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Sensors, Volume 19, Issue 14 (July-2 2019) – 213 articles

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Cover Story (view full-size image) 5G technology will enable the development of a plethora of new services in vehicular scenarios. In [...] Read more.
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Open AccessArticle
Feasibility Study on Temperature Distribution Measurement Method of Thrust Sliding Bearing Bush Based on FBG Quasi-Distributed Sensing
Sensors 2019, 19(14), 3245; https://doi.org/10.3390/s19143245 - 23 Jul 2019
Viewed by 997
Abstract
According to the characteristics of the temperature distribution of the thrust sliding bearing bush, the principle and method of quasi-distributed fiber Bragg grating (FBG) sensing is used to measure it. The key problems such as calibration, arrangement and lying of optical FBG sensors [...] Read more.
According to the characteristics of the temperature distribution of the thrust sliding bearing bush, the principle and method of quasi-distributed fiber Bragg grating (FBG) sensing is used to measure it. The key problems such as calibration, arrangement and lying of optical FBG sensors are studied by using the simulated thrust sliding bearing bush, which was customized in the laboratory. Combined with the thrust sliding bearing bush, the measurement experiments were carried out, which were divided into two groups: Steady-state experiments and transient experiment. The steady-state experiments obtain the temperature data measured by the FBG temperature sensors at each setting temperature, and the transient experiment obtains the relationship between the measured temperature by each temperature sensor and time in the heating and cooling process. The experimental results showed that the FBG temperature sensors had good accuracy, stability and consistency when measuring the temperature distribution of bearing bush. Full article
(This article belongs to the Special Issue Fiber-Based Sensing Technology: Recent Progresses and New Challenges)
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Open AccessArticle
Can You Ink While You Blink? Assessing Mental Effort in a Sensor-Based Calligraphy Trainer
Sensors 2019, 19(14), 3244; https://doi.org/10.3390/s19143244 - 23 Jul 2019
Cited by 1 | Viewed by 1531
Abstract
Sensors can monitor physical attributes and record multimodal data in order to provide feedback. The application calligraphy trainer, exploits these affordances in the context of handwriting learning. It records the expert’s handwriting performance to compute an expert model. The application then uses the [...] Read more.
Sensors can monitor physical attributes and record multimodal data in order to provide feedback. The application calligraphy trainer, exploits these affordances in the context of handwriting learning. It records the expert’s handwriting performance to compute an expert model. The application then uses the expert model to provide guidance and feedback to the learners. However, new learners can be overwhelmed by the feedback as handwriting learning is a tedious task. This paper presents the pilot study done with the calligraphy trainer to evaluate the mental effort induced by various types of feedback provided by the application. Ten participants, five in the control group and five in the treatment group, who were Ph.D. students in the technology-enhanced learning domain, took part in the study. The participants used the application to learn three characters from the Devanagari script. The results show higher mental effort in the treatment group when all types of feedback are provided simultaneously. The mental efforts for individual feedback were similar to the control group. In conclusion, the feedback provided by the calligraphy trainer does not impose high mental effort and, therefore, the design considerations of the calligraphy trainer can be insightful for multimodal feedback designers. Full article
(This article belongs to the Special Issue Advanced Sensors Technology in Education)
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Open AccessCorrection
Correction: Design and Simulation of a Wireless SAW–Pirani Sensor with Extended Range and Sensitivity
Sensors 2019, 19(14), 3243; https://doi.org/10.3390/s19143243 - 23 Jul 2019
Viewed by 1134
Abstract
The authors wish to make the following erratum to Reference [...] Full article
(This article belongs to the Special Issue Advances in Surface Acoustic Wave Sensors)
Open AccessArticle
A Novel Centralized Range-Free Static Node Localization Algorithm with Memetic Algorithm and Lévy Flight
Sensors 2019, 19(14), 3242; https://doi.org/10.3390/s19143242 - 23 Jul 2019
Viewed by 1046
Abstract
Node localization, which is formulated as an unconstrained NP-hard optimization problem, is considered as one of the most significant issues of wireless sensor networks (WSNs). Recently, many swarm intelligent algorithms (SIAs) were applied to solve this problem. This study aimed to determine node [...] Read more.
Node localization, which is formulated as an unconstrained NP-hard optimization problem, is considered as one of the most significant issues of wireless sensor networks (WSNs). Recently, many swarm intelligent algorithms (SIAs) were applied to solve this problem. This study aimed to determine node location with high precision by SIA and presented a new localization algorithm named LMQPDV-hop. In LMQPDV-hop, an improved DV-Hop was employed as an underground mechanism to gather the estimation distance, in which the average hop distance was modified by a defined weight to reduce the distance errors among nodes. Furthermore, an efficient quantum-behaved particle swarm optimization algorithm (QPSO), named LMQPSO, was developed to find the best coordinates of unknown nodes. In LMQPSO, the memetic algorithm (MA) and Lévy flight were introduced into QPSO to enhance the global searching ability and a new fast local search rule was designed to speed up the convergence. Extensive simulations were conducted on different WSN deployment scenarios to evaluate the performance of the new algorithm and the results show that the new algorithm can effectively improve position precision. Full article
(This article belongs to the Section Sensor Networks)
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Open AccessArticle
An Active Self-Driven Piezoelectric Sensor Enabling Real-Time Respiration Monitoring
Sensors 2019, 19(14), 3241; https://doi.org/10.3390/s19143241 - 23 Jul 2019
Viewed by 1355
Abstract
In this work, we report an active respiration monitoring sensor based on a piezoelectric-transducer-gated thin-film transistor (PTGTFT) aiming to measure respiration-induced dynamic force in real time with high sensitivity and robustness. It differs from passive piezoelectric sensors in that the piezoelectric transducer signal [...] Read more.
