Systems and methods for automated anomaly detection in univariate time-series
US12314125B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Jul 27, 2023 |
| Grant date | May 27, 2025 |
| Priority date | — |
| Expiry date | Sep 11, 2043 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06F16/2474
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Systems and methods of anomaly detection in time-series are disclosed. A time-series dataset is received and a set of segments is iteratively defined from the time-series dataset by identifying a set of changepoints in the time-series dataset based on a changepoint type and a sensitivity parameter, determining whether the set of segments defined by the changepoints satisfy at least one threshold criteria, and modifying the sensitivity parameter when the threshold criteria is not met or outputting the set of segments when the threshold criteria is met. A segment-specific anomaly detection threshold is determined for each segment in the set of segments and a set of anomaly-flagged segments is generated. The set of anomaly flagged segments are generated by an anomaly detection process based on the segment-specific anomaly detection threshold for a corresponding segment. An anomaly-flagged time-series is generated by combining the set of anomaly-flagged segments.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.