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Volume 22
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Sensors, Volume 22, Issue 24 (December-2 2022) – 454 articles

Cover Story (view full-size image): In this paper, we propose a technique that detects whether there is a diversion on a pipe or not. The proposed model transmits ultrasound signals through a pipe using a custom-designed array of piezoelectric transmitters and receivers. We propose to use the Zadoff–Chu sequence to modulate the input signals, then utilize its correlation properties to estimate the pipe channel response. The processed signal is then fed to a DNN that extracts the features and decides whether there is a diversion or not. The proposed technique demonstrates an average classification accuracy of 90.3% (when one sensor is used) and 99.6% (when two sensors are used) on 3/4 inch pipes. The technique can be readily generalized for pipes of different diameters and materials. View this paper
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16 pages, 1052 KiB  
Article
Flexible IoT Agriculture Systems for Irrigation Control Based on Software Services
by Eva Palomar-Cosín and Marisol García-Valls
Sensors 2022, 22(24), 9999; https://doi.org/10.3390/s22249999 - 19 Dec 2022
Cited by 3 | Viewed by 2150
Abstract
IoT technology applied to agriculture has produced a number of contributions in the recent years. Such solutions are, most of the time, fully tailored to a particular functional target and focus extensively on sensor-hardware development and customization. As a result, software-centered solutions for [...] Read more.
IoT technology applied to agriculture has produced a number of contributions in the recent years. Such solutions are, most of the time, fully tailored to a particular functional target and focus extensively on sensor-hardware development and customization. As a result, software-centered solutions for IoT system development are infrequent. This is not suitable, as the software is the bottleneck in modern computer systems, being the main source of performance loss, errors, and even cyber attacks. This paper takes a software-centric perspective to model and design IoT systems in a flexible manner. We contribute a software framework that supports the design of the IoT systems’ software based on software services in a client–server model with REST interactions; and it is exemplified on the domain of efficient irrigation in agriculture. We decompose the services’ design into the set of constituent functions and operations both at client and server sides. As a result, we provide a simple and novel view on the design of IoT systems in agriculture from a sofware perspective: we contribute simple design structure based on the identification of the front-end software services, their internal software functions and operations, and their interconnections as software services. We have implemented the software framework on an IoT irrigation use case that monitors the conditions of the field and processes the sampled data, detecting alarms when needed. We demonstrate that the temporal overhead of our solution is bounded and suitable for the target domain, reaching a response time of roughly 11 s for bursts of 3000 requests. Full article
(This article belongs to the Topic Advanced Systems Engineering: Theory and Applications)
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23 pages, 20762 KiB  
Article
Damage Assessment in Rural Environments Following Natural Disasters Using Multi-Sensor Remote Sensing Data
by Shiran Havivi, Stanley R. Rotman, Dan G. Blumberg and Shimrit Maman
Sensors 2022, 22(24), 9998; https://doi.org/10.3390/s22249998 - 19 Dec 2022
Cited by 2 | Viewed by 2336
Abstract
The damage caused by natural disasters in rural areas differs in nature extent, landscape, and structure, from the damage caused in urban environments. Previous and current studies have focused mainly on mapping damaged structures in urban areas after catastrophic events such as earthquakes [...] Read more.
The damage caused by natural disasters in rural areas differs in nature extent, landscape, and structure, from the damage caused in urban environments. Previous and current studies have focused mainly on mapping damaged structures in urban areas after catastrophic events such as earthquakes or tsunamis. However, research focusing on the level of damage or its distribution in rural areas is lacking. This study presents a methodology for mapping, characterizing, and assessing the damage in rural environments following natural disasters, both in built-up and vegetation areas, by combining synthetic-aperture radar (SAR) and optical remote sensing data. As a case study, we applied the methodology to characterize the rural areas affected by the Sulawesi earthquake and the subsequent tsunami event in Indonesia that occurred on 28 September 2018. High-resolution COSMO-SkyMed images obtained pre- and post-event, alongside Sentinel-2 images, were used as inputs. This study’s results emphasize that remote sensing data from rural areas must be treated differently from that of urban areas following a disaster. Additionally, the analysis must include the surrounding features, not only the damaged structures. Furthermore, the results highlight the applicability of the methodology for a variety of disaster events, as well as multiple hazards, and can be adapted using a combination of different optical and SAR sensors. Full article
(This article belongs to the Special Issue Remote Sensing, Sensor Networks and GIS for Hazards and Disasters)
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15 pages, 5236 KiB  
Article
Methodology for Designing an Optimal Test Stand for Camera Thermal Drift Measurements and Its Stability Verification
by Kohhei Nimura and Marcin Adamczyk
Sensors 2022, 22(24), 9997; https://doi.org/10.3390/s22249997 - 19 Dec 2022
Cited by 1 | Viewed by 1551
Abstract
The effects of temperature changes on cameras are realized by observing the drifts of characteristic points in the image plane. Compensation for these effects is crucial to maintain the precision of cameras applied in machine vision systems and those expected to work in [...] Read more.
The effects of temperature changes on cameras are realized by observing the drifts of characteristic points in the image plane. Compensation for these effects is crucial to maintain the precision of cameras applied in machine vision systems and those expected to work in environments with varying factors, including temperature changes. Generally, mathematical compensation models are built by measuring the changes in the intrinsic and extrinsic parameters under the temperature effect; however, due to the assumptions of certain factors based on the conditions of the test stand used for the measurements, errors can become apparent. In this paper, test stands for thermal image drift measurements used in other works are assessed, and a methodology to design a test stand, which can measure thermal image drifts while eliminating other external influences on the camera, is proposed. A test stand was built accordingly, and thermal image drift measurements were performed along with a measurement to verify that the test stand did eliminate external influences on the camera. The experiment was performed for various temperatures from 5 °C to 45 5 °C, and as a result, the thermal image drift measured with the designed test stand showed its maximum error of 16% during its most rapid temperature change from 25 °C to 5 °C. Full article
(This article belongs to the Special Issue Sensing Technologies and Applications in Infrared and Visible Imaging)
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13 pages, 2276 KiB  
Article
Performance of the SABAT Neutron-Based Explosives Detector Integrated with an Unmanned Ground Vehicle: A Simulation Study
by Michał Silarski and Marek Nowakowski
Sensors 2022, 22(24), 9996; https://doi.org/10.3390/s22249996 - 19 Dec 2022
Cited by 2 | Viewed by 2071
Abstract
The effective and safe detection of illicit materials, explosives in particular, is currently of growing importance taking into account the geopolitical situation and increasing risk of a terrorist attack. The commonly used methods of detection are based predominantly on metal detectors and georadars, [...] Read more.
