INTERACTIVE REPRESENTATION OF A ROUTE FOR PRODUCT TRANSPORTATION

Techniques for applying a machine learning model to historical shipping data to generate an interactive graphical user interface of a transport route are disclosed. A machine learning model is trained to compute route attributes for at least one transport provider for transporting items along a rout...

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Bibliographische Detailangaben
Hauptverfasser:	Darmour, Jennifer, Giovanetti, Nicole Santina, Wong, Jason, Kim, Min Hye, Lapurga Viernes, Ronald Paul, Grande, Loretta Marie, Han, Jingyi
Format:	Patent
Sprache:	eng
Schlagworte:	CALCULATING COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS COMPUTING COUNTING DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FORADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORYOR FORECASTING PURPOSES GYROSCOPIC INSTRUMENTS HANDLING RECORD CARRIERS MEASURING MEASURING DISTANCES, LEVELS OR BEARINGS NAVIGATION PHOTOGRAMMETRY OR VIDEOGRAMMETRY PHYSICS PRESENTATION OF DATA RECOGNITION OF DATA RECORD CARRIERS SURVEYING SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE,COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTINGPURPOSES, NOT OTHERWISE PROVIDED FOR TESTING
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Beschreibung
Zusammenfassung:	Techniques for applying a machine learning model to historical shipping data to generate an interactive graphical user interface of a transport route are disclosed. A machine learning model is trained to compute route attributes for at least one transport provider for transporting items along a route between a source location and a destination location. The system is further configured to display the actual or estimated location of an item along the route based on a timeline. The position of the item along the route is updated as the user drags a time marker along a timeline. The system identifies and displays the attributes of the transportation segment that includes the currently displayed position of the item along the route.