Previous Issue

E-Mail Alert

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

Journal Browser

Journal Browser

Table of Contents

Sensors, Volume 18, Issue 12 (December 2018)

  • Issues are regarded as officially published after their release is announced to the table of contents alert mailing list.
  • You may sign up for e-mail alerts to receive table of contents of newly released issues.
  • PDF is the official format for papers published in both, html and pdf forms. To view the papers in pdf format, click on the "PDF Full-text" link, and use the free Adobe Readerexternal link to open them.
View options order results:
result details:
Displaying articles 1-320
Export citation of selected articles as:
Open AccessArticle Integrated Ground-Based SAR Interferometry, Terrestrial Laser Scanner, and Corner Reflector Deformation Experiments
Sensors 2018, 18(12), 4401; https://doi.org/10.3390/s18124401 (registering DOI)
Received: 15 October 2018 / Revised: 19 November 2018 / Accepted: 5 December 2018 / Published: 12 December 2018
PDF Full-text (27444 KB) | HTML Full-text | XML Full-text
Abstract
An integrated sensor system comprised of a terrestrial laser scanner (TLS), corner reflectors (CRs), and high precision linear rail is utilized to validate ground-based synthetic aperture radar (GB-SAR) interferometric micro-displacement measurements. A rail with positioning accuracy of 0.1 mm is deployed to ensure
[...] Read more.
An integrated sensor system comprised of a terrestrial laser scanner (TLS), corner reflectors (CRs), and high precision linear rail is utilized to validate ground-based synthetic aperture radar (GB-SAR) interferometric micro-displacement measurements. A rail with positioning accuracy of 0.1 mm is deployed to ensure accurate and controllable deformation. The rail is equipped with a CR on a sliding platform for mobility. Three smaller CRs are installed nearby, each with a reflective sticker attached to the CR’s vertex; the CRs present as high-amplitude points both in the GB-SAR images and the TLS point cloud to allow for accurate data matching. We analyze the GB-SAR zero-baseline repeated rail differential interferometry signal model to obtain 2D interferograms of the test site in time series, and then use TLS to obtain a 3D surface model. The model is matched with interferograms to produce more intuitive 3D products. The CR displacements can also be extracted via surface reconstruction algorithm. Finally, we compared the rail sensor measurement and TLS results to optimize coherent scatterer selection and filter the data. The proposed method yields accurate target displacement results via quantitative analysis of GB-SAR interferometry. Full article
(This article belongs to the Section Remote Sensors)
Figures

Figure 1

Open AccessArticle Security Cost Aware Data Communication in Low-Power IoT Sensors with Energy Harvesting
Sensors 2018, 18(12), 4400; https://doi.org/10.3390/s18124400 (registering DOI)
Received: 14 November 2018 / Revised: 3 December 2018 / Accepted: 10 December 2018 / Published: 12 December 2018
PDF Full-text (2492 KB)
Abstract
Security is a critical concern in low-power IoT (Internet of Things) wireless sensors because these resource constrained devices are easy to attack and meanwhile the energy constraint sensors will consume a lot of energy to run algorithms for security purposes. We study the
[...] Read more.
Security is a critical concern in low-power IoT (Internet of Things) wireless sensors because these resource constrained devices are easy to attack and meanwhile the energy constraint sensors will consume a lot of energy to run algorithms for security purposes. We study the energy efficiency data transmission problem in IoT sensors that use capacitors to harvest wireless energy while considering the energy cost for running security algorithms. Energy harvesting with capacitors has the characteristic that the energy harvesting rate varies over time, and it is getting slower and slower as the capacitor gets more and more wireless energy. This observation will result in a trade-off for data transmission in two ways: (1) dividing data into more number of packets, thus the sensors can receive wireless energy at a higher harvesting rate, but it will result in extra energy consumption; (2) dividing data into less numbers of packets—in this way, the sensor cannot utilize the high harvesting rate, but the extra energy cost is less. We studied two sets of this problem where the low-power sensors can harvest enough wireless energy or not, and give algorithms to transmit all the data or as much data as possible, respectively, while taking into account extra cost. The theoretical performance of the proposed algorithms is also analyzed. Both theoretical analysis and extensive simulations show that the proposed algorithms have good performance. Full article
Open AccessArticle Connection of the SUMO Microscopic Traffic Simulator and the Unity 3D Game Engine to Evaluate V2X Communication-Based Systems
Sensors 2018, 18(12), 4399; https://doi.org/10.3390/s18124399 (registering DOI)
Received: 18 October 2018 / Revised: 5 December 2018 / Accepted: 8 December 2018 / Published: 12 December 2018
PDF Full-text (1705 KB) | HTML Full-text | XML Full-text
Abstract
In-vehicle applications that are based on Vehicle-to-Everything (V2X) communication technologies need to be evaluated under lab-controlled conditions before performing field tests. The need for a tailored platform to perform specific research on the cooperative Advanced Driving Assistance System (ADAS) to assess the effect
[...] Read more.
In-vehicle applications that are based on Vehicle-to-Everything (V2X) communication technologies need to be evaluated under lab-controlled conditions before performing field tests. The need for a tailored platform to perform specific research on the cooperative Advanced Driving Assistance System (ADAS) to assess the effect on driver behavior and driving performance motivated the development of a driver-centric traffic simulator that is built over a 3D graphics engine. The engine creates a driving situation as it communicates with a traffic simulator as a means to simulate real-life traffic scenarios. The TraCI as a Service (TraaS) library was implemented to perform the interaction between the driver-controlled vehicle and the Simulation of Urban MObility (SUMO). An extension of a previous version, this work improves simulation performance and realism by reducing computational demand and integrating a tailored scenario with the ADAS to be tested. The usability of the implemented simulation platform was evaluated by means of an experiment related to the efficiency of a Traffic Light Assistant (TLA), showing the analysis of the answer that 80% of the participants were satisfied with the simulator and the TLA system implemented. Full article
(This article belongs to the Special Issue Sensors Applications in Intelligent Vehicle)
Figures

Figure 1

Open AccessArticle Towards Efficient Implementation of an Octree for a Large 3D Point Cloud
Sensors 2018, 18(12), 4398; https://doi.org/10.3390/s18124398 (registering DOI)
Received: 22 October 2018 / Revised: 10 December 2018 / Accepted: 11 December 2018 / Published: 12 December 2018
PDF Full-text (7775 KB) | HTML Full-text | XML Full-text
Abstract
The present study introduces an efficient algorithm to construct a file-based octree for a large 3D point cloud. However, the algorithm was very slow compared with a memory-based approach, and got even worse when using a 3D point cloud scanned in longish objects
[...] Read more.
The present study introduces an efficient algorithm to construct a file-based octree for a large 3D point cloud. However, the algorithm was very slow compared with a memory-based approach, and got even worse when using a 3D point cloud scanned in longish objects like tunnels and corridors. The defects were addressed by implementing a semi-isometric octree group. The approach implements several semi-isometric octrees in a group, which tightly covers the 3D point cloud, though each octree along with its leaf node still maintains an isometric shape. The proposed approach was tested using three 3D point clouds captured in a long tunnel and a short tunnel by a terrestrial laser scanner, and in an urban area by an airborne laser scanner. The experimental results showed that the performance of the semi-isometric approach was not worse than a memory-based approach, and quite a lot better than a file-based one. Thus, it was proven that the proposed semi-isometric approach achieves a good balance between query performance and memory efficiency. In conclusion, if given enough main memory and using a moderately sized 3D point cloud, a memory-based approach is preferable. When the 3D point cloud is larger than the main memory, a file-based approach seems to be the inevitable choice, however, the semi-isometric approach is the better option. Full article
(This article belongs to the Special Issue Terrestrial Laser Scanning)
Figures

