OFFLINE TRAFFIC VIDEO ANALYSIS

In Vietnam, the proliferation of traffic cameras for monitoring purposes has led to the need for efficient processing of vast amounts of video data to enforce traffic laws effectively. This project proposes the development of an AI-based offline traffic video analysis, monitoring and management system to address this challenge. Leveraging advanced AI models and video analytics algorithms, the system aims to analyse recorded traffic videos to provide insights into traffic flow, incidents, and violations. The proposed solution includes a user-friendly web interface integrated with AI models for easy upload of offline traffic videos and generation of summaries, charts, and pictures of violated along with their plates if possible. Key features include illegal parking/stopping detection and red-light violation detection, with potential expansion to lane departure and wrong-way detection. By accurately identifying violations and summarizing vehicle plates, the project aims to enhance traffic law enforcement and management. Additionally, the insights derived from traffic monitoring data can inform urban planning initiatives, transportation infrastructure projects, and development strategies, contributing to improved urban planning practices.