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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61-70 订阅

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Vehicle-Mounted Millimeter-Wave radar Vital Signs Detection and Early Warning Control System

Vehicle-Mounted Millimeter-Wave Radar Vital Signs Detection ...

引用

Integrated Circuits and Communication Systems (ICICACS), IEEE International conference on

作者： Wenshan Li Hunan Institute of Traffic Engineering Hengyang Hunan China

ISBN: (数字)9798331508456

ISBN: (纸本)9798331508463

Traditional methods of monitoring vital signs in vehicles often fall short when it comes to response time, especially in fast-moving situations. To tackle this, our paper introduces a groundbreaking solution: leveraging millimeter-wave radar technology to monitor vital signs in real time within the vehicle, providing timely alerts when necessary. This approach not only enhances the accuracy of readings but also ensures a swift response that is crucial during vehicle operation. By tapping into the unique abilities of millimeter-wave radar to detect subtle human signs, we propose a novel method that processes radar signals to monitor vital signs like heart rate and respiratory rate. This technique is highly effective in meeting the stringent demands of real-time accuracy and speed, especially while driving. Our system includes three main components: radar sensors, a signal processing unit, and an early-warning control module, working together seamlessly to ensure optimal monitoring. The radar sensor continuously transmits and receives millimeter-wave signals, allowing it to track vital signs without interruption. A specially designed feature extraction algorithm filters out noise and extracts critical information, including heart and respiratory rates. Then, advanced algorithms analyze this data in real time, spotting any abnormalities and triggering alerts through the control module. What sets this system apart is its rigorous testing under various vehicle speeds and environmental conditions, confirming its stability, reliability, and fast response times. In real-world applications, the system responds to a high heart rate in 3.7 to 4.0 seconds and to a rapid breathing rate in 4.1 to 4.3 seconds. This millimeter-wave radar-based system offers a fresh approach to vehicle safety, combining practicality with promising future potential.

关键词： Heart rate Accuracy Signal processing algorithms Millimeter wave radar Real-time systems Stability analysis sensor systems sensors Time factors Monitoring

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Detection, Tracking, and Identification of Drones: an Overview on Counter-Uas Techniques, and Open Challenges

Detection, Tracking, and Identification of Drones: an Overvi...

引用

Integrated Communications, Navigation and Surveillance conference, ICNS

作者： Giovanni Grieco Danilo Amendola David Anderson European Commission Joint Research Centre (JRC) Geel Belgium

ISBN: (数字)9798331534738

ISBN: (纸本)9798331534745

With the proliferation of Unmanned Aircraft Systems (UASs), a broad spectrum of legitimate, nuisance, and malicious applications has introduced new challenges for airspace management. A large number of UASs available on the market, and UASs can also be homemade (including being 3D printed), further complicating detection and classification efforts. Traditional traffic control and surveillance systems are facing disruption from UASs proliferation, which enable innovative use cases across various sectors, such as precision agriculture and infrastructure inspection, but also create opportunities for misuse, such as illegal surveillance and contraband delivery. In this evolving landscape, C-UAS technology has emerged as a crucial tool to mitigate the growing risks associated with unauthorized drone usage. To this end, it is critical to understand the capability, limitations and challenges associated to C-UAS research and development efforts related to detection, tracking, and identification of unauthorized UASs in public and critical infrastructures. Given the diverse range of sensors employed in C-UAS systems, such as radar, radiofrequency, electro-optical, and acoustic sensors, and the heterogeneous nature of UASs, this study emphasizes the importance of multi-sensor data fusion to achieve accurate DTI in real-time. The integration of different sensors is key to enhancing system reliability and addressing the complexities of modern airspace. Furthermore, new models and algorithms are necessary to improve target tracking capabilities for UASs. The study presents a taxonomy of sensors used in C-UAS and highlights the need for a comprehensive, integrated approach. It also delves into the challenges of implementing a multi sensor data fusion algorithm, providing a model for sensor fusion in DTI, along with an overview of the current literature and available commercial solutions. By adopting a holistic approach, this study aims to contribute to the advancement of robust, r

