US 12,481,894 B1
Federated on-sensor learning for local device adaptation and global improvement of machine learning model
Syed Shakib Sarwar, Bellevue, WA (US); Barbara De Salvo, Belmont, CA (US); and Xinqiao Liu, Medina, WA (US)
Assigned to Meta Platforms Technologies, LLC, Menlo Park, CA (US)
Filed by META PLATFORMS TECHNOLOGIES, LLC, Menlo Park, CA (US)
Filed on Feb. 7, 2022, as Appl. No. 17/666,455.
Int. Cl. G06N 3/08 (2023.01); G06F 3/01 (2006.01); G06F 16/23 (2019.01); G06N 3/00 (2023.01); G06N 3/098 (2023.01); H04L 9/40 (2022.01); A61B 5/00 (2006.01); G06N 3/047 (2023.01); G16H 10/60 (2018.01); H04L 9/32 (2006.01)
CPC G06N 3/098 (2023.01) [G06F 3/016 (2013.01); G06F 16/2379 (2019.01); G06N 3/002 (2013.01); G06N 3/08 (2013.01); H04L 63/0428 (2013.01); A61B 5/486 (2013.01); G06N 3/047 (2023.01); G16H 10/60 (2018.01); H04L 9/3263 (2013.01)] 20 Claims
OG exemplary drawing
 
1. A method comprising:
receiving, by a smart sensor of an artificial reality headset, parameters of a machine learning model;
updating, by the smart sensor, the machine learning model based on feature data extracted from the sensor data; and
repeatedly performing:
sending, by the smart sensor, encrypted data associated with the machine learning model to a system on chip (SoC) of the headset;
receiving, by the SoC, encrypted data associated with the machine learning model from one or more smart sensors;
sending, by the SoC, encrypted data associated with the machine learning model collected from the one or more smart sensors to a server;
receiving, by the SoC, parameters of a base machine learning model from the server, and
sending, by the SoC, parameters of the base machine learning model to the smart sensor; and
locally updating, by the smart sensor, the received base machine learning model based on the stored feature data.