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.

Repository
Team Members
Syed Umair Ahmed
Syed Umair Ahmed
syed_umair_ahmed
 Abdul Wasay
Abdul Wasay
abdul_wasay
 Sulthan Mohammed
Sulthan Mohammed
sulthan_mohammed
 Syed Faiz Ali
Syed Faiz Ali
syed_faiz_ali
Description

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.

Issues & PRs Board
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