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检索条件"任意字段=Conference on Radar Sensor Technology and Data Visualization"

共 4468 条记录，以下是41-50 订阅

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Design of an HP-RTM Flow Monitoring System Based on Embedded Capacitive sensors

Design of an HP-RTM Flow Monitoring System Based on Embedded...

引用

sensors and Information technology (ICSI), International conference on

作者： Haolong Zhang Ping'an Guo Kang Jin China Machinery Industry Technology Research Institute of Precision Forming China Academy of Machinery Beijing Research Institute of Mechanical & Electrical Technology Co. Ltd. Wuhu China

ISBN: (数字)9798331542887

ISBN: (纸本)9798331542894

This study addresses the challenge of optimizing high-pressure resin transfer molding (HP-RTM) by proposing a low-cost, high-precision embedded capacitive sensor system for monitoring resin flow. The system uses an FDC2214 capacitive-to-digital converter for signal generation and a PLC for signal acquisition, with protocol conversion enabling communication. A custom PLC program and interface allow real-time capacitance data collection and display. Resin flow into the sensor area causes measurable capacitance changes, enabling visual monitoring. An experimental setup with a transparent mold validated the system, showing minimal error between observed and measured flow front positions. This work improves HP-RTM quality control, boosts product quality and efficiency, and enhances the competitiveness of HP-RTM technology.

关键词： visualization Measurement uncertainty data acquisition Capacitance Capacitive sensors Real-time systems sensor systems Resins Transfer molding Monitoring

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Proceedings of SPIE: radar sensor technology and data visualization

Proceedings of SPIE: Radar sensor technology and data visual...

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radar sensor technology and data Visualisation

The proceedings contain 24 papers from the conference of SPIE: radar sensor technology and data visualization. Topics discussed include: use of passive radar for mapping lightning channels in a thunderstorm;high-resolution Doppler model of the human gait;modeling targets in a forest at VHF and UHF frequencies;ground penetrating radar signal processing techniques for airfield evaluations;three-dimensional reconstruction from ISAR sequences and general-purpose electronic warfare system test configuration data model.

关键词： Doppler radar

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Guiding Autonomous Vehicles in Challenging Weather Using Machine Learning Techniques

Guiding Autonomous Vehicles in Challenging Weather Using Mac...

引用

Visual Analytics and data visualization (ICVADV), International conference on

作者： S. Pavithran R. Praveenraj M.K. Vishnupriyan S. ArulMurugan Department of Information Technology K.S.Rangasamy College of Technology Tiruchengode Tamil Nadu India Department of Information Technology K.S.Rangasamy College of Technology Tiruchengode India

ISBN: (数字)9798331521394

ISBN: (纸本)9798331521400

The emergence of autonomous cars has transformed transport, providing enhanced safety, efficiency, and convenience. Yet, it is still difficult to incorporate these cars into regular traffic, especially under unfavorable weather conditions like rain, snow, fog, and storms, which greatly affect the performance of their perception and sensing systems. This paper surveys the current state of machine learning, sensor fusion, and intelligent transportation systems (ITS) to improve autonomous vehicle operation in adverse environments. Different methodologies such as Support Vector Machines (SVM), Deep Neural Networks (DNN), and Convolutional Neural Networks (CNN) are analyzed for their efficiency in traffic congestion forecasting and vehicular control. In addition to this, RSUs' use in traffic observation, smart cloud-based transport infrastructure, and automobile location tracking are examined. Outcomes show that sophisticated machine learning algorithms and sensor fusion are both effective in the reduction of negative impacts of unfavorable weather on the navigation of self-driving cars. This review highlights the importance of additional research in the integration of strong machine learning models and smart transportation solutions to make autonomous vehicle deployment safer and more reliable under varying environmental conditions.

关键词： Support vector machines Machine learning sensor fusion Real-time systems Safety Convolutional neural networks Automobiles Autonomous vehicles Traffic congestion Meteorology

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RADCI: A Synchronized radar-RGBT Object Detecting-Tracking dataset And A Benchmark

RADCI: A Synchronized Radar-RGBT Object Detecting-Tracking D...

引用

International conference on Acoustics, Speech, and Signal Processing (ICASSP)

作者： Heng Yu Ruiheng Zhang Haoyang Sun Zhe Cao Biwen Yang Jin Zhang Guanyu Liu Beijing Institute of Technology Beijing China

ISBN: (数字)9798350368741

ISBN: (纸本)9798350368758

High-quality perception is crucial in autonomous driving and monitoring systems, where millimeter-wave radar and infrared cameras play important roles due to their robustness and reliability under harsh conditions. Both technologies can serve as low-cost supplements to optical image detection, improving overall system robustness. However, there is currently a lack of widely applicable feature-level fusion methods and multimodal datasets to effectively integrate visible light with these two heterogeneous data types for multiple tasks. In this work, we collect a new multimodal dataset, RADCI8, which synchronizes data from a camera, an infrared camera, and a radar for target detection and tracking. The dataset includes 2D image annotations, radar RAD tensor data with distance, angle, and Doppler information, as well as target ID annotations in both data formats. In addition, to address the incomplete use of radar data in previous fusion algorithms, we propose a detection method that fuses image and radar features using feature concatenation and an attention mechanism. Our proposed algorithm achieves 51.5% AP with an IOU of 50:95 on 2D bounding box prediction, significantly improving average detection accuracy over vision-based methods and maintaining robustness even when a single sensor degrades.

