IEEE Sensors Journal最新文献_第6页

Hybrid Energy-Efficient Clustering With Reinforcement Learning for IoT-WSNs Using Knapsack and K -Means 基于背包和K均值的物联网wsns混合强化学习节能聚类

IF 4.3 2区综合性期刊

IEEE Sensors Journal Pub Date : 2025-06-30 DOI: 10.1109/JSEN.2025.3582381

Abdul Aleem;Rajesh Thumma

{"title":"Hybrid Energy-Efficient Clustering With Reinforcement Learning for IoT-WSNs Using Knapsack and K -Means","authors":"Abdul Aleem;Rajesh Thumma","doi":"10.1109/JSEN.2025.3582381","DOIUrl":"https://doi.org/10.1109/JSEN.2025.3582381","url":null,"abstract":"Wireless sensor networks (WSNs) play a fundamental role in the Internet of Things (IoTs), with widespread applications in areas such as smart city infrastructure, industrial control systems, and environmental monitoring. Despite their broad utility, challenges related to energy efficiency and network longevity persist. To address these issues, this article introduces an integrated framework that leverages distributed energy-efficient clustering (DEEC), the energy-efficient Knapsack algorithm (EEKA), K-means clustering, and reinforcement learning (RL) to optimize energy usage and improve overall network performance. While cluster-heads (CHs) selection is conducted in a balanced manner by DEEC to prevent energy depletion, the selection of sensor node CHs also avoids exhausting sensor node energy. EEKA optimizes task allocation under energy constraints, allowing for efficient distribution of tasks based on available energy levels. This approach conserves more energy spent on data transmission compared to other techniques, as K-means clustering minimizes intracluster communication overhead. Moreover, during varying conditions such as cluster sizes or transmission power, parameters related to the network can be adaptively tuned in real-time by RL, enhancing stability and performance. Simulation results demonstrate a significant improvement in energy efficiency with this hybrid model compared to traditional approaches under similar conditions. Therefore, for sustainable energy management within IoT-enabled WSNs, the DEEC-EEKA–K-means-RL framework offers a robust adaptive method for efficient resource utilization across diverse operational contexts, rather than relying solely on robustness and resilience-based solutions.","PeriodicalId":447,"journal":{"name":"IEEE Sensors Journal","volume":"25 15","pages":"30047-30059"},"PeriodicalIF":4.3,"publicationDate":"2025-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144758455","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Fan Pressurization Method to Measure House Leakage Area Using Built-in Exhaust Fans and Window Openings as Reference Areas 以内置排风机和开窗作为参考面积测量房屋泄漏面积的风机加压法

IF 4.3 2区综合性期刊

IEEE Sensors Journal Pub Date : 2025-06-30 DOI: 10.1109/JSEN.2025.3582369

Y. Kurihara;K. Kobayashi;K. Watanabe

{"title":"Fan Pressurization Method to Measure House Leakage Area Using Built-in Exhaust Fans and Window Openings as Reference Areas","authors":"Y. Kurihara;K. Kobayashi;K. Watanabe","doi":"10.1109/JSEN.2025.3582369","DOIUrl":"https://doi.org/10.1109/JSEN.2025.3582369","url":null,"abstract":"The fan pressurization method described in ISO 9972:2015 evaluates the air permeability of houses by measuring the effective leakage area (ELA). This method uses a specialized blower equipped with a volumetric airflow meter and a differential pressure sensor. This study proposes an alternative that utilizes a differential pressure sensor along with household exhaust fans to depressurize a house. Additionally, the known area of an open house window is used to calibrate the ELA against the corresponding geometrical area. To validate this method, the relationship between the geometric leakage area and the ELA obtained through this approach, as well as comparisons with other methods, were examined via theoretical analysis and experiments in a small container space. In a single room in an actual building characterized by substantial leakage gaps, such as those around interior doors, the total leakage area measured with a gap meter was 311.5 cm2, and the proposed method yielded the same value, demonstrating excellent agreement between the two. The proposed method was tested in a 36-year-old American-style house with a total floor area of 226.59 m2 and resulted in an ELA of 672 cm2 and a C-value of 2.96 cm2/m2. The geometrically measurable leakage area and the area estimated using the proposed method showed good agreement, confirming the reliability of the approach. Furthermore, the C-value of 2.96 cm2/m2, derived from the ELA measured in an actual house experiment, falls within the typical range for residential buildings (110 cm2/m<inline-formula> <tex-math>${}^{{2}}text {)}$ </tex-math></inline-formula>.","PeriodicalId":447,"journal":{"name":"IEEE Sensors Journal","volume":"25 15","pages":"29880-29889"},"PeriodicalIF":4.3,"publicationDate":"2025-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144751116","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A Compact and Wireless Wearable System for Sleep Apnea Detection 一种用于睡眠呼吸暂停检测的紧凑无线可穿戴系统

