Finding available parking in congested cities is a pressing issue. This research proposes a cost-effective solution using IP cameras instead of sensors to detect vehicles. Deep learning algorithms analyze camera images to compute available parking spaces. An intuitive User Interface (UI) application assists users in locating nearby parking spots and provides GPS navigation. Previous approaches relying on sensors for vehicle detection have limitations due to high costs and infrastructure requirements. This research approach aims to save time and effort in finding suitable parking, offering an efficient solution to the problem.


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    Titel :

    A Machine Learning Based Street Parking Finder


    Beteiligte:
    Asham, Fadi (Autor:in) / Ghantous, Milad (Autor:in)


    Erscheinungsdatum :

    22.10.2023


    Format / Umfang :

    3126139 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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