In this work, we report an active respiration monitoring sensor based on a piezoelectric-transducer-gated thin-film transistor (PTGTFT) aiming to measure respiration-induced dynamic force in real time with high sensitivity and robustness. It differs from passive piezoelectric sensors in that the piezoelectric transducer signal is rectified and amplified by the PTGTFT. Thus, a detailed and easy-to-analyze respiration rhythm waveform can be collected with a sufficient time resolution. The respiration rate, three phases of respiration cycle, as well as phase patterns can be further extracted for prognosis and caution of potential apnea and other respiratory abnormalities, making the PTGTFT a great promise for application in long-term real-time respiration monitoring. Full article
(This article belongs to the Section Physical Sensors)
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Open AccessArticle
Does the Femoral Head Size in Hip Arthroplasty Influence Lower Body Movements during Squats, Gait and Stair Walking? A Clinical Pilot Study Based on Wearable Motion Sensors
Sensors 2019, 19(14), 3240; https://doi.org/10.3390/s19143240 - 23 Jul 2019
Cited by 2 | Viewed by 1006
Abstract
A hip prosthesis design with larger femoral head size may improve functional outcomes compared to the conventional total hip arthroplasty (THA) design. Our aim was to compare the range of motion (RoM) in lower body joints during squats, gait and stair walking using [...] Read more.
A hip prosthesis design with larger femoral head size may improve functional outcomes compared to the conventional total hip arthroplasty (THA) design. Our aim was to compare the range of motion (RoM) in lower body joints during squats, gait and stair walking using a wearable movement analysis system based on inertial measurement units (IMUs) in three age-matched male groups: 6 males with a conventional THA (THAC), 9 with a large femoral head (LFH) design, and 8 hip- and knee-asymptomatic controls (CTRL). We hypothesized that the LFH design would allow a greater hip RoM, providing movement patterns more like CTRL, and a larger side difference in hip RoM in THAC when compared to LFH and controls. IMUs were attached to the pelvis, thighs and shanks during five trials of squats, gait, and stair ascending/descending performed at self-selected speed. THAC and LFH participants completed the Hip dysfunction and Osteoarthritis Outcome Score (HOOS). The results showed a larger hip RoM during squats in LFH compared to THAC. Side differences in LFH and THAC groups (operated vs. non-operated side) indicated that movement function was not fully recovered in either group, further corroborated by non-maximal mean HOOS scores (LFH: 83 ± 13, THAC: 84 ± 19 groups, vs. normal function 100). The IMU system may have the potential to enhance clinical movement evaluations as an adjunct to clinical scales. Full article
(This article belongs to the Special Issue Gyroscopes and Accelerometers)
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Open AccessArticle
Low Power Wide Area Networks (LPWAN) at Sea: Performance Analysis of Offshore Data Transmission by Means of LoRaWAN Connectivity for Marine Monitoring Applications
Sensors 2019, 19(14), 3239; https://doi.org/10.3390/s19143239 - 23 Jul 2019
Cited by 8 | Viewed by 2713
Abstract
In this paper the authors discuss the realization of a Long Range Wide Area Network (LoRaWAN) network infrastructure to be employed for monitoring activities within the marine environment. In particular, transmission ranges as well as the assessment of parameters like Signal to Noise [...] Read more.
In this paper the authors discuss the realization of a Long Range Wide Area Network (LoRaWAN) network infrastructure to be employed for monitoring activities within the marine environment. In particular, transmission ranges as well as the assessment of parameters like Signal to Noise Ratio (SNR) and Received Signal Strength Indicator (RSSI) are analyzed in the specific context of an aquaculture industrial plant, setting up a transmission channel from an offshore monitoring structure provided with a LoRaWAN transmitter, to an ashore receiving device composed of two LoRaWAN Gateways. A theoretical analysis about the feasibility of the transmission is provided. The performances of the system are then measured with different network parameters (in particular the Spreading Factor—SF) as well as with two different heights for the transmitting antenna. Test results prove that efficient data transmission can be achieved at a distance of 8.33 km even using worst case network settings: this suggests the effectiveness of the system even in harsher environmental conditions, thus entailing a lower quality of the transmission channel, or for larger transmission ranges. Full article
(This article belongs to the Section Internet of Things)
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Open AccessArticle
IoT-Based Home Monitoring: Supporting Practitioners’ Assessment by Behavioral Analysis
Sensors 2019, 19(14), 3238; https://doi.org/10.3390/s19143238 - 23 Jul 2019
Cited by 4 | Viewed by 1327
Abstract
This paper introduces technical solutions devised to support the Deployment Site - Regione Emilia Romagna (DS-RER) of the ACTIVAGE project. The ACTIVAGE project aims at promoting IoT (Internet of Things)-based solutions for Active and Healthy ageing. DS-RER focuses on improving continuity of care [...] Read more.
