Indian Railways are an integral part of India’s economic ecosystem. The annual ridership of Indian Railways is approximately 9.16 billion with the total length of railway tracks being 1150 billion km, and the total freight/goods transported annually stand at 1.1 billion tonnes. Hence, we need a reliable, accurate and agile method of finding complications in railway tracks as both lives and goods are at stake. An advanced railway track fault detection system (ARTFDS) is intended for monitoring faults in railway tracks. It is an IoT-based application of ultrasonic sensors and utilizes an ML model to identify nature of defects in the track and hence ascertain the severity of the defects. The bot has added an Android application interface and SIM-based GSM message communication to provide exact GPS location enabled via Google Maps on a mobile device. The data stored on the application is backed up on Firebase real-time database which is a cloud-based solution that keeps data secure from crashes and other intrusion-related threats.


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    Title :

    ARTFDS–Advanced Railway Track Fault Detection System Using Machine Learning


    Additional title:

    Lect. Notes in Networks, Syst.




    Publication date :

    2022-08-02


    Size :

    16 pages





    Type of media :

    Article/Chapter (Book)


    Type of material :

    Electronic Resource


    Language :

    English




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