Computer vision-based real-time vehicle and traffic management and classification system

This research presents a real-time vehicle and traffic management system leveraging computer vision to provide a comprehensive solution for monitoring and managing vehicles across various sectors, including traffic control, law enforcement, parking management, transportation systems, and toll plaza operations. The system is composed of four primary modules: vehicle counting, speed detection, vehicle classification, and license plate recognition. The vehicle counting module accurately tracks and records the number of vehicles passing a designated point, storing the data with timestamps in an Excel sheet for further analysis. The speed detection module monitors vehicle speeds, issuing alerts when a predefined speed limit is exceeded, making it particularly suitable for enhancing safety in sensitive areas such as university campuses, residential zones, and high-traffic intersections. Together, these functionalities contribute to an integrated approach to effective traffic and vehicle management.