This paper introduces technical solutions devised to support the Deployment Site - Regione Emilia Romagna (DS-RER) of the ACTIVAGE project. The ACTIVAGE project aims at promoting IoT (Internet of Things)-based solutions for Active and Healthy ageing. DS-RER focuses on improving continuity of care for older adults (65+) suffering from aftereffects of a stroke event. A Wireless Sensor Kit based on Wi-Fi connectivity was suitably engineered and realized to monitor behavioral aspects, possibly relevant to health and wellbeing assessment. This includes bed/rests patterns, toilet usage, room presence and many others. Besides hardware design and validation, cloud-based analytics services are introduced, suitable for automatic extraction of relevant information (trends and anomalies) from raw sensor data streams. The approach is general and applicable to a wider range of use cases; however, for readability’s sake, two simple cases are analyzed, related to bed and toilet usage patterns. In particular, a regression framework is introduced, suitable for detecting trends (long and short-term) and labeling anomalies. A methodology for assessing multi-modal daily behavioral profiles is introduced, based on unsupervised clustering techniques. The proposed framework has been successfully deployed at several real-users’ homes, allowing for its functional validation. Clinical effectiveness will be assessed instead through a Randomized Control Trial study, currently being carried out. Full article
(This article belongs to the Special Issue IoT Sensors in E-Health)
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Open AccessFeature PaperArticle
On the Evaluation of the NB-IoT Random Access Procedure in Monitoring Infrastructures
Sensors 2019, 19(14), 3237; https://doi.org/10.3390/s19143237 - 23 Jul 2019
Cited by 4 | Viewed by 1107
Abstract
NarrowBand IoT (NB-IoT) is emerging as a promising communication technology offering a reliable wireless connection to a large number of devices employed in pervasive monitoring scenarios, such as Smart City, Precision Agriculture, and Industry 4.0. Since most of the NB-IoT transmissions occur in [...] Read more.
NarrowBand IoT (NB-IoT) is emerging as a promising communication technology offering a reliable wireless connection to a large number of devices employed in pervasive monitoring scenarios, such as Smart City, Precision Agriculture, and Industry 4.0. Since most of the NB-IoT transmissions occur in the uplink, the random access channel (that is the primary interface between devices and the base station) may usually become the main bottleneck of the entire system. For this reason, analytical models and simulation tools able to investigate its behavior in different scenarios are of the utmost importance for driving current and future research activities. Unfortunately, scientific literature partially addresses the current open issues by means of simplified and, in many cases, not standard-compliant approaches. To provide a significant step forward in this direction, the contribution of this paper is three-folded. First, it presents a flexible, open-source, and 3GPP-compliant implementation of the NB-IoT random access procedure. Second, it formulates an analytical model capturing both collision and success probabilities associated with the aforementioned procedure. Third, it presents the cross-validation of both the analytical model and the simulation tool, by taking into account reference applications scenarios of sensor networks enabling periodic reporting in monitoring infrastructures. Obtained results prove the remarkable accuracy, demonstrating a well-calibrated instrument, which will be also useful for future research activities. Full article
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Open AccessArticle
Methylated Poly(ethylene)imine Modified Capacitive Micromachined Ultrasonic Transducer for Measurements of CO2 and SO2 in Their Mixtures
Sensors 2019, 19(14), 3236; https://doi.org/10.3390/s19143236 - 23 Jul 2019
Cited by 3 | Viewed by 1249
Abstract
A gravimetric gas detection device based on surface functionalized Capacitive Micromachined Ultrasound Transducers (CMUTs) was designed, fabricated and tested for detection of carbon dioxide (CO2) and sulfur dioxide (SO2) mixtures in nitrogen. The created measurement setup of continuous data [...] Read more.
A gravimetric gas detection device based on surface functionalized Capacitive Micromachined Ultrasound Transducers (CMUTs) was designed, fabricated and tested for detection of carbon dioxide (CO2) and sulfur dioxide (SO2) mixtures in nitrogen. The created measurement setup of continuous data collection, integrated with an in-situ Fourier Transform Infrared (FT-IR) spectroscopy, allows for better understanding of the mechanisms and molecular interactions with the sensing layer (methylated poly(ethylene)imine) and its need of surface functionalization for multiple gas detection. During experimentation with CO2 gases, weak molecular interactions were observed in spectroscopy data. Linear sensor response to frequency shift was observed with CO2 concentrations ranging from 0.16 vol % to 1 vol %. Moreover, the Raman and FT-IR spectroscopy data showed much stronger SO2 and the polymer interactions, molecules were bound by stronger forces and irreversibly changed the polymer film properties. However, the sensor change in resonance frequency in the tested region of 1 vol % to 5 vol % SO2 showed a linear response. This effect changed not only the device resonance frequency but also affected the magnitude of electroacoustic impedance which was used for differentiating the gas mixture of CO2, SO2, in dry N2. Full article
(This article belongs to the Special Issue Infrared Spectroscopy and Sensors)
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Open AccessArticle
Curve Similarity Model for Real-Time Gait Phase Detection Based on Ground Contact Forces
Sensors 2019, 19(14), 3235; https://doi.org/10.3390/s19143235 - 23 Jul 2019
Cited by 1 | Viewed by 1102
Abstract
This paper proposed a new novel method to adaptively detect gait patterns in real time through the ground contact forces (GCFs) measured by load cell. The curve similarity model (CSM) is used to identify the division of off-ground and on-ground statuses, and differentiate [...] Read more.
This paper proposed a new novel method to adaptively detect gait patterns in real time through the ground contact forces (GCFs) measured by load cell. The curve similarity model (CSM) is used to identify the division of off-ground and on-ground statuses, and differentiate gait patterns based on the detection rules. Traditionally, published threshold-based methods detect gait patterns by means of setting a fixed threshold to divide the GCFs into on-ground and off-ground statuses. However, the threshold-based methods in the literature are neither an adaptive nor a real-time approach. In this paper, the curve is composed of a series of continuous or discrete ordered GCF data points, and the CSM is built offline to obtain a training template. Then, the testing curve is compared with the training template to figure out the degree of similarity. If the computed degree of similarity is less than a given threshold, they are considered to be similar, which would lead to the division of off-ground and on-ground statuses. Finally, gait patterns could be differentiated according to the status division based on the detection rules. In order to test the detection error rate of the proposed method, a method in the literature is introduced as the reference method to obtain comparative results. The experimental results indicated that the proposed method could be used for real-time gait pattern detection, detect the gait patterns adaptively, and obtain a low error rate compared with the reference method. Full article
(This article belongs to the Special Issue Wearable Sensors for Gait and Motion Analysis 2018)
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Open AccessArticle
A Comparable Study of CNN-Based Single Image Super-Resolution for Space-Based Imaging Sensors
Sensors 2019, 19(14), 3234; https://doi.org/10.3390/s19143234 - 23 Jul 2019
Cited by 3 | Viewed by 994
Abstract
In the case of space-based space surveillance (SBSS), images of the target space objects captured by space-based imaging sensors usually suffer from low spatial resolution due to the extremely long distance between the target and the imaging sensor. Image super-resolution is an effective [...] Read more.
