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.