The effective and safe detection of illicit materials, explosives in particular, is currently of growing importance taking into account the geopolitical situation and increasing risk of a terrorist attack. The commonly used methods of detection are based predominantly on metal detectors and georadars, which show only the shapes of the possible dangerous objects and do not allow for exact identification and risk assessment. A supplementary or even alternative method may be based on neutron activation analysis, which provides the possibility of a stoichiometric analysis of the suspected object and its non-invasive identification. One such sensor is developed by the SABAT collaboration, with its primary application being underwater threat detection. In this article, we present performance studies of this sensor, integrated with a mobile robot, in terms of the minimal detectable quantity of commonly used explosives in different environmental conditions. The paper describes the functionality of the used platform considering electronics, sensors, onboard computing power, and communication system to carry out manual operation and remote control. Robotics solutions based on modularized structures allow the extension of sensors and effectors that can significantly improve the safety of personnel as well as work efficiency, productivity, and flexibility. Full article
(This article belongs to the Special Issue Monitoring System for Aircraft, Vehicle and Transport Systems)
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15 pages, 6714 KiB  
Article
The Application of PVDF-Based Piezoelectric Patches in Energy Harvesting from Tire Deformation
by Kevin Nguyen, Matthew Bryant, In-Hyouk Song, Byoung Hee You and Seyedmeysam Khaleghian
Sensors 2022, 22(24), 9995; https://doi.org/10.3390/s22249995 - 19 Dec 2022
Cited by 4 | Viewed by 1881
Abstract
The application of Polyvinylidene Fluoride or Polyvinylidene Difluoride (PVDF) in harvesting energy from tire deformation was investigated in this study. An instrumented tire with different sizes of PVDF-based piezoelectric patches and a tri-axial accelerometer attached to its inner liner was used for this [...] Read more.
The application of Polyvinylidene Fluoride or Polyvinylidene Difluoride (PVDF) in harvesting energy from tire deformation was investigated in this study. An instrumented tire with different sizes of PVDF-based piezoelectric patches and a tri-axial accelerometer attached to its inner liner was used for this purpose and was tested under different conditions on asphalt and concrete surfaces. The results demonstrated that on both pavement types, the generated voltage was directly proportional to the size of the harvester patches, the longitudinal velocity, and the normal load. Additionally, the generated voltage was inversely proportional to the tire inflation pressure. Moreover, the range of generated voltages was slightly higher on asphalt compared to the same testing conditions on the concrete surface. Based on the results, it was concluded that in addition to the potential role of the PVDF-based piezoelectric film in harvesting energy from tire deformation, they demonstrate great potential to be used as self-powered sensors to estimate the tire-road contact parameters. Full article
(This article belongs to the Special Issue On-Board and Remote Sensors in Intelligent Vehicles)
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15 pages, 1189 KiB  
Article
Plasmonic Sensors beyond the Phase Matching Condition: A Simplified Approach
by Alessandro Tuniz, Alex Y. Song, Giuseppe Della Valle and C. Martijn de Sterke
Sensors 2022, 22(24), 9994; https://doi.org/10.3390/s22249994 - 19 Dec 2022
Cited by 2 | Viewed by 1855
Abstract
The conventional approach to optimising plasmonic sensors is typically based entirely on ensuring phase matching between the excitation wave and the surface plasmon supported by the metallic structure. However, this leads to suboptimal performance, even in the simplest sensor configuration based on the [...] Read more.
The conventional approach to optimising plasmonic sensors is typically based entirely on ensuring phase matching between the excitation wave and the surface plasmon supported by the metallic structure. However, this leads to suboptimal performance, even in the simplest sensor configuration based on the Otto geometry. We present a simplified coupled mode theory approach for evaluating and optimizing the sensing properties of plasmonic waveguide refractive index sensors. It only requires the calculation of propagation constants, without the need for calculating mode overlap integrals. We apply our method by evaluating the wavelength-, device length- and refractive index-dependent transmission spectra for an example silicon-on-insulator-based sensor of finite length. This reveals all salient spectral features which are consistent with full-field finite element calculations. This work provides a rapid and convenient framework for designing dielectric-plasmonic sensor prototypes—its applicability to the case of fibre plasmonic sensors is also discussed. Full article
(This article belongs to the Special Issue Plasmonic Optical Fiber Sensors: Technology and Applications)
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24 pages, 11528 KiB  
Article
Driver Take-Over Behaviour Study Based on Gaze Focalization and Vehicle Data in CARLA Simulator
by Javier Araluce, Luis M. Bergasa, Manuel Ocaña, Elena López-Guillén, Rodrigo Gutiérrez-Moreno and J. Felipe Arango
Sensors 2022, 22(24), 9993; https://doi.org/10.3390/s22249993 - 19 Dec 2022
Cited by 3 | Viewed by 2945
Abstract
Autonomous vehicles are the near future of the automobile industry. However, until they reach Level 5, humans and cars will share this intermediate future. Therefore, studying the transition between autonomous and manual modes is a fascinating topic. Automated vehicles may still need to [...] Read more.
Autonomous vehicles are the near future of the automobile industry. However, until they reach Level 5, humans and cars will share this intermediate future. Therefore, studying the transition between autonomous and manual modes is a fascinating topic. Automated vehicles may still need to occasionally hand the control to drivers due to technology limitations and legal requirements. This paper presents a study of driver behaviour in the transition between autonomous and manual modes using a CARLA simulator. To our knowledge, this is the first take-over study with transitions conducted on this simulator. For this purpose, we obtain driver gaze focalization and fuse it with the road’s semantic segmentation to track to where and when the user is paying attention, besides the actuators’ reaction-time measurements provided in the literature. To track gaze focalization in a non-intrusive and inexpensive way, we use a method based on a camera developed in previous works. We devised it with the OpenFace 2.0 toolkit and a NARMAX calibration method. It transforms the face parameters extracted by the toolkit into the point where the user is looking on the simulator scene. The study was carried out by different users using our simulator, which is composed of three screens, a steering wheel and pedals. We distributed this proposal in two different computer systems due to the computational cost of the simulator based on the CARLA simulator. The robot operating system (ROS) framework is in charge of the communication of both systems to provide portability and flexibility to the proposal. Results of the transition analysis are provided using state-of-the-art metrics and a novel driver situation-awareness metric for 20 users in two different scenarios. Full article
(This article belongs to the Special Issue Feature Papers in Vehicular Sensing)
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12 pages, 5793 KiB  
Article
Development of a Large-Scale Roadside Facility Detection Model Based on the Mapillary Dataset
by Zhehui Yang, Chenbo Zhao, Hiroya Maeda and Yoshihide Sekimoto
Sensors 2022, 22(24), 9992; https://doi.org/10.3390/s22249992 - 19 Dec 2022
Cited by 4 | Viewed by 2678
Abstract
The detection of road facilities or roadside structures is essential for high-definition (HD) maps and intelligent transportation systems (ITSs). With the rapid development of deep-learning algorithms in recent years, deep-learning-based object detection techniques have provided more accurate and efficient performance, and have become [...] Read more.
