Journal Description
Sensors
Sensors
is an international, peer-reviewed, open access journal on the science and technology of sensors. Sensors is published semimonthly online by MDPI. The Polish Society of Applied Electromagnetics (PTZE), Japan Society of Photogrammetry and Remote Sensing (JSPRS), Spanish Society of Biomedical Engineering (SEIB), International Society for the Measurement of Physical Behaviour (ISMPB) and Chinese Society of Micro-Nano Technology (CSMNT) are affiliated with Sensors and their members receive a discount on the article processing charges.
- Open Access — free for readers, with article processing charges (APC) paid by authors or their institutions.
- High Visibility: indexed within Scopus, SCIE (Web of Science), PubMed, MEDLINE, PMC, Ei Compendex, Inspec, Astrophysics Data System, and other databases.
- Journal Rank: JCR - Q2 (Chemistry, Analytical) / CiteScore - Q1 (Instrumentation)
- Rapid Publication: manuscripts are peer-reviewed and a first decision is provided to authors approximately 16.8 days after submission; acceptance to publication is undertaken in 2.6 days (median values for papers published in this journal in the first half of 2024).
- Recognition of Reviewers: reviewers who provide timely, thorough peer-review reports receive vouchers entitling them to a discount on the APC of their next publication in any MDPI journal, in appreciation of the work done.
- Testimonials: See what our editors and authors say about Sensors.
- Companion journals for Sensors include: Chips, JCP and Targets.
Impact Factor:
3.4 (2023);
5-Year Impact Factor:
3.7 (2023)
Latest Articles
A Rotating Machinery Fault Diagnosis Method Based on Dynamic Graph Convolution Network and Hard Threshold Denoising
Sensors 2024, 24(15), 4887; https://doi.org/10.3390/s24154887 (registering DOI) - 27 Jul 2024
Abstract
With the development of precision sensing instruments and data storage devices, the fusion of multi-sensor data in gearbox fault diagnosis has attracted much attention. However, existing methods have difficulty in capturing the local temporal dependencies of multi-sensor monitoring information, and the inescapable noise
[...] Read more.
With the development of precision sensing instruments and data storage devices, the fusion of multi-sensor data in gearbox fault diagnosis has attracted much attention. However, existing methods have difficulty in capturing the local temporal dependencies of multi-sensor monitoring information, and the inescapable noise severely decreases the accuracy of multi-sensor information fusion diagnosis. To address these issues, this paper proposes a fault diagnosis method based on dynamic graph convolutional neural networks and hard threshold denoising. Firstly, considering that the relationships between monitoring data from different sensors change over time, a dynamic graph structure is adopted to model the temporal dependencies of multi-sensor data, and, further, a graph convolutional neural network is constructed to achieve the interaction and feature extraction of temporal information from multi-sensor data. Secondly, to avoid the influence of noise in practical engineering, a hard threshold denoising strategy is designed, and a learnable hard threshold denoising layer is embedded into the graph neural network. Experimental fault datasets from two typical gearbox fault test benches under environmental noise are used to verify the effectiveness of the proposed method in gearbox fault diagnosis. The experimental results show that the proposed DDGCN method achieves an average diagnostic accuracy of up to 99.7% under different levels of environmental noise, demonstrating good noise resistance.
Full article
(This article belongs to the Topic Recent Advances in Structural Health Monitoring, 2nd Volume)
Open AccessArticle
Damage Characteristics Analysis of Laser Ablation Triple-Junction Solar Cells Based on Electroluminescence Characteristics
by
Wei Guo, Jifei Ye, Hao Chang and Chenghao Yu
Sensors 2024, 24(15), 4886; https://doi.org/10.3390/s24154886 (registering DOI) - 27 Jul 2024
Abstract
To study the physical property effects of the laser on GaInP/GaAs/Ge solar cells and their sub-cell layers, a pulsed laser with a wavelength of 532 nm was used to irradiate the solar cells under various energy conditions. The working performance of the cell
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To study the physical property effects of the laser on GaInP/GaAs/Ge solar cells and their sub-cell layers, a pulsed laser with a wavelength of 532 nm was used to irradiate the solar cells under various energy conditions. The working performance of the cell was measured with a source meter. The electroluminescence (EL) characteristics were assessed using an ordinary and an infrared camera. Based on the detailed balance theory, in the voltage characteristics of an ideal pristine cell, the GaInP layer made the most significant voltage contribution, followed by the GaAs layer, with the Ge layer contributing the least. When a bias voltage was applied to the pristine cell, the top GaInP cell emitted red light at 670 nm, the middle GaAs cell emitted near-infrared light at 926 nm, and the bottom Ge cell emitted infrared light at 1852 nm. In the experiment, the 532 nm laser wavelength within the response spectrum bands of the GaInP layer and the laser passed through the glass cover slip and directly interacted with the GaInP layer. The experimental results indicated that the GaInP layer first exhibited different degrees of damage under laser irradiation, and the cell voltage was substantially attenuated. The GaInP/GaAs/Ge solar cell showed a decrease in electrical and light emission characteristics. As the laser energy increased, the cell’s damage intensified, gradually leading to a loss of photoelectric conversion capability, the near-complete disappearance of red light emission, and a gradual degradation of near-infrared emission properties. The EL imaging revealed varying damage states across the triple-junction gallium arsenide solar cell’s sub-cells.
