With the increasing global population and emerging technologies, there is a pressing need for efficient traffic management systems. Unfortunately, the traditional traffic control system, which relies on tri-colour signals is unable to prioritize emergency vehicles or control traffic effectively. Resulting in accidents, loss of life, and traffic congestion. However, recent technologies such as GPS, which provides live traffic data and emergency vehicle tracking, Artificial Intelligence (AI) and Deep Learning (DL), which can predict traffic solutions, Cloud Computing it processes the data and Internet of Things (IoI), which collects real-time data and offers promising solutions. Some of the challenges include the integration of various technologies, complexity in algorithms, scalability concerns, security and privacy. In this paper, we present a study on the role of AI, IoT and GPS in traffic management, proposing a better traffic signal management system that reduces congestion, prioritizes emergency vehicles, reduces commuting time and tracks vehicles.


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    Titel :

    Intelligent Traffic Monitoring, Prioritizing and Controlling Model based on GPS


    Beteiligte:


    Erscheinungsdatum :

    14.03.2023


    Format / Umfang :

    752156 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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