The detection of road facilities or roadside structures is essential for high-definition (HD) maps and intelligent transportation systems (ITSs). With the rapid development of deep-learning algorithms in recent years, deep-learning-based object detection techniques have provided more accurate and efficient performance, and have become an essential tool for HD map reconstruction and advanced driver-assistance systems (ADASs). Therefore, the performance evaluation and comparison of the latest deep-learning algorithms in this field is indispensable. However, most existing works in this area limit their focus to the detection of individual targets, such as vehicles or pedestrians and traffic signs, from driving view images. In this study, we present a systematic comparison of three recent algorithms for large-scale multi-class road facility detection, namely Mask R-CNN, YOLOx, and YOLOv7, on the Mapillary dataset. The experimental results are evaluated according to the recall, precision, mean F1-score and computational consumption. YOLOv7 outperforms the other two networks in road facility detection, with a precision and recall of 87.57% and 72.60%, respectively. Furthermore, we test the model performance on our custom dataset obtained from the Japanese road environment. The results demonstrate that models trained on the Mapillary dataset exhibit sufficient generalization ability. The comparison presented in this study aids in understanding the strengths and limitations of the latest networks in multiclass object detection on large-scale street-level datasets. Full article
(This article belongs to the Special Issue AI Applications in Smart Networks and Sensor Devices)
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15 pages, 1894 KiB  
Article
A Mobility Model for a 3D Non-Stationary Geometry Cluster-Based Channel Model for High Speed Trains in MIMO Wireless Channels
by Eva Assiimwe and Yihenew Wondie Marye
Sensors 2022, 22(24), 10019; https://doi.org/10.3390/s222410019 - 19 Dec 2022
Cited by 2 | Viewed by 1560
Abstract
During channel modeling for high-mobility channels, such as high-speed train (HST) channels, the velocity of the mobile radio station is assumed to be constant. However, this might not be realistic due to the dynamic movement of the train along the track. Therefore, in [...] Read more.
During channel modeling for high-mobility channels, such as high-speed train (HST) channels, the velocity of the mobile radio station is assumed to be constant. However, this might not be realistic due to the dynamic movement of the train along the track. Therefore, in this paper, an enhanced Gauss–Markov mobility model with a 3D non-stationary geometry based stochastic model (GBSM) for HST in MIMO Wireless Channels is proposed. The non-isotropic scatterers within a cluster are assumed to be around the sphere in which the mobile relay station (MRS) is located. The multi-path components (MPCs) are modeled with varying velocities, whereas the mobility model is a function of time. The MPCs are represented in a death–birth cluster using the Markov process. Furthermore, the channel statistics, i.e., the space-time correlation function, the root-mean-square Doppler shift, and the quasi-stationary interval, are derived from the non-stationary model. The model shows how the quasi-stationary time increases from 0.21 to 0.451 s with a decreasing acceleration of 0.6 to 0.2 m/s2 of the HST. In addition, the impact of the distribution of the angles on the channel statistics is presented. Finally, the simulated results are compared with the measured results. Therefore, there is a close relationship between the proposed model and the measured results, and the model can be used to characterize the channel’s properties. Full article
(This article belongs to the Special Issue Modeling and Measurements of Propagation Environments for 5G and beyond Networks)
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12 pages, 3308 KiB  
Article
Joint Estimation of Mass and Center of Gravity Position for Distributed Drive Electric Vehicles Using Dual Robust Embedded Cubature Kalman Filter
by Zhiguo Zhang, Guodong Yin and Zhixin Wu
Sensors 2022, 22(24), 10018; https://doi.org/10.3390/s222410018 - 19 Dec 2022
Cited by 7 | Viewed by 2046
Abstract
The accurate estimation of the mass and center of gravity (CG) position is key to vehicle dynamics modeling. The perturbation of key parameters in vehicle dynamics models can result in a reduction of accurate vehicle control and may even cause serious traffic accidents. [...] Read more.
The accurate estimation of the mass and center of gravity (CG) position is key to vehicle dynamics modeling. The perturbation of key parameters in vehicle dynamics models can result in a reduction of accurate vehicle control and may even cause serious traffic accidents. A dual robust embedded cubature Kalman filter (RECKF) algorithm, which takes into account unknown measurement noise, is proposed for the joint estimation of mass and CG position. First, the mass parameters are identified based on directly obtained longitudinal forces in the distributed drive electric vehicle tires using the whole vehicle longitudinal dynamics model and the RECKF. Then, the CG is estimated with the RECKF using the mass estimation results and the vertical vehicle model. Finally, different virtual tests show that, compared with the cubature Kalman algorithm, the RECKF reduces the root mean square error of mass and CG by at least 7.4%, and 2.9%, respectively. Full article
(This article belongs to the Topic Vehicle Dynamics and Control)
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11 pages, 9939 KiB  
Brief Report
Spatial Distribution of Muscular Effects of Acute Whole-Body Electromyostimulation at the Mid-Thigh and Lower Leg—A Pilot Study Applying Magnetic Resonance Imaging
by Marina Götz, Rafael Heiss, Simon von Stengel, Frank Roemer, Joshua Berger, Armin Nagel, Michael Uder and Wolfgang Kemmler
Sensors 2022, 22(24), 10017; https://doi.org/10.3390/s222410017 - 19 Dec 2022
Cited by 3 | Viewed by 1769
Abstract
Whole-body electromyostimulation (WB-EMS) is an innovative training method that stimulates large areas simultaneously. In order to determine the spatial distribution of WB-EMS with respect to volume involvement and stimulation depth, we determined the extent of intramuscular edema using magnetic resonance imaging (MRI) as [...] Read more.
Whole-body electromyostimulation (WB-EMS) is an innovative training method that stimulates large areas simultaneously. In order to determine the spatial distribution of WB-EMS with respect to volume involvement and stimulation depth, we determined the extent of intramuscular edema using magnetic resonance imaging (MRI) as a marker of structural effects. Intense WB-EMS first application (20 min, bipolar, 85 Hz, 350 µs) was conducted with eight physically less trained students without previous WB-EMS experience. Transversal T2-weighted MRI was performed at baseline and 72 h post WB-EMS to identify edema at the mid-thigh and lower leg. The depth of the edema ranged from superficial to maximum depth with superficial and deeper muscle groups of the mid-thigh or lower leg area approximately affected in a similar fashion. However, the grade of edema differed between the muscle groups, which suggests that the intensity of EMS-induced muscular contraction was not identical for all muscles. WB-EMS of the muscles via surface cuff electrodes has an effect on deeper parts of the stimulated anatomy. Reviewing the spatial and volume distribution, we observed a heterogeneous pattern of edema. We attribute this finding predominately to different stimulus thresholds of the muscles and differences in the stress resistance of the muscles. Full article
(This article belongs to the Section Biomedical Sensors)
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16 pages, 33181 KiB  
Article
CamNuvem: A Robbery Dataset for Video Anomaly Detection
by Davi D. de Paula, Denis H. P. Salvadeo and Darlan M. N. de Araujo
Sensors 2022, 22(24), 10016; https://doi.org/10.3390/s222410016 - 19 Dec 2022
Cited by 3 | Viewed by 4157
Abstract
(1) Background: The research area of video surveillance anomaly detection aims to automatically detect the moment when a video surveillance camera captures something that does not fit the normal pattern. This is a difficult task, but it is important to automate, improve, and [...] Read more.