IF 4.3 2区综合性期刊

IEEE Sensors Journal Pub Date : 2025-06-30 DOI: 10.1109/JSEN.2025.3582712

Hamidreza Rahimi;Ashkan Rahdar;Amirhossein Moradi;Fatemeh Akbar;Ali Fotowat-Ahmady

{"title":"A Compact and Wireless Wearable System for Sleep Apnea Detection","authors":"Hamidreza Rahimi;Ashkan Rahdar;Amirhossein Moradi;Fatemeh Akbar;Ali Fotowat-Ahmady","doi":"10.1109/JSEN.2025.3582712","DOIUrl":"https://doi.org/10.1109/JSEN.2025.3582712","url":null,"abstract":"Sleep apnea is a prevalent sleep disorder with serious health consequences. While polysomnography (PSG) is the clinical gold standard for apnea diagnosis, it is costly, obtrusive, and impractical for continuous or home-based monitoring. Existing wearable solutions also often lack sufficient accuracy and reliability. This article presents a novel and practical method for the accurate diagnosis of sleep apnea. A compact wireless wearable device is developed to capture biosignals and transmit them to a smartphone. The device integrates an inertial measurement unit (IMU) and a photoplethysmogram (PPG) block to directly capture signals from the body. These signals are then modulated and wirelessly transmitted to the user’s smartphone via Bluetooth low energy (BLE). As the third block of the system, the smartphone’s internal microphone records the user’s breathing sounds throughout sleep. Together, the three blocks generate six signals: SpO2, heart rate (HR) (both extracted from the PPG signal), breathing sound, and three-axis acceleration, which are subsequently processed in MATLAB. By applying signal processing techniques, sleep apnea and hypopnea events, along with their timing, can be diagnosed with high accuracy. Based on an event-to-event comparison, the developed system achieves a sensitivity of 85.8% and an <inline-formula> <tex-math>${F}1$ </tex-math></inline-formula>-score of 87.3% using a single signal. The use of a combined approach further enhances sensitivity, reliability, and the <inline-formula> <tex-math>${F}1$ </tex-math></inline-formula>-score to 91%.","PeriodicalId":447,"journal":{"name":"IEEE Sensors Journal","volume":"25 15","pages":"29605-29617"},"PeriodicalIF":4.3,"publicationDate":"2025-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144758156","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

RoboTuni: An Intelligent Servo-Tuning for Improving Path Accuracy in Robot Manipulators RoboTuni：一种提高机械臂路径精度的智能伺服整定方法

IF 4.3 2区综合性期刊

IEEE Sensors Journal Pub Date : 2025-06-30 DOI: 10.1109/JSEN.2025.3582409

Bo-Ru Tseng;Shih-Hsien Yang;Ching-Hung Lee

引用次数: 0

Development of Lossy Mode Resonance Optical Fiber Humidity Sensor Using M13 Bacteriophage 利用M13噬菌体研制损耗模共振光纤湿度传感器

