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.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    An Intelligent Framework for Helmet Detection and Traffic Violation Automation using Machine Learning




    Publication date :

    2025-06-11


    Size :

    1156496 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



    Helmet violation processing using deep learning

    Raj, K C Dharma / Chairat, Aphinya / Timtong, Vasan et al. | IEEE | 2018


    Intelligent Traffic Violation Detection

    Ravish, Roopa / Rangaswamy, Shanta / Char, Kausthub | IEEE | 2021


    Traffic Signal Violation Handling Using Machine Learning

    Sharmila Agnal, A / Aakash, K / Navin, C S | IEEE | 2024


    Traffic Rules Violation Detection using Deep Learning

    Tonge, Aniruddha / Chandak, Shashank / Khiste, Renuka et al. | IEEE | 2020


    Violation behavior detection system for intelligent traffic management

    QIN CHAOJUN / WANG WEI / ZHANG HAITAO et al. | European Patent Office | 2021

    Free access