Project Description:

The Forest Traffic Violation Detection System is a smart surveillance project aimed at monitoring unauthorized vehicle movement and traffic violations within protected forest areas, wildlife zones, and eco-sensitive zones. It uses AI-powered image processing and IoT sensors to detect activities such as overspeeding, off-track movement, unauthorized entry, and night-time violations.

The system ensures environmental conservation, helps wildlife protection authorities, and enables law enforcement to monitor and penalize violators.

Technologies Used:

• Backend: Node.js / PHP / Java

• Frontend: HTML, CSS, Bootstrap, JavaScript

• Database: MySQL / MongoDB

• AI/ML: Python (OpenCV, YOLO, TensorFlow, etc.)

• IoT Hardware:

  • Motion Sensors (PIR/LIDAR)

  • IR Cameras / Night Vision Cameras

  • GPS Modules

  • Speed Sensors

  • Raspberry Pi / ESP32 Controller

Core Features:

1. Vehicle Detection Using AI:

   • Use object detection models (YOLO or Haar cascades) to identify vehicles from surveillance footage.

2. Violation Classification:

   • Detect and log incidents such as:

     • Speeding

     • Entering restricted zones

     • Driving during prohibited hours

     • Off-road path traversal

3. License Plate Recognition (ANPR):

   • Use AI to read number plates for identification and enforcement.

4. Real-Time Alert System:

   • Notify forest officials immediately through a web dashboard or SMS.

5. Web-Based Monitoring Dashboard:

   • Admin panel for monitoring live camera feeds, violation logs, and offender details.

6. GPS-Based Tracking:

   • Monitor vehicle movement and route compliance using GPS and maps.

7. Violation Reports & Analytics:

   • Generate downloadable reports for action or evidence.