Machine learning based energy use prediction
AssigneeExergi Predictive LLC
InventorsHarish Panneer Selvam, Andrew Kotz, William Northrop
Life of this patent
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Abstract
Techniques for using machine learning to predict the energy use of mobile actors such as a moving person or a mobile machine, as well as technologies for using such predictions. Energy use prediction for a moving person or a mobile machine can include an energy use prediction for a person or machine moving from one place to another regardless of the complexity of the corresponding route and the complexity of other variables involved. Mobile machines can include any type of mobile machine for any industrial or consumer use. Mobile machines can include watercraft, aircraft, terrestrial vehicles, automobiles, or robots, for example.
Claims21
1-20. (canceled)
A method, comprising:
- generating, by a computing system, a speed-time profile for at least one route from a starting point to a destination point, based on a first model and a task profile used as an input for the first model;
- predicting, by the computing system, an energy-use profile for the at least one route, based on a second model and the speed-time profile used as an input for the second model;
- using, by the computing system, the energy-use profile to at least partially control a mobile machine or to generate a graphical user interface according to data in the energy-use profile;
- repeating the generation of the speed-time profile and the energy-use profile in a statistical analysis to generate a statistical distribution;
- and
- using the statistical distribution of the energy-use profile to generate a graphical user interface according to data in the statistical distribution.
A method, comprising:
- generating, by a computing system, a speed-time profile for at least one route from a starting point to a destination point, based on a first model and a task profile used as an input for the first model;
- predicting, by the computing system, an energy-use profile for the at least one route, based on a second model and the speed-time profile used as an input for the second model;
- using, by the computing system, the energy-use profile to at least partially control a mobile machine or to generate a graphical user interface according to data in the energy-use profile;
- repeating the generation of the speed-time profile and the energy-use profile in a statistical analysis to generate a statistical distribution;
- using the statistical distribution of the energy-use profile to generate a graphical user interface according to data in the statistical distribution;
- and
- emulating, in the graphical user interface, a state of an actor to be directed or controlled according to the energy-use profile.
A method, comprising:
- generating, by a computing system, a speed-time profile for at least one route from a starting point to a destination point, based on a first model and a task profile used as an input for the first model;
- predicting, by the computing system, an energy-use profile for the at least one route, based on a second model and the speed-time profile used as an input for the second model;
- using, by the computing system, the energy-use profile to at least partially control a mobile machine or to generate a graphical user interface according to data in the energy-use profile;
- repeating the generation of the speed-time profile and the energy-use profile in a statistical analysis to generate a statistical distribution;
- using the statistical distribution of the energy-use profile to generate a graphical user interface according to data in the statistical distribution;
- and
- emulating, in the graphical user interface, a state of an actor to be directed or controlled according to the energy-use profile,
- wherein the generating the speed-time profile is also based on an actor profile used as a second input for the first model, and
- wherein the actor profile input and the task profile input are two separate inputs of the first model.
Dependencies are inferred from the claim text.