US 12,293,583 B2
Notification priority sequencing for video security
Peiman Amini, Mountain View, CA (US); and Joseph Amalan Arul Emmanuel, Cupertino, CA (US)
Assigned to Arlo Technologies, Inc., Carlsbad, CA (US)
Filed by Arlo Technologies, Inc., Carlsbad, CA (US)
Filed on Aug. 7, 2023, as Appl. No. 18/366,325.
Application 18/366,325 is a continuation in part of application No. 17/358,259, filed on Jun. 25, 2021, granted, now 11,756,390.
Application 17/358,259 is a continuation in part of application No. 16/276,422, filed on Feb. 14, 2019, granted, now 11,076,161, issued on Jul. 27, 2021.
Claims priority of provisional application 62/633,017, filed on Feb. 20, 2018.
Prior Publication US 2023/0386207 A1, Nov. 30, 2023
Int. Cl. G08B 21/00 (2006.01); G06V 20/40 (2022.01); H04N 23/66 (2023.01)
CPC G06V 20/44 (2022.01) [G06V 20/46 (2022.01); H04N 23/66 (2023.01)] 20 Claims
OG exemplary drawing
 
1. A camera comprising:
at least one hardware processor; and
at least one non-transitory memory storing instructions, which, when executed by the at least one hardware processor, cause the camera to:
capture video at a particular time,
wherein information describing the particular time is embedded within the video;
extract a feature vector from the video,
wherein the feature vector describes an event depicted by the video and the particular time;
determine, using a machine learning model embedded in the camera, a priority sequence, based on the feature vector, for providing a notification to at least one of a plurality of user devices,
wherein the machine learning model is trained based on user preferences and characteristics of the plurality of user devices,
wherein the user preferences are related to the particular time and the characteristics of the plurality of user devices, and
wherein determining the priority sequence is performed using edge computing; and
provide the notification to the at least one of the plurality of user devices based on the priority sequence.