Full article
(This article belongs to the Section Physical Sensors)
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Open AccessArticle
Laser-Induced Interference to Infrared Detector Using Continuous Wave and Short-Pulse Lasers
by
Yingjie Ma, Weijing Zhou, Hao Chang and Zhilong Jian
Sensors 2024, 24(15), 4885; https://doi.org/10.3390/s24154885 (registering DOI) - 27 Jul 2024
Abstract
The response of a DPbS3200 infrared detector irradiated by a nanosecond pulsed laser and CW laser has been investigated to study laser-induced interference. A laser interference experiment system was constructed to measure the time-varying response signal. A nanosecond pulsed laser and a CW
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The response of a DPbS3200 infrared detector irradiated by a nanosecond pulsed laser and CW laser has been investigated to study laser-induced interference. A laser interference experiment system was constructed to measure the time-varying response signal. A nanosecond pulsed laser and a CW laser of 10 Hz were used, with a 1064 nm wavelength and a millimeter-scale irradiation spot diameter. Firstly, the characteristics of transient interference signals induced by pulsed lasers were analyzed. Then, the characteristics of response signal interference by both CW laser and pulsed laser irradiation were further investigated. The results showed that the pulsed laser only produced transient interference. However, the CW laser led to a significant amplitude reduction of the response signal, which could continuously interfere in the operating time. For transient interferences, the amplitude of the interference signal increased linearly with the laser fluence. The relation between the pulse repetition rate of the incident laser and the operating frequency of the detector determined the numbers of transient interference signals in one response period; for the interference induced by both the CW laser and pulsed laser, CW laser interference played a leading role when CW laser power density increased to 4.1 W/cm2 or more. As the CW laser fluence reached 6.1 W/cm2, the PbS infrared detector was no longer able to detect any signal, which caused temporary blindness. In the end, a probit model was used to determine the interference threshold.
Full article
(This article belongs to the Special Issue Optoelectronic Sensors)
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Open AccessArticle
Improved A* Algorithm for Mobile Robots under Rough Terrain Based on Ground Trafficability Model and Ground Ruggedness Model
by
Zhiguang Liu, Song Guo, Fei Yu, Jianhong Hao and Peng Zhang
Sensors 2024, 24(15), 4884; https://doi.org/10.3390/s24154884 (registering DOI) - 27 Jul 2024
Abstract
Considering that the existing path planning algorithms for mobile robots under rugged terrain do not consider the ground flatness and the lack of optimality, which leads to the instability of the center of mass of the mobile robot, this paper proposes an improved
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Considering that the existing path planning algorithms for mobile robots under rugged terrain do not consider the ground flatness and the lack of optimality, which leads to the instability of the center of mass of the mobile robot, this paper proposes an improved A* algorithm for mobile robots under rugged terrain based on the ground accessibility model and the ground ruggedness model. Firstly, the ground accessibility and ruggedness models are established based on the elevation map, expressing the ground flatness. Secondly, the elevation cost function that can obtain the optimal path is designed based on the two types of models combined with the characteristics of the A* algorithm, and the continuous cost function is established by connecting with the original distance cost function, which avoids the center-of-mass instability caused by the non-optimal path. Finally, the effectiveness of the improved algorithm is verified by simulation and experiment. The results show that compared with the existing commonly used path planning algorithms under rugged terrain, the enhanced algorithm improves the smoothness of paths and the optimization degree of paths in the path planning process under rough terrain.
Full article
(This article belongs to the Topic Advances in Mobile Robotics Navigation, 2nd Volume)
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Open AccessArticle
Calibrating the Discrete Boundary Conditions of a Dynamic Simulation: A Combinatorial Approximate Bayesian Computation Sequential Monte Carlo (ABC-SMC) Approach
by
Jah Shamas, Tim Rogers, Anton Krynkin, Jevgenija Prisutova, Paul Gardner, Kirill V. Horoshenkov, Samuel R. Shelley and Paul Dickenson
Sensors 2024, 24(15), 4883; https://doi.org/10.3390/s24154883 (registering DOI) - 27 Jul 2024
Abstract
This paper presents a novel adaptation of the conventional approximate Bayesian computation sequential Monte Carlo (ABC-SMC) sampling algorithm for parameter estimation in the presence of uncertainties, coined combinatorial ABC-SMC. Inference of this type is used in situations where there does not exist a
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This paper presents a novel adaptation of the conventional approximate Bayesian computation sequential Monte Carlo (ABC-SMC) sampling algorithm for parameter estimation in the presence of uncertainties, coined combinatorial ABC-SMC. Inference of this type is used in situations where there does not exist a closed form of the associated likelihood function, which is replaced by a simulating model capable of producing artificial data. In the literature, conventional ABC-SMC is utilised to perform inference on continuous parameters. The novel scheme presented here has been developed to perform inference on parameters that are high-dimensional binary, rather than continuous. By altering the form of the proposal distribution from which to sample candidates in subsequent iterations (referred to as waves), high-dimensional binary variables may be targeted and inferred by the scheme. The efficacy of the proposed scheme is demonstrated through application to vibration data obtained in a structural dynamics experiment on a fibre-optic sensor simulated as a finite plate with uncertain boundary conditions at its edges. Results indicate that the method provides sound inference on the plate boundary conditions, which is validated through subsequent application of the method to multiple vibration datasets. Comparisons between appropriate forms of the metric function used in the scheme are also developed to highlight the effect of this element in the schemes convergence.
