AI-Based Violation Alert System for Helmets

Abstract: This project presents an AI-based smart helmet system designed for real-time traffic violation detection and automated enforcement. The system captures live video using a helmet-mounted camera and processes it using advanced techniques from Artificial Intelligence and Computer Vision. It employs deep learning models such as YOLO for object detection to identify motorcycles and detect violations like riding without a helmet, followed by number plate recognition using OCR techniques. Upon detecting a violation, the system generates a video clip, extracts the vehicle number, and stores the information in a database for automated fine generation. This approach enhances road safety, reduces manual monitoring, and provides evidence-based enforcement. The proposed system aims to contribute to intelligent transportation systems by offering a scalable, efficient, and real-time solution, although challenges such as environmental conditions, computational requirements, and privacy concerns need to be addressed.

Keywords: Helmet violation detection, YOLOv8, object detection, number plate recognition, OCR, Tesseract, ALPR, computer vision, intelligent transportation, ESP32, deep learning, traffic enforcement.