IEEE Journal of Selected Areas in Sensors最新文献_第5页

Stub-Loaded Patch Antenna for Development of High Sensitivity Crack Monitoring Sensor 用于开发高灵敏度裂缝监测传感器的存根负载贴片天线

IEEE Journal of Selected Areas in Sensors Pub Date : 2024-04-29 DOI: 10.1109/JSAS.2024.3394393

Nan-Wei Chen;Chih-Ying Chen;Ren-Rong Guo

{"title":"Stub-Loaded Patch Antenna for Development of High Sensitivity Crack Monitoring Sensor","authors":"Nan-Wei Chen;Chih-Ying Chen;Ren-Rong Guo","doi":"10.1109/JSAS.2024.3394393","DOIUrl":"https://doi.org/10.1109/JSAS.2024.3394393","url":null,"abstract":"This article proposes the use of a wireless sensor developed with a microstrip patch antenna in conjunction with an open-circuited stub for remote, real-time monitoring of crack width expansion. Technically, the open-circuited stub is exploited as a sensing structure with excellent sensitivity, and the crack growth is able to be mechanically mapped to the stub length extension via an incorporation of a mirrored stub structure placed right on top of the open-circuited stub. Thanks to a very strong relationship between the stub input admittance and its electrical length, the operating frequency of the patch is able to be significantly downshifted as the stub is mechanically lengthened (i.e., the crack grows). With the proposed wireless sensing scheme, the crack width expansion can be determined by identifying the dominant frequency component of the sensing signal received at remote data stations in a real-time manner. The sensor operating at 4 GHz was developed for experimental verification and as a demonstration of effectiveness. The experimental results show that the wireless sensor is able to identify the crack expansion of up to 2 mm with a resonant frequency downshift of 110 MHz. Furthermore, the maximum expansion and the finest increment can be simply specified with the sensor operating frequency regime. Moreover, a stable wireless link can be sustained as the patch radiation patterns remain unaffected while crack grows, and the sensor can be reused since the proposed monitoring does not result in any structure destruction or deformation.","PeriodicalId":100622,"journal":{"name":"IEEE Journal of Selected Areas in Sensors","volume":"1 ","pages":"29-35"},"PeriodicalIF":0.0,"publicationDate":"2024-04-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10509741","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141078757","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Adaptive Age of Information Optimization in Rateless Coding-Based Multicast-Enabled Sensor Networks 基于无鼠编码的多播传感器网络中的自适应信息优化时代

IEEE Journal of Selected Areas in Sensors Pub Date : 2024-03-30 DOI: 10.1109/JSAS.2024.3407689

Hung-Chun Lin;Kuang-Hsun Lin;Hung-Yu Wei

{"title":"Adaptive Age of Information Optimization in Rateless Coding-Based Multicast-Enabled Sensor Networks","authors":"Hung-Chun Lin;Kuang-Hsun Lin;Hung-Yu Wei","doi":"10.1109/JSAS.2024.3407689","DOIUrl":"https://doi.org/10.1109/JSAS.2024.3407689","url":null,"abstract":"As the demand for real-time information in Internet of Things and wireless sensor networks (WSN) scenarios grows with the evolution of bandwidth-intensive 5G applications, multicast transmission becomes increasingly vital. This article delves into the significant role of multicast in WSN, exploring a novel perspective of using rateless codes over the traditionally employed hybrid automatic repeat request for eliminating retransmissions in a wireless multicast system. We aim to optimize data freshness, quantified by the age of information (AoI), and analyze strategies to minimize time-average AoI in a multicast environment with diverse channel conditions. Specifically, our policy focuses on optimizing the time-average AoI based on sensor devices' feedback. We transform the problem into a Markov decision process to locate optimal and low-complexity suboptimal policies. We present the first age-minimum scheme for rateless code-based wireless multicast systems. Our numerical simulations reveal that the proposed policies, developed considering unique system structural properties, consistently surpass baseline strategies. We are thus able to preempt updates at the most beneficial time, thereby addressing the issue of the bottleneck device's adverse impact on overall performance.","PeriodicalId":100622,"journal":{"name":"IEEE Journal of Selected Areas in Sensors","volume":"1 ","pages":"73-92"},"PeriodicalIF":0.0,"publicationDate":"2024-03-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10542217","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141430052","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Circular Polarized Antennas With Harmonic Radar: Passive Nonlinear Tag Localization 带谐波雷达的圆极化天线：无源非线性标签定位

IEEE Journal of Selected Areas in Sensors Pub Date : 2024-03-18 DOI: 10.1109/JSAS.2024.3378157

