Transportation system has been a part of evolving of humans. One can not image the life without vehicles. To accommodate the vast number of population, the number of vehicles also has been increased rapidly. This also led to increased number of accidents. The accident avoidance measures used now a day are all static and old. Also, there is no proper accident detection mechanism. This study proposes Smart Vehicle Monitoring System (SVMS) for early detection of accidents and also to prevent thefts. SVMS uses IoT technology to monitor the vehicle continuously and also to access and control remotely. The IoT devices placed in vehicles is designed using Raspberry Pi (RPi) that is acquainted with sensors to detect accidents immediately. The RPi is also acquainted with a camera to find the severity of accident. To detect the severity, SVMS uses machine learning based image classification model. When the accidents happen the SVMS detects it immediately and finds the severity of the accident. Then the system will immediately inform that to the authorities. The SVMS also acquainted with GPS system. This will allow the SVMS to continuously keep track of vehicles location. This data will be used to find the vehicles location during an accident or theft. The results of SVMS system were promising in terms of efficiently detecting the accidents, finding the severity of accident and also detecting the location of vehicle.


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    Title :

    IoT Based Smart Vehicle Monitoring System


    Contributors:

    Publication date :

    2018-04-20


    Remarks:

    doi:10.26483/ijarcs.v9i2.5870
    International Journal of Advanced Research in Computer Science; Vol 9, No 2 (2018): March-April 2018; 738-741 ; 0976-5697 ; 10.26483/ijarcs.v9i2



    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English



    Classification :

    DDC:    629



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