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IF 3.4 3区综合性期刊

Sensors Pub Date : 2025-06-18 DOI: 10.3390/s25123808

Olga Dos Santos Duarte, Gustavo Jacinto, Mário Véstias, Rui Policarpo Duarte

引用次数: 0

LGFUNet: A Water Extraction Network in SAR Images Based on Multiscale Local Features with Global Information. LGFUNet：基于多尺度局部特征和全局信息的SAR图像水提取网络。

IF 3.4 3区综合性期刊

Sensors Pub Date : 2025-06-18 DOI: 10.3390/s25123814

Xiaowei Bai, Yonghong Zhang, Jujie Wei

{"title":"LGFUNet: A Water Extraction Network in SAR Images Based on Multiscale Local Features with Global Information.","authors":"Xiaowei Bai, Yonghong Zhang, Jujie Wei","doi":"10.3390/s25123814","DOIUrl":"https://doi.org/10.3390/s25123814","url":null,"abstract":"To address existing issues in water extraction from SAR images based on deep learning, such as confusion between mountain shadows and water bodies and difficulty in extracting complex boundary details for continuous water bodies, the LGFUNet model is proposed. The LGFUNet model consists of three parts: the encoder-decoder, the DECASPP module, and the LGFF module. In the encoder-decoder, the Swin-Transformer module is used instead of convolution kernels for feature extraction, enhancing the learning of global information and improving the model's ability to capture the spatial features of continuous water bodies. The DECASPP module is employed to extract and select multiscale features, focusing on complex water body boundary details. Additionally, a series of LGFF modules are inserted between the encoder and decoder to reduce the semantic gap between the encoder and decoder feature maps and the spatial information loss caused by the encoder's downsampling process, improving the model's ability to learn detailed information. Sentinel-1 SAR data from the Qinghai-Tibet Plateau region are selected, and the water extraction performance of the proposed LGFUNet model is compared with that of existing methods such as U-Net, Swin-UNet, and SCUNet++. The results show that the LGFUNet model achieves the best performance, respectively.","PeriodicalId":21698,"journal":{"name":"Sensors","volume":"25 12","pages":""},"PeriodicalIF":3.4,"publicationDate":"2025-06-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144508224","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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 Lightweight Multi-Scale Context Detail Network for Efficient Target Detection in Resource-Constrained Environments. 资源受限环境下高效目标检测的轻量级多尺度上下文细节网络。

IF 3.4 3区综合性期刊

Sensors Pub Date : 2025-06-18 DOI: 10.3390/s25123800

Kaipeng Wang, Guanglin He, Xinmin Li

{"title":"A Lightweight Multi-Scale Context Detail Network for Efficient Target Detection in Resource-Constrained Environments.","authors":"Kaipeng Wang, Guanglin He, Xinmin Li","doi":"10.3390/s25123800","DOIUrl":"https://doi.org/10.3390/s25123800","url":null,"abstract":"Target detection in resource-constrained environments faces multiple challenges such as the use of camouflage, diverse target sizes, and harsh environmental conditions. Moreover, the need for solutions suitable for edge computing environments, which have limited computational resources, adds complexity to the task. To meet these challenges, we propose MSCDNet (Multi-Scale Context Detail Network), an innovative and lightweight architecture designed specifically for efficient target detection in such environments. MSCDNet integrates three key components: the Multi-Scale Fusion Module, which improves the representation of features at various target scales; the Context Merge Module, which enables adaptive feature integration across scales to handle a wide range of target conditions; and the Detail Enhance Module, which emphasizes preserving crucial edge and texture details for detecting camouflaged targets. Extensive evaluations highlight the effectiveness of MSCDNet, which achieves 40.1% mAP50-95, 86.1% precision, and 68.1% recall while maintaining a low computational load with only 2.22 M parameters and 6.0 G FLOPs. When compared to other models, MSCDNet outperforms YOLO-family variants by 1.9% in mAP50-95 and uses 14% fewer parameters. Additional generalization tests on VisDrone2019 and BDD100K further validate its robustness, with improvements of 1.1% in mAP50 on VisDrone and 1.2% in mAP50-95 on BDD100K over baseline models. These results affirm that MSCDNet is well suited for tactical deployment in scenarios with limited computational resources, where reliable target detection is paramount.","PeriodicalId":21698,"journal":{"name":"Sensors","volume":"25 12","pages":""},"PeriodicalIF":3.4,"publicationDate":"2025-06-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144508103","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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