Full article
(This article belongs to the Topic Uncertainty Quantification in Design, Manufacturing and Maintenance of Complex Systems)
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Open AccessArticle
Unobtrusive Skin Temperature Estimation on a Smart Bed
by
Gary Garcia-Molina, Trevor Winger, Nikhil Makaram, Megha Rajam Rao, Pavlo Chernega, Yehor Shcherbakov, Leah McGhee, Vidhya Chellamuthu, Erwin Veneros, Raj Mills, Mark Aloia and Kathryn J. Reid
Sensors 2024, 24(15), 4882; https://doi.org/10.3390/s24154882 (registering DOI) - 27 Jul 2024
Abstract
The transition from wakefulness to sleep occurs when the core body temperature decreases. The latter is facilitated by an increase in the cutaneous blood flow, which dissipates internal heat into the micro-environment surrounding the sleeper’s body. The rise in cutaneous blood flow near
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The transition from wakefulness to sleep occurs when the core body temperature decreases. The latter is facilitated by an increase in the cutaneous blood flow, which dissipates internal heat into the micro-environment surrounding the sleeper’s body. The rise in cutaneous blood flow near sleep onset causes the distal (hands and feet) and proximal (abdomen) temperatures to increase by about 1 °C and 0.5 °C, respectively. Characterizing the dynamics of skin temperature changes throughout sleep phases and understanding its relationship with sleep quality requires a means to unobtrusively and longitudinally estimate the skin temperature. Leveraging the data from a temperature sensor strip (TSS) with five individual temperature sensors embedded near the surface of a smart bed’s mattress, we have developed an algorithm to estimate the distal skin temperature with a minute-long temporal resolution. The data from 18 participants who recorded TSS and ground-truth temperature data from sleep during 14 nights at home and 2 nights in a lab were used to develop an algorithm that uses a two-stage regression model (gradient boosted tree followed by a random forest) to estimate the distal skin temperature. A five-fold cross-validation procedure was applied to train and validate the model such that the data from a participant could only be either in the training or validation set but not in both. The algorithm verification was performed with the in-lab data. The algorithm presented in this research can estimate the distal skin temperature at a minute-level resolution, with accuracy characterized by the mean limits of agreement [−0.79 to +0.79 °C] and mean coefficient of determination . This method may enable the unobtrusive, longitudinal and ecologically valid collection of distal skin temperature values during sleep. Therelatively small sample size motivates the need for further validation efforts.
Full article
(This article belongs to the Section Biomedical Sensors)
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Open AccessArticle
Enabling Seamless Connectivity: Networking Innovations in Wireless Sensor Networks for Industrial Application
by
Shathya Duobiene, Rimantas Simniškis and Gediminas Račiukaitis
Sensors 2024, 24(15), 4881; https://doi.org/10.3390/s24154881 (registering DOI) - 27 Jul 2024
Abstract
The wide-ranging applications of the Internet of Things (IoT) show that it has the potential to revolutionise industry, improve daily life, and overcome global challenges. This study aims to evaluate the performance scalability of mature industrial wireless sensor networks (IWSNs). A new classification
[...] Read more.
The wide-ranging applications of the Internet of Things (IoT) show that it has the potential to revolutionise industry, improve daily life, and overcome global challenges. This study aims to evaluate the performance scalability of mature industrial wireless sensor networks (IWSNs). A new classification approach for IoT in the industrial sector is proposed based on multiple factors and we introduce the integration of 6LoWPAN (IPv6 over low-power wireless personal area networks), message queuing telemetry transport for sensor networks (MQTT-SN), and ContikiMAC protocols for sensor nodes in an industrial IoT system to improve energy-efficient connectivity. The Contiki COOJA WSN simulator was applied to model and simulate the performance of the protocols in two static and moving scenarios and evaluate the proposed novelty detection system (NDS) for network intrusions in order to identify certain events in real time for realistic dataset analysis. The simulation results show that our method is an essential measure in determining the number of transmissions required to achieve a certain reliability target in an IWSNs. Despite the growing demand for low-power operation, deterministic communication, and end-to-end reliability, our methodology of an innovative sensor design using selective surface activation induced by laser (SSAIL) technology was developed and deployed in the FTMC premises to demonstrate its long-term functionality and reliability. The proposed framework was experimentally validated and tested through simulations to demonstrate the applicability and suitability of the proposed approach. The energy efficiency in the optimised WSN was increased by 50%, battery life was extended by 350%, duplicated packets were reduced by 80%, data collisions were reduced by 80%, and it was shown that the proposed methodology and tools could be used effectively in the development of telemetry node networks in new industrial projects in order to detect events and breaches in IoT networks accurately. The energy consumption of the developed sensor nodes was measured. Overall, this study performed a comprehensive assessment of the challenges of industrial processes, such as the reliability and stability of telemetry channels, the energy efficiency of autonomous nodes, and the minimisation of duplicate information transmission in IWSNs.
