This initiative aims to quickly identify individuals who violate traffic laws and notify them of their violations via What’s App, reducing the burden on law enforcement officers." The major goal is to improve traffic law enforcement. The rise in road accidents is mostly due to widespread noncompliance with traffic rules, which includes failure to wear a helmet, exceeding speed limits, and taking the wrong route. By integrating cutting-edge approaches in computer vision, image processing, and machine learning, the system overcomes considerable problems connected with traffic rule breaches. The primary goals include accurately identifying individuals operating automobiles, validating helmet usage, and recognizing license plates using image processing techniques. Following that, automatic traffic challans are issued in compliance with the violations. In essence, the Intelligent Traffic Management System combines these technological breakthroughs to provide a complete strategy to improving traffic safety, reducing traffic offenses, and optimizing traffic law enforcement. This groundbreaking technology announces a path towards safer and better organized streets, representing a significant advancement in the field of intelligent traffic management.


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    Titel :

    Enforcing Helmet Compliance Via WhatsApp using Clustering Algorithms


    Beteiligte:
    Swaroop, P. Chaitanya (Autor:in) / Sri, G. Hruthi (Autor:in) / Teja, V. (Autor:in) / Jahnavi, V. (Autor:in) / Kumar, C S Pavan (Autor:in)


    Erscheinungsdatum :

    24.04.2024


    Format / Umfang :

    1148591 byte





    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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