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

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; and

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, 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.

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. 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, wherein the adjusting the wake-up interval comprises applying machine learning with one or more inputs associated with the DTIM interval;

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; and

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.

5. The method of claim 4 , wherein the adjusting the wake-up interval further comprises disconnecting tracking data that identifies information associated with one or more disconnections between the edge device and the wireless access point.

6. 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;

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; and

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 the adjusting the transmit power of comprises applying machine learning with one or more inputs associated with acknowledgment data that identifies signal reliability of communications with the wireless access point.

7. The method of claim 4 , 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.

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

9. 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.

10. 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.

11. 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 delivery traffic indication map (DTIM) interval of a wireless access point communicatively coupled to the edge device via the Wi-Fi communication circuitry; and

adjust a wake-up interval of the Wi-Fi communication circuitry based on the DTIM interval to reduce the power consumption of the edge device, wherein to adjust the wake-up interval of the Wi-Fi communication circuitry comprises to apply 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 Wi-Fi communication circuitry and the wireless access point.

12. The edge device of claim 11 , 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.

13. The edge device of claim 12 , wherein to adjust the wake-up interval of the Wi-Fi communication circuitry comprises to adjust the wake-up interval of the Wi-Fi communication circuitry based on the DTIM interval and the number of beacons.

14. 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 delivery traffic indication map (DTIM) interval of a wireless access point communicatively coupled to the edge device via the Wi-Fi communication circuitry;

adjust a wake-up interval of the Wi-Fi communication circuitry based on the DTIM interval to reduce the power consumption of the edge device;

determine a reduced transmit power of the Wi-Fi communication circuitry sufficient for reliable communication with the wireless access point, wherein the reduced transmit power is reduced relative to a full transmit power of the Wi-Fi communication circuitry;

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 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.

15. The edge device of claim 14 , wherein to adjust the wake-up interval of the Wi-Fi communication circuitry comprises to apply 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 Wi-Fi communication circuitry and the wireless access point.

16. The edge device of claim 11 , 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.

17. The edge device of claim 14 , 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.

18. The edge device of claim 11 , further comprising a physical lock mechanism having at least one of a latch or a bolt to secure a corresponding passageway.