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{"title":"LSReg-Net: An End-to-End Registration Network for Large-Scale LiDAR Point Cloud in Autonomous Driving","authors":"Yucheng Tao;Xiuqing Yang;Hanqi Wang;Jian Wang;Zhiyuan Li;Huawei Liang","doi":"10.1109/JSEN.2025.3562916","DOIUrl":"https://doi.org/10.1109/JSEN.2025.3562916","url":null,"abstract":"Large-scale point cloud registration is a fundamental problem for autonomous driving. To achieve alignment, most existing methods focus on local point cloud features for matching. However, these approaches fail to account for the sparse distribution of features in large-scale driving scenarios, limiting their effectiveness. This article introduces an end-to-end registration network, named LSReg-Net, specifically designed to address this challenge, offering a more reliable solution for large-scale LiDAR point cloud. The LSReg-Net performs registration by following sequential modules. First, this study develops a sampling strategy, distance-weighted farthest point sampling (DW-FPS), which effectively enhances sparse feature robustness. Then, a scale attention fusion (SAF) network is proposed to capture both local and geometric features. By considering both spatial sparsity and geometric context of the keypoints, the LSReg-Net obtains accurate correspondences after matching. Finally, a coarse-to-fine registration module is conducted with multilevel correspondences to acquire a precise rigid transformation. Extensive experiments on two large-scale LiDAR datasets demonstrate that the proposed approach outperforms existing registration methods. In addition, real-world experiments based on an experimental platform further validate the high efficiency.","PeriodicalId":447,"journal":{"name":"IEEE Sensors Journal","volume":"25 11","pages":"20675-20686"},"PeriodicalIF":4.3,"publicationDate":"2025-04-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144205946","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}

{"title":"The Digital-Twin Modeling Method and Cross-Coupling Mechanism of Quartz Flexible Accelerometer","authors":"Wanying Huang;Chunxi Zhang;Lailiang Song;Wei Zhang;Zhifang Zhu;Longjun Ran","doi":"10.1109/JSEN.2025.3550722","DOIUrl":"https://doi.org/10.1109/JSEN.2025.3550722","url":null,"abstract":"Quartz flexible accelerometers (QFAs) are widely applied in navigation systems. Although mechanical excitation is known to degrade the QFA performance and lower the positioning accuracy of the system, the mechanism underlying the dynamic performance deterioration remains obscure. Considering the etching process and assembly deviation, this article theoretically derives a pendulum cross-coupling mechanism and quantifies the transfer process of the structural error in the beams. The physical process of QFA is represented by a motion model, electrostatic and electromagnetic field models, and a signal transmission model. The QFA was analyzed through a digital-twin modeling approach incorporating finite element modeling and numerical analysis. The digital-twin model verified the error-transfer process of the beam structure and vibration experiments confirmed the specific effects of cross coupling. This article quantifies the dynamic accuracy degradation caused by interior errors in the QFA, providing guidance for optimizing the structure and assembly process of QFAs and promoting their environmental adaptability.","PeriodicalId":447,"journal":{"name":"IEEE Sensors Journal","volume":"25 9","pages":"14799-14809"},"PeriodicalIF":4.3,"publicationDate":"2025-04-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143898365","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}

{"title":"Thickness Measurement of Single-Mode Fiber Coating Layer Based on Forward Brillouin Scattering","authors":"Yongqi Zhang;Tao Wang;Yijia Liu;Li Liu;Mingjiang Zhang","doi":"10.1109/JSEN.2025.3562572","DOIUrl":"https://doi.org/10.1109/JSEN.2025.3562572","url":null,"abstract":"The coating layer is essential for protecting and applying optical fibers. Nowadays, the thickness measurement of the coating layer relies on point measurement schemes, such as the side-looking light distribution method and mechanical method. However, there are some problems with the above methods, such as the tradeoff between resolution and field of view (FOV), the cutting of the measurement position, and the long measurement time. To overcome these problems, we propose a new method based on forward Brillouin scattering (FBS), which measures the coating layer thickness of single mode fibers (SMFs). The physical properties of the transverse acoustic field involved in FBS make it possible to measure the thickness of the fiber coating. The corresponding relationship between the transverse acoustic mode frequency and the diameter of the coating layer can be calculated. The coating layer thickness can be measured with high precision by measuring the frequency spectrum of FBS corresponding to multiple transverse acoustic modes at a given temperature. In the verification experiment, three types of SMF coated with polyimide are used as the sensing fiber to measure the thickness of the coating layer at multiple temperatures. The experimental results show that the error in the coating layer thickness obtained is less than <inline-formula> <tex-math>$0.05~mu $ </tex-math></inline-formula>m. To the best of our knowledge, this is the first demonstration of nondestructive, high-precision monitoring of fiber coating thickness.","PeriodicalId":447,"journal":{"name":"IEEE Sensors Journal","volume":"25 11","pages":"19332-19340"},"PeriodicalIF":4.3,"publicationDate":"2025-04-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144196644","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}