In the case of space-based space surveillance (SBSS), images of the target space objects captured by space-based imaging sensors usually suffer from low spatial resolution due to the extremely long distance between the target and the imaging sensor. Image super-resolution is an effective data processing operation to get informative high resolution images. In this paper, we comparably study four recent popular models for single image super-resolution based on convolutional neural networks (CNNs) with the purpose of space applications. We specially fine-tune the super-resolution models designed for natural images using simulated images of space objects, and test the performance of different CNN-based models in different conditions that are mainly considered for SBSS. Experimental results show the advantages and drawbacks of these models, which could be helpful for the choice of proper CNN-based super-resolution method to deal with image data of space objects. Full article
(This article belongs to the Special Issue Intelligent Sensors Applications in Aerospace)
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Open AccessArticle
A Device-Free Indoor Localization Method Using CSI with Wi-Fi Signals
Sensors 2019, 19(14), 3233; https://doi.org/10.3390/s19143233 - 23 Jul 2019
Cited by 2 | Viewed by 1248
Abstract
Amid the ever-accelerated development of wireless communication technology, we have become increasingly demanding for location-based service; thus, passive indoor positioning has gained widespread attention. Channel State Information (CSI), as it can provide more detailed and fine-grained information, has been followed by researchers. Existing [...] Read more.
Amid the ever-accelerated development of wireless communication technology, we have become increasingly demanding for location-based service; thus, passive indoor positioning has gained widespread attention. Channel State Information (CSI), as it can provide more detailed and fine-grained information, has been followed by researchers. Existing indoor positioning methods, however, are vulnerable to the environment and thus fail to fully reflect all the position features, due to limited accuracy of the fingerprint. As a solution, a CSI-based passive indoor positioning method was proposed, Wavelet Domain Denoising (WDD) was adopted to deal with the collected CSI amplitude, and the CSI phase information was unwound and transformed linearly in the offline phase. The post-processed amplitude and phase were taken as fingerprint data to build a fingerprint database, correlating with reference point position information. Results of experimental data analyzed under two different environments show that the present method boasts lower positioning error and higher stability than similar methods and can offer decimeter-level positioning accuracy. Full article
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Open AccessArticle
Influence of Volumetric Damage Parameters on Patch Antenna Sensor-Based Damage Detection of Metallic Structure
Sensors 2019, 19(14), 3232; https://doi.org/10.3390/s19143232 - 23 Jul 2019
Viewed by 993
Abstract
Antenna sensors have been employed for crack monitoring of metallic materials. Existing studies have mainly focused on the mathematical relationship between the surface crack length of metallic material and the resonant frequency. The influence of the crack depth on the sensor output and [...] Read more.
Antenna sensors have been employed for crack monitoring of metallic materials. Existing studies have mainly focused on the mathematical relationship between the surface crack length of metallic material and the resonant frequency. The influence of the crack depth on the sensor output and the difference of whether the crack is depth-penetrated remains unexplored. Therefore, in this work, a numerical simulation method was used to investigate the current density distribution characteristics of the ground plane (metallic material) with different crack geometric parameters. The data reveals that, compared with the crack length, the crack depth has a greater influence on the resonant frequency. The relationship between the frequency and the crack geometric parameters was discussed by characterizing the current density and sensor output under different crack lengths and depths. Therefore, the feasibility of monitoring another common damage of metallic materials, i.e., corrosion pit, was explored. Furthermore, the influences of crack and corrosion pit geometric parameters on the output results were validated by experiments. Full article
(This article belongs to the Special Issue Sensors for Structural Health Monitoring and Condition Monitoring)
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Open AccessArticle
Optimal Offloading Decision Strategies and Their Influence Analysis of Mobile Edge Computing
Sensors 2019, 19(14), 3231; https://doi.org/10.3390/s19143231 - 23 Jul 2019
Cited by 1 | Viewed by 888
Abstract
Mobile edge computing (MEC) has become more popular both in academia and industry. Currently, with the help of edge servers and cloud servers, it is one of the substantial technologies to overcome the latency between cloud server and wireless device, computation capability and [...] Read more.