Full article
(This article belongs to the Special Issue IoT Sensors Development and Application for Environment & Safety)
Open AccessArticle
Design and Analysis of Receiver Coils with Multiple In-Series Windings for Inductive Eddy Current Angle Position Sensors Based on Coupling of Coils on Printed Circuit Boards
by
Stefan Kuntz, Daniel Gerber, Gerald Gerlach and Sina Fella
Sensors 2024, 24(15), 4880; https://doi.org/10.3390/s24154880 (registering DOI) - 27 Jul 2024
Abstract
We present a method for improving the amplitude and angular error of inductive position sensors, by advancing the design of receiver coil systems with multiple windings on two layers of a printed circuit board. Multiple phase-shifted windings are connected in series, resulting in
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We present a method for improving the amplitude and angular error of inductive position sensors, by advancing the design of receiver coil systems with multiple windings on two layers of a printed circuit board. Multiple phase-shifted windings are connected in series, resulting in an increased amplitude of the induced voltage while decreasing the angular error of the sensor. The amplitude increase for a specific number of windings can be predicted in closed form. Windings are placed electrically in series by means of a differential connection structure, without adversely affecting the signal quality while requiring a minimal amount of space in the layout. Further, we introduce a receiver coil centerline function which specifically enables dense, space-constrained designs. It allows for maximization of the number of possible coil windings while minimizing the impact on angular error. This compromise can be fine-tuned freely with a shape parameter. The application to a typical rotary encoder design for motor control applications with five periods is presented as an example and analyzed in detail by 3D finite-element simulation of 18 different variants, varying both the number of windings and the type of centerline functions. The best peak-to-peak angular error achieved in the examples is smaller than 0.1° electrically (0.02° mechanically, periodicity 5) under nominal tolerance conditions, in addition to an amplitude increase of more than 170% compared to a conventional design which exhibits more than twice the angular error. Amplitude gains of more than 270% are achieved at the expense of increased angular error.
Full article
(This article belongs to the Section Electronic Sensors)
Open AccessArticle
GTR: GAN-Based Trusted Routing Algorithm for Underwater Wireless Sensor Networks
by
Bin Wang and Kerong Ben
Sensors 2024, 24(15), 4879; https://doi.org/10.3390/s24154879 (registering DOI) - 27 Jul 2024
Abstract
The transmission environment of underwater wireless sensor networks is open, and important transmission data can be easily intercepted, interfered with, and tampered with by malicious nodes. Malicious nodes can be mixed in the network and are difficult to distinguish, especially in time-varying underwater
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The transmission environment of underwater wireless sensor networks is open, and important transmission data can be easily intercepted, interfered with, and tampered with by malicious nodes. Malicious nodes can be mixed in the network and are difficult to distinguish, especially in time-varying underwater environments. To address this issue, this article proposes a GAN-based trusted routing algorithm (GTR). GTR defines the trust feature attributes and trust evaluation matrix of underwater network nodes, constructs the trust evaluation model based on a generative adversarial network (GAN), and achieves malicious node detection by establishing a trust feature profile of a trusted node, which improves the detection performance for malicious nodes in underwater networks under unlabeled and imbalanced training data conditions. GTR combines the trust evaluation algorithm with the adaptive routing algorithm based on Q-Learning to provide an optimal trusted data forwarding route for underwater network applications, improving the security, reliability, and efficiency of data forwarding in underwater networks. GTR relies on the trust feature profile of trusted nodes to distinguish malicious nodes and can adaptively select the forwarding route based on the status of trusted candidate next-hop nodes, which enables GTR to better cope with the changing underwater transmission environment and more accurately detect malicious nodes, especially unknown malicious node intrusions, compared to baseline algorithms. Simulation experiments showed that, compared to baseline algorithms, GTR can provide a better malicious node detection performance and data forwarding performance. Under the condition of 15% malicious nodes and 10% unknown malicious nodes mixed in, the detection rate of malicious nodes by the underwater network configured with GTR increased by 5.4%, the error detection rate decreased by 36.4%, the packet delivery rate increased by 11.0%, the energy tax decreased by 11.4%, and the network throughput increased by 20.4%.
Full article
(This article belongs to the Special Issue Underwater Wireless Communications)
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Open AccessArticle
Investigation of the Zero-Frequency Component of Nonlinear Lamb Waves in a Symmetrical Undulated Plate
by
Xiaoqiang Sun and Guoshuang Shui
Sensors 2024, 24(15), 4878; https://doi.org/10.3390/s24154878 (registering DOI) - 27 Jul 2024
Abstract
When an ultrasonic pulse propagates in a thin plate, nonlinear Lamb waves with higher harmonics and a zero-frequency component (ZFC) will be generated because of the nonlinearity of materials. The ZFC, also known as the static displacement or static component, has its unique
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When an ultrasonic pulse propagates in a thin plate, nonlinear Lamb waves with higher harmonics and a zero-frequency component (ZFC) will be generated because of the nonlinearity of materials. The ZFC, also known as the static displacement or static component, has its unique application on the evaluation of early-stage damages in the elastic symmetrical undulated plate. In this study, analysis of the excitation mechanism of the ZFC and the second harmonic component (SHC) was theoretically and numerically investigated, and the material early-stage damage of a symmetrical undulated was characterized by studying the propagation of nonlinear Lamb waves. Both the ZFC and SHC can be effectively employed in monitoring the material damages of the undulated plate in its early stage. However, several factors must be considered for the propagation of the SHC in an undulated plate because of the geometric curvature and interference between the second harmonics during propagation, preventing efficient application of this technique. If the fundamental wave can propagate in the plate regardless of the plate boundary conditions, an accumulative effect always exists for the ZFC in a thin plate, indicating that the ZFC is independent of the structural geometry. This study reveals that the ZFC-based inspection technique is more efficient and powerful in characterizing the damages of a symmetrical undulated plate in the early stage of service compared to the second harmonic method.