(1) Background: The research area of video surveillance anomaly detection aims to automatically detect the moment when a video surveillance camera captures something that does not fit the normal pattern. This is a difficult task, but it is important to automate, improve, and lower the cost of the detection of crimes and other accidents. The UCF–Crime dataset is currently the most realistic crime dataset, and it contains hundreds of videos distributed in several categories; it includes a robbery category, which contains videos of people stealing material goods using violence, but this category only includes a few videos. (2) Methods: This work focuses only on the robbery category, presenting a new weakly labelled dataset that contains 486 new real–world robbery surveillance videos acquired from public sources. (3) Results: We have modified and applied three state–of–the–art video surveillance anomaly detection methods to create a benchmark for future studies. We showed that in the best scenario, taking into account only the anomaly videos in our dataset, the best method achieved an AUC of 66.35%. When all anomaly and normal videos were taken into account, the best method achieved an AUC of 88.75%. (4) Conclusion: This result shows that there is a huge research opportunity to create new methods and approaches that can improve robbery detection in video surveillance. Full article
(This article belongs to the Special Issue Computer Vision Techniques Applied to Human Behaviour Analysis in the Real-World)
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17 pages, 2584 KiB  
Article
Evaluation of the Influence of Machine Tools on the Accuracy of Indoor Positioning Systems
by Till Neuber, Anna-Maria Schmitt, Bastian Engelmann and Jan Schmitt
Sensors 2022, 22(24), 10015; https://doi.org/10.3390/s222410015 - 19 Dec 2022
Cited by 2 | Viewed by 1616
Abstract
In recent years, the use of indoor localization techniques has increased significantly in a large number of areas, including industry and healthcare, primarily for monitoring and tracking reasons. From the field of radio frequency technologies, an ultra-wideband (UWB) system offers comparatively high accuracy [...] Read more.
In recent years, the use of indoor localization techniques has increased significantly in a large number of areas, including industry and healthcare, primarily for monitoring and tracking reasons. From the field of radio frequency technologies, an ultra-wideband (UWB) system offers comparatively high accuracy and is therefore suitable for use cases with high precision requirements in position determination, for example for localizing an employee when interacting with a machine tool on the shopfloor. Indoor positioning systems with radio signals are influenced by environmental obstacles. Although the influence of building structures like walls and furniture was already analysed in the literature before, the influence of metal machine tools was not yet evaluated concerning the accuracy of the position determination. Accordingly, the research question for this article is defined: To what extent is the positioning accuracy of the UWB system influenced by a metal machine tool?The accuracy was measured in a test setup, which consists of a total of four scenarios in a production environment. For this purpose, the visual contact between the transmitter and the receiver modules, including the influence of further interfering factors of a commercially available indoor positioning system, was improved step by step from scenario 1 to 4. A laser tracker was used as the reference measuring device. The data was analysed based on the type A evaluation of standard uncertainty according to the guide to the expression of uncertainty in measurement (GUM). It was possible to show an improvement in standard deviation from 87.64cm±32.27cm to 6.07cm±2.24cm with confidence level 95% and thus provides conclusions about the setup of an indoor positioning system on the shopfloor. Full article
(This article belongs to the Special Issue State-of-the-Art Sensors Technology in Germany 2022)
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20 pages, 1671 KiB  
Article
Low-Complexity Lossless Coding of Asynchronous Event Sequences for Low-Power Chip Integration
by Ionut Schiopu and Radu Ciprian Bilcu
Sensors 2022, 22(24), 10014; https://doi.org/10.3390/s222410014 - 19 Dec 2022
Cited by 3 | Viewed by 1582
Abstract
The event sensor provides high temporal resolution and generates large amounts of raw event data. Efficient low-complexity coding solutions are required for integration into low-power event-processing chips with limited memory. In this paper, a novel lossless compression method is proposed for encoding the [...] Read more.
The event sensor provides high temporal resolution and generates large amounts of raw event data. Efficient low-complexity coding solutions are required for integration into low-power event-processing chips with limited memory. In this paper, a novel lossless compression method is proposed for encoding the event data represented as asynchronous event sequences. The proposed method employs only low-complexity coding techniques so that it is suitable for hardware implementation into low-power event-processing chips. A first, novel, contribution consists of a low-complexity coding scheme which uses a decision tree to reduce the representation range of the residual error. The decision tree is formed by using a triplet threshold parameter which divides the input data range into several coding ranges arranged at concentric distances from an initial prediction, so that the residual error of the true value information is represented by using a reduced number of bits. Another novel contribution consists of an improved representation, which divides the input sequence into same-timestamp subsequences, wherein each subsequence collects the same timestamp events in ascending order of the largest dimension of the event spatial information. The proposed same-timestamp representation replaces the event timestamp information with the same-timestamp subsequence length and encodes it together with the event spatial and polarity information into a different bitstream. Another novel contribution is the random access to any time window by using additional header information. The experimental evaluation on a highly variable event density dataset demonstrates that the proposed low-complexity lossless coding method provides an average improvement of 5.49%, 11.45%, and 35.57% compared with the state-of-the-art performance-oriented lossless data compression codecs Bzip2, LZMA, and ZLIB, respectively. To our knowledge, the paper proposes the first low-complexity lossless compression method for encoding asynchronous event sequences that are suitable for hardware implementation into low-power chips. Full article
(This article belongs to the Special Issue Image/Video Coding and Processing Techniques for Intelligent Sensor Nodes)
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21 pages, 4936 KiB  
Article
Versatile Confocal Raman Imaging Microscope Built from Off-the-Shelf Opto-Mechanical Components
by Deseada Diaz Barrero, Genrich Zeller, Magnus Schlösser, Beate Bornschein and Helmut H. Telle
Sensors 2022, 22(24), 10013; https://doi.org/10.3390/s222410013 - 19 Dec 2022
Cited by 1 | Viewed by 2217
Abstract
Confocal Raman microscopic (CRM) imaging has evolved to become a key tool for spatially resolved, compositional analysis and imaging, down to the μm-scale, and nowadays one may choose between numerous commercial instruments. That notwithstanding, situations may arise which exclude the use of a [...] Read more.
