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. 21, 2023

Filed:

Nov. 10, 2021
Applicant:

Lennox Industries Inc., Richardson, TX (US);

Inventors:

Sridhar Venkatesh, Irving, TX (US);

Payam Delgoshaei, Addison, TX (US);

Janathkumar Manohararaj, McKinney, TX (US);

Assignee:

Lennox Industries Inc., Richardson, TX (US);

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
F24F 11/46 (2018.01); G05B 13/02 (2006.01); F24F 11/64 (2018.01); F24F 11/65 (2018.01); F24F 140/60 (2018.01); F24F 110/10 (2018.01); F24F 120/12 (2018.01); F24F 130/10 (2018.01); F24F 140/50 (2018.01);
U.S. Cl.
CPC ...
F24F 11/46 (2018.01); F24F 11/64 (2018.01); F24F 11/65 (2018.01); G05B 13/026 (2013.01); G05B 13/0265 (2013.01); F24F 2110/10 (2018.01); F24F 2120/12 (2018.01); F24F 2130/10 (2018.01); F24F 2140/50 (2018.01); F24F 2140/60 (2018.01);
Abstract

A heating, ventilation, and air conditioning (HVAC) control device configured to generate the machine learning model using the first set of weights and the second set of weights. The machine learning model is configured to output a probability that a user is present at the space based on an input that identifies a day of the week and a time of a day. The device is further configured to determine a probability that a user is present at the space for a predicted occupancy schedule using the machine learning model, to determine an occupancy status based on a determined probability that a user is present at the space, and to set a predicted occupancy status in the predicted occupancy schedule based on a determined occupancy status for each time entry. The device is further configured to output the predicted occupancy schedule.


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