Mobile edge computing (MEC) has become more popular both in academia and industry. Currently, with the help of edge servers and cloud servers, it is one of the substantial technologies to overcome the latency between cloud server and wireless device, computation capability and storage shortage of wireless devices. In mobile edge computing, wireless devices take responsibility with input data. At the same time, edge servers and cloud servers take charge of computation and storage. However, until now, how to balance the power consumption of edge devices and time delay has not been well addressed in mobile edge computing. In this paper, we focus on strategies of the task offloading decision and the influence analysis of offloading decisions on different environments. Firstly, we propose a system model considering both energy consumption and time delay and formulate it into an optimization problem. Then, we employ two algorithms—Enumerating and Branch-and-Bound—to get the optimal or near-optimal decision for minimizing the system cost including the time delay and energy consumption. Furthermore, we compare the performance between two algorithms and draw the conclusion that the comprehensive performance of Branch-and-Bound algorithm is better than that of the other. Finally, we analyse the influence factors of optimal offloading decisions and the minimum cost in detail by changing key parameters. Full article
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Open AccessArticle
Enhanced 3-D GM-MAC Protocol for Guaranteeing Stability and Energy Efficiency of IoT Mobile Sensor Networks
Sensors 2019, 19(14), 3230; https://doi.org/10.3390/s19143230 - 23 Jul 2019
Cited by 1 | Viewed by 856
Abstract
In wireless sensor networks, energy efficiency is important because sensor nodes have limited energy. 3-dimensional group management medium access control (3-D GM-MAC) is an attractive MAC protocol for application to the Internet of Things (IoT) environment with various sensors. 3-D GM-MAC outperforms the [...] Read more.
In wireless sensor networks, energy efficiency is important because sensor nodes have limited energy. 3-dimensional group management medium access control (3-D GM-MAC) is an attractive MAC protocol for application to the Internet of Things (IoT) environment with various sensors. 3-D GM-MAC outperforms the existing MAC schemes in terms of energy efficiency, but has some stability issues. In this paper, methods that improve the stability and transmission performance of 3-D GM-MAC are proposed. A buffer management scheme for sensor nodes is newly proposed. Fixed sensor nodes that have a higher priority than the mobile sensor nodes in determining the group numbers that were added, and an advanced group number management scheme was introduced. The proposed methods were simulated and analyzed. The newly derived buffer threshold had a similar energy efficiency to the original 3-D GM-MAC, but improved performance in the aspects of data loss rate and data collection rate. Data delay was not included in the comparison factors as 3-D GM-MAC targets non-real-time applications. When using fixed sensor nodes, the number of group number resets is reduced by about 43.4% and energy efficiency increased by about 10%. Advanced group number management improved energy efficiency by about 23.4%. In addition, the advanced group number management with periodical group number resets of the entire sensor nodes showed about a 48.9% improvement in energy efficiency. Full article
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Open AccessArticle
Structured Light Three-Dimensional Measurement Based on Machine Learning
Sensors 2019, 19(14), 3229; https://doi.org/10.3390/s19143229 - 23 Jul 2019
Cited by 1 | Viewed by 956
Abstract
The three-dimensional measurement of structured light is commonly used and has widespread applications in many industries. In this study, machine learning is used for structured light 3D measurement to recover the phase distribution of the measured object by employing two machine learning models. [...] Read more.
The three-dimensional measurement of structured light is commonly used and has widespread applications in many industries. In this study, machine learning is used for structured light 3D measurement to recover the phase distribution of the measured object by employing two machine learning models. Without phase shift, the measurement operational complexity and computation time decline renders real-time measurement possible. Finally, a grating-based structured light measurement system is constructed, and machine learning is used to recover the phase. The calculated phase of distribution is wrapped in only one dimension and not in two dimensions, as in other methods. The measurement error is observed to be under 1%. Full article
(This article belongs to the Section Physical Sensors)
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Open AccessArticle
RTK with the Assistance of an IMU-Based Pedestrian Navigation Algorithm for Smartphones
Sensors 2019, 19(14), 3228; https://doi.org/10.3390/s19143228 - 22 Jul 2019
Cited by 4 | Viewed by 1245
Abstract
Real-time kinematic (RTK) technique is widely used in modern society because of its high accuracy and real-time positioning. The appearance of Android P and the application of BCM47755 chipset make it possible to use single-frequency RTK and dual-frequency RTK on smartphones. The Xiaomi [...] Read more.
Real-time kinematic (RTK) technique is widely used in modern society because of its high accuracy and real-time positioning. The appearance of Android P and the application of BCM47755 chipset make it possible to use single-frequency RTK and dual-frequency RTK on smartphones. The Xiaomi Mi 8 is the first dual-frequency Global Navigation Satellite System (GNSS) smartphone equipped with BCM47755 chipset. However, the performance of RTK in urban areas is much poorer compared with its performance under the open sky because the satellite signals can be blocked by the buildings and trees. RTK can't provide the positioning results in some specific areas such as the urban canyons and the crossings under an overpass. This paper combines RTK with an IMU-based pedestrian navigation algorithm. We utilize attitude and heading reference system (AHRS) algorithm and zero velocity update (ZUPT) algorithm based on micro electro mechanical systems (MEMS) inertial measurement unit (IMU) in smartphones to assist RTK for the sake of improving positioning performance in urban areas. Some tests are carried out to verify the performance of RTK on the Xiaomi Mi 8 and we respectively assess the performances of RTK with and without the assistance of an IMU-based pedestrian navigation algorithm in urban areas. Results on actual tests show RTK with the assistance of an IMU-based pedestrian navigation algorithm is more robust and adaptable to complex environments than that without it. Full article
(This article belongs to the Section Remote Sensors)
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Open AccessArticle
Hough Transform-Based Large Dynamic Reflection Coefficient Micro-Motion Target Detection in SAR
Sensors 2019, 19(14), 3227; https://doi.org/10.3390/s19143227 - 22 Jul 2019
Viewed by 904
Abstract
Special phase modulation of SAR echoes resulted from target rotation or vibration, is a phenomenon called the micro-Doppler (m-D) effect. Such an effect offers favorable information for micro-motion (MM) target detection, thereby improving the performance of the synthetic aperture radar (SAR) system. However, [...] Read more.
