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:
Mar. 05, 2024

Filed:

Sep. 20, 2022
Applicant:

Motorola Solutions, Inc., Chicago, IL (US);

Inventors:

Leszek Wojcik, Cracow, PL;

Grzegorz Chwierut, Cracow, PL;

Pawel Pluszynski, Cracow, PL;

Michal Janowski, Cracow, PL;

Assignee:

MOTOROLA SOLUTIONS, INC., Chicago, IL (US);

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06F 11/30 (2006.01); G06F 11/34 (2006.01); G06N 20/00 (2019.01); H04L 41/0803 (2022.01); H04L 41/16 (2022.01); H04L 67/00 (2022.01);
U.S. Cl.
CPC ...
G06F 11/3051 (2013.01); G06F 11/3409 (2013.01); G06N 20/00 (2019.01); H04L 41/0803 (2013.01); H04L 41/16 (2013.01); H04L 67/34 (2013.01);
Abstract

Device configurations for a machine-learned model. A device analytics system includes an electronic processor configured to determine, for a machine-learned model configured to detect a plurality of features, a prioritization ranking for a plurality of input parameters provided to the machine-learned model and receive, for each device, a confidence value for each feature included in the plurality of features. The electronic processor is configured to determine, for each device included in the plurality of devices, a performance value for each feature included in the plurality of features based on the prioritization ranking for the plurality of input parameters and the confidence value for each feature for the respective device. The electronic processor is configured to select, based on the performance value for each device included in the plurality of devices for a feature, a device configuration for the machine-learned model, and implement the selected device configuration.


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