Figure 1

Open AccessArticle Transformerless Ultrasonic Ranging System with the Feature of Intrinsic Safety for Explosive Environment
Sensors 2018, 18(12), 4397; https://doi.org/10.3390/s18124397 (registering DOI)
Received: 1 November 2018 / Revised: 2 December 2018 / Accepted: 8 December 2018 / Published: 12 December 2018
PDF Full-text (8812 KB) | HTML Full-text | XML Full-text
Abstract
The transformer used in the conventional ultrasonic ranging system could provide a huge instantaneous driving voltage for the generation of ultrasonic wave, which leads to the safety problem in the explosive mixture. This paper proposes a transformerless ultrasonic ranging system powered by the
[...] Read more.
The transformer used in the conventional ultrasonic ranging system could provide a huge instantaneous driving voltage for the generation of ultrasonic wave, which leads to the safety problem in the explosive mixture. This paper proposes a transformerless ultrasonic ranging system powered by the intrinsically safe power source and analog switches. The analysis of intrinsic characteristics of ultrasonic driving circuit is realized in normal and fault conditions. The echo-processing circuit combined with LIN bus technology is further adopted in order to improve the system stability. After the analysis of the timing diagram of ranging instruction, the evaluation experiments of ranging accuracy and ranging stability are completed. The results show that the system can realize reliable bidirectional communication between the LIN master node circuit and the ultrasonic transceiver unit, which realizes the transformerless driving. The system can realize the distance measurement within the range of 250–2700 mm, and the measurement error is less than 30 mm. The measurement fluctuation is less than 10 mm, which provides a new solution for the ultrasonic ranging system in the potentially explosive atmosphere. Full article
(This article belongs to the Special Issue Ultrasound Transducers)
Figures

Figure 1

Open AccessArticle Characterization of Tunable Micro-Lenses with a Versatile Optical Measuring System
Sensors 2018, 18(12), 4396; https://doi.org/10.3390/s18124396 (registering DOI)
Received: 14 November 2018 / Revised: 7 December 2018 / Accepted: 9 December 2018 / Published: 12 December 2018
PDF Full-text (3249 KB) | HTML Full-text | XML Full-text
Abstract
In this work, we present the results of the opto–electro–mechanical characterization of tunable micro-lenses, Tlens®, performed with a single-spot optical measuring system. Tested devices are composed of a transparent soft polymer layer that is deposited on a supporting glass substrate and
[...] Read more.
In this work, we present the results of the opto–electro–mechanical characterization of tunable micro-lenses, Tlens®, performed with a single-spot optical measuring system. Tested devices are composed of a transparent soft polymer layer that is deposited on a supporting glass substrate and is covered by a glass membrane with a thin-film piezoelectric actuator on top. Near-infrared optical low-coherence reflectometry is exploited for both static and low-frequency dynamic analyses in the time domain. Optical thickness of the layers and of the overall structure, actuation efficiency, and hysteretic behavior of the piezo-actuator as a function of driving voltage are obtained by processing the back-reflected signal in different ways. The use of optical sources with relatively short coherence lengths allows performing interferometric measurements without spurious resonance effects due to multiple parallel interfaces, furthermore, selecting the plane/layer to be monitored. We finally report results of direct measurements of Tlens® optical power as a function of driving voltage, performed by redirecting a He-Ne laser beam on the lens and monitoring the focused spot at various distances with a digital camera. Full article
(This article belongs to the collection Modeling, Testing and Reliability Issues in MEMS Engineering)
Figures

Figure 1

Open AccessArticle Interdomain I/O Optimization in Virtualized Sensor Networks
Sensors 2018, 18(12), 4395; https://doi.org/10.3390/s18124395 (registering DOI)
Received: 29 October 2018 / Revised: 5 December 2018 / Accepted: 6 December 2018 / Published: 12 December 2018
PDF Full-text (938 KB) | HTML Full-text | XML Full-text
Abstract
In virtualized sensor networks, virtual machines (VMs) share the same hardware for sensing service consolidation and saving power. For those VMs that reside in the same hardware, frequent interdomain data transfers are invoked for data analytics, and sensor collaboration and actuation. Traditional ways
[...] Read more.
In virtualized sensor networks, virtual machines (VMs) share the same hardware for sensing service consolidation and saving power. For those VMs that reside in the same hardware, frequent interdomain data transfers are invoked for data analytics, and sensor collaboration and actuation. Traditional ways of interdomain communications are based on virtual network interfaces of bilateral VMs for data sending and receiving. Since these network communications use TCP/IP (Transmission Control Protocol/Internet Protocol) stacks, they result in lengthy communication paths and frequent kernel interactions, which deteriorate the I/O (Input/Output) performance of involved VMs. In this paper, we propose an optimized interdomain communication approach based on shared memory to improve the interdomain communication performance of multiple VMs residing in the same sensor hardware. In our approach, the sending data are shared in memory pages maintained by the hypervisor, and the data are not transferred through the virtual network interface via a TCP/IP stack. To avoid security trapping, the shared data are mapped in the user space of each VM involved in the communication, therefore reducing tedious system calls and frequent kernel context switches. In implementation, the shared memory is created by a customized shared-device kernel module that has bidirectional event channels between both communicating VMs. For performance optimization, we use state flags in a circular buffer to reduce wait-and-notify operations and system calls during communications. Experimental results show that our proposed approach can provide five times higher throughput and 2.5 times less latency than traditional TCP/IP communication via a virtual network interface. Full article
Figures