Special phase modulation of SAR echoes resulted from target rotation or vibration, is a phenomenon called the micro-Doppler (m-D) effect. Such an effect offers favorable information for micro-motion (MM) target detection, thereby improving the performance of the synthetic aperture radar (SAR) system. However, when there are MM targets with large differences in reflection coefficient, the weak reflection components will be difficult to be detected. To find a solution to this problem, we propose a novel algorithm. First, we extract and detect the strongest reflection component. By removing the strongest reflection component from the original azimuth echo one by one, we realize the detection of reflection components sequentially, from the strongest to the weakest. Our algorithm applies to detecting MM targets with different reflection coefficients and has high precision of parameter estimation. The results of simulation and field experiments verify the advantages of the algorithm. Full article
(This article belongs to the Special Issue Sensors In Target Detection)
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Open AccessArticle
Use of Computing Devices as Sensors to Measure Their Impact on Primary and Secondary Students’ Performance
Sensors 2019, 19(14), 3226; https://doi.org/10.3390/s19143226 - 22 Jul 2019
Cited by 1 | Viewed by 1011
Abstract
The constant innovation in new technologies and the increase in the use of computing devices in different areas of the society have contributed to a digital transformation in almost every sector. This digital transformation has also reached the world of education, making it [...] Read more.
The constant innovation in new technologies and the increase in the use of computing devices in different areas of the society have contributed to a digital transformation in almost every sector. This digital transformation has also reached the world of education, making it possible for members of the educational community to adopt Learning Management Systems (LMS), where the digital contents replacing the traditional textbooks are exploited and managed. This article aims to study the relationship between the type of computing device from which students access the LMS and how affects their performance. To achieve this, the LMS accesses of students in a school comprising from elementary to bachelor’s degree stages have been monitored by means of different computing devices acting as sensors to gather data such as the type of device and operating system used by the students.The main conclusion is that students who access the LMS improve significantly their performance and that the type of device and the operating system has an influence in the number of passed subjects. Moreover, a predictive model has been generated to predict the number of passed subjects according to these factors, showing promising results. Full article
(This article belongs to the Special Issue Advanced Sensors Technology in Education)
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Open AccessArticle
Meat and Fish Freshness Assessment by a Portable and Simplified Electronic Nose System (Mastersense)
Sensors 2019, 19(14), 3225; https://doi.org/10.3390/s19143225 - 22 Jul 2019
Cited by 7 | Viewed by 1116
Abstract
The evaluation of meat and fish quality is crucial to ensure that products are safe and meet the consumers’ expectation. The present work aims at developing a new low-cost, portable, and simplified electronic nose system, named Mastersense, to assess meat and fish freshness. [...] Read more.
The evaluation of meat and fish quality is crucial to ensure that products are safe and meet the consumers’ expectation. The present work aims at developing a new low-cost, portable, and simplified electronic nose system, named Mastersense, to assess meat and fish freshness. Four metal oxide semiconductor sensors were selected by principal component analysis and were inserted in an “ad hoc” designed measuring chamber. The Mastersense system was used to test beef and poultry slices, and plaice and salmon fillets during their shelf life at 4 °C, from the day of packaging and beyond the expiration date. The same samples were tested for Total Viable Count, and the microbial results were used to define freshness classes to develop classification models by the K-Nearest Neighbours’ algorithm and Partial Least Square–Discriminant Analysis. All the obtained models gave global sensitivity and specificity with prediction higher than 83.3% and 84.0%, respectively. Moreover, a McNemar’s test was performed to compare the prediction ability of the two classification algorithms, which resulted in comparable values (p > 0.05). Thus, the Mastersense prototype implemented with the K-Nearest Neighbours’ model is considered the most convenient strategy to assess meat and fish freshness. Full article
(This article belongs to the Section Chemical Sensors)
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Open AccessArticle
SemanticDepth: Fusing Semantic Segmentation and Monocular Depth Estimation for Enabling Autonomous Driving in Roads without Lane Lines
Sensors 2019, 19(14), 3224; https://doi.org/10.3390/s19143224 - 22 Jul 2019
Cited by 4 | Viewed by 1371
Abstract
Typically, lane departure warning systems rely on lane lines being present on the road.
However, in many scenarios, e.g., secondary roads or some streets in cities, lane lines are either
not present or not sufficiently well signaled. In this work, we present a [...] Read more.
Typically, lane departure warning systems rely on lane lines being present on the road.
However, in many scenarios, e.g., secondary roads or some streets in cities, lane lines are either
not present or not sufficiently well signaled. In this work, we present a vision-based method to
locate a vehicle within the road when no lane lines are present using only RGB images as input.
To this end, we propose to fuse together the outputs of a semantic segmentation and a monocular
depth estimation architecture to reconstruct locally a semantic 3D point cloud of the viewed scene.
We only retain points belonging to the road and, additionally, to any kind of fences or walls that
might be present right at the sides of the road. We then compute the width of the road at a certain
point on the planned trajectory and, additionally, what we denote as the fence-to-fence distance.
Our system is suited to any kind of motoring scenario and is especially useful when lane lines are
not present on the road or do not signal the path correctly. The additional fence-to-fence distance
computation is complementary to the road’s width estimation. We quantitatively test our method
on a set of images featuring streets of the city of Munich that contain a road-fence structure, so as
to compare our two proposed variants, namely the road’s width and the fence-to-fence distance
computation. In addition, we also validate our system qualitatively on the Stuttgart sequence of the
publicly available Cityscapes dataset, where no fences or walls are present at the sides of the road,
thus demonstrating that our system can be deployed in a standard city-like environment. For the
benefit of the community, we make our software open source. Full article
(This article belongs to the Special Issue Sensor Data Fusion for Autonomous and Connected Driving)
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Open AccessArticle
Orthogonal Demodulation Pound–Drever–Hall Technique for Ultra-Low Detection Limit Pressure Sensing
Sensors 2019, 19(14), 3223; https://doi.org/10.3390/s19143223 - 22 Jul 2019
Viewed by 909
Abstract
We report on a novel optical microcavity sensing scheme by using the orthogonal demodulation Pound–Drever–Hall (PDH) technique. We found that larger sensitivity in a broad range of cavity quality factor (Q) could be obtained. Taking microbubble resonator (MBR) pressure sensing as an example, [...] Read more.
