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.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

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


    Contributors:


    Publication date :

    2021-11-19


    Size :

    367911 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



    FOUR-WHEEL DERIVE VEHICLE

    YUASA RYOHEI / ISHIDA SEISHI / MURAI SHOTA et al. | European Patent Office | 2019

    Free access

    Analysing pedestrian-vehicle interaction to derive implications for automated driving

    Ackermann, Claudia / Technische Universität Chemnitz | TIBKAT | 2019

    Free access

    VEHICLE-DATA ANALYTICS

    MILTON STEPHEN | European Patent Office | 2024

    Free access

    VEHICLE-DATA ANALYTICS

    MILTON STEPHEN | European Patent Office | 2023

    Free access

    VEHICLE-DATA ANALYTICS

    MILTON STEPHEN | European Patent Office | 2021

    Free access