The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.

The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.

Date of Patent:
Dec. 28, 2021

Filed:

Oct. 31, 2017
Applicant:

Microsoft Technology Licensing, Llc, Redmond, WA (US);

Inventors:

Xiaoyu Chai, Issaquah, WA (US);

Choo Yei Chong, Redmond, WA (US);

Ioana Laura Marginas, Bellevue, WA (US);

Eleanor Ann Robinson, Sammamish, WA (US);

Dale R. Johnson, Sammamish, WA (US);

Xinyi Zhang, Issaquah, WA (US);

Xiao Cai, Bellevue, WA (US);

Assignee:
Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G05B 23/02 (2006.01); G06F 9/30 (2018.01); G06N 20/00 (2019.01); G06F 16/2457 (2019.01); G06F 9/451 (2018.01); G06F 9/445 (2018.01);
U.S. Cl.
CPC ...
G05B 23/0216 (2013.01); G06F 9/30029 (2013.01); G06F 9/44505 (2013.01); G06F 9/453 (2018.02); G06F 16/2457 (2019.01); G06N 20/00 (2019.01);
Abstract

Technologies are described for utilizing machine learning ('ML') to adjust operational characteristics of a computing system based upon detected HID activity. Labeled training data is collected with user consent that includes data describing HID activity and data that identifies user activity taking place on a computing device when the data HID activity took place. A ML model is trained using the labeled training data that can receive data describing current HID activity and identify user activity currently taking place on another computing device based upon the current HID activity. The ML model can then select features of the other computing device that are beneficial to the identified user activity. The ML model can then cause one or more operational characteristics of the other computing device to be adjusted based upon the identified user activity, thereby saving valuable computing resources. A UI can also be presented that describes the identified features.


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