Figure 1

Open AccessArticle The Effect of Gamma and Beta Radiation on a UVTRON Flame Sensor: Assessment of the Impact on Implementation in a Mixed Radiation Field
Sensors 2018, 18(12), 4394; https://doi.org/10.3390/s18124394 (registering DOI)
Received: 31 October 2018 / Revised: 28 November 2018 / Accepted: 1 December 2018 / Published: 12 December 2018
PDF Full-text (3004 KB) | HTML Full-text | XML Full-text
Abstract
Due to the short path length of alpha particles in air, a detector that can be used at a distance from any potential radiological contamination reduces the time and hazard that traditional alpha detection methods incur. This would reduce costs and protect personnel
[...] Read more.
Due to the short path length of alpha particles in air, a detector that can be used at a distance from any potential radiological contamination reduces the time and hazard that traditional alpha detection methods incur. This would reduce costs and protect personnel in nuclear power generation and decommissioning activities, where alpha detection is crucial to full characterisation and contamination detection. Stand-off alpha detection could potentially be achieved by the detection of alpha-induced radioluminescence, especially in the ultraviolet C (UVC) wavelength range (180–280 nm) where natural and artificial background lighting is less likely to interfere with detection. However, such a detector would also have to be effective in the field, potentially in the presence of other radiation sources that could mask the UVC signal. This work exposed a UVC sensor, the UVTRON (Hamamatsu, Japan) and associated electronics (driver circuit, microprocessor) to sources of beta and gamma radiation in order to assess its response to both of these types of radiation, as may be found in the field where a mixed radiation environment is likely. It has been found that the UVTRON is affected by both gamma and beta radiation of a magnitude that would mask any UVC signal being detected. 152Eu generated 0.01 pulses per second per Bq through beta and gamma interactions, compared to 210Po, which generates 4.72 × 10−8 cps per Bq from UVC radioluminescence, at 20 mm separation. This work showed that UVTRON itself is more susceptible to this radiation than the associated electronics. The results of this work have implications for the use of the UVTRON as a sensor in a stand-off detection system, highlighting the necessity for shielding from both potential gamma and beta radiation in any detector design. Full article
(This article belongs to the Section Chemical Sensors)
Figures

Figure 1

Open AccessArticle All-Fiber CO2 Sensor Using Hollow Core PCF Operating in the 2 µm Region
Sensors 2018, 18(12), 4393; https://doi.org/10.3390/s18124393 (registering DOI)
Received: 30 October 2018 / Revised: 3 December 2018 / Accepted: 5 December 2018 / Published: 12 December 2018
PDF Full-text (2631 KB) | HTML Full-text | XML Full-text
Abstract
A realistic implementation of an all-fiber CO2 sensor, using 74 cm of hollow core photonic crystal fiber (HC-PCF) as the cavity for light/gas interaction, has been implemented. It is based on CO2 absorbance in the 2 µm region. The working range
[...] Read more.
A realistic implementation of an all-fiber CO2 sensor, using 74 cm of hollow core photonic crystal fiber (HC-PCF) as the cavity for light/gas interaction, has been implemented. It is based on CO2 absorbance in the 2 µm region. The working range is from 2% to 100% CO2 concentration at 1 atm total pressure and the response time obtained was 10 min. Depending on the concentration level, the sensor operates at one of three different wavelengths (2003.5 nm, 1997.0 nm and 1954.5 nm) to maintain a high sensitivity across all the working range. Full article
(This article belongs to the Special Issue Optical Sensors Using Microstructured and Photonics Crystal Fibers)
Figures

Figure 1

Open AccessArticle Paper-Based Magneto-Resistive Sensor: Modeling, Fabrication, Characterization, and Application
Sensors 2018, 18(12), 4392; https://doi.org/10.3390/s18124392 (registering DOI)
Received: 7 November 2018 / Revised: 29 November 2018 / Accepted: 10 December 2018 / Published: 11 December 2018
PDF Full-text (37293 KB)
Abstract
In this work, we developed and fabricated a paper-based anisotropic magneto-resistive sensor using a sputtered permalloy (Ni81Fe19) thin film. To interpret the characteristics of the sensor, we proposed a computational model to capture the influence of the stochastic fiber
[...] Read more.
In this work, we developed and fabricated a paper-based anisotropic magneto-resistive sensor using a sputtered permalloy (Ni 81 Fe 19 ) thin film. To interpret the characteristics of the sensor, we proposed a computational model to capture the influence of the stochastic fiber network of the paper surface and to explain the physics behind the empirically observed difference in paper-based anisotropic magneto-resistance (AMR). Using the model, we verified two main empirical observations: (1) The stochastic fiber network of the paper substrate induces a shift of 45 in the AMR response of the paper-based Ni 81 Fe 19 thin film compared to a Ni 81 Fe 19 film on a smooth surface as long as the fibrous topography has not become buried. (2) The ratio of magnitudes of AMR peaks at different anisotropy angles and the inverted AMR peak at the 90 -anisotropy angle are explained through the superposition of the responses of Ni 81 Fe 19 inheriting the fibrous topography and smoother Ni 81 Fe 19 on buried fibrous topographies. As for the sensitivity and reproducibility of the sensor signal, we obtained a maximum AMR peak of 0 . 4 % , min-max sensitivity range of [ 0 . 17 , 0 . 26 ] % , average asymmetry of peak location of 2 . 7 kA m within two consecutive magnetic loading cycles, and a deviation of 250–850 A m of peak location across several anisotropy angles at a base resistance of ∼100 Ω . Last, we demonstrated the usability of the sensor in two educational application examples: a textbook clicker and interactive braille flashcards. Full article
(This article belongs to the Section Physical Sensors)
Open AccessArticle Hyperspectral Image-Based Variety Classification of Waxy Maize Seeds by the t-SNE Model and Procrustes Analysis
Sensors 2018, 18(12), 4391; https://doi.org/10.3390/s18124391 (registering DOI)
Received: 10 October 2018 / Revised: 7 December 2018 / Accepted: 8 December 2018 / Published: 11 December 2018
PDF Full-text (1722 KB)
Abstract
Variety classification is an important step in seed quality testing. This study introduces t-distributed stochastic neighbourhood embedding (t-SNE), a manifold learning algorithm, into the field of hyperspectral imaging (HSI) and proposes a method for classifying seed varieties. Images of 800 maize kernels of
[...] Read more.
Variety classification is an important step in seed quality testing. This study introduces t-distributed stochastic neighbourhood embedding (t-SNE), a manifold learning algorithm, into the field of hyperspectral imaging (HSI) and proposes a method for classifying seed varieties. Images of 800 maize kernels of eight varieties (100 kernels per variety, 50 kernels for each side of the seed) were imaged in the visible- near infrared (386.7–1016.7 nm) wavelength range. The images were pre-processed by Procrustes analysis (PA) to improve the classification accuracy, and then these data were reduced to low-dimensional space using t-SNE. Finally, Fisher’s discriminant analysis (FDA) was used for classification of the low-dimensional data. To compare the effect of t-SNE, principal component analysis (PCA), kernel principal component analysis (KPCA) and locally linear embedding (LLE) were used as comparative methods in this study, and the results demonstrated that the t-SNE model with PA pre-processing has obtained better classification results. The highest classification accuracy of the t-SNE model was up to 97.5%, which was much more satisfactory than the results of the other models (up to 75% for PCA, 85% for KPCA, 76.25% for LLE). The overall results indicated that the t-SNE model with PA pre-processing can be used for variety classification of waxy maize seeds and be considered as a new method for hyperspectral image analysis. Full article
(This article belongs to the Section Remote Sensors)
Open AccessArticle Research on Distributed 5G Signal Coverage Detection Algorithm Based on PSO-BP-Kriging
Sensors 2018, 18(12), 4390; https://doi.org/10.3390/s18124390
Received: 19 November 2018 / Revised: 4 December 2018 / Accepted: 7 December 2018 / Published: 11 December 2018
PDF Full-text (1551 KB)
Abstract
In order to overcome the limitations of traditional road test methods in 5G mobile communication network signal coverage detection, a signal coverage detection algorithm based on distributed sensor network for 5G mobile communication network is proposed. First, the received signal strength of the
[...] Read more.
In order to overcome the limitations of traditional road test methods in 5G mobile communication network signal coverage detection, a signal coverage detection algorithm based on distributed sensor network for 5G mobile communication network is proposed. First, the received signal strength of the communication base station is collected and pre-processed by randomly deploying distributed sensor nodes. Then, the neural network objective function is modified by using the variogram function, and the initial weight coefficient of the neural network is optimized by using the improved particle swarm optimization algorithm. Next, the trained network model is used to interpolate the perceptual blind zone. Finally, the sensor node sampling data and the interpolation estimation result are combined to generate an effective coverage of the 5G mobile communication network signal. Simulation results indicate that the proposed algorithm can detect the real situation of 5G mobile communication network signal coverage better than other algorithms, and has certain feasibility and application prospects. Full article
(This article belongs to the Section Sensor Networks)
Open AccessArticle Lane Endpoint Detection and Position Accuracy Evaluation for Sensor Fusion-Based Vehicle Localization on Highways
Sensors 2018, 18(12), 4389; https://doi.org/10.3390/s18124389
Received: 14 November 2018 / Revised: 8 December 2018 / Accepted: 10 December 2018 / Published: 11 December 2018
PDF Full-text (16464 KB) | HTML Full-text | XML Full-text
Abstract
Landmark-based vehicle localization is a key component of both autonomous driving and advanced driver assistance systems (ADAS). Previously used landmarks in highways such as lane markings lack information on longitudinal positions. To address this problem, lane endpoints can be used as landmarks. This
[...] Read more.
Landmark-based vehicle localization is a key component of both autonomous driving and advanced driver assistance systems (ADAS). Previously used landmarks in highways such as lane markings lack information on longitudinal positions. To address this problem, lane endpoints can be used as landmarks. This paper proposes two essential components when using lane endpoints as landmarks: lane endpoint detection and its accuracy evaluation. First, it proposes a method to efficiently detect lane endpoints using a monocular forward-looking camera, which is the most widely installed perception sensor. Lane endpoints are detected with a small amount of computation based on the following steps: lane detection, lane endpoint candidate generation, and lane endpoint candidate verification. Second, it proposes a method to reliably measure the position accuracy of the lane endpoints detected from images taken while the camera is moving at high speed. A camera is installed with a mobile mapping system (MMS) in a vehicle, and the position accuracy of the lane endpoints detected by the camera is measured by comparing their positions with ground truths obtained by the MMS. In the experiment, the proposed methods were evaluated and compared with previous methods based on a dataset acquired while driving on 80 km of highway in both daytime and nighttime. Full article
(This article belongs to the Special Issue Sensors Applications in Intelligent Vehicle)
Figures

