US Patent 11271957 Contextual anomaly detection across assets

Methods, systems, and computer program products for contextual anomaly detection across assets are provided herein. A method includes obtaining time-series data frames corresponding to assets; clustering the assets into one or more cohorts based on the time-series data frames, each cohort comprising assets having statistically similar time-series data frames; for each given asset within each cohort: applying a time-context window to the portion of the time-series data frames corresponding to the given asset to generate at least one transformed data frame, and determining an asset distribution for the given asset based on the at least one transformed data frame; determining one or more of that at least one of the assets within at least one of the cohorts is anomalous and that at least one of the cohorts is anomalous; and causing at least one remediation action to be performed based on the determining.