US 12,265,821 B2
Orchestrator reporting of probability of downtime from machine learning process
Zohar Fox, Tel Aviv (IL)
Assigned to Aurora Labs Ltd., Tel Aviv (IL)
Filed by Aurora Labs Ltd., Tel Aviv (IL)
Filed on Oct. 17, 2023, as Appl. No. 18/488,485.
Application 18/488,485 is a continuation of application No. 17/818,197, filed on Aug. 8, 2022, granted, now 11,829,750.
Application 17/818,197 is a continuation of application No. 17/466,560, filed on Sep. 3, 2021, granted, now 11,442,721, issued on Sep. 13, 2022.
Application 17/466,560 is a continuation of application No. 17/205,626, filed on Mar. 18, 2021, granted, now 11,137,997, issued on Oct. 5, 2021.
Application 17/205,626 is a continuation of application No. 16/874,887, filed on May 15, 2020, granted, now 10,983,784, issued on Apr. 20, 2021.
Application 16/874,887 is a continuation of application No. 16/450,022, filed on Jun. 24, 2019, granted, now 10,691,525, issued on Jun. 23, 2020.
Application 16/450,022 is a continuation of application No. 16/044,435, filed on Jul. 24, 2018, granted, now 10,387,139, issued on Aug. 20, 2019.
Claims priority of provisional application 62/560,224, filed on Sep. 19, 2017.
Claims priority of provisional application 62/536,767, filed on Jul. 25, 2017.
Prior Publication US 2024/0045668 A1, Feb. 8, 2024
This patent is subject to a terminal disclaimer.
Int. Cl. G06F 8/658 (2018.01); B60W 50/02 (2012.01); B60W 50/04 (2006.01); G06F 8/60 (2018.01); G06F 8/65 (2018.01); G06F 8/654 (2018.01); G06F 8/656 (2018.01); G06F 8/71 (2018.01); G06F 9/4401 (2018.01); G06F 9/445 (2018.01); G06F 11/07 (2006.01); G06F 11/14 (2006.01); G06F 11/16 (2006.01); G06F 11/3604 (2025.01); G06F 12/02 (2006.01); G06F 12/06 (2006.01); G06F 16/188 (2019.01); G06F 21/57 (2013.01); G06N 20/00 (2019.01)
CPC G06F 8/658 (2018.02) [B60W 50/02 (2013.01); B60W 50/0205 (2013.01); B60W 50/0225 (2013.01); B60W 50/04 (2013.01); B60W 50/045 (2013.01); G06F 8/60 (2013.01); G06F 8/65 (2013.01); G06F 8/654 (2018.02); G06F 8/656 (2018.02); G06F 8/71 (2013.01); G06F 9/4401 (2013.01); G06F 9/445 (2013.01); G06F 9/44521 (2013.01); G06F 11/0721 (2013.01); G06F 11/0751 (2013.01); G06F 11/079 (2013.01); G06F 11/0793 (2013.01); G06F 11/1433 (2013.01); G06F 11/1629 (2013.01); G06F 11/3612 (2013.01); G06F 12/0284 (2013.01); G06F 12/0646 (2013.01); G06F 16/188 (2019.01); G06F 21/57 (2013.01); G06F 21/572 (2013.01); G06F 21/577 (2013.01); B60W 2050/021 (2013.01); G06F 8/66 (2013.01); G06F 2212/1008 (2013.01); G06F 2212/1044 (2013.01); G06F 2212/1056 (2013.01); G06F 2221/033 (2013.01); G06N 20/00 (2019.01)] 20 Claims
OG exemplary drawing
 
1. A non-transitory computer-readable medium including instructions that, when executed by at least one processor, cause the at least one processor to perform error-monitoring operations for remediating controller errors, comprising:
receiving operational data from a plurality of controllers, the operational data being indicative of a plurality of runtime attributes associated with the plurality of controllers, the plurality of runtime attributes comprising at least one of a memory activity or a processing activity;
generating a model of the operational data received from the plurality of controllers based on a predetermined set of controller functionalities, wherein the model is based on time-based analysis of controller attributes associated with one or more of the plurality of controllers, the controller attributes associated with the plurality of controllers comprising at least one of a central processing unit operation, information stored in a memory component, or information accessed from a memory component;
receiving live, runtime updates from the plurality of controllers; and
identifying, based on a comparison of the live, runtime updates to the model, an error of a monitored controller.