IF 4.3 2区综合性期刊

IEEE Sensors Journal Pub Date : 2025-06-30 DOI: 10.1109/JSEN.2025.3582873

Sung Yoon Cho;Ji Su Kim;Soyeon Ahn;Min Su Kim;Byeong Kwon Choi;Minjun Kim;Jong-Min Lee;Min Yong Jeon

引用次数: 0

A Highly Sensitive RFID Displacement Sensor Based on EIT-Like Effect 基于类eit效应的高灵敏度RFID位移传感器

IF 4.3 2区综合性期刊

IEEE Sensors Journal Pub Date : 2025-06-27 DOI: 10.1109/JSEN.2025.3581985

Huijuan Gu;Xiaofeng Gan;Yanbin Zhang;Jun Zhang;Xiangyu Xie;Haidou Wang;Lihong Dong

{"title":"A Highly Sensitive RFID Displacement Sensor Based on EIT-Like Effect","authors":"Huijuan Gu;Xiaofeng Gan;Yanbin Zhang;Jun Zhang;Xiangyu Xie;Haidou Wang;Lihong Dong","doi":"10.1109/JSEN.2025.3581985","DOIUrl":"https://doi.org/10.1109/JSEN.2025.3581985","url":null,"abstract":"In this work, a wireless passive high-sensitivity displacement sensor operated in the ultrahigh-frequency (UHF) radio frequency identification (RFID) band is proposed for displacement monitoring. The sensor is designed based on the principle of electromagnetically induced transparency (EIT)-like effect, the strip dipole (SD) rendering a bright mode, and a pair of U-shaped ring resonators (USRRs) producing a dark mode. The coupling between these two modes is extremely sensitive to micro displacement, enabling high-sensitivity displacement detection. The bright mode can directly capture the electromagnetic wave energy emitted by the RFID reader antenna and activate the RFID tag chip, enabling passive sensing. The resonant characteristics within the threshold power to activate the tag are utilized for displacement characterization, ensuring reliable wireless measurement. The proposed wireless passive displacement sensor has undergone simulation and experimental validation. The results indicate that the prototype sensor is capable of detecting displacement variations as small as 0.01 mm, consistently achieving deep submillimeter resolution, and demonstrating a detection sensitivity of 110 MHz/mm.","PeriodicalId":447,"journal":{"name":"IEEE Sensors Journal","volume":"25 15","pages":"28349-28359"},"PeriodicalIF":4.3,"publicationDate":"2025-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144758265","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A Multiagent Reinforcement Learning-Based MAC Protocol for Clustered Multihop Underwater Acoustic Sensor Networks 基于多智能体强化学习的聚类多跳水声传感器网络MAC协议

