US 12,266,185 B2
Method and system for real-time health monitoring and activity detection of users
Arvind Radhakrishnen, Tega Cay, SC (US); Manish Purohit, Flower Mound, TX (US); and Sahil Sharma, Deerfield, IL (US)
Filed by Arvind Radhakrishnen, Tega Cay, SC (US); Manish Purohit, Flower Mound, TX (US); and Sahil Sharma, Deerfield, IL (US)
Filed on Nov. 15, 2022, as Appl. No. 17/986,998.
Prior Publication US 2023/0071470 A1, Mar. 9, 2023
Int. Cl. H04N 7/18 (2006.01); G06V 10/774 (2022.01); G06V 20/40 (2022.01); G06V 20/52 (2022.01); G16H 40/67 (2018.01); G16H 50/20 (2018.01)
CPC G06V 20/52 (2022.01) [G06V 10/774 (2022.01); G06V 20/41 (2022.01); G06V 20/46 (2022.01); G16H 40/67 (2018.01); G16H 50/20 (2018.01); H04N 7/181 (2013.01)] 20 Claims
OG exemplary drawing
 
1. A system for health monitoring and activity detection of users, the system comprising:
a facility installed with a plurality of cameras,
wherein the cameras are configured to capture a video feed of a user in the facility, and wherein the cameras are further configured to generate a 3D map of the facility by processing the video feed; and
an AI edge device configured to:
receive the captured video feed from the cameras in real-time from the cameras, wherein the captured video feed is received in an encrypted and secured format;
process the captured video feed to detect one or more activities of the user, and generate a real-time 3D map of the facility and identify specific health-related events, based on predefined patterns, wherein the AI edge device lookouts for a specific action of the user captured in the same video feed and the action is compared with the predefined patterns, and wherein, if a match is found, then the AI edge device uses stored annotations of the predefined patterns to identify a current activity of the user captured in the video feed;
generate one or more alerts based on the detected activities; and
notify other users associated with the user based on the generated alerts via a notification interface,
wherein the above operations including the receiving, the processing, the generating, and the notifying are performed by the AI edge device on its edge and no data is transmitted over from the AI edge device to a remote server for further processing and storage.