Confocal Raman microscopic (CRM) imaging has evolved to become a key tool for spatially resolved, compositional analysis and imaging, down to the μm-scale, and nowadays one may choose between numerous commercial instruments. That notwithstanding, situations may arise which exclude the use of a commercial instrument, e.g., if the analysis involves toxic or radioactive samples/environments; one may not wish to render an expensive instrument unusable for other uses, due to contamination. Therefore, custom-designed CRM instrumentation—being adaptable to hazardous conditions and providing operational flexibility—may be beneficial. Here, we describe a CRM setup, which is constructed nearly in its entirety from off-the-shelf optomechanical and optical components. The original aim was to develop a CRM suitable for the investigation of samples exposed to tritium. For increased flexibility, the CRM system incorporates optical fiber coupling to both the Raman excitation laser and the spectrometer. Lateral raster scans and axial profiling of samples are facilitated by the use of a motorized xyz-translation assembly. Besides the description of the construction and alignment of the CRM system, we also provide (i) the experimental evaluation of system performance (such as, e.g., spatial resolution) and (ii) examples of Raman raster maps and axial profiles of selected thin-film samples (such as, e.g., graphene sheets). Full article
(This article belongs to the Section Sensing and Imaging)
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16 pages, 4632 KiB  
Article
Nanocomposite Based on HA/PVTMS/Cl2FeH8O4 as a Gas and Temperature Sensor
by Sohrab Nasiri, Marzieh Rabiei, Ieva Markuniene, Mozhgan Hosseinnezhad, Reza Ebrahimi-Kahrizsangi, Arvydas Palevicius, Andrius Vilkauskas and Giedrius Janusas
Sensors 2022, 22(24), 10012; https://doi.org/10.3390/s222410012 - 19 Dec 2022
Viewed by 2151
Abstract
In this paper, a novel nanocrystalline composite material of hydroxyapatite (HA)/polyvinyltrimethoxysilane (PVTMS)/iron(II)chloride tetrahydrate (Cl2FeH8-O4) with hexagonal structure is proposed for the fabrication of a gas/temperature sensor. Taking into account the sensitivity of HA to high temperatures, to [...] Read more.
In this paper, a novel nanocrystalline composite material of hydroxyapatite (HA)/polyvinyltrimethoxysilane (PVTMS)/iron(II)chloride tetrahydrate (Cl2FeH8-O4) with hexagonal structure is proposed for the fabrication of a gas/temperature sensor. Taking into account the sensitivity of HA to high temperatures, to prevent the collapse and breakdown of bonds and the leakage of volatiles without damaging the composite structure, a freeze-drying machine is designed and fabricated. X-ray diffraction, FTIR, SEM, EDAX, TEM, absorption and photoluminescence analyses of composite are studied. XRD is used to confirm the material structure and the crystallite size of the composite is calculated by the Monshi–Scherrer method, and a value of 81.60 ± 0.06 nm is obtained. The influence of the oxygen environment on the absorption and photoluminescence measurements of the composite and the influence of vaporized ethanol, N2 and CO on the SiO2/composite/Ag sensor device are investigated. The sensor with a 30 nm-thick layer of composite shows the highest response to vaporized ethanol, N2 and ambient CO. Overall, the composite and sensor exhibit a good selectivity to oxygen, vaporized ethanol, N2 and CO environments. Full article
(This article belongs to the Special Issue Recent Advances in Thin Film Gas Sensors)
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23 pages, 11988 KiB  
Article
Equipment Identification and Localization Method Based on Improved YOLOv5s Model for Production Line
by Ming Yu, Qian Wan, Songling Tian, Yanyan Hou, Yimiao Wang and Jian Zhao
Sensors 2022, 22(24), 10011; https://doi.org/10.3390/s222410011 - 19 Dec 2022
Cited by 5 | Viewed by 2414
Abstract
Intelligent video surveillance based on artificial intelligence, image processing, and other advanced technologies is a hot topic of research in the upcoming era of Industry 5.0. Currently, low recognition accuracy and low location precision of devices in intelligent monitoring remain a problem in [...] Read more.
Intelligent video surveillance based on artificial intelligence, image processing, and other advanced technologies is a hot topic of research in the upcoming era of Industry 5.0. Currently, low recognition accuracy and low location precision of devices in intelligent monitoring remain a problem in production lines. This paper proposes a production line device recognition and localization method based on an improved YOLOv5s model. The proposed method can achieve real-time detection and localization of production line equipment such as robotic arms and AGV carts by introducing CA attention module in YOLOv5s network model architecture, GSConv lightweight convolution method and Slim-Neck method in Neck layer, add Decoupled Head structure to the Detect layer. The experimental results show that the improved method achieves 93.6% Precision, 85.6% recall, and 91.8% mAP@0.5, and the Pascal VOC2007 public dataset test shows that the improved method effectively improves the recognition accuracy. The research results can substantially improve the intelligence level of production lines and provide an important reference for manufacturing industries to realize intelligent and digital transformation. Full article
(This article belongs to the Topic Modern Technologies and Manufacturing Systems, 2nd Volume)
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14 pages, 3602 KiB  
Article
Generalized Scale Factor Calibration Method for an Off-Axis Digital Image Correlation-Based Video Deflectometer
by Long Tian, Tong Ding and Bing Pan
Sensors 2022, 22(24), 10010; https://doi.org/10.3390/s222410010 - 19 Dec 2022
Cited by 3 | Viewed by 1181
Abstract
When using off-axis digital image correlation (DIC) for non-contact, remote, and multipoint deflection monitoring of engineering structures, accurate calibration of the scale factor (SF), which converts image displacement to physical displacement for each measurement point, is critical to realize high-quality displacement measurement. In [...] Read more.
When using off-axis digital image correlation (DIC) for non-contact, remote, and multipoint deflection monitoring of engineering structures, accurate calibration of the scale factor (SF), which converts image displacement to physical displacement for each measurement point, is critical to realize high-quality displacement measurement. In this work, based on the distortion-free pinhole imaging model, a generalized SF calibration model is proposed for an off-axis DIC-based video deflectometer. Then, the transversal relationship between the proposed SF calibration method and three commonly used SF calibration methods was discussed. The accuracy of these SF calibration methods was also compared using indoor rigid body translation experiments. It is proved that the proposed method can be degraded to one of the existing calibration methods in most cases, but will provide more accurate results under the following four conditions: (1) the camera’s pitch angle is more than 20°, (2) the focal length is more than 25 mm, (3) the pixel size of the camera sensor is more than 5 um, and (4) the image y-coordinate corresponding to the measurement point after deformation is far from the image center. Full article
(This article belongs to the Collection Vision Sensors and Systems in Structural Health Monitoring)
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13 pages, 4174 KiB  
Article
Multi-Scale Strengthened Directional Difference Algorithm Based on the Human Vision System
by Yuye Zhang, Ying Zheng and Xiuhong Li
Sensors 2022, 22(24), 10009; https://doi.org/10.3390/s222410009 - 19 Dec 2022
Cited by 1 | Viewed by 1253
Abstract
The human visual system (HVS) mechanism has been successfully introduced into the field of infrared small target detection. However, most of the current detection algorithms based on the mechanism of the human visual system ignore the continuous direction information and are easily disturbed [...] Read more.