An Iterative Error Correction Procedure for Single Sheet Testers Using FEM 3D Model. 基于有限元三维模型的单片试验机迭代误差修正方法。

IF 3.4 3区综合性期刊

Sensors Pub Date : 2025-06-18 DOI: 10.3390/s25123813

Robert Krobot, Martin Dadić

引用次数: 0

Benchmarking Accelerometer and CNN-Based Vision Systems for Sleep Posture Classification in Healthcare Applications. 基准加速计和基于cnn的视觉系统在医疗保健应用中的睡眠姿势分类。

IF 3.4 3区综合性期刊

Sensors Pub Date : 2025-06-18 DOI: 10.3390/s25123816

Minh Long Hoang, Guido Matrella, Dalila Giannetto, Paolo Craparo, Paolo Ciampolini

{"title":"Benchmarking Accelerometer and CNN-Based Vision Systems for Sleep Posture Classification in Healthcare Applications.","authors":"Minh Long Hoang, Guido Matrella, Dalila Giannetto, Paolo Craparo, Paolo Ciampolini","doi":"10.3390/s25123816","DOIUrl":"https://doi.org/10.3390/s25123816","url":null,"abstract":"Sleep position recognition plays a crucial role in diagnosing and managing various health conditions, such as sleep apnea, pressure ulcers, and musculoskeletal disorders. Accurate monitoring of body posture during sleep can provide valuable insights for clinicians and support the development of intelligent healthcare systems. This research presents a comparative analysis of sleep position recognition using two distinct approaches: image-based deep learning and accelerometer-based classification. There are five classes: prone, supine, right side, left side, and wake up. For the image-based method, the Visual Geometry Group 16 (VGG16) convolutional neural network was fine-tuned with data augmentation strategies including rotation, reflection, scaling, and translation to enhance model generalization. The image-based model achieved an overall accuracy of 93.49%, with perfect precision and recall for \"right side\" and \"wakeup\" positions, but slightly lower performance for \"left side\" and \"supine\" classes. In contrast, the accelerometer-based method employed a feedforward neural network trained on features extracted from segmented accelerometer data, such as signal sum, standard deviation, maximum, and spike count. This method yielded superior performance, reaching an accuracy exceeding 99.8% across most sleep positions. The \"wake up\" position was particularly easy to detect due to the absence of body movements such as heartbeat or respiration when the person is no longer in bed. The results demonstrate that while image-based models are effective, accelerometer-based classification offers higher precision and robustness, particularly in real-time and privacy-sensitive scenarios. Further comparisons of the system characteristics, data size, and training time are also carried out to offer crucial insights for selecting the appropriate technology in clinical, in-home, or embedded healthcare monitoring applications.","PeriodicalId":21698,"journal":{"name":"Sensors","volume":"25 12","pages":""},"PeriodicalIF":3.4,"publicationDate":"2025-06-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144508136","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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

Wearable Spine Tracker vs. Video-Based Pose Estimation for Human Activity Recognition. 可穿戴脊柱跟踪器与基于视频的人体活动识别姿势估计。

IF 3.4 3区综合性期刊

Sensors Pub Date : 2025-06-18 DOI: 10.3390/s25123806

Jonas Walkling, Luca Sander, Arwed Masch, Thomas M Deserno

引用次数: 0

Decentralized Communication-Free Controller for Synchronous Solar-Powered Water Pumping with Emulated Neighbor Sensing. 具有模拟邻居感知的太阳能同步水泵分散无通信控制器。