关键词： Tensors radar detection Signal processing algorithms radar imaging radar tracking Cameras Prediction algorithms Robustness Doppler radar Synchronization

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Exploring Antenna Placement Configurations with a radar-based Silent Speech Interface

Exploring Antenna Placement Configurations with a Radar-base...

引用

International conference on Acoustics, Speech, and Signal Processing (ICASSP)

作者： João Menezes Martin Schütze Petr Schaffer Dirk Plettemeier Peter Birkholz Inst. of Acoustics and Speech Communication Dresden University of Technology Dresden Germany Inst. of Communication Technology Dresden University of Technology Dresden Germany

ISBN: (数字)9798350368741

ISBN: (纸本)9798350368758

Silent Speech Interfaces (SSIs) are systems developed to reconstruct speech based on non-acoustic bio-signals generated by brain, muscular or articulatory activity. A broad variety of sensing methods have been employed in SSIs, but determining a single optimal sensor configuration is generally a challenge. This work focuses on investigating sensing configurations for an on-body radar-based SSI and evaluating them based on their phoneme recognition performance. Audio and radar data were recorded synchronously by 8 native German speakers. One emitting and two receiving antennas were placed on the cheeks of each speaker in three different configurations, which were evaluated by nested cross-validated Support Vector Machines (SVMs). With these sensing configurations, higher accuracies than in previous works with on-body radar-based SSIs were achieved for individual speakers and for a multi-speaker evaluation. This work succeeds to produce an antenna placement guideline for future recordings with similar SSIs.

关键词： Support vector machines Receiving antennas Speech recognition radar radar antennas Acoustics sensors Recording Speech processing Guidelines

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ZigBee-Enabled Long-Range IoT-Based Monitoring and data Acquisition System for Real-Time Flow and Temperature Monitoring in Oil Pipelines with Cloud-Based data visualization

ZigBee-Enabled Long-Range IoT-Based Monitoring and Data Acqu...

引用

Cognitive Computing in Engineering, Communications, Sciences and Biomedical Health Informatics (IC3ECSBHI), International conference on

作者： Swati Vashisht Naresh Kumar Sanjeev Pippal Department of CS-AIML G.L. Bajaj Institute of Technology and Management Greater Noida Gautam Budh Nagar India Department of CS-AI G.L. Bajaj Institute of Technology and Management Greater Noida Gautam Budh Nagar India

ISBN: (数字)9798331518523

ISBN: (纸本)9798331518530

The reliable and cost-effective monitoring of critical infrastructure, such as oil pipelines, is essential for addressing operational challenges, economic losses, and environmental risks caused by issues like blockages, leaks, and temperature fluctuations. There is a growing need for comprehensive, scalable monitoring solutions with predictive capabilities. Advances in wireless communication and IoT platforms have enabled wireless sensor networks to provide continuous data collection and transmission across large areas, enhancing operational efficiency and safety. This paper presents a novel architecture for long-range monitoring of pipeline flow and temperature via wireless communication. The system facilitates real-time data collection, storage, and cloud-based visualization, allowing operators to detect abnormalities, prevent disruptions, and improve the reliability of oil transportation.

关键词： Temperature sensors Wireless communication Cloud computing Temperature distribution Oils Pipelines data visualization Zigbee Real-time systems Monitoring

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Research on sensor data Spatiotemporal Synchronization technology for Onboard Visual Navigation Systems

Research on Sensor Data Spatiotemporal Synchronization Techn...

引用

Power Electronics, Computer Applications (ICPECA), IEEE International conference on

作者： Yanna Yuan Huimin Liu Chenqiang Zhao Aviation Industry Computing Technology Research Institute Xi'an China

ISBN: (数字)9798331533694

ISBN: (纸本)9798331533700

Against the backdrop of the rapid development of unmanned aerial vehicle (UAV) technology, onboard visual navigation systems have become the core support technology for achieving precise positioning and efficient map construction of UAVs. This paper deeply explores the key technologies of sensor data spatiotemporal synchronization in onboard visual navigation systems, aiming to solve the synchronization issues in multi-sensor data fusion in variable environments, and enhance the navigation accuracy and reliability of UAVs. The research covers both spatial and temporal synchronization dimensions, with a focus on the technical implementation of Visual-Inertial Odometry (VIO). For spatial synchronization, a target-based method is proposed to construct an error equation for solving the extrinsic parameters between the camera and the Inertial Measurement Unit (IMU), achieving precise alignment of sensor coordinate systems through the identification and matching of visual target feature points. In terms of temporal synchronization, considering the data frequency differences between the camera and IMU, this paper designs a time alignment strategy that realizes efficient temporal alignment of data through data buffering and timestamp matching. Additionally, the initialization and local sliding window optimization process of the Visual-Inertial Odometry are detailed, achieving high-precision fusion of visual and inertial data through feature extraction, optical flow tracking, and motion structure recovery. Experimental results show that the methods proposed in this paper can technically provide strong support for the autonomous flight of UAVs, effectively improving the navigation performance of UAVs in complex environments, and enhancing the robustness of the system.