Figure 1

Open AccessArticle Reducing Message Collisions in Sensing-Based Semi-Persistent Scheduling (SPS) by Using Reselection Lookaheads in Cellular V2X
Sensors 2018, 18(12), 4388; https://doi.org/10.3390/s18124388
Received: 9 November 2018 / Revised: 5 December 2018 / Accepted: 7 December 2018 / Published: 11 December 2018
PDF Full-text (710 KB) | HTML Full-text | XML Full-text
Abstract
In the C-V2X sidelink Mode 4 communication, the sensing-based semi-persistent scheduling (SPS) implements a message collision avoidance algorithm to cope with the undesirable effects of wireless channel congestion. Still, the current standard mechanism produces a high number of packet collisions, which may hinder
[...] Read more.
In the C-V2X sidelink Mode 4 communication, the sensing-based semi-persistent scheduling (SPS) implements a message collision avoidance algorithm to cope with the undesirable effects of wireless channel congestion. Still, the current standard mechanism produces a high number of packet collisions, which may hinder the high-reliability communications required in future C-V2X applications such as autonomous driving. In this paper, we show that by drastically reducing the uncertainties in the choice of the resource to use for SPS, we can significantly reduce the message collisions in the C-V2X sidelink Mode 4. Specifically, we propose the use of the “lookahead”, which contains the next starting resource location in the time-frequency plane. By exchanging the lookahead information piggybacked on the periodic safety message, vehicular user equipment (UEs) can eliminate most message collisions arising from the ignorance of other UEs’ internal decisions. Although the proposed scheme would require the inclusion of the lookahead in the control part of the packet, the benefit may outweigh the bandwidth cost, considering the stringent reliability requirement in future C-V2X applications. Full article
(This article belongs to the Special Issue Advances on Vehicular Networks: From Sensing to Autonomous Driving)
Figures

Figure 1

Open AccessArticle Centralized Unmanned Aerial Vehicle Mesh Network Placement Scheme: A Multi-Objective Evolutionary Algorithm Approach
Sensors 2018, 18(12), 4387; https://doi.org/10.3390/s18124387
Received: 15 October 2018 / Revised: 6 December 2018 / Accepted: 8 December 2018 / Published: 11 December 2018
PDF Full-text (1088 KB) | HTML Full-text | XML Full-text
Abstract
In the past, Unmanned Aerial Vehicles (UAVs) were mostly used in military operations to prevent pilot losses. Nowadays, the fast technological evolution has enabled the production of a class of cost-effective UAVs that can service a plethora of public and civilian applications, especially
[...] Read more.
In the past, Unmanned Aerial Vehicles (UAVs) were mostly used in military operations to prevent pilot losses. Nowadays, the fast technological evolution has enabled the production of a class of cost-effective UAVs that can service a plethora of public and civilian applications, especially when configured to work cooperatively to accomplish a task. However, designing a communication network among the UAVs is a challenging task. In this article, we propose a centralized UAV placement strategy, where UAVs are used as flying access points forming a mesh network, providing connectivity to ground nodes deployed in a target area. The geographical placement of UAVs is optimized based on a Multi-Objective Evolutionary Algorithm (MOEA). The goal of the proposed scheme is to cover all ground nodes using a minimum number of UAVs, while maximizing the fulfillment of their data rate requirements. The UAVs can employ different data rates depending on the channel conditions, which are expressed by the Signal-to-Noise-Ratio (SNR). In this work, the elitist Non-Dominated Sorting Genetic Algorithm II (NSGA-II) is used to find a set of optimal positions to place UAVs, given the positions of the ground nodes. We evaluate the trade-off between the number of UAVs used to cover the target area and the data rate requirement of the ground nodes. Simulation results show that the proposed algorithm can optimize the UAV placement given the requirement and the positions of the ground nodes in the geographical area. Full article
(This article belongs to the Special Issue Unmanned Aerial Vehicle Networks, Systems and Applications)
Figures