IF 4.3 2区综合性期刊

IEEE Sensors Journal Pub Date : 2025-06-27 DOI: 10.1109/JSEN.2025.3581990

Yihao Zhao;Yougan Chen;Wenxiang Zhang;Xuchen Wang;Yi Tao;Chao Li;Xiaomei Xu

{"title":"A Multiagent Reinforcement Learning-Based MAC Protocol for Clustered Multihop Underwater Acoustic Sensor Networks","authors":"Yihao Zhao;Yougan Chen;Wenxiang Zhang;Xuchen Wang;Yi Tao;Chao Li;Xiaomei Xu","doi":"10.1109/JSEN.2025.3581990","DOIUrl":"https://doi.org/10.1109/JSEN.2025.3581990","url":null,"abstract":"Underwater acoustic channels present unique challenges, including long propagation delays and narrow bandwidth, which complicate channel access in clustered underwater acoustic sensor networks (UASNs). This article proposes a multiagent reinforcement learning (MARL)-based media access control (MAC) protocol for clustered multihop UASNs (MARL-CMH-MAC) to address channel access issues within intracluster and intercluster transmission. The protocol employs efficient time-slot scheduling and a handshake-based channel reservation mechanism for each transmission type. A special MAC frame with adaptable slots is tailored for the clustered architecture based on the composition of intracluster nodes and the relaying conditions of cluster head (CH) nodes, ensuring adequate transmission time for both CH and non-CH (nCH) nodes. Additionally, the MARL model is introduced to adjust the intracluster access slots of nCH nodes and optimize the position of intracluster slots in the MAC frame, avoiding possible transmission conflicts and enhancing overall network transmission efficiency. Simulation results demonstrate that the proposed protocol is well-suited for clustered multihop UASNs, effectively improving the network throughput and channel utilization.","PeriodicalId":447,"journal":{"name":"IEEE Sensors Journal","volume":"25 15","pages":"30034-30046"},"PeriodicalIF":4.3,"publicationDate":"2025-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144758194","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A Novel Fiber Sagnac Interferometer Independent of Eigenfrequency Constraints 一种不受特征频率约束的新型光纤Sagnac干涉仪

IF 4.3 2区综合性期刊

IEEE Sensors Journal Pub Date : 2025-06-27 DOI: 10.1109/JSEN.2025.3580839

Xudong Wu;Yangtao Wang;Yuhan Li;Yang Li;Yanhui Hu;Xuejing Liu

{"title":"A Novel Fiber Sagnac Interferometer Independent of Eigenfrequency Constraints","authors":"Xudong Wu;Yangtao Wang;Yuhan Li;Yang Li;Yanhui Hu;Xuejing Liu","doi":"10.1109/JSEN.2025.3580839","DOIUrl":"https://doi.org/10.1109/JSEN.2025.3580839","url":null,"abstract":"The fiber Sagnac interferometer (FSI) is widely used in aerospace, inertial navigation, weak magnetic field measurement, and other critical applications. This article proposes a novel FSI model that eliminates the limitation imposed by the crossing time <inline-formula> <tex-math>$tau $ </tex-math></inline-formula>, i.e., the eigenfrequency. This innovation significantly shortens the length of the fiber-optic ring, thereby effectively reducing the system’s backscattering noise. Numerical simulations leveraging Bessel expansions were conducted to analyze the proposed system, demonstrating that the output term is independent of the eigenfrequency. Within a modulation frequency range of 90–120 kHz, the maximum fluctuation of the first harmonic component is only 4.6%, further confirming the system’s immunity to eigenfrequency constraints. The limit sensitivity of the system is then analyzed for applications in weak magnetic field measurement, and the detection sensitivity is up to <inline-formula> <tex-math>${3.7} times {10}^{-{3}}~text {fT/Hz}^{text {1/2}}$ </tex-math></inline-formula>. The proposed system can be applied to any Sagnac interferometer-centered instrument, eliminating eigenfrequency limitations. This is particularly valuable for applications, such as current transformers, inertial measurements, and weak magnetic field detection.","PeriodicalId":447,"journal":{"name":"IEEE Sensors Journal","volume":"25 15","pages":"28419-28426"},"PeriodicalIF":4.3,"publicationDate":"2025-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144758415","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Nondestructive Testing of Harmonic Magnetic Fields in Steel Pipelines Based on Probe Size Adapted Five-Order Response Model 基于探头尺寸自适应五阶响应模型的钢管谐波磁场无损检测

IF 4.3 2区综合性期刊

IEEE Sensors Journal Pub Date : 2025-06-27 DOI: 10.1109/JSEN.2025.3577812

Zisheng Guo;Xinhua Wang;Guiming Zhang;Yuchen Shi;Tao Sun;Shabir Ali;Zhen Zhang;Xinbo Yu