{"title":"Bismuth Functionalized Inkjet-Printed Electrochemical Sensor for Aqueous Lead (II) Detection","authors":"Annatoma Arif;Alexis J. Acevedo-González;Carlos R. Cabrera;Robert C. Roberts","doi":"10.1109/JSEN.2025.3562804","DOIUrl":"https://doi.org/10.1109/JSEN.2025.3562804","url":null,"abstract":"This article introduces a sensitive, selective, and reusable 3-D bismuth functionalized inkjet-printed shape memory polymer (SMP) incorporated electrochemical sensor (ECS) for detecting lead (II) in aqueous solution, that is, deionized water, tap water, and river water. The reported ECS comprises a bismuth deposited working electrode (WE), a gold (Au) counter electrode, and a silver chloride (AgCl) reference electrode. Bismuth functionalization was performed through two approaches on the inkjet-printed Au-plated (thickness –<inline-formula> <tex-math>$8.24~mu $ </tex-math></inline-formula>m ±1.42) electrodes: ex situ, involving a full cycle of cyclic voltammetry (CV) process to deposit bismuth –<inline-formula> <tex-math>$400~mu $ </tex-math></inline-formula>g/L bismuth, and in situ, where CV or square wave anodic stripping voltammetry were performed with a lead (II) contaminated aqueous solution diluted with <inline-formula> <tex-math>$200~mu $ </tex-math></inline-formula>g/L bismuth. The limit of detection (LOD) for the bismuth functionalized inkjet-printed ECSs are <inline-formula> <tex-math>$0.64~mu $ </tex-math></inline-formula>g/dL (ex situ) for the bismuth deposited WE (<inline-formula> <tex-math>$13.92Omega $ </tex-math></inline-formula>.<inline-formula> <tex-math>$Box ~pm ~1.96$ </tex-math></inline-formula>) and <inline-formula> <tex-math>$1.09~mu $ </tex-math></inline-formula>g/dL (in situ) for the Au WE (<inline-formula> <tex-math>$4.4Omega $ </tex-math></inline-formula>.<inline-formula> <tex-math>$Box ~pm ~0.3$ </tex-math></inline-formula>). The sensor, designed for miniaturization, exhibits enhanced performance in electrochemical sensing due to its increased effective electrode surface area (EESA) (7.25 mm<inline-formula> <tex-math>${}^{{2}}~pm ~0.15$ </tex-math></inline-formula>) despite a reduced lateral surface area (4.19 mm2). An optimized cleaning process and a mathematical model representing the relationship between printed and electrical areas of the inkjet-printed electrodes are presented thoroughly to provide flexibility and certainty of designing different electrochemical and biosensors. Conclusively, the design, fabrication, bismuth functionalization, characterization, and optimization encompassing sensitivity, selectivity, reproducibility, reusability, and cost-assessment of the bismuth functionalized inkjet-printed ECS for aqueous lead (II) detection are delineated in this article in detail.","PeriodicalId":447,"journal":{"name":"IEEE Sensors Journal","volume":"25 11","pages":"18574-18583"},"PeriodicalIF":4.3,"publicationDate":"2025-04-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10977756","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144196699","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Temperature Distribution Sensor for Real-Time Monitoring of Thermal Interface Material","authors":"Sunbin Hwang;Junya Kurumida","doi":"10.1109/JSEN.2025.3562841","DOIUrl":"https://doi.org/10.1109/JSEN.2025.3562841","url":null,"abstract":"Effective thermal management is crucial for state-of-the-art semiconductor devices as power consumption continues to rise. A key challenge lies in enhancing the performance of thermal interface materials (TIMs), which contribute the highest thermal resistance in heat dissipation pathways. This study proposes a contact-type, 2-D thin-film temperature distribution sensor design for real-time TIM performance monitoring. Its thin-film configuration enables direct implementation into TIM layers or heat sink structures, ensuring compatibility with typical cooling solutions. The sensor was designed to integrate thermocouples (TCs) and metal-oxide–semiconductor field-effect transistors (MOSFETs) in a cross-point-switching circuit configuration. This configuration minimizes wiring complexity, which is advantageous for high-speed data acquisition, suppresses leakage currents, and maintains the linearity of thermoelectric voltage outputs. Considering the sensor manufacturing process, materials with high thermal conductivity were tested to achieve compatibility with both effective heat dissipation design and temperature sensing capability. To validate the feasibility and effectiveness of the proposed design, equivalent circuit simulations were performed, and finite element method (FEM)-based approaches were also adopted to analyze electrical, thermal, and structural properties. The simulation results demonstrated the potential of this sensor design to effectively detect thermal conduction losses caused by contact failure, aging, and void formation within TIM layers. As semiconductor technology advances, this sensor will play a crucial role in improving thermal management by providing precise, real-time evaluations of TIM performance, enabling predictive maintenance, and optimizing next-generation heat dissipation designs.","PeriodicalId":447,"journal":{"name":"IEEE Sensors Journal","volume":"25 11","pages":"19497-19505"},"PeriodicalIF":4.3,"publicationDate":"2025-04-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144196759","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}