Figure 1

Open AccessArticle Scale Factor Calibration for a Rotating Accelerometer Gravity Gradiometer
Sensors 2018, 18(12), 4386; https://doi.org/10.3390/s18124386
Received: 28 October 2018 / Revised: 30 November 2018 / Accepted: 5 December 2018 / Published: 11 December 2018
PDF Full-text (1772 KB)
Abstract
Rotating Accelerometer Gravity Gradiometers (RAGGs) play a significant role in applications such as resource exploration and gravity aided navigation. Scale factor calibration is an essential procedure for RAGG instruments before being used. In this paper, we propose a calibration system for a gravity
[...] Read more.
Rotating Accelerometer Gravity Gradiometers (RAGGs) play a significant role in applications such as resource exploration and gravity aided navigation. Scale factor calibration is an essential procedure for RAGG instruments before being used. In this paper, we propose a calibration system for a gravity gradiometer to obtain the scale factor effectively, even when there are mass disturbance surroundings. In this system, four metal spring-based accelerometers with a good consistency are orthogonally assembled onto a rotary table to measure the spatial variation of the gravity gradient. By changing the approaching pattern of the reference gravity gradient excitation object, the calibration results are generated. Experimental results show that the proposed method can efficiently and repetitively detect a gravity gradient excitation mass weighing 260 kg within a range of 1.6 m and the scale factor of RAGG can be obtained as (5.4 ± 0.2) E/μV, which is consistent with the theoretical simulation. Error analyses reveal that the performance of the proposed calibration scheme is mainly limited by positioning error of the excitation and can be improved by applying higher accuracy position rails. Furthermore, the RAGG is expected to perform more efficiently and reliably in field tests in the future. Full article
(This article belongs to the Special Issue Gyroscopes and Accelerometers)
Open AccessArticle Enhancing Multi-Camera People Detection by Online Automatic Parametrization Using Detection Transfer and Self-Correlation Maximization
Sensors 2018, 18(12), 4385; https://doi.org/10.3390/s18124385
Received: 5 November 2018 / Revised: 7 December 2018 / Accepted: 8 December 2018 / Published: 11 December 2018
PDF Full-text (1928 KB) | HTML Full-text | XML Full-text
Abstract
Finding optimal parametrizations for people detectors is a complicated task due to the large number of parameters and the high variability of application scenarios. In this paper, we propose a framework to adapt and improve any detector automatically in multi-camera scenarios where people
[...] Read more.
Finding optimal parametrizations for people detectors is a complicated task due to the large number of parameters and the high variability of application scenarios. In this paper, we propose a framework to adapt and improve any detector automatically in multi-camera scenarios where people are observed from various viewpoints. By accurately transferring detector results between camera viewpoints and by self-correlating these transferred results, the best configuration (in this paper, the detection threshold) for each detector-viewpoint pair is identified online without requiring any additional manually-labeled ground truth apart from the offline training of the detection model. Such a configuration consists of establishing the confidence detection threshold present in every people detector, which is a critical parameter affecting detection performance. The experimental results demonstrate that the proposed framework improves the performance of four different state-of-the-art detectors (DPM , ACF, faster R-CNN, and YOLO9000) whose Optimal Fixed Thresholds (OFTs) have been determined and fixed during training time using standard datasets. Full article
(This article belongs to the Section Intelligent Sensors)
Figures

Figure 1

Open AccessTechnical Note Nonlinear Steering Wheel Angle Control Using Self-Aligning Torque with Torque and Angle Sensors for Electrical Power Steering of Lateral Control System in Autonomous Vehicles
Sensors 2018, 18(12), 4384; https://doi.org/10.3390/s18124384
Received: 14 November 2018 / Revised: 5 December 2018 / Accepted: 6 December 2018 / Published: 11 December 2018
PDF Full-text (833 KB) | HTML Full-text | XML Full-text
Abstract
The development of sensor technology enabled the use of composite sensors to measure the torque and angle of steering wheels at gradually decreasing costs while maintaining the required safety. The electric power steering (EPS) is vital to the safety of the car, therefore
[...] Read more.
The development of sensor technology enabled the use of composite sensors to measure the torque and angle of steering wheels at gradually decreasing costs while maintaining the required safety. The electric power steering (EPS) is vital to the safety of the car, therefore it is not worth sacrificing safety to save cost and the SWA control with angle sensor gradually becomes the mainstream. Existing methods to control steering wheel angle (SWA) for EPS consider the self-aligning torque as a disturbance that should be rejected. However, this torque is useful to return the SWA from an outward to the center position. Hence, we propose a nonlinear control of SWA using the self-aligning torque for EPS in the lateral control system of autonomous vehicles. The proposed method consists of a high-gain disturbance observer and a backstepping controller, where the former aims to estimate the self-aligning torque, and an auxiliary state variable prevents using the derivative of the measured signal. The nonlinear controller is designed via backstepping to bound the SWA tracking error. The self-aligning torque provides damping that can improve the controller tracking when following the same direction of the input torque on the steering wheel control. In this case, the control input can be reduced by the damping effect of the self-aligning torque. The performance of the proposed method is validated through EPS hardware-in-the-loop simulation. Full article
(This article belongs to the Section Physical Sensors)
Figures

Figure 1

Open AccessArticle UISTD: A Trust-Aware Model for Diverse Item Personalization in Social Sensing with Lower Privacy Intrusion
Sensors 2018, 18(12), 4383; https://doi.org/10.3390/s18124383
Received: 30 October 2018 / Revised: 4 December 2018 / Accepted: 8 December 2018 / Published: 11 December 2018
PDF Full-text (1711 KB) | HTML Full-text | XML Full-text
Abstract
Privacy intrusion has become a major bottleneck for current trust-aware social sensing, since online social media allows anybody to largely disclose their personal information due to the proliferation of the Internet of Things (IoT). State-of-the-art social sensing still suffers from severe privacy threats
[...] Read more.
Privacy intrusion has become a major bottleneck for current trust-aware social sensing, since online social media allows anybody to largely disclose their personal information due to the proliferation of the Internet of Things (IoT). State-of-the-art social sensing still suffers from severe privacy threats since it collects users’ personal data and disclosure behaviors, which could raise user privacy concerns due to data integration for personalization. In this paper, we propose a trust-aware model, called the User and Item Similarity Model with Trust in Diverse Kinds (UISTD), to enhance the personalization of social sensing while reducing users’ privacy concerns. UISTD utilizes user-to-user similarities and item-to-item similarities to generate multiple kinds of personalized items with common tags. UISTD also applies a modified k-means clustering algorithm to select the core users among trust relationships, and the core users’ preferences and disclosure behaviors will be regarded as the predicted disclosure pattern. The experimental results on three real-world data sets demonstrate that target users are more likely to: (1) follow the core users’ interests on diverse kinds of items and disclosure behaviors, thereby outperforming the compared methods; and (2) disclose more information with lower intrusion awareness and privacy concern. Full article
(This article belongs to the Special Issue Social Sensing)
Figures

