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You have Azure IoT Edge devices that generate streaming data.
On the devices, you need to detect anomalies in the data by using Azure Machine Learning models. Once an
anomaly is detected, the devices must add information about the anomaly to the Azure IoT Hub stream.
Solution: You deploy Azure Stream Analytics as an IoT Edge module.
Does this meet the goal?
Available in both the cloud and Azure IoT Edge, Azure Stream Analytics offers built-in machine learning based
anomaly detection capabilities that can be used to monitor the two most commonly occurring anomalies:
temporary and persistent.
Stream Analytics supports user-defined functions, via REST API, that call out to Azure Machine Learning
endpoints.
References:
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