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:
Jul. 04, 2023

Filed:

Nov. 05, 2021
Applicant:

Sonos, Inc., Santa Barbara, CA (US);

Inventors:

Kurt Thomas Soto, Ventura, CA (US);

Charles Conor Sleith, Waltham, MA (US);

Assignee:

Sonos, Inc., Santa Barbara, CA (US);

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
H04W 4/02 (2018.01); H04B 17/27 (2015.01); H04B 17/318 (2015.01); G06F 3/04847 (2022.01); G08C 17/02 (2006.01); G06F 3/0488 (2022.01); G06F 3/048 (2013.01); H04N 21/2387 (2011.01); H04N 21/472 (2011.01); G06N 20/00 (2019.01); G06F 3/0481 (2022.01); G06F 3/04883 (2022.01); G06F 3/16 (2006.01); G06N 5/04 (2023.01);
U.S. Cl.
CPC ...
H04W 4/023 (2013.01); G06F 3/048 (2013.01); G06F 3/0481 (2013.01); G06F 3/0488 (2013.01); G06F 3/04847 (2013.01); G06F 3/04883 (2013.01); G06F 3/165 (2013.01); G06N 5/04 (2013.01); G06N 20/00 (2019.01); G08C 17/02 (2013.01); H04B 17/27 (2015.01); H04B 17/318 (2015.01); H04N 21/2387 (2013.01); H04N 21/47217 (2013.01); G08C 2201/34 (2013.01); G08C 2201/91 (2013.01);
Abstract

Systems and methods for localizing portable devices are illustrated. One embodiment includes a method for locating a portable device in a network that includes several reference devices. The method measures characteristics of signals transmitted via signal paths between reference devices and a portable device, normalizes the measurements to estimate characteristics of the signal paths, and estimates the likelihood that the portable device is in a particular location. Systems and methods for training prediction models include a method that includes steps for receiving context data for a portable device in a system, wherein the context data includes localization data that describes a location of the portable device, identifying a predicted stationary device based on the context data using a prediction model, identifying a target stationary device from the several stationary devices, training the prediction model based on based on the predicted stationary device and the received input.


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