关键词： visualization Accuracy Navigation Cameras Feature extraction Solids Robustness Spatiotemporal phenomena Synchronization Odometry

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Event-based sensor Fusion and Application on Odometry: A Survey

Event-based Sensor Fusion and Application on Odometry: A Sur...

引用

International Image Processing, Applications and Systems conference (IPAS)

作者： Jiaqiang Zhang Xianjia Yu Ha Sier Haizhou Zhang Tomi Westerlund TIERS Lab University of Turku Turku Finland

ISBN: (数字)9798331506520

ISBN: (纸本)9798331506537

Event cameras, inspired by biological vision, are asynchronous sensors that detect changes in brightness. They offer notable advantages in environments characterized by high-speed motion, low lighting, or wide dynamic range. These distinctive properties render event cameras particularly effective for sensor fusion in robotics and computer vision, especially in enhancing traditional visual or LiDAR-inertial odometry. Conventional frame-based cameras suffer from limitations such as motion blur and drift, which can be mitigated by the continuous, low-latency data provided by event cameras. Similarly, LiDAR-based odometry encounters challenges related to the loss of geometric information in environments such as corridors. To address these limitations, unlike the existing event camera-related surveys, this survey presents a comprehensive overview of recent advancements in event-based sensor fusion for odometry applications particularly investigating fusion strategies that incorporate frame-based cameras, inertial measurement units, and LiDAR. The survey critically assesses the contributions of these fusion methods to improving odometry performance in complex environments, while highlighting key applications, and discussing the strengths, limitations, and unresolved challenges. Additionally, it offers insights into potential future research directions to advance event-based sensor fusion for next-generation odometry applications.

关键词： Surveys visualization Laser radar Event detection Robot vision systems sensor fusion sensor phenomena and characterization Cameras Odometry Next generation networking

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Design and Analysis of Non-Invasive RF Microwave Based sensor for Water Quality Monitoring

Design and Analysis of Non-Invasive RF Microwave Based Senso...

引用

2025 International conference on Visual Analytics and data visualization, ICVADV 2025

作者： Karthikeyan, K. Sujitha, R. Sanjai, B. Centre of Excellence in Pcb Design and Analysis MKumarasamy College of Engineering Department of Electronics and Commuication Engineering TamilNadu Karur639113 India MKumarasamy College of Engineering Department of Electronics and Commuication Engineering TamilNadu Karur639113 India

ISBN: (数字)9798331521394

ISBN: (纸本)9798331521394

Water quality monitoring plays a pivotal role in maintaining environmental sustainability and ensuring public health. This study introduces the design, fabrication, and analysis of a non-invasive circular-shaped complementary split-ring resonator (CSRR) RF microwave-based sensor specifically developed for water quality assessment. By integrating CSRR technology, the sensor offers enhanced sensitivity to variations in electromagnetic properties, enabling accurate real-time monitoring of water quality parameters such as permittivity and conductivity without direct contact with the water sample. The sensor is designed using HFSS simulation software and fabricated on an FR4 substrate using standard PCB fabrication techniques, ensuring cost-effectiveness and scalability. The developed sensor was analyzed using different water samples, and changes in the s-parameter reflection coefficient were observed. © 2025 IEEE.

关键词： Microwave sensors

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Motion Detection Based IoT System for Optimizing Power Consumption

Motion Detection Based IoT System for Optimizing Power Consu...

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Power, Control and Computing Technologies (ICPC2T), conference on

作者： Viren Sharma Kartik Khandelwal M. V. Deepak Nair Department of Electronics and Communication Engineering The LNM Institute of Information Technology Jaipur Rajasthan India

ISBN: (数字)9798331530402

ISBN: (纸本)9798331530419

This paper proposes an intelligent Internet of Things (IoT) network to optimize power consumption in large halls, amphitheater, auditoriums, theatres, dining halls, etc., by controlling the appliances based on motion detection. The proposed network deploys individual sensor nodes at different zones with a microwave radar module for human presence detection and monitoring. The RCWL radar module, utilizing the Doppler effect and operating at $\mathbf{3. 1 8 \mathrm { GHz } \text {, is used to sense }}$ objects in confined aperture-based zones. After sensing human motion, the node utilizes the NodeMCU microcontroller board to switch the relay using an intelligent switching algorithm. Using the MQTT protocol, data is collected from each sensor node in the network and is shared and stored in a secure database. Node-RED dashboard is used to monitor and control the network remotely. An accuracy of nearly 95% is achieved after multiple iterations of prototyping and measurements using a 7.5-digit Keithley multimeter, RSA306B spectrum analyzer, and EMI and EMC probes.

关键词： Microwave integrated circuits Power demand radar detection Switches Motion detection Doppler radar Internet of Things Doppler effect Microwave FET integrated circuits Monitoring

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