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

作者： Bhuvanesh K Chandru S Hariharan S Poorna Kumar D Department of ECE KS Rangasamy College of Technology Tamil Nadu India

ISBN: (数字)9798331501488

ISBN: (纸本)9798331501495

It is an IoT-based system that detects and prevents animal incidents Utilizing cutting-edge sensors and continuous monitoring on railway tracks to minimize the risk of train accidents involving animals has been a notable issue. The proposed system integrates various sensors such as LIDAR, infrared (IR), ultrasonic, and vibration sensors with an ESP32 microcontroller to detect animals and obstacles on the tracks. The system constantly observes the track and transmits the data to a mobile application (Blynk) and a web interface for real-time monitoring. The LIDAR sensor measures the distance to objects on the track, while the IR sensor detects the heat signature of the animals. The ultrasonic sensor detects obstacles in close range, and the vibration sensor detects vibrations due to trains, disturbances, etc. When an anomaly, such as an animal, is detected, the system immediately alerts the operator via the Blynk app and provides a notification on the web interface. The ESP32 CAM captures an image of the detected object for visual confirmation. The ESP32 microcontroller facilitates real-time processing and decision making, while the Blynk app provides an intuitive interface for notifications and sensor data visualization. The Web interface allows operators to monitor multiple track sections, access live sensor data, and remotely manage the system. It will save the animals on the tracks and improve railway safety by providing efficient real-time warnings and allowing immediate intervention. Using low-cost IoT components, the system provides a scalable and practical solution to reduce animal-related incidents, contributing to safer and more efficient rail transport.

关键词： Vibrations Laser radar Animals Microcontrollers sensor systems Real-time systems Rail transportation Acoustics sensors Accidents

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Semantic-Aware Spatiotemporal Alignment of Natural Outdoor Surveys

Field Robotics

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Field Robotics 2025年 2卷 1819-1848页

作者： Georges Chahine Cédric Pradalier College of Engineering Georgia Institute of Technology Atlanta GA 30332 IRL 2958 GT-CNRS - GeorgiaTech Lorraine College of Computing Georgia Institute of Technology Atlanta GA 30332 IRL 2958 GT-CNRS - GeorgiaTech Lorraine

This article presents a keyframe-based, innovative map registration scheme for applications that benefit from recurring data acquisition, such as long-term natural environment monitoring. The proposed method consists of a multistage pipeline, in which semantic knowledge of the scene is acquired using a pretrained neural network. The semantic knowledge is subsequently employed to constrain the Iterative Closest Point algorithm (ICP). In this article, semantic-aware ICP is used to build keyframes as well as to align them both spatially and temporally, with neighboring keyframes and those captured around the same area but at a different point in time, respectively. Hierarchical clustering of ICP-generated transformations is then used to both eliminate outliers and find alignment consensus, followed by an optimization scheme based on a factor graph that includes loop closure. To evaluate the proposed framework, data were captured using a portable robotic sensor suite consisting of three cameras, a three-dimensional lidar, and an inertial navigation system. The data were acquired monthly over 12 months by revisiting the same trajectory between August 2020 and July 2021.

关键词： Surveys Semantics Laser radar Cameras Point cloud compression visualization Optimization Transforms Spatiotemporal phenomena Simultaneous localization and mapping

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Demo Abstract: C-Shenron: A Realistic radar Simulation Framework for CARLA 25

Demo Abstract: C-Shenron: A Realistic Radar Simulation Frame...

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Proceedings of the 23rd ACM conference on Embedded Networked sensor Systems

作者： Pushkal Mishra Satyam Srivastava Jerry Li Kshitiz Bansal Dinesh Bharadia Electrical and Computer Engineering University of California San Diego San Diego California USA Birla Institute of Technology Pilani Pilani Rajasthan India Electrical and Computer Engineering University of California Riverside Riverside California USA Electrical and Computer Engineering UCSD San Diego California USA

ISBN: (纸本)9798400714795

The advancement of self-driving technology is driven by the need for robust and efficient perception systems along with frameworks for End-to-End testing, enabled by the CARLA simulator. We introduce C-Shenron, a novel integration of a realistic radar sensor model within CARLA, enabling researchers to develop and test navigation algorithms using radar data. It is the first realistic radar simulator which utilizes LiDAR and camera sensors to generate high-fidelity radar ADC measurements from physics based modeling of the environment. Utilizing this radar sensor and showcasing its capabilities in simulation, we demonstrate improved performance in end-to-end driving scenarios. Our setup aims to rekindle the interest in radar-based self-driving research and promote the development of algorithms that leverages its strengths.