The human visual system (HVS) mechanism has been successfully introduced into the field of infrared small target detection. However, most of the current detection algorithms based on the mechanism of the human visual system ignore the continuous direction information and are easily disturbed by highlight noise and object edges. In this paper, a multi-scale strengthened directional difference (MSDD) algorithm is proposed. It is mainly divided into two parts: local directional intensity measure (LDIM) and local directional fluctuation measure (LDFM). In LDIM, an improved window is used to suppress most edge clutter, highlights, and holes and enhance true targets. In LDFM, the characteristics of the target area, the background area, and the connection between the target and the background are considered, which further highlights the true target signal and suppresses the corner clutter. Then, the MSDD saliency map is obtained by fusing the LDIM map and the LDFM map. Finally, an adaptive threshold segmentation method is employed to capture true targets. The experiments show that the proposed method achieves better detection performance in complex backgrounds than several classical and widely used methods. Full article
(This article belongs to the Section Intelligent Sensors)
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17 pages, 5321 KiB  
Article
Research on Smart Tourism Oriented Sensor Network Construction and Information Service Mode
by Ruomei Tang, Chenyue Huang, Xinyu Zhao and Yunbing Tang
Sensors 2022, 22(24), 10008; https://doi.org/10.3390/s222410008 - 19 Dec 2022
Cited by 2 | Viewed by 1708
Abstract
Smart tourism is the latest achievement of tourism development at home and abroad. It is also an essential part of the smart city. Promoting the application of computer and sensor technology in smart tourism is conducive to improving the efficiency of public tourism [...] Read more.
Smart tourism is the latest achievement of tourism development at home and abroad. It is also an essential part of the smart city. Promoting the application of computer and sensor technology in smart tourism is conducive to improving the efficiency of public tourism services and guiding the innovation of the tourism public service mode. In this paper, we have proposed a new method of using data collected by sensor networks. We have developed and deployed sensors to collect data, which are transmitted to the modular cloud platform, and combined with cluster technology and an Uncertain Support Vector Classifier (A-USVC) location prediction method to assist in emergency events. Considering the attraction of tourists, the system also incorporated human trajectory analysis and intensity of interaction as consideration factors to validate the spatial dynamics of different interests and enhance the tourists’ experience. The system explored the innovative road of computer technology to boost the development of smart tourism, which helps to promote the high-quality development of tourism. Full article
(This article belongs to the Special Issue Smart Mobile and Sensing Applications)
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16 pages, 5831 KiB  
Article
Design of a High-Efficiency DC-DC Boost Converter for RF Energy Harvesting IoT Sensors
by Juntae Kim and Ickjin Kwon
Sensors 2022, 22(24), 10007; https://doi.org/10.3390/s222410007 - 19 Dec 2022
Cited by 7 | Viewed by 1974
Abstract
In this paper, an optimal design of a high-efficiency DC-DC boost converter is proposed for RF energy harvesting Internet of Things (IoT) sensors. Since the output DC voltage of the RF-DC rectifier for RF energy harvesting varies considerably depending on the RF input [...] Read more.
In this paper, an optimal design of a high-efficiency DC-DC boost converter is proposed for RF energy harvesting Internet of Things (IoT) sensors. Since the output DC voltage of the RF-DC rectifier for RF energy harvesting varies considerably depending on the RF input power, the DC-DC boost converter following the RF-DC rectifier is required to achieve high power conversion efficiency (PCE) in a wide input voltage range. Therefore, based on the loss analysis and modeling of an inductor-based DC-DC boost converter, an optimal design method of design parameters, including inductance and peak inductor current, is proposed to obtain the maximum PCE by minimizing the total loss according to different input voltages in a wide input voltage range. A high-efficiency DC-DC boost converter for RF energy harvesting applications is designed using a 65 nm CMOS process. The modeled total losses agree well with the circuit simulation results and the proposed loss modeling results accurately predict the optimal design parameters to obtain the maximum PCE. Based on the proposed loss modeling, the optimally designed DC-DC boost converter achieves a power conversion efficiency of 96.5% at a low input voltage of 0.1 V and a peak efficiency of 98.4% at an input voltage of 0.4 V. Full article
(This article belongs to the Section Industrial Sensors)
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12 pages, 2817 KiB  
Article
Non-Specific Responsive Nanogels and Plasmonics to Design MathMaterial Sensing Interfaces: The Case of a Solvent Sensor
by Nunzio Cennamo, Francesco Arcadio, Fiore Capasso, Devid Maniglio, Luigi Zeni and Alessandra Maria Bossi
Sensors 2022, 22(24), 10006; https://doi.org/10.3390/s222410006 - 19 Dec 2022
Cited by 2 | Viewed by 1741
Abstract
The combination of non-specific deformable nanogels and plasmonic optical probes provides an innovative solution for specific sensing using a generalistic recognition layer. Soft polyacrylamide nanogels that lack specific selectivity but are characterized by responsive behavior, i.e., shrinking and swelling dependent on the surrounding [...] Read more.
The combination of non-specific deformable nanogels and plasmonic optical probes provides an innovative solution for specific sensing using a generalistic recognition layer. Soft polyacrylamide nanogels that lack specific selectivity but are characterized by responsive behavior, i.e., shrinking and swelling dependent on the surrounding environment, were grafted to a gold plasmonic D-shaped plastic optical fiber (POF) probe. The nanogel–POF cyclically challenged with water or alcoholic solutions optically reported the reversible solvent-to-phase transitions of the nanomaterial, embodying a primary optical switch. Additionally, the non-specific nanogel–POF interface exhibited more degrees of freedom through which specific sensing was enabled. The real-time monitoring of the refractive index variations due to the time-related volume-to-phase transition effects of the nanogels enabled us to determine the environment’s characteristics and broadly classify solvents. Hence the nanogel–POF interface was a descriptor of mathematical functions for substance identification and classification processes. These results epitomize the concept of responsive non-specific nanomaterials to perform a multiparametric description of the environment, offering a specific set of features for the processing stage and particularly suitable for machine and deep learning. Thus, soft MathMaterial interfaces provide the ground to devise devices suitable for the next generation of smart intelligent sensing processes. Full article
(This article belongs to the Topic Artificial Intelligence in Sensors)
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16 pages, 6263 KiB  
Article
Retrieval of Suspended Sediment Concentration from Bathymetric Bias of Airborne LiDAR
by Xinglei Zhao, Jianfei Gao, Hui Xia and Fengnian Zhou
Sensors 2022, 22(24), 10005; https://doi.org/10.3390/s222410005 - 19 Dec 2022
Viewed by 1293
Abstract
In addition to depth measurements, airborne LiDAR bathymetry (ALB) has shown usefulness in suspended sediment concentration (SSC) inversion. However, SSC retrieval using ALB based on waveform decomposition or near-water-surface penetration by green lasers requires access to full-waveform data or infrared laser data, which [...] Read more.
