Design and Implementation of a Computer Vision-Based Traffic Monitoring System
Computer Science — 2025, Undergraduate
web applicationtraffic monitoringvideo analysiscomputer vision
This study designed and implemented a Computer Vision-Based Traffic Monitoring System that analyses traffic video feeds to estimate congestion levels and detect violations. Manual observation of traffic is labour-intensive and cannot provide real-time metrics across multiple points. The system processes video frames, counts vehicles, and classifies traffic density for display on dashboards. Built with Python Django and SQLite, the system was evaluated on recorded urban traffic footage. Findings confirmed reliable vehicle counting and density classification. The study recommends deployment for traffic management centres and integration with traffic light control.
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