Full article
(This article belongs to the Special Issue Ultrasound Imaging and Sensing for Nondestructive Testing)
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Open AccessArticle
High-Sensitivity Differential Sensor for Characterizing Complex Permittivity of Liquids Based on LC Resonators
by
Zhongjun Li, Shuang Tian, Jiaxin Tang, Weichao Yang, Tao Hong and Huacheng Zhu
Sensors 2024, 24(15), 4877; https://doi.org/10.3390/s24154877 (registering DOI) - 27 Jul 2024
Abstract
This paper proposes a high-sensitivity microstrip differential sensor for measuring the complex permittivity of liquids. The prototype of the differential sensor was formed by cascading two LC resonators on a microstrip transmission line based on stepped impedance. A strong electric field was found
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This paper proposes a high-sensitivity microstrip differential sensor for measuring the complex permittivity of liquids. The prototype of the differential sensor was formed by cascading two LC resonators on a microstrip transmission line based on stepped impedance. A strong electric field was found to be distributed in the circular patch of the LC resonator; therefore, a cylindrical micropore was set in the center of the circular LC resonator to measure the dielectric sample, which maximized the disturbance of the dielectric sample on the sensor. By optimizing the size of the circular LC resonator, a high-sensitivity sensor circuit was designed and manufactured. The complex permittivity of the test sample was calculated by measuring the transmission coefficient of different molar concentrations of ethanol–water solutions. The experimental results show that the designed differential sensor can accurately measure the complex permittivity of liquid materials with an average sensitivity of 0.76%.
Full article
(This article belongs to the Section Electronic Sensors)
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Open AccessArticle
Policy Compression for Intelligent Continuous Control on Low-Power Edge Devices
by
Thomas Avé, Tom De Schepper and Kevin Mets
Sensors 2024, 24(15), 4876; https://doi.org/10.3390/s24154876 (registering DOI) - 27 Jul 2024
Abstract
Interest in deploying deep reinforcement learning (DRL) models on low-power edge devices, such as Autonomous Mobile Robots (AMRs) and Internet of Things (IoT) devices, has seen a significant rise due to the potential of performing real-time inference by eliminating the latency and reliability
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Interest in deploying deep reinforcement learning (DRL) models on low-power edge devices, such as Autonomous Mobile Robots (AMRs) and Internet of Things (IoT) devices, has seen a significant rise due to the potential of performing real-time inference by eliminating the latency and reliability issues incurred from wireless communication and the privacy benefits of processing data locally. Deploying such energy-intensive models on power-constrained devices is not always feasible, however, which has led to the development of model compression techniques that can reduce the size and computational complexity of DRL policies. Policy distillation, the most popular of these methods, can be used to first lower the number of network parameters by transferring the behavior of a large teacher network to a smaller student model before deploying these students at the edge. This works well with deterministic policies that operate using discrete actions. However, many real-world tasks that are power constrained, such as in the field of robotics, are formulated using continuous action spaces, which are not supported. In this work, we improve the policy distillation method to support the compression of DRL models designed to solve these continuous control tasks, with an emphasis on maintaining the stochastic nature of continuous DRL algorithms. Experiments show that our methods can be used effectively to compress such policies up to 750% while maintaining or even exceeding their teacher’s performance by up to 41% in solving two popular continuous control tasks.
Full article
(This article belongs to the Special Issue Deep Reinforcement Learning in Communication Systems and Networks)
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Open AccessArticle
Capturing How the Accelerometer Measured Physical Activity Profile Differs in People with Diabetic Foot Ulceration
by
Liam Neal, Matthew McCarthy, Paddy Dempsey, Francesco Zaccardi, Rachel Berrington, Emer M. Brady, Charlotte L. Edwardson, Frances Game, Andrew Hall, Joseph Henson, Kamlesh Khunti, Bethany Turner, David Webb, Melanie J. Davies, Alex V. Rowlands and Tom Yates
Sensors 2024, 24(15), 4875; https://doi.org/10.3390/s24154875 (registering DOI) - 27 Jul 2024
Abstract
Diabetic Foot Ulcers (DFUs) are a major complication of diabetes, with treatment requiring offloading. This study aimed to capture how the accelerometer-assessed physical activity profile differs in those with DFUs compared to those with diabetes but without ulceration (non-DFU). Participants were requested to
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Diabetic Foot Ulcers (DFUs) are a major complication of diabetes, with treatment requiring offloading. This study aimed to capture how the accelerometer-assessed physical activity profile differs in those with DFUs compared to those with diabetes but without ulceration (non-DFU). Participants were requested to wear an accelerometer on their non-dominant wrist for up to 8days. Physical activity outcomes included average acceleration (volume), intensity gradient (intensity distribution), the intensity of the most active sustained (continuous) 5–120 min of activity (MXCONT), and accumulated 5–120 min of activity (MXACC). A total of 595 participants (non-DFU = 561, DFU = 34) were included in the analysis. Average acceleration was lower in DFU participants compared to non-DFU participants (21.9 mg [95%CI:21.2, 22.7] vs. 16.9 mg [15.3, 18.8], p < 0.001). DFU participants also had a lower intensity gradient, indicating proportionally less time spent in higher-intensity activities. The relative difference between DFU and non-DFU participants was greater for sustained activity (MXCONT) than for accumulated (MXACC) activity. In conclusion, physical activity, particularly the intensity of sustained activity, is lower in those with DFUs compared to non-DFUs. This highlights the need for safe, offloaded modes of activity that contribute to an active lifestyle for people with DFUs.