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LabVIEW based Patient Monitoring System

LabVIEW based Patient Monitoring System

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

作者： R.Kalaivani K.P.Sampooranam V M Balamurugan N.Chandru R.P.Cipiraj G.S Gokulakrishnan Electronics and Communication Engineering Erode Sengunthar Engineering College Erode India Electronics and Communication Engineering Bannari Amman Institute of Technology Erode India

ISBN: (数字)9798331501488

ISBN: (纸本)9798331501495

In modern healthcare, real-time patient monitoring is essential for timely diagnosis and intervention. This paper presents the development of a Patient Monitoring System using LabVIEW, integrating multiple sensors and wireless communication for efficient data acquisition and visualization. The system utilizes Arduino-based DHT11 and MAX30100 sensors to measure temperature, humidity, heart rate, and SpO₂ (oxygen saturation) levels. The acquired physiological data is interfaced with LabVIEW to provide real-time visualization and analysis. To enable wireless transmission, Amplitude Shift Keying (ASK) modulation is applied to the sensor data, which is then transmitted and received using a Universal Software Radio Peripheral (USRP). This system enhances remote patient monitoring by ensuring real-time, reliable, and secure data transmission, making it suitable for telemedicine and IoT-based healthcare applications.

关键词： Heart rate Wireless communication Temperature sensors Patient monitoring Wireless sensor networks data visualization Medical services Real-time systems sensor systems sensors

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LoRa Based Low-Cost Real-Time Air Quality Monitoring System

LoRa Based Low-Cost Real-Time Air Quality Monitoring System

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

作者： Pinaq Sharma Ashutosh Singh Baghel Parakh Sharma Rajdeep Karmakar Arpit Khandelwal Department of Electrical Engineering IIT Jodhpur Rajasthan India

ISBN: (数字)9798331518523

ISBN: (纸本)9798331518530

A low-cost indoor and outdoor air quality monitoring system is implemented using LoRa technology to measure parameters like temperature, humidity, PM 2.5 and Formalde-hyde in real-time. The system is designed in a star topology where the sensor nodes are connected to a routing node which in turn is connected to a gateway node. The sensor nodes are implemented using low-cost off-the-shelf sensors interfaced with a microcontroller unit. A LoRa hat module SX1268 is used to transmit the sensor data to the routing node, which is again implemented using a low-cost microprocessor (like Raspberry Pi). A time-series database and a server is implemented on the gateway device for data storage, visualization and processing. Using LoRa technology, the transmission range achieved is around 3 kms with zero packet loss and 4 kms with 20% packet loss.

关键词： Temperature measurement Temperature sensors Packet loss data visualization Humidity Logic gates Air quality Routing Real-time systems Monitoring

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A Study on Smart Assistive Stick for Visually Impaired Individuals

A Study on Smart Assistive Stick for Visually Impaired Indiv...

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

作者： K.Y Megajai. P Nithish Kumar. K Lakshmi Prabha. Department of Advanced Communication Technology Chennai Institute Of Technology Chennai Tamil Nadu India

ISBN: (数字)9798331521394

ISBN: (纸本)9798331521400

Vision impairment heavily affects mobility, information access, employment, and independence for millions of people across the globe. Assistive technology for blind and visually impaired persons has grown from conventional white canes to high-tech smart devices with ultrasonic sensors, GPS, GSM modules, and artificial intelligence (AI). The current review compares development in smart assistive devices, such as smart blind sticks, wearable navigation systems, and IoT-based solutions. New technology like AI-based obstacle detection, image processing, and sensor fusion provide higher accuracy and realtime feedback. Despite this, prohibitive costs, short detection ranges, and issues in dynamic environments prevent its broad application. This research highlights major advancements, their drawbacks, and directions for future enhancement of accessibility, safety, and autonomy for the visually impaired. The suggested smart assistive stick prototype combines multi-sensor technology with AI-based capabilities to improve mobility and independence, overcoming current limitations in assistive navigation devices.

关键词： GSM Accuracy Navigation Visual impairment Real-time systems Acoustics sensor systems Artificial intelligence Intelligent sensors Global Positioning System

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Adaptive radar and AIS Trajectory Association Method Based on a Dynamic Feedback Strategy

Adaptive Radar and AIS Trajectory Association Method Based o...

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sensors and Information technology (ICSI), International conference on

作者： Yaotian Shi Tongsheng Shen Feng Liu Chinese Academy of Military Science National Innovation Institute of Defense Technology Beijing China

ISBN: (数字)9798331542887

ISBN: (纸本)9798331542894

To address the limitations of traditional fixed dual-threshold trajectory association algorithms in dynamic maritime environments with increasing vessel traffic density, this paper introduces a dynamic feedback strategy into the conventional multi-factor fuzzy comprehensive decision-making(MF-FCDM) association model, optimizing thresholds to enhance robustness. Experimental results demonstrate that the proposed method reduces the average association error by 23.33% in dense scenarios while maintaining stable performance within a second threshold range of 0.8-0.95. This achievement provides a novel approach for multi-sensor data association and holds significant practical value for improving real-time vessel monitoring capabilities.

