AI-Powered Hit-and-Run Investigation System
An advanced deep learning-based system for analyzing hit-and-run incidents using CCTV footage.
Project Overview
The Hit-and-Run Investigation System leverages advanced AI techniques to automate the detection and analysis of hit-and-run incidents in CCTV footage. By integrating object detection, motion analysis, and OCR, the system helps law enforcement and forensic teams quickly identify and investigate cases.
Features
- Vehicle Detection & Tracking: Uses advanced deep learning models for accurate real-time tracking.
- Collision Detection: AI-based motion analysis detects hit-and-run incidents.
- License Plate Recognition: OCR extracts vehicle details from footage.
- Automated Report Generation: Generates comprehensive reports with timestamps, visual evidence, and geolocation data.
Challenges & Solutions
- Low-Quality CCTV Footage: Applied super-resolution techniques for clarity.
- Real-Time Processing: Optimized model inference with hardware acceleration.
- Multiple Object Tracking: Implemented tracking algorithm for robust multi-vehicle tracking.
Results
The system enhances law enforcement capabilities by reducing investigation time, improving accuracy, and automating evidence collection for legal proceedings.
Gradio demo of project.