关键词： Surveillance Atmospheric modeling data integration sensor fusion Traffic control radar tracking Aircraft navigation sensors Drones Diffusion tensor imaging

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Parking Reservation and Smart Allocation using IoT

Parking Reservation and Smart Allocation using IoT

引用

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

作者： JaiAmudhan Dhakshinamoorthy Vishwa Varshini Viswanathan Yamuneswar Annadurai V.P. Dhivya Department of Information Technology K.S. Rangasamy College of Technology Tiruchengode India

ISBN: (数字)9798331521394

ISBN: (纸本)9798331521400

Smart Parking System with Dynamic Slot Allocation Using IoT and Paging Method: The aim of this proposed parking system is enhancing the user experience within an urban environment and the development of parking efficiency. A traditional system is inefficient regarding poor slot utilization and also cannot perform dynamic re-allocation. The proposed parking system utilizes IR sensors to detect the space in real-time, and it uses Paging Method to optimize slot allocation. A mobile application allows slot pre-booking, receives updates, and processes secure payments. Automatic Number Plate Recognition ensures that only authorized people get access. With a dynamic reallocation of slots depending on the users, it manages time slots effectively. The Billing Module integrates within it to calculate fees automatically for seamless payment processing. This reduces congestion, increases utilization, and provides a scalable solution to the infrastructure of modern urban life.

关键词： Visual analytics Urban areas Dynamic scheduling Real-time systems User experience sensor systems sensors Mobile applications Resource management License plate recognition

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AI–based IoT Real Time Air Monitoring System

AI–based IoT Real Time Air Monitoring System

引用

Trends in Material Science and Inventive Materials (ICTMIM), International conference on

作者： R. Kalaivani K P. Sampoornam G. Sri Mathi M. Nivetha Electronics and Communication Engineering Erode Sengunthar Engineering College Erode India Electronics and Communication Engineering Bannariamman Institute of Technology Sathiyamangalam India

ISBN: (数字)9798331501488

ISBN: (纸本)9798331501495

In order to detect and forecast air pollutants, this study suggests a real-time air quality monitoring system based on AI and IoT. To offer precise and trustworthy air quality data, the system combines sensors, Internet of Things devices, and machine learning algorithms. With an accuracy rate of more than 90%, the suggested system can identify and predict air pollutants such as O3, PM2.5, and NO2. Stakeholders can access air quality data and get tailored suggestions using a mobile application and real-time data visualization dashboard. Proactive steps to lower air pollution are made possible by the system's predictive analytics capability, improving public health and environmental sustainability.

关键词： Accuracy Green products data visualization Air pollution Real-time systems sensor systems Mobile applications Stakeholders Public healthcare Monitoring

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A Smart Agrisense IoT System with ML Integration

A Smart Agrisense IoT System with ML Integration

引用

International conference on Computer, Electrical & Communication Engineering (ICCECE)

作者： P. Vishnu Kumar Gorantla Rohith Kumar Sirigiri Rithwik Gurram Deepesh Department of Internet of Things G. Pullaiah College of Engineering and Technology Kurnool Andhra Pradesh India

ISBN: (数字)9798331513894

ISBN: (纸本)9798331513900

This paper presents an advanced agricultural monitoring system utilizing Internet of Things (IoT) technology to provide precise soil and nutrient analysis. The core of the system is the ESP32 microcontroller, which processes data from various sensors to facilitate seamless operation. The focus is on improving crop yield and soil health by continuously monitoring nitrogen, phosphorus, and potassium (NPK) levels. The system explores recent advancements, including machine learning algorithms for accurate crop recommendations and edge computing for real-time data processing. Challenges faced in implementing such systems-such as sensor calibration, maintaining data consistency, and integrating predictive models-are addressed. Despite these obstacles, field tests demonstrate the system’s reliability in analyzing soil fertility and offering tailored crop suggestions. The system consistently provides actionable insights to identify suitable crops, ensuring efficient resource use. This proposed agricultural monitoring system is designed to overcome these challenges and significantly advance precision farming. It is innovative, affordable, and easy to operate, making it a valuable tool for modern agriculture.

