Machine learning enabled self-detection for truck rolls on end-user satellite terminals
AssigneeHughes Network Systems, LLC
InventorsSoham Sheth, David Whitefield, Amit Arora
Life of this patent
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Abstract
A system and method for collecting, at a terminal, statistical data regarding performance of a transport between the terminal and a satellite; analyzing, at the terminal with an ML model, the statistical data to determine a failure state of the terminal and notifying a user of the failure state, wherein the ML model is trained on a training dataset collected from a terminal population, and the statistical data comprises a terminal state and transport metrics for the terminal.
Claims18
A method for determining a failure state of a satellite terminal using a Machine Learning (ML) system comprising a computer processor, the method comprising:
- collecting, at a terminal, statistical data regarding performance of a transport between the terminal and a satellite;
- analyzing, at the terminal with an ML model, the statistical data to determine a failure state of the terminal;
- notifying a user of the failure state;
- and
- pre-processing the statistical data to homogenize and to normalize the statistical data prior to the analyzing,
- wherein the ML model is trained on a training dataset collected from a terminal population, and the statistical data comprises a terminal state and transport metrics for the terminal.
A satellite communication system to determine a failure state of a satellite terminal using a Machine Learning (ML) system comprising a computer processor, the satellite communication system comprising:
- a terminal to collect statistical data regarding performance of a transport between the terminal and a satellite, and to notify a user of a failure state;
- and
- an ML model, at the terminal, to analyze the statistical data to determine the failure state of the terminal,
- wherein the ML model is trained on a training dataset collected from a terminal population, and the statistical data comprises a terminal state and transport metrics for the terminal, and
- wherein the ML model pre-processes the statistical data to homogenize and to normalize the statistical data prior to the analyzing.
Dependencies are inferred from the claim text.