We report on a novel optical microcavity sensing scheme by using the orthogonal demodulation Pound–Drever–Hall (PDH) technique. We found that larger sensitivity in a broad range of cavity quality factor (Q) could be obtained. Taking microbubble resonator (MBR) pressure sensing as an example, a lower detection limit than the conventional wavelength shift detection method was achieved. When the MBR cavity Q is about 105–106, the technique can decrease the detection limit by one or two orders of magnitude. The pressure-frequency sensitivity is 11.6 GHz/bar at wavelength of 850 nm, and its detection limit can approach 0.0515 mbar. This technique can also be applied to other kinds of microcavity sensors to improve sensing performance. Full article
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Open AccessArticle
Wireless, Portable Fiber Bragg Grating Interrogation System Employing Optical Edge Filter
Sensors 2019, 19(14), 3222; https://doi.org/10.3390/s19143222 - 22 Jul 2019
Cited by 4 | Viewed by 1029
Abstract
A small-size, high-precision fiber Bragg grating interrogator was developed for continuous plethysmograph monitoring. The interrogator employs optical edge filters, which were integrated with a broad-band light source and photodetector to demodulate the Bragg wavelength shift. An amplifier circuit was designed to effectively amplify [...] Read more.
A small-size, high-precision fiber Bragg grating interrogator was developed for continuous plethysmograph monitoring. The interrogator employs optical edge filters, which were integrated with a broad-band light source and photodetector to demodulate the Bragg wavelength shift. An amplifier circuit was designed to effectively amplify the plethysmograph signal, obtained as a small vibration of optical power on the large offset. The standard deviation of the measured Bragg wavelength was about 0.1 pm. The developed edge filter module and amplifier circuit were encased with a single-board computer and communicated with a laptop computer via Wi-Fi. As a result, the plethysmograph was clearly obtained remotely, indicating the possibility of continuous vital sign measurement. Full article
(This article belongs to the Special Issue Wearable Sensors and Devices for Healthcare Applications)
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Open AccessArticle
Experimental Validation of Gaussian Process-Based Air-to-Ground Communication Quality Prediction in Urban Environments
Sensors 2019, 19(14), 3221; https://doi.org/10.3390/s19143221 - 22 Jul 2019
Cited by 1 | Viewed by 899
Abstract
This paper presents a detailed experimental assessment of Gaussian Process (GP) regression for air-to-ground communication channel prediction for relay missions in urban environment. Considering restrictions from outdoor urban flight experiments, a way to simulate complex urban environments at an indoor room scale is [...] Read more.
This paper presents a detailed experimental assessment of Gaussian Process (GP) regression for air-to-ground communication channel prediction for relay missions in urban environment. Considering restrictions from outdoor urban flight experiments, a way to simulate complex urban environments at an indoor room scale is introduced. Since water significantly absorbs wireless communication signal, water containers are utilized to replace buildings in a real-world city. To evaluate the performance of the GP-based channel prediction approach, several indoor experiments in an artificial urban environment were conducted. The performance of the GP-based and empirical model-based prediction methods for a relay mission was evaluated by measuring and comparing the communication signal strength at the optimal relay position obtained from each method. The GP-based prediction approach shows an advantage over the model-based one as it provides a reasonable performance without a need for a priori information of the environment (e.g., 3D map of the city and communication model parameters) in dynamic urban environments. Full article
(This article belongs to the Section Sensor Networks)
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Open AccessArticle
Monocular Robust Depth Estimation Vision System for Robotic Tasks Interventions in Metallic Targets
Sensors 2019, 19(14), 3220; https://doi.org/10.3390/s19143220 - 22 Jul 2019
Cited by 1 | Viewed by 968
Abstract
Robotic interventions in hazardous scenarios need to pay special attention to safety, as in most cases it is necessary to have an expert operator in the loop. Moreover, the use of a multi-modal Human-Robot Interface allows the user to interact with the robot [...] Read more.
Robotic interventions in hazardous scenarios need to pay special attention to safety, as in most cases it is necessary to have an expert operator in the loop. Moreover, the use of a multi-modal Human-Robot Interface allows the user to interact with the robot using manual control in critical steps, as well as semi-autonomous behaviours in more secure scenarios, by using, for example, object tracking and recognition techniques. This paper describes a novel vision system to track and estimate the depth of metallic targets for robotic interventions. The system has been designed for on-hand monocular cameras, focusing on solving lack of visibility and partial occlusions. This solution has been validated during real interventions at the Centre for Nuclear Research (CERN) accelerator facilities, achieving 95% success in autonomous mode and 100% in a supervised manner. The system increases the safety and efficiency of the robotic operations, reducing the cognitive fatigue of the operator during non-critical mission phases. The integration of such an assistance system is especially important when facing complex (or repetitive) tasks, in order to reduce the work load and accumulated stress of the operator, enhancing the performance and safety of the mission. Full article
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Open AccessArticle
Two Degree-of-Freedom Fiber-Coupled Heterodyne Grating Interferometer with Milli-Radian Operating Range of Rotation
Sensors 2019, 19(14), 3219; https://doi.org/10.3390/s19143219 - 22 Jul 2019
Cited by 1 | Viewed by 761
Abstract
In the displacement measurement of the wafer stage in lithography machines, signal quality is affected by the relative angular position between the encoder head and the grating. In this study, a two-degree-of-freedom fiber-coupled heterodyne grating interferometer with large operating range of rotation is [...] Read more.
