This paper focuses on automating parking management, including ticket issuance, billing, and space allocation, to enhance the efficiency and modernization of traditional parking systems. The system comprises of three modules: Automatic Number Plate Recognition (ANPR) based billing, ticketing system driven by an algorithm of parking space assignment to avoid congestion, and a navigation system based on Augmented Reality (AR) to guide users to the parking lot. The ANPR component uses computer vision to obtain number the plate information of the users so that entry and exit vectors are in the right order. The algorithm for parking space allotment takes into account diverse aspects like preferred floor, distance from destination time of stay, electric car charging zone and disability space. The rate of dynamic parking nudges vehicle users in traffic crowded areas to use off-peak hours that helps manage parking lot occupancy as well avoid traffic jam. The application system provides occupants with real-time updates on parking space assignments and charges. Also navigation of the allocated spaces becomes much easier with the aid of augmented reality direction indications. It succinctly provides all the transactions using IoT driven engine.


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    Titel :

    Automated Parking Management System Using Computer Vision and Parking Optimization


    Beteiligte:


    Erscheinungsdatum :

    05.06.2025


    Format / Umfang :

    645736 byte





    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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