Azure-Samples/digital-twins-mvad-integration
A code sample for integrating Azure Digital Twins to a multivariate anomaly detection solution (Anomaly Detector)
This toolkit helps operations engineers or asset managers monitor complex physical systems by detecting unusual behavior in their digital twin models. It takes time-series data from multiple sensors or operational parameters within an Azure Digital Twin environment and outputs identified anomalies, allowing users to proactively address potential issues in real assets or processes.
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Use this if you manage physical assets or operational environments modeled in Azure Digital Twins and need to automatically identify multivariate anomalies to maintain normal operations or prevent defects.
Not ideal if your systems are not modeled in Azure Digital Twins or if you only need to detect simple, single-variable anomalies.
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MIT
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Last pushed
Jul 06, 2023
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