Vishal G Yadav;Leya Zeng;Changzhi Li

{"title":"Circular Polarized Antennas With Harmonic Radar: Passive Nonlinear Tag Localization","authors":"Vishal G Yadav;Leya Zeng;Changzhi Li","doi":"10.1109/JSAS.2024.3378157","DOIUrl":"https://doi.org/10.1109/JSAS.2024.3378157","url":null,"abstract":"This research proposes a high performance, low-profile planar design, and demonstration of circularly polarized harmonic antenna arrays for 4 and 8 GHz harmonic radar system, which is equipped, and the antenna's circular polarization (CP) performance is tested using a passive nonlinear harmonic tag (snowflake) in a noisy environment. This work mainly concentrates on investigation of the wave polarization (circular), gain estimation and impedance matching of the antenna arrays that will be potentially assembled to the second-order harmonic radar system operating at 4 and 8 GHz, which plays a critical role in 2-D tag localization and post processing methods. The passive snowflake tag design is implemented in the simulation to determine the current distribution and gain plot patterns in comparison to a classic dipole antenna tag structure. In experiments: a combination of fundamental circular polarized (left-hand) antennas were demonstrated to find axial ratio \u0000<inline-formula><tex-math>$ leq $</tex-math></inline-formula>\u0000 3 dB band. A novel tag 2-D localization measurement, combination of CP harmonic antenna arrays is utilized to perform and obtain the circular polarized received signal power in dBm versus angle rotation by every 10° on a rotating platform setup. Finally, the wireless tag tracking result is achieved by using the designed circularly polarized antennas and the passive nonlinear tag orientation setup.","PeriodicalId":100622,"journal":{"name":"IEEE Journal of Selected Areas in Sensors","volume":"1 ","pages":"9-19"},"PeriodicalIF":0.0,"publicationDate":"2024-03-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10474130","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140641639","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Iterative Vector-Based Localization in a Large Heterogeneous Sensor Network 大型异构传感器网络中基于矢量的迭代定位

IEEE Journal of Selected Areas in Sensors Pub Date : 2024-03-07 DOI: 10.1109/JSAS.2024.3397769

Insung Kang;Haewoon Nam

{"title":"Iterative Vector-Based Localization in a Large Heterogeneous Sensor Network","authors":"Insung Kang;Haewoon Nam","doi":"10.1109/JSAS.2024.3397769","DOIUrl":"https://doi.org/10.1109/JSAS.2024.3397769","url":null,"abstract":"This article proposes a novel iterative vector-based localization method in a large heterogeneous sensor network, where a subset of nodes possesses the capability to measure both distance and angle information, while the others are only limited to distance measurements. Unlike conventional vector-based positioning methods that assume all nodes can measure both distance and angle, our approach tackles a more realistic scenario where some nodes are limited to distance-only measurements. To address the challenges of the node localization in a heterogeneous sensor network, the proposed positioning method calculates vector information between the nodes that are not directly communicated and aligns it with a reference coordinate. In addition, the proposed method employs an iterative calculation, such as least-squares minimization, thereby achieving high positioning accuracy. Simulation results demonstrate that the proposed positioning method outperforms the conventional distance-based positioning method in environments with low angle measurement errors, exhibiting up to 44% higher positioning accuracy. Furthermore, the proposed positioning method shows 24% higher positioning accuracy compared with the conventional vector-based positioning method.","PeriodicalId":100622,"journal":{"name":"IEEE Journal of Selected Areas in Sensors","volume":"1 ","pages":"60-72"},"PeriodicalIF":0.0,"publicationDate":"2024-03-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10521718","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141292483","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

MASTER: Machine Learning-Based Cold Start Latency Prediction Framework in Serverless Edge Computing Environments for Industry 4.0 MASTER：面向工业 4.0 的无服务器边缘计算环境中基于机器学习的冷启动延迟预测框架

IEEE Journal of Selected Areas in Sensors Pub Date : 2024-03-02 DOI: 10.1109/JSAS.2024.3396440

Muhammed Golec;Sukhpal Singh Gill;Huaming Wu;Talat Cemre Can;Mustafa Golec;Oktay Cetinkaya;Felix Cuadrado;Ajith Kumar Parlikad;Steve Uhlig

