This project focuses on developing an efficient traffic management system for congestion detection and alert using the HAAR Cascade algorithm. The system aims to detect traffic congestion in real-time and alert authorities to take necessary actions for traffic management.
Congestion Detection: The HAAR Cascade algorithm is utilized to detect congestion by analyzing live traffic footage or images captured from surveillance cameras.
HAAR Cascade Training: Train the HAAR Cascade classifier using a labeled dataset of congested and uncongested traffic images.
Deployment: Deploy the trained model to analyze live traffic footage or images obtained from surveillance cameras.
The Efficient Traffic Management System with HAAR Cascade offers a reliable solution for congestion detection and alerting. By leveraging advanced image processing techniques, the system contributes to improved traffic management and enhanced safety on roads.