{"title":"An Additively Manufactured Novel RFID-Based 3-D Printed Leaf Moisture Sensor for Smart Farming","authors":"Srabana Maiti;Md Mirazur Rahman;Shuvashis Dey","doi":"10.1109/JSEN.2025.3562607","DOIUrl":"https://doi.org/10.1109/JSEN.2025.3562607","url":null,"abstract":"This work presents the design, analysis, and experimental validation of a novel chip-based 3-D printed ultra-high frequency (UHF) radio frequency identification (RFID) sensor designed for leaf moisture detection for smart farming applications. The presented sensor is designed to operate at a frequency of 915 MHz and utilizes an integrated circuit (IC) chip having a specified impedance of <inline-formula> <tex-math>$18.06- {j} 164~Omega $ </tex-math></inline-formula> at 915 MHz. The proposed sensor is fabricated by the state-of-the-art Nano Dimension DragonFly IV 3-D printer. The 3-D printer uses both dielectric and conductive inks in a single printer for producing additive manufactured electronics (AME). The performance of the sensor is validated by experiments conducted on Valley Oak, Japanese tree lilac, and Crabapple leaf samples. The sensor’s functionality is based on its ability to detect variations in the dielectric properties of leaves, which are caused by changes in moisture content. This is achieved by analyzing the radio frequency (RF) backscattered signal, measured in terms of the received signal strength indicator (RSSI) levels, using a standard RFID reader. Experimental results demonstrate a consistent linear relationship between RSSI levels and leaf moisture content that is used to obtain a calibration curve that can accurately determine unknown moisture levels. By integrating advanced fabrication techniques with reliable RF sensing mechanisms, this work offers a sustainable, and scalable solution for monitoring plant health and optimizing agricultural productivity.","PeriodicalId":447,"journal":{"name":"IEEE Sensors Journal","volume":"25 11","pages":"20666-20674"},"PeriodicalIF":4.3,"publicationDate":"2025-04-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144206090","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}

{"title":"Design of Transparent Nonmagnetic Electric Heating Film Based on MEMS Technology for Microalkali Metal Vapor Cell","authors":"Sitian Wu;Si Zhu;Weiqian Wang;Zhen Li;Jinguo Mu;Xiangyang Zhou","doi":"10.1109/JSEN.2025.3562578","DOIUrl":"https://doi.org/10.1109/JSEN.2025.3562578","url":null,"abstract":"Aiming to address the limitations of traditional heating films in balancing the magnetic field suppression and uniform heating in spin-exchange relaxation-free (SERF) atomic magnetometer applications, this article designs a transparent, nonmagnetic electric heating film based on the MEMS technology, in which indium tin oxide (ITO) is used as the core heating material. First, a model is developed to analyze the spatial magnetic field strength induced by current flowing in different directions through the wiring. The layout design of the heating film is then optimized through the quantitative analysis and simulation. Next, ITO, a transparent material, is selected and processed using the MEMS technology. This successfully addresses the condensation issue at the optical apertures of traditional flexible printed circuit (FPC) heating films, which is caused by uneven heating, thereby improving the heating uniformity. The final experiment validated the feasibility and effectiveness of the design. The experimental results show that the magnetic flux density of the designed heating film under dc conditions is 0.8154 nT/mA. Under the same heating conditions, the temperature variance in the vapor cell area decreased from <inline-formula> <tex-math>$0.0125~^{circ } {text {C}}^{{2}}$ </tex-math></inline-formula> for traditional heating films to <inline-formula> <tex-math>$0.0103~^{circ } {text {C}}^{{2}}$ </tex-math></inline-formula>, with a particularly significant temperature increase observed in the optical aperture region. Experimental data confirm that the MEMS-based transparent heating film developed in this study demonstrates significant advantages in both magnetic field suppression and heating uniformity.","PeriodicalId":447,"journal":{"name":"IEEE Sensors Journal","volume":"25 11","pages":"18962-18970"},"PeriodicalIF":4.3,"publicationDate":"2025-04-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144205806","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}

