US 11,747,038 B2
Occupancy tracking using sound recognition
Sunil Bondalapati, Frisco, TX (US); and Prasad Mecheri Chandravihar, Richardson, TX (US)
Assigned to Lennox Industries Inc., Richardson, TX (US)
Filed by Lennox Industries Inc., Richardson, TX (US)
Filed on Jul. 19, 2022, as Appl. No. 17/868,274.
Application 17/868,274 is a continuation of application No. 17/139,155, filed on Dec. 31, 2020, granted, now 11,448,413.
Prior Publication US 2022/0357065 A1, Nov. 10, 2022
This patent is subject to a terminal disclaimer.
Int. Cl. F24F 11/63 (2018.01); H04R 1/40 (2006.01); H04R 3/00 (2006.01); G10L 25/78 (2013.01); G06F 3/16 (2006.01); G10L 15/22 (2006.01); G10L 25/51 (2013.01); F24F 120/10 (2018.01)
CPC F24F 11/63 (2018.01) [G06F 3/167 (2013.01); G10L 15/22 (2013.01); G10L 25/51 (2013.01); G10L 25/78 (2013.01); H04R 1/406 (2013.01); H04R 3/005 (2013.01); F24F 2120/10 (2018.01)] 20 Claims
OG exemplary drawing
 
1. An occupancy tracking device, comprising:
a network interface operably coupled to a Heating, Ventilation, and Air Conditioning (HVAC) system, wherein the HVAC system is configured to control a temperature of a space;
a memory operable to store a voice data log comprising a plurality of entries, wherein each entry comprises:
a timestamp that identifies when a sound sample was recorded; and
an audio signature that describes characteristics of the sound sample, wherein the audio signature comprises a numerical value that uniquely identifies characteristics of an audio signal; and
a processor operably coupled to the network interface and the memory, the processor configured to:
receive a plurality of sound samples over a predetermined time period;
compute an audio signature for each sound sample from the plurality of sound samples;
populate entries in the voice data log for the plurality of sound samples, wherein populating the entries in the voice data log comprises associating each sound sample with a timestamp and an audio signature;
identify one or more clusters for the populated entries based on an audio signature that is associated with the populated entries, wherein each cluster comprises audio signatures that are associated with a voice of a person;
determine a number of clusters that are identified;
determine a predicted occupancy level based on the number of clusters that are identified, wherein the predicted occupancy level is equal to the number of clusters that are identified; and
control the HVAC system based on the predicted occupancy level.