Many vehicles have the facility to check the health of the engine, driving characteristics, ADAS, and many more advanced features. But they all are observed in high-end cars which are costly. This paper focuses on creating a low-cost framework for existing vehicles, where the framework will contain the driving environment characteristics, driving analysis, and vehicle health characteristics. We have utilized the On-Board Diagnostic II (OBD II) module and also smartphone to build the ML and analytics model and this model is used in our proposed framework. So, with the help of OBD II and smartphone, we can collect the vision data, sensor data which we can further use in our model to derive the result which will help the driver in regards to car maintenance, driving skills in a way to improve driving skills, and also to government by reporting road anomalies.


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    Titel :

    Scalable Machine Learning and Analytics of the Vehicle Data to derive Vehicle Health and Driving Characteristics


    Beteiligte:


    Erscheinungsdatum :

    19.11.2021


    Format / Umfang :

    367911 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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