{"title":"mmWave Radar-Based Noninvasive Vehicle Occupancy Detection With Insights From Vision, RF, and Physical Sensors: A Review","authors":"Jawad Yousaf;Alyssa Palmer;Maitha Shams;Zayna Wasma;Montasir Qasymeh;Taimur Hassan;Deepak Arora;Mohammed Ghazal","doi":"10.1109/JSEN.2025.3562685","DOIUrl":"https://doi.org/10.1109/JSEN.2025.3562685","url":null,"abstract":"The potential uses of human occupancy detection (HOD) in vehicles are crucial for handling resources, passenger safety, and privacy-preserving technology. In this study, the usage of various sensor systems for noninvasive vehicle occupant detection is examined, including millimeter-wave (mmWave) radar, vision-based, and physical sensors. These technologies undergo a thorough review analysis that looks at methods, performance indicators, and use cases before being assessed for robustness, accuracy, real-time capabilities, scalability, and cost-effectiveness. The impact of clutter, scalability, and privacy in car interiors on HOD is also thoroughly discussed. Based on its ability to balance cost, accuracy, and adaptability, frequency-modulated continuous-wave (FMCW) radar is termed the best option for vehicle occupant identification. The study discussed the possible challenges and future direction, as well as provided research opportunities in hybrid sensing systems and advanced machine learning integration to overcome existing constraints.","PeriodicalId":447,"journal":{"name":"IEEE Sensors Journal","volume":"25 11","pages":"18643-18661"},"PeriodicalIF":4.3,"publicationDate":"2025-04-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144196945","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}

{"title":"Physically Enriched Product Adaptive Deep Networks for Industrial Metal Detection","authors":"Suhrid Das;Ankit Tyagi;Vishal Monga","doi":"10.1109/JSEN.2025.3562705","DOIUrl":"https://doi.org/10.1109/JSEN.2025.3562705","url":null,"abstract":"This study addresses a longstanding metal-detection problem (classifying a product as clean or contaminated) using two-frequency electromagnetic fields by analyzing complex temporal data. Traditional contamination detection methods rely on analyzing permittivity and conductivity signals obtained when products pass through the detector’s electromagnetic field. While reliable, these methods struggle with product effect—a phenomenon where conductive product signals overshadow contaminant signals, leading to false negatives. Advances in deep learning (DL) have enhanced detection accuracy but often require large training datasets, which are impractical in many industrial metal detection scenarios where the cost of data acquisition is high. To address these challenges, we propose physically enriched DL architectures that integrate domain knowledge with state-of-the-art feature extraction models. Our contribution centers on two key innovations: adaptive models capable of countering product effect and improving contamination detection accuracy compared to both traditional signal processing and machine learning (ML) methods, and second, an enhanced ability to classify contaminant (metal) type, enabled by a data preprocessing module that we call learnable denoisers. Extensive experiments on challenging real-world data demonstrate that our product adaptation modules and a newly designed training strategy that extracts pure metal signatures from contaminated products enable scalable performance across diverse products. The proposed models successfully mitigate both false positives and negatives (missed metal detection) breaking a stiff tradeoff. Further, the benefits of our approach are most pronounced when training data are limited indicating superior generalizability.","PeriodicalId":447,"journal":{"name":"IEEE Sensors Journal","volume":"25 11","pages":"20124-20135"},"PeriodicalIF":4.3,"publicationDate":"2025-04-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144206127","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}

{"title":"Influence of Operating Air Pressure on the Frequency Shift of an Electrostatic MEMS Micromirror: Theoretical Modeling and Experimental Investigation","authors":"Anjie Peng;Dayong Qiao;Zhen Chen;Changfeng Xia;Xiumin Song","doi":"10.1109/JSEN.2025.3562334","DOIUrl":"https://doi.org/10.1109/JSEN.2025.3562334","url":null,"abstract":"This work investigates the influence and mechanism of operating air pressure on the frequency shift characteristics of an electrostatically actuated micromirror. The dependence of air damping and air additional inertia moment of the micromirror on air pressure are investigated through fluid theory and computational fluid dynamics (CFDs) simulations. The results show that the air damping and air additional inertia moment of the micromirror decrease with the decrease of air pressure. The influence of the damping, additional inertia moment, and air pressure on the frequency response shift is investigated by numerically solving the established dynamic model of the micromirror. The numerical simulation frequency responses reveal that the downward sweep jump frequency <inline-formula> <tex-math>${f} _{{1}}$ </tex-math></inline-formula> of the micromirror linearly decreases with the decrease of damping and linearly increases with the decrease of additional inertia moment. Furthermore, the numerical results also show that the downward sweep jump frequency <inline-formula> <tex-math>${f} _{{1}}$ </tex-math></inline-formula> linearly increases with the decrease of air pressure. The measured data provide good validation for the numerical results. The results demonstrate that the downward sweep jump frequency under different air pressures is primarily influenced by the inertial effect of air, while the air damping mainly affects the amplitude.","PeriodicalId":447,"journal":{"name":"IEEE Sensors Journal","volume":"25 11","pages":"19147-19158"},"PeriodicalIF":4.3,"publicationDate":"2025-04-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144206055","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}