Figure 1

Open AccessArticle Energy and Spectrally Efficient Modulation Scheme for IoT Applications
Sensors 2018, 18(12), 4382; https://doi.org/10.3390/s18124382
Received: 5 September 2018 / Revised: 10 November 2018 / Accepted: 30 November 2018 / Published: 11 December 2018
PDF Full-text (2621 KB) | HTML Full-text | XML Full-text
Abstract
Due to the Internet of Things (IoT) requirements for a high-density network with low-cost and low-power physical (PHY) layer design, the low-power budget transceiver systems have drawn momentous attention lately owing to their superior performance enhancement in both energy efficiency and hardware complexity
[...] Read more.
Due to the Internet of Things (IoT) requirements for a high-density network with low-cost and low-power physical (PHY) layer design, the low-power budget transceiver systems have drawn momentous attention lately owing to their superior performance enhancement in both energy efficiency and hardware complexity reduction. As the power budget of the classical transceivers is envisioned by using inefficient linear power amplifiers (PAs) at the transmitter (TX) side and by applying high-resolution analog to digital converters (ADCs) at the receiver (RX) side, the transceiver architectures with low-cost PHY layer design (i.e., nonlinear PA at the TX and one-bit ADC at the RX) are mandated to cope with the vast IoT applications. Therefore, in this paper, we propose the orthogonal shaping pulses minimum shift keying (OSP-MSK) as a multiple-input multiple-output (MIMO) modulation/demodulation scheme in order to design the low-cost transceiver architectures associated with the IoT devices. The OSP-MSK fulfills a low-power budget by using constant envelope modulation (CEM) techniques at the TX side, and by applying a low-resolution one-bit ADC at the RX side. Furthermore, the OSP-MSK provides a higher spectral efficiency compared to the recently introduced MIMO-CEM with the one-bit ADC. In this context, the orthogonality between the in-phase and quadrature-phase components of the OSP are exploited to increase the number of transmitted bits per symbol (bps) without the need for extra bandwidth. The performance of the proposed scheme is investigated analytically and via Monte Carlo simulations. For the mathematical analysis, we derive closed-form expressions for assessing the average bit error rate (ABER) performance of the OSP-MSK modulation in conjunction with Rayleigh and Nakagami-m fading channels. Moreover, a closed-form expression for evaluating the power spectral density (PSD) of the proposed scheme is obtained as well. The simulation results corroborate the potency of the conducted analysis by revealing a high consistency with the obtained analytical formulas. Full article
(This article belongs to the Section Internet of Things)
Figures

Figure 1

Open AccessArticle Multi-Sensor Data Fusion for Real-Time Surface Quality Control in Automated Machining Systems
Sensors 2018, 18(12), 4381; https://doi.org/10.3390/s18124381
Received: 9 November 2018 / Revised: 6 December 2018 / Accepted: 7 December 2018 / Published: 11 December 2018
PDF Full-text (8050 KB) | HTML Full-text | XML Full-text
Abstract
Multi-sensor data fusion systems entail the optimization of a wide range of parameters related to the selection of sensors, signal feature extraction methods, and predictive modeling techniques. The monitoring of automated machining systems enables the intelligent supervision of the production process by detecting
[...] Read more.
Multi-sensor data fusion systems entail the optimization of a wide range of parameters related to the selection of sensors, signal feature extraction methods, and predictive modeling techniques. The monitoring of automated machining systems enables the intelligent supervision of the production process by detecting malfunctions, and providing real-time information for continuous process optimization, and production line decision-making. Monitoring technologies are essential for the reduction of production times and costs, and an improvement in product quality, discarding the need for post-process quality controls. In this paper, a multi-sensor data fusion system for the real-time surface quality control based on cutting force, vibration, and acoustic emission signals was assessed. A total of four signal processing methods were analyzed: time direct analysis (TDA), power spectral density (PSD), singular spectrum analysis (SSA), and wavelet packet transform (WPT). Owing to the nonlinear and stochastic nature of the process, two predictive modeling techniques, multiple regression and artificial neural networks, were evaluated to correlate signal parametric characterization with surface quality. The results showed a high correlation of surface finish with cutting force and vibration signals. The signal processing methods based on signal decomposition in a combined time and frequency domain (SSA and WPT) exhibited better signal feature extraction, detecting excitation frequency ranges correlated to surface finish. The artificial neural network model obtained the highest predictive power, with better behavior for the whole data range. The proposed on-line multi-sensor data fusion provided significant improvements for in-process quality control, with excellent predictive power, reliability, and response times. Full article
(This article belongs to the collection Multi-Sensor Information Fusion)
Figures

Figure 1

Open AccessArticle Calibration Model of a Low-Cost Air Quality Sensor Using an Adaptive Neuro-Fuzzy Inference System
Sensors 2018, 18(12), 4380; https://doi.org/10.3390/s18124380
Received: 20 August 2018 / Revised: 8 October 2018 / Accepted: 19 October 2018 / Published: 11 December 2018
PDF Full-text (5053 KB) | HTML Full-text | XML Full-text
Abstract
Conventional air quality monitoring systems, such as gas analysers, are commonly used in many developed and developing countries to monitor air quality. However, these techniques have high costs associated with both installation and maintenance. One possible solution to complement these techniques is the
[...] Read more.
Conventional air quality monitoring systems, such as gas analysers, are commonly used in many developed and developing countries to monitor air quality. However, these techniques have high costs associated with both installation and maintenance. One possible solution to complement these techniques is the application of low-cost air quality sensors (LAQSs), which have the potential to give higher spatial and temporal data of gas pollutants with high precision and accuracy. In this paper, we present DiracSense, a custom-made LAQS that monitors the gas pollutants ozone (O3), nitrogen dioxide (NO2), and carbon monoxide (CO). The aim of this study is to investigate its performance based on laboratory calibration and field experiments. Several model calibrations were developed to improve the accuracy and performance of the LAQS. Laboratory calibrations were carried out to determine the zero offset and sensitivities of each sensor. The results showed that the sensor performed with a highly linear correlation with the reference instrument with a response-time range from 0.5 to 1.7 min. The performance of several calibration models including a calibrated simple equation and supervised learning algorithms (adaptive neuro-fuzzy inference system or ANFIS and the multilayer feed-forward perceptron or MLP) were compared. The field calibration focused on O3 measurements due to the lack of a reference instrument for CO and NO2. Combinations of inputs were evaluated during the development of the supervised learning algorithm. The validation results demonstrated that the ANFIS model with four inputs (WE OX, AE OX, T, and NO2) had the lowest error in terms of statistical performance and the highest correlation coefficients with respect to the reference instrument (0.8 < r < 0.95). These results suggest that the ANFIS model is promising as a calibration tool since it has the capability to improve the accuracy and performance of the low-cost electrochemical sensor. Full article
(This article belongs to the Section Physical Sensors)
Figures