关键词： Machine learning algorithms Crops data visualization Soil Nutrients sensor systems Real-time systems Internet of Things Monitoring Farming

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Enabling Vehicular mmWave Communication Links Using cmWave Information

Enabling Vehicular mmWave Communication Links Using cmWave I...

引用

European conference on Antennas and Propagation, EuCAP

作者： Markus Hofer Faruk Pasic Benjamin Rainer Jiri Blumenstein Ales Prokes Christoph F. Mecklenbräuker Andreas F. Molisch Thomas Zemen AIT Austrian Institute of Technology GmbH Austria Institute of Telecommunications TU Wien Vienna Austria Dept. of Radio Electronics Brno University of Technology Czech Republic University of Southern California Los Angeles CA USA

ISBN: (数字)9788831299107

ISBN: (纸本)9798350366327

Future connected cooperative automated mobility can benefit from high-data-rate wireless communication links between vehicles to exchange LIDAR and/or radar data. The millimeter wave (mmWave) frequency range offers large bandwidth for rapid sensor data exchange but suffers from higher signal attenuation compared to the centimeter wave (cmWave) band. In this paper we obtain cmWave and mmWave multipath component (MPC) parameters by combining a single omnidirectional antenna that is used as virtual array with the CLEAN algorithm. The cmWave MPC information enables low-overhead mmWave beamforming by means of an antenna array. Empirical multi-band measurement data ( $3.2 \text{GHz}, 34.3 \text{GHz}$ , and 62.35 GHz) shows that considering the 5 strongest MPCs, a signal-to-noise ratio of up to 25 dB for a V2I scenario can be achieved.

关键词： Antenna measurements Wireless communication Software algorithms Omnidirectional antennas radar antennas Arrays Millimeter wave communication Antenna arrays Signal to noise ratio Software radio

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Research on Multi-Target Tracking Model of data Fusion between Autonomous Driving Millimeter-Wave radar and Visual sensors 24

Research on Multi-Target Tracking Model of Data Fusion betwe...

引用

Proceedings of the 2024 4th International conference on Computational Modeling, Simulation and data Analysis

作者： Xinzhen Long Tao Lin Xingzhi Lin Faculty of Computer and Information Engineering GuangXi Vocational Normal University Nanning Guangxi China Guangxi Minzu University Nanning Guangxi China GuangXi Vocational Normal University Nanning Guangxi China

ISBN: (纸本)9798400711831

The research mainly addresses the multi-target tracking problem encountered in the data fusion process of millimeter-wave radar and visual sensors in unmanned systems. Multi-sensor data fusion models are investigated to optimize target detection performance and improve the accuracy of tracking models. The research analyzed the accuracy of the Kalman filter and the convolutional neural network, and used joint data association technology to achieve high-precision target detection, stable real-time tracking, and excellent adaptability to dynamic environments. The tracking accuracy reached 97.87% and the false detection rate was less than 2.13% through simulation experiments in a simulated driving environment. The experimental results verified that the fusion model performs excellently in complex driving scenarios, maintaining high-precision target tracking, proving that the technical methods used are feasible.

关键词： Autonomous driving

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GeoRescue Drone

GeoRescue Drone

引用

data Science, Agents & Artificial Intelligence (ICDSAAI), International conference on

作者： Su. Suganthi J. Ilakkiya Risheeth C Madhumitha V D Subbiah V Artificial Intelligence and Data Science Sri Sairam Institute of Technology Chennai India

ISBN: (数字)9798331537555

ISBN: (纸本)9798331537562

Earthquakes, landslides, and floods are natural disaster induced catastrophes resulting in victim detection delay and greater casualties. The traditional rescue processes like manual digging,thermal imaging, and sonar scanning fail tolocate buried survivors under the rubble. In response to this, an Artificial Intelligence-based Unmanned Aerial Vehicle (UAV) with Ground Penetrating radar (GPR), GeoRescue Drone, is introduced to scan subsurface in real-time to identify buried victims accurately and minimize rescue time. The drone emits high-frequency electromagnetic waves, sweeps reflected waves, and distinguishes human bodies from other objects with a machine learning-based classifier. GPS navigation and AI-driven autonomous flight offer high coverage with low human *** testing shows 92.8% detection rate, 90.5% precision, and 1.2 seconds response time per sweep. Future plans involve multi-sensor fusion, onboard LiDAR, and optimized AI-driven signal processing for enhanced accuracy.

