In today's cities, maintaining road safety and enforcing traffic laws are major concerns. This research introduces an automated system that uses Machine Learning to identify helmet use and read motorcycle license plates for immediate traffic law enforcement. The system uses YOLOv8 for object detection, OCR to extract text from license plates, and OpenCV for image processing. When a violation is identified, such as not wearing a helmet, the system checks the vehicle's registration details against a central database and automatically sends a fine to the registered owner. The proposed method shows great accuracy in both helmet detection and license plate recognition. The goal is to reduce the need for manual work, simplify enforcement, and improve road safety by using intelligent automation.
An Intelligent Framework for Helmet Detection and Traffic Violation Automation using Machine Learning
11.06.2025
1156496 byte
Aufsatz (Konferenz)
Elektronische Ressource
Englisch
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