In recent times, the roadways in India are improving. Vehicles are travelling at a fast rate of speed on Indian roadways. The Indian government wants to implement a system known as vehicle over-speed detection at a low cost to identify and warn the vehicles that are travelling at more than the prescribed speed limits. The speed limit on the roadways depends on the type of vehicle. In our proposed system, every toll booth has been fitted with a camera that identifies the vehicle's type using relevant AI techniques. Once the vehicle type is identified, we extract the license plate and recognize it using appropriate deep learning algorithm. The retrieved vehicle data along with current time stamp information are transferred to a central cloud server. Every toll plaza server has access to the vehicle information maintained on the central cloud server. Once the vehicle enters the next toll plaza, the system extracts once again the vehicle information and adds time stamp information. Using Google maps, we identify the road geometry between the toll plazas and calculate the curvature of the road. Subsequently we compute the average time that a vehicle should take between the toll plazas. If the actual time taken by the vehicle between the toll plazas is less than the scientifically computed time limit, then it is detected as over speeding vehicle. The vehicle details of such over speeding vehicles are extracted from the Regional Transport Office server and vehicle owner’s contact details are extracted. Then the necessary tickets are issued to the offenders with evidence.


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    Titel :

    Vehicle Over Speed Detection System


    Weitere Titelangaben:

    Studies in Big Data


    Beteiligte:
    Roy, Sanjiban Sekhar (Herausgeber:in) / Hsu, Ching-Hsien (Herausgeber:in) / Kagita, Venkateshwara (Herausgeber:in) / Ganesan, K. (Autor:in) / Manikandan, N. S. (Autor:in) / Sugumaran, Vijayan (Autor:in)


    Erscheinungsdatum :

    2023-07-09


    Format / Umfang :

    25 pages





    Medientyp :

    Aufsatz/Kapitel (Buch)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




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