关键词： Ground penetrating radar Accuracy Disasters Surveillance Signal processing Autonomous aerial vehicles Real-time systems Time factors Drones Testing

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AI-Powered Soil Stability Assessment and Landslide Forecasting with Multi-sensor Networks, Edge Computing, and Jetson Nano Integration

AI-Powered Soil Stability Assessment and Landslide Forecasti...

引用

Trends in Material Science and Inventive Materials (ICTMIM), International conference on

作者： N. Muthukumaran A. Vignesh S. Aruna M. Jenish T. Vinoth Kumar Shanthi Madasamy Department of ECE Sri Eshwar College of Engineering Coimbatore India Department of EEE Dr. N.G.P Institute of Technology Coimbatore India Department of EEE RVS College of Engineering and Technology Coimbatore India Department of EEE JCT College Of Engineering And Technology Coimbatore India

ISBN: (数字)9798331501488

ISBN: (纸本)9798331501495

Landslides pose a severe threat to mountainous regions, often resulting in catastrophic damage and loss of life. Existing prediction methods rely on limited data sources and infrequent monitoring, leading to delays in early warnings. Previous technologies have explored individual sensor applications, such as Ground-Penetrating radar (GPR) and seismic sensors, but lack a comprehensive multi-sensor approach with real-time processing. Notable cases, like the Wayanad landslides in Kerala, India, highlight the urgent need for advanced predictive systems. This study proposes an AI-driven landslide prediction system using a network of 40 sensor-equipped slave kits. Each kit integrates GPR, seismic, Electromagnetic Induction (EMI), ultrasonic, LiDAR, capacitance probes, gravimeters, Electrical Resistivity Tomography (ERT), and magnetometers onto a Teensy 4.1 microcontroller with an ESP8266 for wireless data transmission. data is processed at a central master unit featuring a Jetson Nano module, employing the ALEXNET+BILSTM model for real-time analysis of soil stability and landslide risk. By leveraging edge computing, this system enables rapid decision-making and early warnings, addressing the limitations of existing methods. Its scalable, cost-effective architecture enhances environmental monitoring, offering a robust solution for landslide-prone communities and significantly improving disaster preparedness.

关键词： Wireless communication Landslides Wireless sensor networks Soft sensors Soil Tomography Stability analysis Real-time systems Terrain factors Edge computing

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Real-Time Recursive Point Cloud Prediction for Interpolating Anomalous Frames

Real-Time Recursive Point Cloud Prediction for Interpolating...

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IEEE International conference on Consumer Electronics (ICCE)

作者： Yoshiki Yamaguchi Yuki Umemoto Takumi Miyoshi Taku Yamazaki Ryoichi Shinkuma College of Systems Engineering and Science Shibaura Institute of Technology Saitama Japan Graduate School of Engineering and Science Shibaura Institute of Technology Tokyo Japan College of Engineering Shibaura Institute of Technology Tokyo Japan

ISBN: (数字)9798331521165

ISBN: (纸本)9798331521172

Physical attacks that target light detection and ranging (LiDAR) sensors have become a significant threat to the security and reliability of LiDAR-based systems, particularly in autonomous driving and digital twin applications. These attacks selectively manipulate or remove point cloud data, thereby undermining the functionality of safety-critical systems. In this study, we propose a recursive point cloud prediction mechanism that anticipates future frames based on past data, enabling real-time interpolation of anomalous frames. The proposed mechanism predicts five future frames based on the preceding five frames and replaces compromised frames with interpolated predictions, thereby ensuring data continuity. Furthermore, we demonstrate the effectiveness of the proposed approach using a major dataset, showing that it can maintain data integrity even during physical attacks.

关键词： Point cloud compression Interpolation Laser radar data integrity sensor systems and applications Real-time systems Digital twins Security Anomaly detection Autonomous vehicles

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