AI-Based Traffic Violation Detection System

I am looking for an experienced developer/team to build a smart Traffic Violation Detection System using AI, Computer Vision, and Deep Learning technologies. The system should automatically detect and monitor traffic violations from CCTV/live camera footage and generate reports in real time. Main Features Required: Vehicle detection and tracking Number plate detection and OCR recognition Helmet detection for two-wheelers Seatbelt detection Red light violation detection Wrong-side driving detection Over-speed detection Lane violation detection Real-time alerts and logging Store violation data in database Dashboard/Admin panel for monitoring Upload video or use live camera feed Export reports and screenshots of violations Technologies Preferred: Python OpenCV YOLO / TensorFlow / PyTorch OCR for number plates Flask/Django for web dashboard MySQL or MongoDB database Expected Output: The system should detect traffic violations automatically and save: Vehicle image Number plate text Time and date Type of violation Camera/location details Additional Requirements: Clean UI dashboard Proper documentation Source code included Efficient and optimized detection Ability to run on local machine/server Project Goal: To create an intelligent automated traffic monitoring system that reduces manual work and helps improve road safety using AI and surveillance technologies.

Project ID: 40463174