Wireless device power optimization utilizing artificial intelligence and/or machine learning

Patent metadata

Field	Value
Publication number	US-11770764-B2
Application number	US-202217868332-A
Country	US
Kind code	B2
Filing date	Jul 19, 2022
Priority date	Nov 13, 2019
Publication date	Sep 26, 2023
Grant date	Sep 26, 2023

Abstract

A method of reducing a power consumption of wireless communication circuitry of an edge device according to one embodiment includes determining a delivery traffic indication map (DTIM) interval of a wireless access point communicatively coupled to the edge device via the wireless communication circuitry of the edge device and adjusting a wake-up interval of the wireless communication circuitry of the edge device based on the DTIM interval to reduce the power consumption of the wireless communication circuitry of the edge device.

First claim

What is claimed is:

1. A method of reducing a power consumption of wireless communication circuitry of an edge device, the method comprising:
determining, by the edge device, a delivery traffic indication map (DTIM) interval of a wireless access point communicatively coupled to the edge device via the wireless communication circuitry of the edge device;
adjusting, by the edge device, a wake-up interval of the wireless communication circuitry of the edge device based on the DTIM interval to reduce the power consumption of the wireless communication circuitry of the edge device;
applying, by the edge device, machine learning with one or more inputs associated with acknowledgement data that identifies signal reliability of communications with the wireless access point; and
adjusting, by the edge device and based on the machine learning, a transmit power of the wireless communication circuitry to reduce the power consumption of the wireless communication circuitry of the edge device.

2. The method of claim 1 , further comprising determining, by the edge device, a number of beacons from the wireless access point that can be ignored without loss of a communication connection between the edge device and the wireless access point.

3. The method of claim 2 , wherein adjusting the wake-up interval of the wireless communication circuitry of the edge device comprises adjusting the wake-up interval of the wireless communication circuitry of the edge device based on the DTIM interval and the number of beacons.

4. The method of claim 1 , wherein adjusting the wake-up interval of the wireless communication circuitry of the edge device comprises applying machine learning with one or more inputs associated with the DTIM interval and disconnect tracking data that identifies information associated with one or more disconnections between the edge device and the wireless access point.

5. A method of reducing a power consumption of wireless communication circuitry of an edge device configured to communicate with a wireless access point, the method comprising:
determining, by the edge device, a reduced transmit power of the wireless communication circuitry of the edge device sufficient for reliable communication with the wireless access point, wherein the reduced transmit power is reduced relative to a full transmit power of the wireless communication circuitry of the edge device;
adjusting, by the edge device, a transmit power of the wireless communication circuitry of the edge device based on the reduced transmit power determined to be sufficient for reliable communication with the wireless access point, wherein adjusting the transmit power of the wireless communication circuitry comprises applying machine learning with one or more inputs associated with acknowledgment data that identifies signal reliability of communications with the wireless access point.

6. The method of claim 5 , further comprising determining, by the edge device, a position of the edge device based on sensor data; and
wherein adjusting the transmit power of the wireless communication circuitry of the edge device comprises adjusting the transmit power of the wireless communication circuitry of the edge device based on the reduced transmit power determined to be sufficient for reliable communication with the wireless access point and the position of the edge device.

7. The method of claim 1 , wherein the wireless communication circuitry comprises a Wi-Fi communication circuitry.

8. The method of claim 1 , wherein the edge device comprises an access control device including a physical lock mechanism to secure a corresponding passageway; and
wherein the wireless access point comprises a router.

9. The method of claim 1 , wherein adjusting the wake-up interval of the wireless communication circuitry of the edge device based on the DTIM interval to reduce the power consumption of the wireless communication circuitry of the edge device comprises adjusting the wake-up interval of the wireless communication circuitry of the edge device to optimize the power consumption of the wireless communication circuitry of the edge device.

10. An edge device, comprising:
a Wi-Fi communication circuitry;
at least one processor; and
at least one memory comprising a plurality of instructions stored thereon that, in response to execution by the at least one processor, causes the edge device to:
determine a reduced transmit power of the Wi-Fi communication circuitry sufficient for reliable communication with a wireless access point, wherein the reduced transmit power is reduced relative to a full transmit power of the Wi-Fi communication circuitry; and
adjust a transmit power of the Wi-Fi communication circuitry based on the reduced transmit power determined to be sufficient for reliable communication with the wireless access point, wherein to adjust the transmit power of the Wi-Fi communication circuitry comprises to apply machine learning with one or more inputs associated with acknowledgment data that identifies signal reliability of Wi-Fi communications with the wireless access point.

11. The edge device of claim 10 , wherein the plurality of instructions further causes the edge device to determine a position of the edge device based on sensor data; and
wherein to adjust the transmit power of the Wi-Fi communication circuitry comprises to adjust the transmit power of the Wi-Fi communication circuitry based on the reduced transmit power determined to be sufficient for reliable communication with the wireless access point and the position of the edge device.

12. The edge device of claim 10 , further comprising a physical lock mechanism having at least one of a latch or a bolt to secure a corresponding passageway.

13. The method of claim 1 , further comprising determining, by the edge device, a position of the edge device based on sensor data; and
wherein adjusting the transmit power of the wireless communication circuitry comprises adjusting the transmit power of the wireless communication circuitry based on the position of the edge device.

14. The method of claim 5 , wherein the wireless communication circuitry comprises a Wi-Fi communication circuitry.

15. The method of claim 5 , wherein the edge device comprises an access control device including a physical lock mechanism to secure a corresponding passageway.

16. The method of claim 15 , wherein the edge device is secured to a barrier that secures the corresponding passageway.

17. The method of claim 8 , wherein the edge device is secured to a barrier that secures the corresponding passageway.

18. The edge device of claim 10 , wherein the plurality of instructions further causes the edge device to determine a number of beacons from the wireless access point that can be ignored without loss of a Wi-Fi communication connection between the edge device and the wireless access point.

19. The edge device of claim 18 , wherein the plurality of instructions further causes the edge device to adjust a wake-up interval of the Wi-Fi communication circuitry based on a delivery traffic indication map (DTIM) interval and the number of beacons.

Assignees

• Schlage Lock Co Llc

Inventors

• Kincaid Ryan C
• Venkateswaran Srikanth
• Prostko Robert

Classifications

• G06N3/0499

  Feedforward networks · CPC title

• H04W52/0203 Primary

  in the radio access network or backbone network of wireless communication networks · CPC title

• G06N20/00

  Machine learning · CPC title

• H04W52/38

  TPC being performed in particular situations · CPC title

• H04W84/12

  WLAN [Wireless Local Area Networks] · CPC title