A machine learning system is provided that receives location information from one or more aircraft, determines a deviation of the actual aircraft flightpath from an expected flight path. The flight path may be determined based on a filed flight plan, one or more historical flight paths. The actual aircraft flightpath is scored with respect to the expected flight path and the score may be used to determine an anomalous condition. In some cases, an aircraft crossing a boundary creates the anomalous condition. The anomalous conditions may be used to create a flag or an alert to indicate further analysis may be required. Through machine learning algorithms, hundreds, thousands, or tens of thousands or more flights can be simultaneously tracked and analyzed for anomalous conditions.


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    Title :

    SYSTEMS AND METHODS FOR DETECTING ANOMALOUS AIRCRAFT FLIGHTS FROM SURVEILLANCE DATA


    Contributors:

    Publication date :

    2024-07-11


    Type of media :

    Patent


    Type of material :

    Electronic Resource


    Language :

    English


    Classification :

    IPC:    G08G Anlagen zur Steuerung, Regelung oder Überwachung des Verkehrs , TRAFFIC CONTROL SYSTEMS / G06N COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS , Rechnersysteme, basierend auf spezifischen Rechenmodellen



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