{"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":"Plasmon-Induced Transparency-Based Metamaterial Sensor for Highly Sensitive Glucose Detection","authors":"Youpeng Yang;Xiaoran Wang;Shuting Fan;Zhengfang Qian","doi":"10.1109/JSEN.2025.3563210","DOIUrl":"https://doi.org/10.1109/JSEN.2025.3563210","url":null,"abstract":"In this work, we propose a metamaterial based on plasmon-induced transparency (PIT) for the detection of glucose solutions. The unit cell structure of this metamaterial comprises two rectangular strips and a pair of “arch-bridge” shaped structures fabricated on a silicon dioxide surface. Simulation results indicate that the biosensor exhibits two resonance frequencies at 1.71 and 2.30 THz, respectively, with a sensitivity of 471.43 GHz/RIU (refractive index unit) at the higher frequency resonance. The sensor fabrication is accomplished through photolithography and its performance is validated with a commercial terahertz time-domain spectrometer (THz-TDS). Glucose solutions of five different concentrations are prepared for testing. Experimental results demonstrate that at the higher frequency resonance, the sensor exhibits a sensitivity of 6.63 GHz/(mmol/L) and a limit of detection (LOD) of 0.0890 mmol/L. This indicates the sensor’s high sensitivity to glucose solutions. Hence, this study presents a potential alternative for glucose detection, with implications for early diabetes monitoring.","PeriodicalId":447,"journal":{"name":"IEEE Sensors Journal","volume":"25 12","pages":"21481-21487"},"PeriodicalIF":4.3,"publicationDate":"2025-04-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144299287","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":"Surface Reconstruction of Trace N, C Co-Doped Co₃O₄ for Fast Detection of Formaldehyde","authors":"Hongda Zhang;Liang Zhao;Yunpeng Xing;Chengchao Yu;Sihao Zhi;Teng Fei;Sen Liu;Haiyan Zhang;Tong Zhang","doi":"10.1109/JSEN.2025.3563244","DOIUrl":"https://doi.org/10.1109/JSEN.2025.3563244","url":null,"abstract":"Formaldehyde (HCHO) is a common volatile organic compound (VOC) in indoor environments, causing significant health hazards and even leading to serious diseases. Therefore, real-time monitoring HCHO is essential. The Co3O4-based chemiresistive gas sensors are promising candidates for monitoring HCHO. However, it is challenging to construct Co3O4-based HCHO sensors with fast response property. In this work, a surface reconstruction strategy was proposed to prepare novel Co3O4-based sensing materials. First, trace N, C co-doped Co3O4 (NC-Co3O4) was synthesized by pyrolysis of ZIF-67 in Ar atmosphere at <inline-formula> <tex-math>$700~^{circ }$ </tex-math></inline-formula>C. Then, the surface of NC-Co3O4 was subsequently reconstructed by H2SO4 etching, leading to forming the stable surfaces with low concentration of oxygen vacancy and Co<inline-formula> <tex-math>${}^{{2}+}$ </tex-math></inline-formula> ions (NC-Co3O4-E80). The gas sensing experiments demonstrate that the optimal NC-Co3O4-E80 exhibits enhanced performance to HCHO detection, including the response value of 103.8% (42.1% for NC-Co3O4) to 100 ppm HCHO at <inline-formula> <tex-math>$140~^{circ }$ </tex-math></inline-formula>C, short response time of 3 s (62 s for NC-Co3O4), short recovery time of 10 s (53 s for NC-Co3O4), and excellent cycle repeatability. This trait can play a significant role in fabricating HCHO sensors for real-time detection.","PeriodicalId":447,"journal":{"name":"IEEE Sensors Journal","volume":"25 12","pages":"21127-21133"},"PeriodicalIF":4.3,"publicationDate":"2025-04-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144308487","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}
Shouqiang Kang;Chuanjin Han;Benkuan Wang;Yuan Wang;Datong Liu
{"title":"Similarity Augmented Incremental Learning-Based Flight Data Anomaly Detection Method for UAV Dynamic Conditions","authors":"Shouqiang Kang;Chuanjin Han;Benkuan Wang;Yuan Wang;Datong Liu","doi":"10.1109/JSEN.2025.3562935","DOIUrl":"https://doi.org/10.1109/JSEN.2025.3562935","url":null,"abstract":"In response to the high accident rate associated with large-scale unmanned aerial vehicle (UAV) deployment, the prediction-based anomaly detection method has emerged as an important research field. This method uses airborne sensor data to predict the expected operational status of UAVs to determine whether their actual status deviates from normal. When the anomaly detection model is exposed to diverse flight conditions and missions, continuously changing sensor data characteristics may, however, lead to model mismatch, resulting in reduced detection accuracy (ACC). This article, therefore, proposes a similarity augmented incremental learning-based flight data anomaly detection method for UAV dynamic conditions. The core goal of this method is to maintain the ACC of anomaly detection in new conditions while preventing issues related to model mismatch. First, an long short-term memory (LSTM)-based anomaly detection model and