IF 3.4 3区综合性期刊

Sensors Pub Date : 2025-06-18 DOI: 10.3390/s25123811

Roungsan Chaisricharoen, Wanus Srimaharaj, Punnarumol Temdee, Hamed Yahoui, Nina Bencheva

{"title":"Decentralized Communication-Free Controller for Synchronous Solar-Powered Water Pumping with Emulated Neighbor Sensing.","authors":"Roungsan Chaisricharoen, Wanus Srimaharaj, Punnarumol Temdee, Hamed Yahoui, Nina Bencheva","doi":"10.3390/s25123811","DOIUrl":"https://doi.org/10.3390/s25123811","url":null,"abstract":"Solar-powered pumping systems using series pumps are commonly applied in the delivery of water to remote agricultural regions, particularly in hilly tropical terrain. The synchronization of these pumps typically depends on reliable communication; however, dense vegetation, elevation changes, and weather conditions often disrupt signals. To address these limitations, a fully decentralized, communication-free control system is proposed. Each pumping station operates independently while maintaining synchronized operation through emulated neighbor sensing. The system applies a discrete-time control algorithm with virtual sensing that estimates neighboring pump statuses. Each station consists of a solar photovoltaic (PV) array, variable-speed drive, variable inlet valve, reserve tank, and local control unit. The controller adjusts the valve positions and pump power based on real-time water level measurements and virtual neighbor sensing. The simulation results across four scenarios, including clear sky, cloudy conditions, temporary outage, and varied irradiance, demonstrated steady-state operation with no water overflow or shortage and a steady-state error less than 4% for 3 m3 transfer. The error decreased as the average power increased. The proposed method maintained system functionality under simulated power outage and variable irradiance, confirming its suitability for remote agricultural areas where communication infrastructure is limited.","PeriodicalId":21698,"journal":{"name":"Sensors","volume":"25 12","pages":""},"PeriodicalIF":3.4,"publicationDate":"2025-06-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144508091","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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

Vega: LLM-Driven Intelligent Chatbot Platform for Internet of Things Control and Development. Vega：面向物联网控制与开发的llm驱动智能聊天机器人平台。

IF 3.4 3区综合性期刊

Sensors Pub Date : 2025-06-18 DOI: 10.3390/s25123809

Harith Al-Safi, Harith Ibrahim, Paul Steenson

{"title":"Vega: LLM-Driven Intelligent Chatbot Platform for Internet of Things Control and Development.","authors":"Harith Al-Safi, Harith Ibrahim, Paul Steenson","doi":"10.3390/s25123809","DOIUrl":"https://doi.org/10.3390/s25123809","url":null,"abstract":"Large language models (LLMs) have revolutionized natural language processing (NLP), yet their potential in Internet of Things (IoT) and embedded systems (ESys) applications remains largely unexplored. Traditional IoT interfaces often require specialized knowledge, creating barriers for non-technical users. We present Vega, a modular system that leverages LLMs to enable intuitive, natural language control and interrogation of IoT devices, specifically, a Raspberry Pi (RPi) connected to various sensors, actuators, and devices. Our solution comprises three key components: a physical circuit with input and output devices used to showcase the LLM's ability to interact with hardware, an RPi integrating a control server, and a web application integrating LLM logic. Users interact with the system through natural language, which the LLM interprets to remotely call appropriate commands for the RPi. The RPi executes these instructions on the physically connected circuit, with outcomes communicated back to the user via LLM-generated responses. The system's performance is empirically evaluated using a range of task complexities and user scenarios, demonstrating its ability to handle complex and conditional logic without additional coding on the RPi, reducing the need for extensive programming on IoT devices. We showcase the system's real-world applicability through physical circuit implementation while providing insights into its limitations and potential scalability. Our findings reveal that LLM-driven IoT control can effectively bridge the gap between complex device functionality and user-friendly interaction, and also opens new avenues for creative and intelligent IoT applications. This research offers insights into the design and implementation of LLM-integrated IoT interfaces.","PeriodicalId":21698,"journal":{"name":"Sensors","volume":"25 12","pages":""},"PeriodicalIF":3.4,"publicationDate":"2025-06-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144508337","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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