In addition to depth measurements, airborne LiDAR bathymetry (ALB) has shown usefulness in suspended sediment concentration (SSC) inversion. However, SSC retrieval using ALB based on waveform decomposition or near-water-surface penetration by green lasers requires access to full-waveform data or infrared laser data, which are not always available for users. Thus, in this study we propose a new SSC inversion method based on the depth bias of ALB. Artificial neural networks were used to build an empirical inversion model by connecting the depth bias and SSC. The proposed method was verified using an ALB dataset collected through Optech coastal zone mapping and imaging LiDAR systems. The results showed that the mean square error of the predicted SSC based on the empirical model of ALB depth bias was less than 2.564 mg/L in the experimental area. The proposed method was compared with the waveform decomposition and regression methods. The advantages and limits of the proposed method were analyzed and summarized. The proposed method can effectively retrieve SSC and only requires ALB-derived and sonar-derived water bottom points, eliminating the dependence on the use of green full-waveforms and infrared lasers. This study provides an alternative means of conducting SSC inversion using ALB. Full article
(This article belongs to the Special Issue Laser Based Remote Sensors for Environmental Science: Measurements and Analysis Techniques)
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20 pages, 9260 KiB  
Article
Automated Identification of Overheated Belt Conveyor Idlers in Thermal Images with Complex Backgrounds Using Binary Classification with CNN
by Mohammad Siami, Tomasz Barszcz, Jacek Wodecki and Radoslaw Zimroz
Sensors 2022, 22(24), 10004; https://doi.org/10.3390/s222410004 - 19 Dec 2022
Cited by 3 | Viewed by 1998
Abstract
Mechanical industrial infrastructures in mining sites must be monitored regularly. Conveyor systems are mechanical systems that are commonly used for safe and efficient transportation of bulk goods in mines. Regular inspection of conveyor systems is a challenging task for mining enterprises, as conveyor [...] Read more.
Mechanical industrial infrastructures in mining sites must be monitored regularly. Conveyor systems are mechanical systems that are commonly used for safe and efficient transportation of bulk goods in mines. Regular inspection of conveyor systems is a challenging task for mining enterprises, as conveyor systems’ lengths can reach tens of kilometers, where several thousand idlers need to be monitored. Considering the harsh environmental conditions that can affect human health, manual inspection of conveyor systems can be extremely difficult. Hence, the authors proposed an automatic robotics-based inspection for condition monitoring of belt conveyor idlers using infrared images, instead of vibrations and acoustic signals that are commonly used for condition monitoring applications. The first step in the whole process is to segment the overheated idlers from the complex background. However, classical image segmentation techniques do not always deliver accurate results in the detection of target in infrared images with complex backgrounds. For improving the quality of captured infrared images, preprocessing stages are introduced. Afterward, an anomaly detection method based on an outlier detection technique is applied to the preprocessed image for the segmentation of hotspots. Due to the presence of different thermal sources in mining sites that can be captured and wrongly identified as overheated idlers, in this research, we address the overheated idler detection process as an image binary classification task. For this reason, a Convolutional Neural Network (CNN) was used for the binary classification of the segmented thermal images. The accuracy of the proposed condition monitoring technique was compared with our previous research. The metrics for the previous methodology reach a precision of 0.4590 and an F1 score of 0.6292. The metrics for the proposed method reach a precision of 0.9740 and an F1 score of 0.9782. The proposed classification method considerably improved our previous results in terms of the true identification of overheated idlers in the presence of complex backgrounds. Full article
(This article belongs to the Special Issue Application of Wireless Sensor Networks in Environmental Monitoring)
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24 pages, 14166 KiB  
Article
Common Frame Dynamics for Conically-Constrained Spacecraft Attitude Control
by Arnold Christopher Cruz and Ahmad Bani Younes
Sensors 2022, 22(24), 10003; https://doi.org/10.3390/s222410003 - 19 Dec 2022
Viewed by 1413
Abstract
Attitude control subjected to pointing constraints is a requirement for most spacecraft missions carrying sensitive on-board equipment. Pointing constraints can be divided into two categories: exclusion zones that are defined for sensitive equipment such as telescopes or cameras that can be damaged from [...] Read more.
Attitude control subjected to pointing constraints is a requirement for most spacecraft missions carrying sensitive on-board equipment. Pointing constraints can be divided into two categories: exclusion zones that are defined for sensitive equipment such as telescopes or cameras that can be damaged from celestial objects, and inclusion zones that are defined for communication hardware and solar arrays. This work derives common frame dynamics that are fully derived for Modified Rodrigues Parameters and introduced to an existing novel technique for constrained spacecraft attitude control, which uses a kinematic steering law and servo sub-system. Lyapunov methods are used to redevelop the steering law and servo sub-system in the common frame for the tracking problem for both static and dynamic conic constraints. A numerical example and comparison between the original frame and the common frame for the static constrained tracking problem are presented under both unbounded and limited torque capabilities. Monte Carlo simulations are performed to validate the convergence of the constrained tracking problem for static conic constraints under small perturbations of the initial conditions. The performance of dynamic conic constraints in the tracking problem is addressed and a numerical example is presented. The result of using common frame dynamics in the constrained problem shows decreased control effort required to rotate the spacecraft. Full article
(This article belongs to the Special Issue Attitude Estimation Based on Data Processing of Sensors)
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3 pages, 165 KiB  
Editorial
Advanced Fault Diagnosis and Health Monitoring Techniques for Complex Engineering Systems
by Yongbo Li, Bing Li, Jinchen Ji and Hamed Kalhori
Sensors 2022, 22(24), 10002; https://doi.org/10.3390/s222410002 - 19 Dec 2022
Viewed by 1079
Abstract
Fault diagnosis and health condition monitoring have always been critical issues in the engineering research community [...] Full article
(This article belongs to the Special Issue Advanced Fault Diagnosis and Health Monitoring Techniques for Complex Engineering Systems)
20 pages, 7847 KiB  
Article
Table-Based Adaptive Digital Phase-Locked Loop for GNSS Receivers Operating in Moon Exploration Missions
by Young-Jin Song and Jong-Hoon Won
Sensors 2022, 22(24), 10001; https://doi.org/10.3390/s222410001 - 19 Dec 2022
Cited by 2 | Viewed by 1554
Abstract
An adaptive digital phase-locked loop (DPLL) continually adjusts the noise bandwidth of the loop filter in global navigation satellite system (GNSS) receivers to track signals by measuring the signal-to-noise ratio and/or dynamic stress. Such DPLLs have a relatively large amount of computational complexity [...] Read more.