关键词： Heuristic algorithms Surveillance Scalability radar Robustness sensor systems Real-time systems Trajectory Optimization Intelligent sensors

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Adaptive Real-Time Lidar Raw Packet Processing for Dynamic Environments

Adaptive Real-Time Lidar Raw Packet Processing for Dynamic E...

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International conference on Computer and Automation Engineering, ICCAE

作者： Raghav Khajuria Abhishek Kumar Prateek Dayal Central Research Laboratory Bharat Electronics Limited Ghaziabad India

ISBN: (数字)9798331533816

ISBN: (纸本)9798331533823

This paper proposes a system for real-time terrestrial 3D LiDAR data capturing and processing using a 32channel LiDAR sensor. The system supports two methods for data acquisition: a basic approach that outputs packet capture (pcap) files and a custom algorithm designed to store raw LiDAR data directly in binary (bin) and point cloud (pcd) formats. Our pipeline includes continuous frame acquisition via UDP port, enabling accurate visualization in both 2D and 3D formats to ensure the reliability of the captured data. We employ azimuthal and elevation-based calibration for precise calculation of 3D coordinates for each LiDAR scan point. A point cloud generation algorithm efficiently parses, transforms, and stores LiDAR data for applications such as 3D mapping, navigation, and object detection in autonomous systems. Our results confirm that the proposed method provides an effective framework for real-time 3D point cloud generation and validation, significantly enhancing the performance of robotics and autonomous vehicle applications.

关键词： Point cloud compression Laser radar Three-dimensional displays Heuristic algorithms Pipelines data visualization Object detection Robot sensing systems Real-time systems Vehicle dynamics

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Real-Time Point Cloud visualization for Sustainable Spatial Digital Twins

Real-Time Point Cloud Visualization for Sustainable Spatial ...

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IEEE International conference on Consumer Electronics (ICCE)

作者： Tatsuya Kase Kenta Hasegawa Kaito Watanabe Takumi Miyoshi Taku Yamazaki Graduate School of Engineering and Science Shibaura Institute of Technology Saitama Japan

ISBN: (数字)9798331521165

ISBN: (纸本)9798331521172

City-scale spatial digital twins require extensive spatial information, such as city-scale point clouds, to remain updated. This study develops a 3D mobile crowdsensing system in which participants collect 3D point cloud data of urban spaces using LiDAR-equipped mobile devices. This system aggregates the collected partial point clouds on a server to merge them into the city digital twin. In such environments, city-scale point clouds are expected to support various smart city tasks. Therefore, diverse types of visualization are necessary for analysis and validation, including task examination, real-time system behavior verification, and crowdsensing system tracking. In this paper, we present a web-based, real-time point cloud visualization mechanism designed to offer tailored views for different use cases.

关键词： Point cloud compression Three-dimensional displays Laser radar Crowdsensing Smart cities data visualization Real-time systems Mobile handsets Digital twins Servers

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SMCNet: Supervised Surface Material Classification Using mmWave radar IQ Signals and Complex-valued CNNs

SMCNet: Supervised Surface Material Classification Using mmW...

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

作者： Stefan Hägele Fabian Seguel Driton Salihu Adam Misik Eckehard Steinbach School of Computation Information and Technology Chair of Media Technology Munich Institute of Robotics and Machine Intelligence Technical University of Munich

ISBN: (数字)9798350368741

ISBN: (纸本)9798350368758

Understanding surface material properties is crucial for enhancing indoor robot perception and indoor digital twinning. However, not all sensor modalities typically employed for this task are capable of reliably capturing detailed surface material characteristics. By analyzing the reflected RF signal from a mmWave radar sensor, it is possible to extract information about the reflective material and its composition from a certain surface. We introduce a mmWave MIMO FMCW radar-based surface material classifier SMCNet, employing a complex-valued Convolutional Neural Network (CNN) and complex radar IQ signal input for classifying indoor surface materials. While current radar-based material estimation approaches rely on a fixed sensing distance and constrained setups, our approach incorporates a setup with multiple sensing distances. We trained SMCNet using data from three distinct distances and subsequently tested it on these distances, as well as on two more unseen distances. We reached an overall accuracy of 99.12-99.53% on our test set. Notably, range FFT pre-processing improved accuracy on unknown distances from 25.25% to 58.81% without re-training.

关键词： Accuracy RF signals radar Robot sensing systems radar signal processing sensors Convolutional neural networks Millimeter wave communication Speech processing Surface treatment

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