Full article
(This article belongs to the Special Issue Diabetic Foot and Fall Prevention Based on Sensors Technology)
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Open AccessArticle
An Empirical Study on the Effect of Training Data Perturbations on Neural Network Robustness
by
Jie Wang, Zili Wu, Minyan Lu and Jun Ai
Sensors 2024, 24(15), 4874; https://doi.org/10.3390/s24154874 - 26 Jul 2024
Abstract
The vulnerability of modern neural networks to random noise and deliberate attacks has raised concerns about their robustness, particularly as they are increasingly utilized in safety- and security-critical applications. Although recent research efforts were made to enhance robustness through retraining with adversarial examples
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The vulnerability of modern neural networks to random noise and deliberate attacks has raised concerns about their robustness, particularly as they are increasingly utilized in safety- and security-critical applications. Although recent research efforts were made to enhance robustness through retraining with adversarial examples or employing data augmentation techniques, a comprehensive investigation into the effects of training data perturbations on model robustness remains lacking. This paper presents the first extensive empirical study investigating the influence of data perturbations during model retraining. The experimental analysis focuses on both random and adversarial robustness, following established practices in the field of robustness analysis. Various types of perturbations in different aspects of the dataset are explored, including input, label, and sampling distribution. Single-factor and multi-factor experiments are conducted to assess individual perturbations and their combinations. The findings provide insights into constructing high-quality training datasets for optimizing robustness and recommend the appropriate degree of training set perturbations that balance robustness and correctness, and contribute to understanding model robustness in deep learning and offer practical guidance for enhancing model performance through perturbed retraining, promoting the development of more reliable and trustworthy deep learning systems for safety-critical applications.
Full article
(This article belongs to the Section Intelligent Sensors)
Open AccessArticle
In Situ Pipe Prover Volume Measurement Method
by
Jiacheng Hu, Weikang Zhou, Aijun Chen, Jiale Cai, Jing Yu, Zhengzhiyong Cui and Dongsheng Li
Sensors 2024, 24(15), 4873; https://doi.org/10.3390/s24154873 - 26 Jul 2024
Abstract
To improve the accuracy of in situ measurement of the standard volumes of pipe provers and to shorten the traceability chain, a new method of in situ pipe prover volume measurement was developed alongside a supporting measurement device. This method is based on
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To improve the accuracy of in situ measurement of the standard volumes of pipe provers and to shorten the traceability chain, a new method of in situ pipe prover volume measurement was developed alongside a supporting measurement device. This method is based on the geometric dimension approach, which measures the inner diameter and length of a pipe prover to calculate its volume. For inner diameter measurement, a three-probe inner-diameter algorithm model was established. This model was calibrated using a standard ring gauge of Φ313 mm, with the parameters calculated through fitting. Another standard ring gauge of Φ320 mm was used to verify the inner diameters determined by the algorithmic model. A laser interferometer was employed for the segmented measurement of the pipe prover length. The comprehensive measurement system was then used for in situ measurement of the standard pipe prover. The newly developed system achieved an expanded uncertainty of 0.012% (k = 2) in volume measurement, with the deviation between the measured and nominal pipe prover volumes being merely 0.007%. These results demonstrate that the proposed in situ measurement method offers ultra-high-precision measurement capabilities.
Full article
(This article belongs to the Section Physical Sensors)
Open AccessArticle
Retrospect on the Ground Deformation Process and Potential Triggering Mechanism of the Traditional Steel Production Base in Laiwu with ALOS PALSAR and Sentinel-1 SAR Sensors
by
Chao Ding, Guangcai Feng, Lu Zhang and Wenxin Wang
Sensors 2024, 24(15), 4872; https://doi.org/10.3390/s24154872 - 26 Jul 2024
Abstract
The realization of a harmonious relationship between the natural environment and economic development has always been the unremitting pursuit of traditional mineral resource-based cities. With rich reserves of iron and coal ore resources, Laiwu has become an important steel production base in Shandong
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The realization of a harmonious relationship between the natural environment and economic development has always been the unremitting pursuit of traditional mineral resource-based cities. With rich reserves of iron and coal ore resources, Laiwu has become an important steel production base in Shandong Province in China, after several decades of industrial development. However, some serious environmental problems have occurred with the quick development of local steel industries, with ground subsidence and consequent secondary disasters as the most representative ones. To better evaluate possible ground collapse risk, comprehensive approaches incorporating the common deformation monitoring with small-baseline subset (SBAS)-synthetic aperture radar interferometry (InSAR) technique, environmental factors analysis, and risk evaluation are designed here with ALOS PALSAR and Sentinel-1 SAR observations. A retrospect on the ground deformation process indicates that ground deformation has largely decreased by around 51.57% in area but increased on average by around −5.4 mm/year in magnitude over the observation period of Sentinel-1 (30 July 2015 to 22 August 2022), compared to that of ALOS PALSAR (17 January 2007 to 28 October 2010). To better reveal the potential triggering mechanism, environmental factors are also utilized and conjointly analyzed with the ground deformation time series. These analysis results indicate that the ground deformation signals are highly correlated with human industrial activities, such underground mining, and the operation of manual infrastructures (landfill, tailing pond, and so on). In addition, the evaluation demonstrates that the area with potential collapse risk (levels of medium, high, and extremely high) occupies around 8.19 km2, approximately 0.86% of the whole study region. This study sheds a bright light on the safety guarantee for the industrial operation and the ecologically friendly urban development of traditional steel production industrial cities in China.
