Systems and methods enable automated intelligent railway monitoring using railway image data from an imaging device. The railway image data includes image frames produced by the imaging device. A railway object recognition model is used to identify objects within the image frames and a railway condition is determined based on the object. A location and time associated with the railway condition are determined based on railway image data. Railway metrics are generated based on the railway condition and historical railway conditions. A railway condition prediction model is used to predict future railway conditions affecting an operating condition, an operating demand or both based on the railway metrics. An operating recommendation is determined to address the future railway condition and an alert is generated to with an indication of railway condition, the operating recommendation or both.


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    Title :

    SYSTEMS AND METHODS FOR MACHINE LEARNING ENHANCED RAILWAY CONDITION MONITORING, ASSESSMENT AND PREDICTION


    Contributors:
    LIU XIANG (author)

    Publication date :

    2024-03-14


    Type of media :

    Patent


    Type of material :

    Electronic Resource


    Language :

    English


    Classification :

    IPC:    B61L Leiten des Eisenbahnverkehrs , GUIDING RAILWAY TRAFFIC / G06T Bilddatenverarbeitung oder Bilddatenerzeugung allgemein , IMAGE DATA PROCESSING OR GENERATION, IN GENERAL / G06V



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