{"title":"MASTER: Machine Learning-Based Cold Start Latency Prediction Framework in Serverless Edge Computing Environments for Industry 4.0","authors":"Muhammed Golec;Sukhpal Singh Gill;Huaming Wu;Talat Cemre Can;Mustafa Golec;Oktay Cetinkaya;Felix Cuadrado;Ajith Kumar Parlikad;Steve Uhlig","doi":"10.1109/JSAS.2024.3396440","DOIUrl":"https://doi.org/10.1109/JSAS.2024.3396440","url":null,"abstract":"The integration of serverless edge computing and the Industrial Internet of Things (IIoT) has the potential to optimize industrial production. However, cold start latency is one of the main challenges in this area, resulting in resource waste. To address this issue, we propose a new machine learning-based resource management framework called MASTER which utilizes an extreme gradient boosting (XGBoost) model to predict the cold start latency for Industry 4.0 applications for performance optimization. Furthermore, we created a new cold start dataset using an IIoT scenario (i.e. predictive maintenance) to validate the proposed MASTER framework in serverless edge computing environments. We have evaluated the performance of the MASTER framework using a real-world serverless platform, Google Cloud Platform for single-step prediction (SSP) and multiple-step prediction (MSP) operations and compared it with existing frameworks that used deep deterministic policy gradient (DDPG) and long short-term memory (LSTM) models. The experimental results show that the XGBoost-based resource management framework is the most successful model in predicting cold start with mean absolute percentage error (MAPE) values of 0.23 in SSP and 0.12 in MSP. It has been also identified that the Linear Regression model (utilized in the MASTER framework) has the least computational time (0.03 seconds) as compared to other deep learning and machine learning models considered in this work. Finally, we compare the energy consumption and \u0000<inline-formula><tex-math>$text{CO}_{2}$</tex-math></inline-formula>\u0000 emissions of all models to emphasize resource awareness.","PeriodicalId":100622,"journal":{"name":"IEEE Journal of Selected Areas in Sensors","volume":"1 ","pages":"36-48"},"PeriodicalIF":0.0,"publicationDate":"2024-03-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10517641","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141084810","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Testing of Emerging Wireless Sensor Networks Using Radar Signals With Machine Learning Algorithms 用机器学习算法测试使用雷达信号的新兴无线传感器网络

IEEE Journal of Selected Areas in Sensors Pub Date : 2024-03-01 DOI: 10.1109/JSAS.2024.3395578

Shitharth Selvarajan;Hariprasath Manoharan;Adil O. Khadidos;Alaa O. Khadidos

{"title":"Testing of Emerging Wireless Sensor Networks Using Radar Signals With Machine Learning Algorithms","authors":"Shitharth Selvarajan;Hariprasath Manoharan;Adil O. Khadidos;Alaa O. Khadidos","doi":"10.1109/JSAS.2024.3395578","DOIUrl":"https://doi.org/10.1109/JSAS.2024.3395578","url":null,"abstract":"In this article, machine learning methods are used to assess how well wireless sensor networks transmit and receive radar signals. Measurements are done with labeled and unlabeled datasets where output functions are modified in relation to transmitted input in order to test the transceiver of radar signals. The main contribution in the proposed method is to focus on the possibility of choosing a free space model that transmits the radar signals in wireless sensor networks without any interruptions. Hence, for such type of transmissions, reference time period is selected in order to perform radar signal classification, and at the same time, separation of unnecessary interruptions is reduced using clustering procedures. Since the radar signals can be monitored with automatic transmission techniques, the outcomes are combined with supervised, unsupervised, and reinforcement learning models to increase the effect of transmissions. Therefore, the objective functions are designed with three scenarios where reinforcement learning proves to provide adequate connections for radar signals to all wireless sensor networks at reduced error of 0.3%. In addition, with reinforcement learning, the distance of radar signal transmission is maximized to a level greater than 75% at minimized noise ratio of 0.8%.","PeriodicalId":100622,"journal":{"name":"IEEE Journal of Selected Areas in Sensors","volume":"1 ","pages":"49-59"},"PeriodicalIF":0.0,"publicationDate":"2024-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10517404","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141096318","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Frequency-Switchable Routing Protocol for Dynamic Magnetic Induction-Based Wireless Underground Sensor Networks 基于动态磁感应的无线地下传感器网络的频率可切换路由协议

IEEE Journal of Selected Areas in Sensors Pub Date : 2024-01-23 DOI: 10.1109/JSAS.2024.3357792

Guanghua Liu

引用次数: 0

IEEE Journal of Selected Areas in Sensors Publication Information IEEE传感器选择领域期刊出版信息

IEEE Journal of Selected Areas in Sensors Pub Date : 2023-07-18 DOI: 10.1109/JSAS.2023.3285333

引用次数: 0