Full article
(This article belongs to the Special Issue Editorial Board Members’ Collection Series: Application of InSAR Technology in Geodesy, Earthquake, Landslides and Other Disaster Warning)
Open AccessArticle
Ultra-Low-Power Sensor Nodes for Real-Time Synchronous and High-Accuracy Timing Wireless Data Acquisition
by
Tadeusz Sondej and Mariusz Bednarczyk
Sensors 2024, 24(15), 4871; https://doi.org/10.3390/s24154871 - 26 Jul 2024
Abstract
This paper presents an energy-efficient and high-accuracy sampling synchronization approach for real-time synchronous data acquisition in wireless sensor networks (saWSNs). A proprietary protocol based on time-division multiple access (TDMA) and deep energy-efficient coding in sensor firmware is proposed. A real saWSN model based
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This paper presents an energy-efficient and high-accuracy sampling synchronization approach for real-time synchronous data acquisition in wireless sensor networks (saWSNs). A proprietary protocol based on time-division multiple access (TDMA) and deep energy-efficient coding in sensor firmware is proposed. A real saWSN model based on 2.4 GHz nRF52832 system-on-chip (SoC) sensors was designed and experimentally tested. The obtained results confirmed significant improvements in data synchronization accuracy (even by several times) and power consumption (even by a hundred times) compared to other recently reported studies. The results demonstrated a sampling synchronization accuracy of 0.8 μs and ultra-low power consumption of 15 μW per 1 kb/s throughput for data. The protocol was well designed, stable, and importantly, lightweight. The complexity and computational performance of the proposed scheme were small. The CPU load for the proposed solution was <2% for a sampling event handler below 200 Hz. Furthermore, the transmission reliability was high with a packet error rate (PER) not exceeding 0.18% for TXPWR ≥ −4 dBm and 0.03% for TXPWR ≥ 3 dBm. The efficiency of the proposed protocol was compared with other solutions presented in the manuscript. While the number of new proposals is large, the technical advantage of our solution is significant.
Full article
(This article belongs to the Section Sensor Networks)
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Open AccessArticle
A New Versatile Jig for the Calibration and Validation of Force Metrics with Instrumented Paddles in Sprint Kayaking
by
Hans Rosdahl, David Aitken, Mark Osborne, Jonas Willén and Johnny Nilsson
Sensors 2024, 24(15), 4870; https://doi.org/10.3390/s24154870 - 26 Jul 2024
Abstract
The interest in using new technologies to obtain recordings of on-water kinetic variables for assessing the performance of elite sprint kayakers has increased over the last decades but systematic approaches are warranted to ensure the validity and reliability of these measures. This study
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The interest in using new technologies to obtain recordings of on-water kinetic variables for assessing the performance of elite sprint kayakers has increased over the last decades but systematic approaches are warranted to ensure the validity and reliability of these measures. This study has an innovative approach, and the aim was to develop a new versatile jig including reference force sensors for both the calibration and validation of mutual static and dynamic stroke forces as measured with instrumented paddles at the high force levels used in elite sprint kayaking. Methods: A jig was constructed using a modified gym weight stack and a frame consisting of aluminum profiles permitting a fastening of custom-made kayak paddle shaft and blade support devices with certified force transducers combined with a data acquisition system to record blade and hand forces during static (constant load) and dynamic conditions (by paddle stroke simulation). A linear motion path incorporating a ball-bearing equipped carriage with sensors for the measurement of vertical distance and horizontal displacement was attached to the frame for recordings of various position measures on the paddle. The jig design with all components is extensively described to permit replication. The procedures for assessing the accuracy of the jig force instrumentation are reported, and with one brand of instrumented paddle used as an example, methods are described for force calibration and validation during static and dynamic conditions. Results: The results illustrate that the measured force with the jig instrumentation was similar to the applied force, calculated from the applied accurate mass (within a −1.4 to 1.8% difference) and similar to the force as calculated from the applied mass with the weight stack (within a −0.57 to 1.16% difference). The jig was suitable for the calibration and validation of forces in a range relevant for elite sprint kayaking under both static and dynamic conditions. During static conditions with a force direction equal to the calibration conditions and a force range from 98 to 590 N, all values for the instrumented paddle were within a −3.4 to 3.0% difference from the jig sensor values and 28 of 36 values were within ±2%. During dynamic conditions with paddle stroke simulations at 60 and 100 strokes/min and a target peak force of 400 N, the common force variables as measured by the instrumented paddle were not significantly different from the same measures by the jig (values at 100 strokes/min: peak force; 406.9 ± 18.4 vs. 401.9 ± 17.2 N, mean force; 212.8 ± 15.4 vs. 212.0 ± 14.4 N, time to peak force; 0.17 ± 0.02 vs. 0.18 ± 0.02 s, force impulse; 90.8 ± 11.2 vs. 90.5 ± 10.8 Ns, impulse duration; 0.43 ± 0.03 vs. 0.43 ± 0.03 s). Conclusion: A novel jig with several new functions is presented that enables the calibration and validation of force measurements with instrumented paddles by providing standardized conditions for calibration and force validation during both static and dynamic conditions in a force range relevant to elite sprint kayaking.