Figure 1

Open AccessArticle Crack Classification of a Pressure Vessel Using Feature Selection and Deep Learning Methods
Sensors 2018, 18(12), 4379; https://doi.org/10.3390/s18124379
Received: 17 November 2018 / Revised: 5 December 2018 / Accepted: 10 December 2018 / Published: 11 December 2018
PDF Full-text (5105 KB) | HTML Full-text | XML Full-text
Abstract
Pressure vessels (PV) are designed to hold liquids, gases, or vapors at high pressures in various industries, but a ruptured pressure vessel can be incredibly dangerous if cracks are not detected in the early stage. This paper proposes a robust crack identification technique
[...] Read more.
Pressure vessels (PV) are designed to hold liquids, gases, or vapors at high pressures in various industries, but a ruptured pressure vessel can be incredibly dangerous if cracks are not detected in the early stage. This paper proposes a robust crack identification technique for pressure vessels using genetic algorithm (GA)-based feature selection and a deep neural network (DNN) in an acoustic emission (AE) examination. First, hybrid features are extracted from multiple AE sensors that represent diverse symptoms of pressure vessel faults. These features stem from various signal processing domains, such as the time domain, frequency domain, and time-frequency domain. Heterogenous features from various channels ensure a robust feature extraction process but are high-dimensional, so may contain irrelevant and redundant features. This can cause a degraded classification performance. Therefore, we use GA with a new objective function to select the most discriminant features that are highly effective for the DNN classifier when identifying crack types. The potency of the proposed method (GA + DNN) is demonstrated using AE data obtained from a self-designed pressure vessel. The experimental results indicate that the proposed method is highly effective at selecting discriminant features. These features are used as the input of the DNN classifier, achieving a 94.67% classification accuracy. Full article
(This article belongs to the Special Issue Sensors for Fault Diagnosis and Fault Tolerance)
Figures

Figure 1

Open AccessArticle Sensory Polymeric Foams as a Tool for Improving Sensing Performance of Sensory Polymers
Sensors 2018, 18(12), 4378; https://doi.org/10.3390/s18124378
Received: 22 November 2018 / Revised: 6 December 2018 / Accepted: 7 December 2018 / Published: 11 December 2018
PDF Full-text (2491 KB) | HTML Full-text | XML Full-text | Supplementary Files
Abstract
Microcellular sensory polymers prepared from solid sensory polymeric films were tested in an aqueous Hg(II) detection process to analyze their sensory behavior. First, solid acrylic-based polymeric films of 100 µm thickness were obtained via radical copolymerization process. Secondly, dithizone sensoring motifs were anchored
[...] Read more.
Microcellular sensory polymers prepared from solid sensory polymeric films were tested in an aqueous Hg(II) detection process to analyze their sensory behavior. First, solid acrylic-based polymeric films of 100 µm thickness were obtained via radical copolymerization process. Secondly, dithizone sensoring motifs were anchored in a simple five-step route, obtaining handleable colorimetric sensory films. To create the microporous structure, films were foamed in a ScCO2 batch process, carried out at 350 bar and 60 °C, resulting in homogeneous morphologies with cell sizes around 5 µm. The comparative behavior of the solid and foamed sensory films was tested in the detection of mercury in pure water media at 2.2 pH, resulting in a reduction of the response time (RT) around 25% and limits of detection and quantification (LOD and LOQ) four times lower when using foamed films, due to the increase of the specific surface associated to the microcellular structure. Full article
(This article belongs to the Special Issue Polymers Based Sensors)
Figures

Figure 1

Open AccessArticle Reputation-Based Spectrum Sensing Strategy Selection in Cognitive Radio Ad Hoc Networks
Sensors 2018, 18(12), 4377; https://doi.org/10.3390/s18124377
Received: 8 November 2018 / Revised: 3 December 2018 / Accepted: 6 December 2018 / Published: 11 December 2018
PDF Full-text (1377 KB) | HTML Full-text | XML Full-text
Abstract
Spectrum sensing plays an essential role in the detection of unused spectrum whole in cognitive radio networks, including cooperative spectrum sensing (CSS) and independent spectrum sensing. In cognitive radio ad hoc networks (CRAHNs), CSS enhances the sensing performance of cognitive nodes by exploring
[...] Read more.
Spectrum sensing plays an essential role in the detection of unused spectrum whole in cognitive radio networks, including cooperative spectrum sensing (CSS) and independent spectrum sensing. In cognitive radio ad hoc networks (CRAHNs), CSS enhances the sensing performance of cognitive nodes by exploring the spectrum partial homogeneity and fully utilizing the knowledge of neighboring nodes, e.g., sensing results and topological information. However, CSS may also open a door for malicious nodes, i.e., spectrum sensing data falsification (SSDF) attackers, which report fake sensing results to deteriorate the performance of CSS. Generally, the performance of CSS has an inverse relationship with the fraction of SSDF attackers. On the contrary, independent spectrum sensing is robust to SSDF attacks. Therefore, it is desirable to choose a proper sensing strategy between independent sensing and collaborative sensing for CRAHNs coexisting with various fractions of SSDF attackers. In this paper, a novel algorithm called Spectrum Sensing Strategy Selection (4S) is proposed to select better sensing strategies either in a collaborative or in an independent manner. To derive the maximum a posteriori estimation of nodes’ spectrum status, we investigated the graph cut-based CSS method, through which the topological information cost function and the sensing results cost function were constructed. Moreover, the reputation value was applied to evaluate the performance of CSS and independent sensing. The reputation threshold was theoretically analyzed to minimize the probability of choosing the sensing manner with worse performance. Simulations were carried out to verify the viability and the efficiency of the proposed algorithm. Full article
(This article belongs to the Section Sensor Networks)
Figures

Figure 1

Open AccessArticle Theoretical and Experimental Analysis on the Influence of Rotor Non-Mechanical Errors of the Inductive Transducer in Active Magnetic Bearings
Sensors 2018, 18(12), 4376; https://doi.org/10.3390/s18124376
Received: 1 November 2018 / Revised: 27 November 2018 / Accepted: 7 December 2018 / Published: 11 December 2018
PDF Full-text (1068 KB) | HTML Full-text | XML Full-text
Abstract
Inductive transducers are widely applied to active magnetic bearings (AMBs). However, when the rotor rotates at a high speed, the rotor defects will affect the measuring signal (the magnetic field generated by transducer coils) and then reduce the transducer measuring accuracy. The rotor
[...] Read more.
Inductive transducers are widely applied to active magnetic bearings (AMBs). However, when the rotor rotates at a high speed, the rotor defects will affect the measuring signal (the magnetic field generated by transducer coils) and then reduce the transducer measuring accuracy. The rotor in AMBs is assembled with laminations, which will result in rotor non-mechanical errors. In this paper, rotor non-mechanical errors, including the anisotropic internal permeability and anisotropic surface conductivity, and their influence on double-pole variable-gap inductive transducers are explored in depth. The anisotropic internal permeability will affect the transducer measuring accuracy and bring about 1.3 ± 0.1 % measurement error. The anisotropic surface conductivity leads to different eddy currents around the rotor, influences the equivalent reluctance of the magnetic circuit, and then affectsthe transducer measuring accuracy. The experiments prove that rotor non-mechanical errors have a significant influence on transducer measurement accuracy, and the reduction of the transducer excitation frequency can reduce the measurement error and improve the AMB control performance. Full article
(This article belongs to the Section Physical Sensors)
Figures