An adaptive digital phase-locked loop (DPLL) continually adjusts the noise bandwidth of the loop filter in global navigation satellite system (GNSS) receivers to track signals by measuring the signal-to-noise ratio and/or dynamic stress. Such DPLLs have a relatively large amount of computational complexity compared with the conventional DPLL. A table-based adaptive DPLL is proposed that adjusts the noise bandwidth value by extracting it from the pre-generated table without additional calculations. The values of the noise bandwidth table are computed in an optimal manner in consideration of the thermal noise, oscillator phase noise, and dynamic stress error. The calculation method of the proper integration time to maintain the stability of the loop filter is presented. Additionally, the simulation is configured using the trajectory analysis results from the Moon exploration mission and shows that the proposed algorithm operates stably in harsh environments, while a conventional fixed bandwidth loop cannot. The proposed algorithm has a similar phase jitter performance to the existing adaptive DPLL algorithms and has an execution time that is approximately 2.4–5.4 times faster. It is verified that the proposed algorithm is computationally efficient while maintaining jitter performance. Full article
(This article belongs to the Special Issue GNSS Signals and Precise Point Positioning)
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14 pages, 3540 KiB  
Article
A Symbols Based BCI Paradigm for Intelligent Home Control Using P300 Event-Related Potentials
by Faraz Akram, Ahmed Alwakeel, Mohammed Alwakeel, Mohammad Hijji and Usman Masud
Sensors 2022, 22(24), 10000; https://doi.org/10.3390/s222410000 - 19 Dec 2022
Cited by 3 | Viewed by 2166
Abstract
Brain-Computer Interface (BCI) is a technique that allows the disabled to interact with a computer directly from their brain. P300 Event-Related Potentials (ERP) of the brain have widely been used in several applications of the BCIs such as character spelling, word typing, wheelchair [...] Read more.
Brain-Computer Interface (BCI) is a technique that allows the disabled to interact with a computer directly from their brain. P300 Event-Related Potentials (ERP) of the brain have widely been used in several applications of the BCIs such as character spelling, word typing, wheelchair control for the disabled, neurorehabilitation, and smart home control. Most of the work done for smart home control relies on an image flashing paradigm where six images are flashed randomly, and the users can select one of the images to control an object of interest. The shortcoming of such a scheme is that the users have only six commands available in a smart home to control. This article presents a symbol-based P300-BCI paradigm for controlling home appliances. The proposed paradigm comprises of a 12-symbols, from which users can choose one to represent their desired command in a smart home. The proposed paradigm allows users to control multiple home appliances from signals generated by the brain. The proposed paradigm also allows the users to make phone calls in a smart home environment. We put our smart home control system to the test with ten healthy volunteers, and the findings show that the proposed system can effectively operate home appliances through BCI. Using the random forest classifier, our participants had an average accuracy of 92.25 percent in controlling the home devices. As compared to the previous studies on the smart home control BCIs, the proposed paradigm gives the users more degree of freedom, and the users are not only able to control several home appliances but also have an option to dial a phone number and make a call inside the smart home. The proposed symbols-based smart home paradigm, along with the option of making a phone call, can effectively be used for controlling home through signals of the brain, as demonstrated by the results. Full article
(This article belongs to the Special Issue Signal Processing for Brain–Computer Interfaces)
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16 pages, 8446 KiB  
Article
Design of a Ultra-Stable Low-Noise Space Camera Based on a Large Target CMOS Detector and Image Data Analysis
by Chao Shen, Caiwen Ma and Wei Gao
Sensors 2022, 22(24), 9991; https://doi.org/10.3390/s22249991 - 18 Dec 2022
Cited by 2 | Viewed by 1809
Abstract
To detect faint target stars of 22nd magnitude and above, an astronomical exploration project requires its space camera’s readout noise to be less than 5e− with long-time working stability. Due to the limitation of satellite, the traditional CCD detector-based camera does not [...] Read more.
To detect faint target stars of 22nd magnitude and above, an astronomical exploration project requires its space camera’s readout noise to be less than 5e− with long-time working stability. Due to the limitation of satellite, the traditional CCD detector-based camera does not meet the requirements, including volume, weight, and power consumption. Thereby, a low-noise ultra-stable camera based on 9 K × 9 K large target surface CMOS is designed to meet the needs. For the first time, the low-noise ultra-stable camera based on CMOS detector will be applied to space astronomy projects, remote sensing imaging, resource survey, atmospheric and oceanic observation and other fields. In this paper, the design of the camera is introduced in detail, and the camera is tested for several rounds at −40 °C; it also undergoes further testing and data analysis. Tests proved super stability and that the readout noise is lower than 4.5e−. Dark current, nonlinearity and PTC indicators meet the requirements of the astronomical exploration project. Full article
(This article belongs to the Special Issue Sensing for Space Applications)
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11 pages, 1790 KiB  
Communication
Simulation of Rapid Thermal Cycle for Ultra-Fast PCR
by Zhuo Yang, Jiali Zhang, Xin Tong, Wenbing Li, Lijuan Liang, Bo Liu and Chang Chen
Sensors 2022, 22(24), 9990; https://doi.org/10.3390/s22249990 - 18 Dec 2022
Cited by 1 | Viewed by 1834
Abstract
The polymerase chain reaction (PCR) technology is a mainstream detection method used in medical diagnoses, environmental monitoring, food hygiene, and safety. However, the systematic analysis of a compact structure with fast temperature changes for an ultra-fast PCR device that is convenient for on-site [...] Read more.
The polymerase chain reaction (PCR) technology is a mainstream detection method used in medical diagnoses, environmental monitoring, food hygiene, and safety. However, the systematic analysis of a compact structure with fast temperature changes for an ultra-fast PCR device that is convenient for on-site detection still lacks investigation. To overcome the problems of low heating efficiency and non-portability of PCR devices currently used, a miniaturized PCR system based on a microfluidic chip, i.e., lab-on-chip technology, has been proposed. The main objective of this paper is to explore the feasibility of using a heat resistor that can reach a fast heating rate and temperature uniformity combined with air cooling technology for rapid cooling and to investigate the influences of various pattern designs and thicknesses of the resistor on heating rates and temperature uniformity. Additionally, a PCR chip made of various materials with different thermal properties, such as surface emissivity, thermal conductivity, mass density, and heat capacity at constant pressure is analyzed. In addition to the heat loss caused by the natural convection of air, the radiation loss of the simulation object is also considered, which makes the model much closer to the practical situation. Our research results provide a considerable reference for the design of the heating and cooling modules used in the ultra-fast PCR protocol, which has great potential in In Vitro Diagnosis (IVD) and the PCR detection of foodborne pathogens and bacteria. Full article
(This article belongs to the Special Issue Advanced Biosensors for Foodborne Pathogens)
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