Full article
(This article belongs to the Special Issue Sensor Techniques and Methods for Sports Science)
Open AccessArticle
Enhancing Reconfigurable Intelligent Surface-Enabled Cognitive Radio Networks for Sixth Generation and Beyond: Performance Analysis and Parameter Optimization
by
Huu Q. Tran and Byung Moo Lee
Sensors 2024, 24(15), 4869; https://doi.org/10.3390/s24154869 - 26 Jul 2024
Abstract
In this paper, we propose a novel system integrating reconfigurable intelligent surfaces (RISs) with cognitive radio (CR) technology, presenting a forward-looking solution aligned with the evolving standards of 6G and beyond networks. The proposed RIS-assisted CR networks operate with a base station (BS)
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In this paper, we propose a novel system integrating reconfigurable intelligent surfaces (RISs) with cognitive radio (CR) technology, presenting a forward-looking solution aligned with the evolving standards of 6G and beyond networks. The proposed RIS-assisted CR networks operate with a base station (BS) transmitting signals to two users, the primary user (PU) and secondary user (SU), through direct and reflected signal paths, respectively. Our mathematical analysis focuses on deriving expressions for SU in the RIS-assisted CR system, validated through Monte Carlo simulations. The investigation covers diverse aspects, including the impact of the signal-to-noise ratio (SNR), power allocations, the number of reflected surfaces, and blocklength variations. The results provide nuanced insights into RIS-assisted CR system performance, highlighting its sensitivity to factors like the number of reflectors, fading severity, and correlation coefficient. Careful parameter selection, such as optimizing the configuration of reflectors, is shown to prevent a complete outage, showcasing the system’s robustness. Additionally, the work suggests that the optimization of reflectors configuration can significantly enhance overall system performance, and RIS-assisted CR systems outperform reference schemes. This work contributes a thorough analysis of the proposed system, offering valuable insights for efficient performance evaluation and parameter optimization in RIS-assisted CR networks.
Full article
(This article belongs to the Section Communications)
Open AccessArticle
Revealing the Ground Deformation and Its Mechanism in the Heihe River Basin by Interferometric Synthetic Aperture Radar and Optical Images
by
Qunpeng Cui, Yuedong Wang, Pengkun Wang, Ke Tan and Guangcai Feng
Sensors 2024, 24(15), 4868; https://doi.org/10.3390/s24154868 - 26 Jul 2024
Abstract
The Heihe River Basin (HRB), located on the northeast margin of the Qilian Mountains, is China’s second largest inland river basin. It is a typical oasis-type agricultural area in northwest China’s arid and semiarid areas. It is important to monitor and investigate the
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The Heihe River Basin (HRB), located on the northeast margin of the Qilian Mountains, is China’s second largest inland river basin. It is a typical oasis-type agricultural area in northwest China’s arid and semiarid areas. It is important to monitor and investigate the spatiotemporal distribution characteristics and mechanisms of surface deformation in HRB for the ecology of inland river basins. In recent years, research on HRB has mainly focused on hydrology, meteorology, geology, or biology. Few studies have conducted wide-area monitoring and mechanism analysis of the surface stability of HRB. In this study, an improved interferometric point target analysis InSAR (IPTA-InSAR) technique is used to process 101 Sentinel-1 SAR images from two adjacent track frames covering the HRB from 2019 to 2020. The wide-area deformation of the HRB is obtained first for this period. The results show that most of the surface around the HRB is relatively stable. There are six areas with an extensive deformation range and magnitude in the plain oasis area. The maximum deformation rate is more than 50 mm/year. The maximum seasonal subsidence and uplift along the satellites’ line-of-sight (LOS) direction can be up to −70 mm and 60 mm, respectively. Moreover, we use the Google Earth Engine platform to process the multisource optical images and analyze the deformation areas. The remote sensing indicators of the deformation areas, such as the normalized difference vegetation index (NDVI), soil moisture (SMMI), and precipitation, are obtained during the InSAR monitoring period. We combine these integrated remote sensing results with soil type and precipitation to analyze the surface deformations of the HRB. The spatiotemporal relationships between soil moisture, vegetation cover, and surface deformation of the HRB are revealed. The results will provide data support and reference for the healthy and sustainable development of the inland river basin economic zone.
Full article
(This article belongs to the Special Issue Editorial Board Members’ Collection Series: Application of InSAR Technology in Geodesy, Earthquake, Landslides and Other Disaster Warning)
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