Azure Stream Analytics anomaly detection on the edge

Back in 2018, the Azure Stream Analytics team announced Anomaly detection for Azure Stream Analytics. And, it was also supported on the Azure IoT Edge. In November 2018, I was allowed to demonstrate this at the SPS IPC Drives in Nuremberg:

Since then, anomaly detection has become a first citizen of Azure Stream Analytics.

Azure Stream Analytics Anomaly Detection is able to ‘automatically’ detect spikes, dips, and trends in a stream of values. This is based on math and all you need to do is to specify how many values you expect and how sensitive the detection must be. It is in fact Machine Learning, in the end. So it is a prediction with a certain certainty…

And it’s just part of the Stream Analytics query language. So on the edge, we can deploy a Stream Analytics module (the engine of stream analytics). This is a fixed module from Microsoft.

All you have to do is feeding it a query, inputs, outputs and, user-defined functions if available:

We can define all this in the cloud, inside a stream analytics job and we can even test it. Those parts are then packed as a blob and put in blob storage. The Stream Analytics job can then download it and run it.

The inputs and outputs of the Stream Analytics job can be attached to the normal Azure IoT Edge routing mechanism.

Let’s see how this is set up:

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IoT on Microsoft Ignite, March 2021

Although 2021 seems to be a copy of 2021, the Microsoft Ignite has brought us a lot of possitive new ragarting new Microsoft technology we can all wait for. Or even better, it’s available right now.

The biggest Azure IoT on the current Ignite is Azure Percept:

 a comprehensive, easy-to-use platform with added security for creating responsible edge AI solutions. With Azure Percept, we have simplified AI on the edge from silicon to service

Documentation can be found here. The dedicated hardeware (Azure Percept DK is designed as a reference implementation) can be found here. (Datasheet DK | Datasheet Vision) (Availability around the world)

But there were also smaller gems. On of them is “30 days to learn it“. You can complete the IoT Developer challenge and get 50 percent off the cost of a Microsoft Certification:

Implement and maintain the cloud and edge components of an IoT solution. Learn how to connect devices, move workloads to the edge, and build scalable, enterprise-grade, secured IoT solutions on Azure to increase performance, reduce costs, and optimize operations. It’ll only take about 15 hours to discover how to securely connect IoT devices to the cloud, build the intelligent edge, and develop solutions with Azure IoT Central.

There are more certificates to earn. See the site for all eight challenges!

All sessions are available now in the session catalog for you to watch. Below, I summerized all IoT related sessions.

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