In the displacement measurement of the wafer stage in lithography machines, signal quality is affected by the relative angular position between the encoder head and the grating. In this study, a two-degree-of-freedom fiber-coupled heterodyne grating interferometer with large operating range of rotation is presented. Fibers without fiber couplers are utilized to receive the interference beams for high-contrast signals under the circumstances of large angular displacement and ZEMAX ray tracing software simulation and experimental validation have been carried out. Meanwhile, a reference beam generated inside the encoder head is adopted to suppress the thermal drift of the interferometer. Experimental results prove that the proposed grating interferometer could realize sub-nanometer displacement measurement stability in both in-plane and out-of-plane directions, which is 0.246 nm and 0.465 nm of 3σ value respectively within 30 s. Full article
(This article belongs to the Section Optical Sensors)
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Open AccessArticle
Electrochemical Sensing of α-Fetoprotein Based on Molecularly Imprinted Polymerized Ionic Liquid Film on a Gold Nanoparticle Modified Electrode Surface
Sensors 2019, 19(14), 3218; https://doi.org/10.3390/s19143218 - 22 Jul 2019
Cited by 1 | Viewed by 954
Abstract
A molecularly imprinted sensor was fabricated for alpha-fetoprotein (AFP) using an ionic liquid as a functional monomer. Ionic liquid possesses many excellent characteristics which can improve the sensing performances of the imprinted electrochemical sensor. To demonstrate this purpose, 1-[3-(N-cystamine)propyl]-3-vinylimidazolium tetrafluoroborate ionic liquid [(Cys)VIMBF [...] Read more.
A molecularly imprinted sensor was fabricated for alpha-fetoprotein (AFP) using an ionic liquid as a functional monomer. Ionic liquid possesses many excellent characteristics which can improve the sensing performances of the imprinted electrochemical sensor. To demonstrate this purpose, 1-[3-(N-cystamine)propyl]-3-vinylimidazolium tetrafluoroborate ionic liquid [(Cys)VIMBF4] was synthesized and used as a functional monomer to fabricate an AFP imprinted polymerized ionic liquid film on a gold nanoparticle modified glassy carbon electrode (GCE) surface at room temperature. After removing the AFP template, a molecularly imprinted electrochemical sensor was successfully prepared. The molecularly imprinted sensor exhibits excellent selectivity towards AFP, and can be used for sensitive determination of AFP. Under the optimized conditions, the imprinted sensor shows a good linear response to AFP in the concentration range of 0.03 ng mL−1~5 ng mL−1. The detection limit is estimated to be 2 pg mL−1. Full article
(This article belongs to the Section Chemical Sensors)
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Moving Object Detection Based on Optical Flow Estimation and a Gaussian Mixture Model for Advanced Driver Assistance Systems
Sensors 2019, 19(14), 3217; https://doi.org/10.3390/s19143217 - 22 Jul 2019
Cited by 6 | Viewed by 1215
Abstract
Most approaches for moving object detection (MOD) based on computer vision are limited to stationary camera environments. In advanced driver assistance systems (ADAS), however, ego-motion is added to image frames owing to the use of a moving camera. This results in mixed motion [...] Read more.
Most approaches for moving object detection (MOD) based on computer vision are limited to stationary camera environments. In advanced driver assistance systems (ADAS), however, ego-motion is added to image frames owing to the use of a moving camera. This results in mixed motion in the image frames and makes it difficult to classify target objects and background. In this paper, we propose an efficient MOD algorithm that can cope with moving camera environments. In addition, we present a hardware design and implementation results for the real-time processing of the proposed algorithm. The proposed moving object detector was designed using hardware description language (HDL) and its real-time performance was evaluated using an FPGA based test system. Experimental results demonstrate that our design achieves better detection performance than existing MOD systems. The proposed moving object detector was implemented with 13.2K logic slices, 104 DSP48s, and 163 BRAM and can support real-time processing of 30 fps at an operating frequency of 200 MHz. Full article
(This article belongs to the Special Issue Perception Sensors for Road Applications)
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Open AccessArticle
Detecting Anomalies of Satellite Power Subsystem via Stage-Training Denoising Autoencoders
Sensors 2019, 19(14), 3216; https://doi.org/10.3390/s19143216 - 22 Jul 2019
Viewed by 811
Abstract
Satellite telemetry data contains satellite status information, and ground-monitoring personnel need to promptly detect satellite anomalies from these data. This paper takes the satellite power subsystem as an example and presents a reliable anomaly detection method. Due to the lack of abnormal data, [...] Read more.
Satellite telemetry data contains satellite status information, and ground-monitoring personnel need to promptly detect satellite anomalies from these data. This paper takes the satellite power subsystem as an example and presents a reliable anomaly detection method. Due to the lack of abnormal data, the autoencoder is a powerful method for unsupervised anomaly detection. This study proposes a novel stage-training denoising autoencoder (ST-DAE) that trains the features, in stages. This novel method has better reconstruction capabilities in comparison to common autoencoders, sparse autoencoders, and denoising autoencoders. Meanwhile, a cluster-based anomaly threshold determination method is proposed. In this study, specific methods were designed to evaluate the autoencoder performance in three perspectives. Experiments were carried out on real satellite telemetry data, and the results showed that the proposed ST-DAE generally outperformed the autoencoders, in comparison. Full article
(This article belongs to the Section Remote Sensors)
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