Aging Effects on a Driver Position Sensor Integrated into a Woven Fabric. 机织物中集成驱动位置传感器的老化效应。

IF 3.4 3区综合性期刊

Sensors Pub Date : 2025-06-18 DOI: 10.3390/s25123797

Marc Martínez-Estrada, Ignacio Gil, Raúl Fernández-García

{"title":"Aging Effects on a Driver Position Sensor Integrated into a Woven Fabric.","authors":"Marc Martínez-Estrada, Ignacio Gil, Raúl Fernández-García","doi":"10.3390/s25123797","DOIUrl":"https://doi.org/10.3390/s25123797","url":null,"abstract":"A textile woven presence sensor was previously presented to demonstrate its functionality in eliminating some false positives on car seat presence sensors. After studying the functionality, the next characteristic that the textile sensor should demonstrate is its reliability. The woven sensor was prepared to be tested against ageing. The ageing cycle was prepared according to the UNE-EN ISO 17228:2015 standard. Nine woven sensors are prepared, seven of them face the aging test, and two are selected as reference sensors. The characterization of the woven sensor has been carried out through a microcontroller measurement circuit that obtains the cycles to charge the sensor. Comparison of the results obtained shows that the effects of ageing are negligible. The behavior of the aged sensors is similar to that of the reference sensors, indicating that the variations in the values of both aged and reference sensors are provoked by the environmental conditions during the measurements. To support this argument, a statistical study based on a t-Student analysis was carried out. After 4 ageing cycles, the functionality of the sensors remains unaffected. This research proves the reliability of the woven textile sensor, which encourages its use in automotive applications.","PeriodicalId":21698,"journal":{"name":"Sensors","volume":"25 12","pages":""},"PeriodicalIF":3.4,"publicationDate":"2025-06-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144508083","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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 Segmented Low-Order Bistable Stochastic Resonance Method for Fixed-Distance Target Detection in Millimeter-Wave Fuze Under Rainy Conditions. 雨天条件下毫米波引信定距目标检测的分段低阶双稳随机共振方法。

IF 3.4 3区综合性期刊

Sensors Pub Date : 2025-06-18 DOI: 10.3390/s25123801

Bing Yang, Kaiwei Wu, Zhe Guo, Yanbin Liang, Shijun Hao, Zhonghua Huang

{"title":"A Segmented Low-Order Bistable Stochastic Resonance Method for Fixed-Distance Target Detection in Millimeter-Wave Fuze Under Rainy Conditions.","authors":"Bing Yang, Kaiwei Wu, Zhe Guo, Yanbin Liang, Shijun Hao, Zhonghua Huang","doi":"10.3390/s25123801","DOIUrl":"https://doi.org/10.3390/s25123801","url":null,"abstract":"Millimeter-wave (MMW) fuze signals experience significant degradation in rainy environments due to combined raindrop-induced attenuation and scattering effects, substantially reducing echo signal-to-noise ratio (SNR) and critically impacting ranging accuracy. To address these limitations while satisfying real-time processing requirements, this study proposes (1) a novel segmented low-order bistable stochastic resonance (SLOBSR) system based on piecewise polynomial potential functions and (2) a corresponding fixed-distance target detection algorithm incorporating signal pre-processing, particle swarm optimization (PSO)-based parameter optimization, and kurtosis threshold detection. Experimental results demonstrate the system's effectiveness in achieving a 9.94 dB SNR enhancement for MMW fuze echoes under rainy conditions, enabling reliable target detection at SNRs as low as -15 dB. Comparative analysis confirms the SLOBSR method's superior performance over conventional approaches in terms of both SNR enhancement and computational efficiency. The proposed method significantly enhances the anti-rainfall interference capability of the MMW fuze.","PeriodicalId":21698,"journal":{"name":"Sensors","volume":"25 12","pages":""},"PeriodicalIF":3.4,"publicationDate":"2025-06-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144508133","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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