US 12,137,124 B2
Detecting physical anomalies of a computing environment using machine learning techniques
Mahmoud Hussein Hamouda, Giza (EG)
Assigned to Dell Products L.P., Round Rock, TX (US)
Filed by Dell Products L.P., Round Rock, TX (US)
Filed on Jan. 20, 2022, as Appl. No. 17/579,943.
Prior Publication US 2023/0231886 A1, Jul. 20, 2023
Int. Cl. G06F 15/16 (2006.01); G16Y 40/50 (2020.01); H04L 9/40 (2022.01)
CPC H04L 63/205 (2013.01) [G16Y 40/50 (2020.01)] 20 Claims
OG exemplary drawing
 
1. A computer-implemented method comprising:
monitoring a physical environment corresponding to at least one component of a distributed computing system using at least one sensor that is at least partially within the at least one component;
performing a local machine learning process, independently executed by the at least one component, comprising:
analyzing data generated by the at least one sensor to detect one or more physical anomalies associated with the physical environment, and
in response to detecting a physical anomaly, selecting at least one automated action, involving at least one additional component of the distributed computing system, to at least partially mitigate the physical anomaly; and
initiating a performance of the at least one automated action;
wherein the method is performed by at least one processing device comprising a processor coupled to a memory.