. The NARX network gets the characteristics of the electrical harmonics from practical data rather than the kinematic equations. Thus, the data-aware network approximates the behavior of the practical electrical parameter with real-time data and improves the retrodiction accuracy. Theoretical analysis demonstrates that the data-aware method maintains a reasonable consumption of computing resources. Experiments on a practical testbed of a cyber-physical system are implemented, and harmonic measurement and analysis accuracy are adopted to evaluate the measuring mechanism under a distributed metering network. Results demonstrate an improvement of the harmonics analysis precision and validate the asynchronous measuring method in cyber-physical energy systems. Full article
(This article belongs to the Special Issue Real-Time and Cyber-Physical Systems)
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22500 KiB  
Article
Accurate Mobile Urban Mapping via Digital Map-Based SLAM
by Hyunchul Roh, Jinyong Jeong, Younggun Cho and Ayoung Kim
Sensors 2016, 16(8), 1315; https://doi.org/10.3390/s16081315 - 18 Aug 2016
Cited by 32 | Viewed by 11219
Abstract
This paper presents accurate urban map generation using digital map-based Simultaneous Localization and Mapping (SLAM). Throughout this work, our main objective is generating a 3D and lane map aiming for sub-meter accuracy. In conventional mapping approaches, achieving extremely high accuracy was performed by [...] Read more.
This paper presents accurate urban map generation using digital map-based Simultaneous Localization and Mapping (SLAM). Throughout this work, our main objective is generating a 3D and lane map aiming for sub-meter accuracy. In conventional mapping approaches, achieving extremely high accuracy was performed by either (i) exploiting costly airborne sensors or (ii) surveying with a static mapping system in a stationary platform. Mobile scanning systems recently have gathered popularity but are mostly limited by the availability of the Global Positioning System (GPS). We focus on the fact that the availability of GPS and urban structures are both sporadic but complementary. By modeling both GPS and digital map data as measurements and integrating them with other sensor measurements, we leverage SLAM for an accurate mobile mapping system. Our proposed algorithm generates an efficient graph SLAM and achieves a framework running in real-time and targeting sub-meter accuracy with a mobile platform. Integrated with the SLAM framework, we implement a motion-adaptive model for the Inverse Perspective Mapping (IPM). Using motion estimation derived from SLAM, the experimental results show that the proposed approaches provide stable bird’s-eye view images, even with significant motion during the drive. Our real-time map generation framework is validated via a long-distance urban test and evaluated at randomly sampled points using Real-Time Kinematic (RTK)-GPS. Full article
(This article belongs to the Section Remote Sensors)
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9895 KiB  
Article
Road Lane Detection by Discriminating Dashed and Solid Road Lanes Using a Visible Light Camera Sensor
by Toan Minh Hoang, Hyung Gil Hong, Husan Vokhidov and Kang Ryoung Park
Sensors 2016, 16(8), 1313; https://doi.org/10.3390/s16081313 - 18 Aug 2016
Cited by 42 | Viewed by 14899
Abstract
With the increasing need for road lane detection used in lane departure warning systems and autonomous vehicles, many studies have been conducted to turn road lane detection into a virtual assistant to improve driving safety and reduce car accidents. Most of the previous [...] Read more.
With the increasing need for road lane detection used in lane departure warning systems and autonomous vehicles, many studies have been conducted to turn road lane detection into a virtual assistant to improve driving safety and reduce car accidents. Most of the previous research approaches detect the central line of a road lane and not the accurate left and right boundaries of the lane. In addition, they do not discriminate between dashed and solid lanes when detecting the road lanes. However, this discrimination is necessary for the safety of autonomous vehicles and the safety of vehicles driven by human drivers. To overcome these problems, we propose a method for road lane detection that distinguishes between dashed and solid lanes. Experimental results with the Caltech open database showed that our method outperforms conventional methods. Full article
(This article belongs to the Special Issue Sensors for Autonomous Road Vehicles)
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1992 KiB  
Review
Airborne Optical and Thermal Remote Sensing for Wildfire Detection and Monitoring
by Robert S. Allison, Joshua M. Johnston, Gregory Craig and Sion Jennings
Sensors 2016, 16(8), 1310; https://doi.org/10.3390/s16081310 - 18 Aug 2016
Cited by 209 | Viewed by 23202
Abstract
For decades detection and monitoring of forest and other wildland fires has relied heavily on aircraft (and satellites). Technical advances and improved affordability of both sensors and sensor platforms promise to revolutionize the way aircraft detect, monitor and help suppress wildfires. Sensor systems [...] Read more.
For decades detection and monitoring of forest and other wildland fires has relied heavily on aircraft (and satellites). Technical advances and improved affordability of both sensors and sensor platforms promise to revolutionize the way aircraft detect, monitor and help suppress wildfires. Sensor systems like hyperspectral cameras, image intensifiers and thermal cameras that have previously been limited in use due to cost or technology considerations are now becoming widely available and affordable. Similarly, new airborne sensor platforms, particularly small, unmanned aircraft or drones, are enabling new applications for airborne fire sensing. In this review we outline the state of the art in direct, semi-automated and automated fire detection from both manned and unmanned aerial platforms. We discuss the operational constraints and opportunities provided by these sensor systems including a discussion of the objective evaluation of these systems in a realistic context. Full article
(This article belongs to the Special Issue Sensors for Fire Detection)
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