The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.

The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.

Date of Patent:
Jun. 13, 2023

Filed:

May. 05, 2020
Applicant:

International Business Machines Corporation, Armonk, NY (US);

Inventors:

Francesco Pierri, Salerno, IT;

Ioana Giurgiu, Zurich, CH;

Monney Serge, Pully, CH;

Mitch Gusat, Langnau a.A., CH;

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06F 11/34 (2006.01); G06F 16/2458 (2019.01); G06N 5/04 (2023.01); G06N 20/00 (2019.01); G06F 11/07 (2006.01);
U.S. Cl.
CPC ...
G06F 16/2474 (2019.01); G06F 11/079 (2013.01); G06F 11/3447 (2013.01); G06F 11/3452 (2013.01); G06N 5/04 (2013.01); G06N 20/00 (2019.01);
Abstract

Aspects of the present invention disclose a method and system for anomaly detection for a data source. The method includes one or more processors identifying unexpected values of monitoring measurands in a monitored time series utilizing an anomaly detection algorithm. A data source provides sensor data, including values of a first group of measurands, which include monitoring measurands. The method further includes determining that values of a second group of one or more of the measurands of a subset of sensor data indicates an anomaly utilizing the anomaly detection algorithm. The method further includes sending anomalous data indicative of the subset of sensor data to a root cause analysis system and receiving corresponding feedback that is indicative of a result of a root cause analysis of the subset of sensor data and comprises a third group of the measurands. The method further includes adapting the anomaly detection algorithm.


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