PDF Vehicular Accident Detection and Alerting System Circuit Diagram Accident Detection and Alert System using Arduino is a simple and effective solution to detect road accidents and send alerts in real-time. This system uses components like an Arduino board, GPS module, GSM module, and sensors (such as accelerometers) to monitor and identify unusual events like sudden impacts or vehicle tilts. When an accident IV. DESIGN AND METHODLOGY An accident detection system uses CCTV cameras to capture footage of the road. The system then processes the video by breaking it down into individual frames for analysis. If an accident is detected, the system will identify the location of the accident and send an alert to rescue systems through an application.
In this study, the research work comes up with a framework that combines IoT with machine learning solutions to improve the real-time detection of vehicle accidents and, at the same time, predict the likelihood of an accident. The framework uses IoT sensors placed on the vehicles to gather a variety of information; speed, acceleration, brake force, and deviation from the lane. The patient data automated, real-time system for the beforehand detection of vehicle collisions during high traffic cation. Our approach will work on still images, recorded- videos, and real- time live videos and will detect, classify, track and compute moving object velocity and direction using a convolution neural network. Using YOLO, it will be able to System Design A) System Architecture Fig-1: System Architecture The Accident Detection and Alert System combines deep learning algorithms with edge computing technology to swiftly detect and respond to accidents on roads. Deep learning models, trained on large datasets, analyze sensor data in real-time for signs of
PDF Road Accident Detection and Prediction System Circuit Diagram
This paper presents a real-time road accident detection and alert system that leverages a custom sequential CNN model optimized for rapid accident identification. Unlike existing approaches, this method integrates an automated alert system through Telegram's API, ensuring immediate notification to emergency responders. This enhancement significantly reduces response time, allowing for faster
offers adaptability and comprehensiveness in accident detection, enhancing safety protocols and urban infrastructure efficiency. III. METHODOLOGY A. Proposed Method The proposed methodology for AcciVue's real-time accident detection system integrates three pivotal components to ensure robust and efficient operation. Title: Car Accident Detection Using Deep Learning with Integrated Emergency Response System. The rapid development of intelligent transportation systems and the rise of smart cities have paved the way for advanced safety mechanisms in vehicular networks.This paper presents a comprehensive approach to car accident detection utilizing deep learning techniques, integrated with OpenCV for image
