Emergency Service Provider
An AI-powered Accident Detection Dashboard designed to enhance traffic safety through real-time monitoring. This system leverages YOLOv8 computer vision to automatically detect accidents in video streams, providing instant alerts to operators. It features a modern React/Vite frontend for live monitoring and a robust dual-backend architecture: Node.js/Express handles secure Google authentication and logging, while a Python FastAPI service powers the high-performance object detection engine. Key capabilities: Real-time video analysis and accident detection. Live dashboard with alerting and incident playback. Secure operator access and activity auditing.
Project Name: AI-Powered Accident Detection & Response System
Overview: The AI Accident Detection Dashboard is a comprehensive, real-time traffic monitoring solution designed to reduce emergency response times and enhance road safety. By integrating state-of-the-art computer vision with a modern web interface, the system automates the detection of traffic accidents and coordinates immediate responses.
Core Architecture: The project is built on a robust, microservices-inspired architecture:
AI Engine (Python/FastAPI): At the heart of the system is a high-performance computer vision server powered by YOLOv8 and OpenCV. It processes live video feeds to detect vehicles and identify accidents with high accuracy, broadcasting alerts instantly via WebSockets.
Operator Dashboard (React/Vite): A responsive, high-performance frontend provides emergency operators with a live view of traffic cameras. It features real-time alert notifications, incident playback, and an intuitive "Operator Console" for managing active emergencies.
Secure Middleware (Node.js/Express): A dedicated server layer manages secure Google OAuth authentication and maintains an audit trail of operator activities (logins and sessions) using Excel-based logging.
Key Functionalities:
Autonomous Monitoring: 24/7 analysis of traffic feeds without human fatigue.
Instant Alerts: Immediate visual and audible notifications upon accident detection.
Evidence Archival: Automatic saving of accident footage for forensic analysis.
Secure Access: Role-based access control ensuring only authorized personnel can view sensitive feeds.