Real Time Traffic Analysis & Vehicle Tracking System
Using Traffic Monitoring Camera Streaming
Duration
6 months
Status
Completed
Team
Team
Type
AI/ML
Project Overview
Developed an AI-powered system that processes live CCTV footage to detect vehicle number plates using YOLO algorithm. Integrated OCR technology to read number plates and store vehicle details in MySQL database. Designed automated tracking system for real-time traffic monitoring, aiding law enforcement and toll management.
Detailed Description
This project implements a comprehensive traffic monitoring solution using advanced computer vision and machine learning techniques. The system captures live video streams from CCTV cameras and processes them in real-time to identify vehicles and extract license plate information.
Key achievements: - Successfully detected and tracked multiple vehicles in real-time with 95%+ accuracy - Implemented OCR (Optical Character Recognition) to automatically read and store license plate numbers - Created a robust MySQL database to store vehicle details including timestamp, location, and camera ID - Built an intuitive dashboard for traffic monitoring and vehicle tracking
The system has applications in law enforcement for vehicle tracking, toll management systems, and smart city traffic regulation. It significantly reduces manual workload and improves traffic management efficiency.
Challenge
Real-time processing of high-resolution video streams while maintaining accuracy and system performance.
Solution
Implemented optimized YOLO model with GPU acceleration and batch processing for efficient real-time detection.
Technologies & Skills
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