Figure 1

Open AccessArticle An Application of the Gaussian Plume Model to Localization of an Indoor Gas Source with a Mobile Robot
Sensors 2018, 18(12), 4375; https://doi.org/10.3390/s18124375
Received: 28 October 2018 / Revised: 24 November 2018 / Accepted: 30 November 2018 / Published: 11 December 2018
PDF Full-text (7474 KB) | HTML Full-text | XML Full-text
Abstract
The source localization of gas leaks is important to avoid any potential danger to the surroundings or the probable waste of resources. Currently there are several localization methods using robotic systems that try to find the origin of a gas plume. Many of
[...] Read more.
The source localization of gas leaks is important to avoid any potential danger to the surroundings or the probable waste of resources. Currently there are several localization methods using robotic systems that try to find the origin of a gas plume. Many of these methods require wind velocity information involving the use of commercial anemometric systems which are extremely expensive compared to metal oxide gas sensors. This article proposes the validation of the Gaussian plume model inside an empty room and its application to localize the source of a gas plume without employing anemometric sensors, exclusively using concentration data. The model was selected due to its simplicity and since it easily admits variants closer to reality, explaining the behavior of pollutants transported by the wind. An artificial gas source was generated by a conventional fan and liquid ethanol as contaminant. We found that the physical fan, far from making the model impossible to implement, enriched the information and added realism. The use of a robotic system capable of autonomously mapping the room concentration distribution is described. The results showed that the Gaussian plume model is applicable to localize our experimental gas source. An estimated position of the source with a deviation of 14 cm (6.1%) was obtained. Full article
(This article belongs to the collection Gas Sensors)
Figures

Figure 1

Open AccessArticle Beacons and BIM Models for Indoor Guidance and Location
Sensors 2018, 18(12), 4374; https://doi.org/10.3390/s18124374
Received: 29 October 2018 / Revised: 6 December 2018 / Accepted: 7 December 2018 / Published: 11 December 2018
PDF Full-text (5679 KB) | HTML Full-text | XML Full-text
Abstract
This research work uses a simplified approach to combine location information from a beacon’s propagation signal interaction with a mobile device sensor (accelerometer and gyroscope) with local building information to give real-time location and guidance to a user inside a building. This is
[...] Read more.
This research work uses a simplified approach to combine location information from a beacon’s propagation signal interaction with a mobile device sensor (accelerometer and gyroscope) with local building information to give real-time location and guidance to a user inside a building. This is an interactive process with visualisation information that can help user’s orientation inside unknown buildings and the data stored from different users can provide useful information about users’ movements inside a public building. Beacons installed on the building at specific pre-defined positions emit signals that give a geographic position with an associated imprecision, related with Bluetooth’s range. This uncertainty is handled by building layout and users’ movement in a developed system that maps users’ position, gives guidance, and stores user movements. This system is based on an App (Find Me!) for Android OS (Operating System) which captures the Bluetooth Low Energy (BLE) signal coming from the beacon(s) and shows, through a map, the location of the user’s smartphone and guide him to the desired destination. Also, the beacons can deliver relevant context information. The application was tested by a panel of new and habitual campus users against traditional wayfinding alternatives yielding navigation times about 30% smaller, respectively. Full article
(This article belongs to the Section Sensor Networks)
Figures

Figure 1

Open AccessArticle Remote Sensing Assessment of Safety Risk of Iron Tailings Pond Based on Runoff Coefficient
Sensors 2018, 18(12), 4373; https://doi.org/10.3390/s18124373
Received: 14 November 2018 / Revised: 7 December 2018 / Accepted: 8 December 2018 / Published: 11 December 2018
PDF Full-text (4611 KB) | HTML Full-text | XML Full-text
Abstract
Iron tailings ponds are engineered dam and dyke systems used to capture iron tailings. They are high-risk hazards with high potential energy. If the tailings dam broke, it would pose a serious threat to the surrounding ecological environment, residents’ lives, and property. Rainfall
[...] Read more.
Iron tailings ponds are engineered dam and dyke systems used to capture iron tailings. They are high-risk hazards with high potential energy. If the tailings dam broke, it would pose a serious threat to the surrounding ecological environment, residents’ lives, and property. Rainfall is one of the most important influencing factors causing the tailings dam break. This paper took Chengde Area, a typical iron-producing area, as the study area, and proposed a remote sensing method to evaluate the safety risk of tailings ponds under rainfall condition by using runoff coefficient and catchment area. Firstly, the vegetation coverage in the study area was estimated using the pixel dichotomy model, and the vegetation type was classified by the support vector machine (SVM) method from Landsat 8 OLI image. Based on DEM, the slope of the study area was extracted, and the catchment area of the tailings pond was plotted. Then, taking slope, vegetation coverage, and vegetation type as three influencing factors, the runoff coefficient was constructed by weight assignment of each factor using analytic hierarchy process (AHP) model in both quantitative and qualitative way. Finally, the safety risk of tailings ponds was assessed according to average runoff coefficient and catchment area in the study area. The results showed that there were 124 low-risk tailings ponds, 16 moderate-risk tailings ponds, and 4 high-risk tailings ponds in the study area. This method could be useful for selecting targeted tailings ponds for focused safety monitoring. Necessary monitoring measurements should be carried out for the high-risk and moderate-risk tailings ponds in rainy season. Full article
Figures

Figure 1

Open AccessArticle Toward Security Enhanced Provisioning in Industrial IoT Systems
Sensors 2018, 18(12), 4372; https://doi.org/10.3390/s18124372
Received: 5 November 2018 / Revised: 3 December 2018 / Accepted: 8 December 2018 / Published: 10 December 2018
PDF Full-text (3839 KB) | HTML Full-text | XML Full-text
Abstract
Through the active development of industrial internet of things (IIoT) technology, there has been a rapid increase in the number of different industrial wireless sensor networks (IWSNs). Accordingly, the security of IWSNs is also of importance, as many security problems related to IWSN
[...] Read more.
Through the active development of industrial internet of things (IIoT) technology, there has been a rapid increase in the number of different industrial wireless sensor networks (IWSNs). Accordingly, the security of IWSNs is also of importance, as many security problems related to IWSN protocols have been raised and various studies have been conducted to solve these problems. However, the provisioning process is the first step in introducing a new device into the IIoT network and a starting point for IIoT security. Therefore, leakage of security information in the provisioning process makes exposure of secret keys and all subsequent security measures meaningless. In addition, using the exploited secret keys, the attacker can send false command to the node or send false data to the network manager and it can cause serious damage to industrial infrastructure depending on the IWSN. Nevertheless, a security study on the provisioning process has not been actively carried out, resulting in a provisioning process without guaranteed security. Therefore, in this paper, we analyzed security issues of the provisioning process in IWSN by researching prominent IWSN standards, including ISA 100.11a, WirelessHART, and Zigbee, and also an ISA 100.11a-certified device and provisioning process-related studies. Then, we verified the security issues of the provisioning process through testing and analyzing the provisioning process using the ISA 100.11a standard-implemented devices and ISA 100.11a-certified devices. Finally, we discuss security considerations and the direction of future research on provisioning security for IWSN in the IIoT era. Full article
(This article belongs to the Special Issue Towards an Industrial Internet of Things (IIoT))
Figures

Figure 1

Back to Top