{"title":"Nondestructive Testing of Harmonic Magnetic Fields in Steel Pipelines Based on Probe Size Adapted Five-Order Response Model","authors":"Zisheng Guo;Xinhua Wang;Guiming Zhang;Yuchen Shi;Tao Sun;Shabir Ali;Zhen Zhang;Xinbo Yu","doi":"10.1109/JSEN.2025.3577812","DOIUrl":"https://doi.org/10.1109/JSEN.2025.3577812","url":null,"abstract":"There are difficulties in selecting and designing probe sizes for nondestructive testing of steel pipelines using harmonic magnetic field detection technology under different operating conditions. This study utilized methods such as objective function optimization, the partial derivative of magnetic coupling energy, defect thinning rate, rate of defect extension change in different directions of the pipe, and their integral elements to deeply analyze the influencing factors of the magnetic field excited by the excitation coil vertically placed outside the pipeline. A five-order mathematical response model for pipe diameter, coil diameter, pipe-to-coil distance, defect expansion direction, and its size change was progressively obtained, namely [(d-R-h)–I] to [(d-R-h)–V]. Through these models, the optimal excitation coil size selection scheme for detection probes under different operating conditions was derived. Finally, the effectiveness of the model was verified through experiments with different defect sizes, pipe specifications, and probe lift distances. In addition, a separable pipeline harmonic magnetic field detector was developed, whose coil probe size can be easily replaced to adapt to different detection requirements.","PeriodicalId":447,"journal":{"name":"IEEE Sensors Journal","volume":"25 15","pages":"28065-28078"},"PeriodicalIF":4.3,"publicationDate":"2025-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144758186","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A Four-Task Convolutional Neural Network Model for Real-Time Volatile Organic Compounds Detection 一种用于挥发性有机物实时检测的四任务卷积神经网络模型

IF 4.3 2区综合性期刊

IEEE Sensors Journal Pub Date : 2025-06-27 DOI: 10.1109/JSEN.2025.3581945

Weiwei Cheng;Tao Wang;Lechen Chen;Wangze Ni;Jiaqing Zhu;Zhi Yang;Shusheng Xu;Bowei Zhang;Fuzhen Xuan

{"title":"A Four-Task Convolutional Neural Network Model for Real-Time Volatile Organic Compounds Detection","authors":"Weiwei Cheng;Tao Wang;Lechen Chen;Wangze Ni;Jiaqing Zhu;Zhi Yang;Shusheng Xu;Bowei Zhang;Fuzhen Xuan","doi":"10.1109/JSEN.2025.3581945","DOIUrl":"https://doi.org/10.1109/JSEN.2025.3581945","url":null,"abstract":"The electronic nose (E-nose) is an advanced technique that has attracted substantial attention across various domains, such as environmental monitoring and disease prevention. This study proposes an innovative four-task convolutional neural network (FT-CNN) model to enhance the performance of E-nose. In contrast to conventional E-nose systems, the proposed FT-CNN model not only accomplishes four tasks simultaneously—gas classification, concentration prediction, state assessment, and anomaly identification—but also facilitates real-time detection, thereby enabling immediate decision-making in dynamic environments. The model employs a unique two-block knowledge-sharing structure, significantly improving system efficiency. Additionally, noise injection and data segmentation mechanisms are incorporated to bolster the robustness and generalization of the model. The million-volume dataset, collected from a self-developed gas sensing system, underscores the model’s capacity to handle real-world variations and anomalies effectively. Experimental results demonstrate that the FT-CNN model achieves remarkable performance, with a gas classification accuracy of 97%, a sensor state assessment accuracy of 98%, an <inline-formula> <tex-math>${R}^{{2}}$ </tex-math></inline-formula> score exceeding 0.97 for concentration prediction, and an area under the curve (AUC) of 0.99 for anomaly identification. This comprehensive framework, integrating efficient data processing, noise immunity mechanisms, and real-time detection capabilities, demonstrates the remarkable potential of FT-CNN in advancing E-nose technology.","PeriodicalId":447,"journal":{"name":"IEEE Sensors Journal","volume":"25 15","pages":"28568-28575"},"PeriodicalIF":4.3,"publicationDate":"2025-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144758227","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0