the feature buffer are established using historical sensor data. The feature buffer is used to update the detection model when new operating conditions arise. Second, a Jensen-Shannon divergence (JS divergence)-based similarity measurement is proposed to monitor changes in the distribution of sensor data and identify whether new operating conditions that differ significantly from historical data occur. Finally, a similarity augmented replay-based incremental learning mechanism is designed for model updates when new operating conditions are detected. During the model update process, similarity measurements are employed to augment the replay-based update strategy, thereby improving the adaptability of the model. Experiments with simulated and real airborne sensor data demonstrate that the proposed method improves anomaly detection ACC, increasing ACC by 0.6%–1.8% and reducing false positive rate (FPR) by 16.5%–95.2%.","PeriodicalId":447,"journal":{"name":"IEEE Sensors Journal","volume":"25 12","pages":"22015-22029"},"PeriodicalIF":4.3,"publicationDate":"2025-04-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144299188","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":"A Wireless, Scalable, and Modular EEG Sensor Network Platform for Unobtrusive Brain Recordings","authors":"Ruochen Ding;Charles Hovine;Piet Callemeyn;Michael Kraft;Alexander Bertrand","doi":"10.1109/JSEN.2025.3562791","DOIUrl":"https://doi.org/10.1109/JSEN.2025.3562791","url":null,"abstract":"This article introduces a modular sensing platform for wearable electroencephalography (EEG) recordings. The platform is conceived as a wireless EEG sensor network (WESN), consisting of multiple miniaturized, wireless EEG sensor nodes that synchronously collect EEG data from different scalp locations. As there are no wires between the different sensors, the platform provides maximal flexibility and discreetness, combined with a reduced sensitivity to motion artifacts or electromagnetic interference. By removing the driven right leg (DRL) electrode and reducing the within node electrode spacing to 3 cm, we obtain a compact design while maintaining a high signal integrity. The WESN system was validated through a series of experiments: achieving synchronization of EEG data transmission across multiple sensor nodes and the detection of actual neural responses in EEG experiments. These results demonstrate the effectiveness and robustness of the proposed WESN platform, establishing it as a promising research platform for scalable, flexible, and discreet multichannel EEG monitoring in ambulatory settings.","PeriodicalId":447,"journal":{"name":"IEEE Sensors Journal","volume":"25 12","pages":"22580-22590"},"PeriodicalIF":4.3,"publicationDate":"2025-04-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144299128","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}
Wanying Huang;Chunxi Zhang;Lailiang Song;Wei Zhang;Zhifang Zhu;Longjun Ran
{"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}
Chuanhao Wei;Qiang Liu;Dongdong Lin;Dan Zhu;Jingzhan Shi;Yiping Wang
{"title":"High-Precision Cross-Sensitivity Mitigation Using CNN-BiLSTM for Multiparameter Optical Sensing","authors":"Chuanhao Wei;Qiang Liu;Dongdong Lin;Dan Zhu;Jingzhan Shi;Yiping Wang","doi":"10.1109/JSEN.2025.3562605","DOIUrl":"https://doi.org/10.1109/JSEN.2025.3562605","url":null,"abstract":"Crosstalk decoupling of multiparameters based on fiber optic sensors is crucial for high-precision detection in complex environments. The traditional sensitivity matrix method (SMM) extracts different parameters through the linear relationship between the spectral eigenvalue drift and the physical quantity to be measured. However, this scheme requires that the sensitivity responses of the different parameters be linear. To address the significant errors caused by nonlinear sensitivity in SMM, the combination of convolutional neural network and bidirectional long short-term memory (CNN-BiLSTM) model was proposed in this work. The information containing the full spectrum rather than only the peak wavelength is utilized to establish the relationship with temperature and strain. Especially when the sensitivity is nonlinear, the parameters can also be extracted accurately. Experimental results show that the deep learning-assisted approach improves the root mean square error (RMSE) of temperature and strain measurements by 9 and 44 times, respectively, compared to the SMM. This CNN-BiLSTM-based interrogation scheme may offer a novel approach to multiparameter demodulation for various sensors, significantly enhancing performance.","PeriodicalId":447,"journal":{"name":"IEEE Sensors Journal","volume":"25 12","pages":"21600-21607"},"PeriodicalIF":4.3,"publicationDate":"2025-04-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144299364","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}
Annatoma Arif;Alexis J. Acevedo-González;Carlos R. Cabrera;Robert C. Roberts
{"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}