Connect Azure Digital twins to a controller.

Question

Hello,

To continue my project my next step would be to connect Azure IoT Hub with an controller which is : IFM cr0303.

Do you know if it is possible to link it or would I have to do it linking with Azure digital twins the database where the data of my controller is stored?

I also wanted to know how I can follow my digital twin, to train it and predict depending on the characteristics that I have?

Answer 1

Hello

I checked the datasheet, this device is a PLC with canbus, running on Codysis.

I have no experience with this particular device so I'm not sure if it can connect to the IoT Hub directly using this client.

If not, you need some edge solution. This is some Linux or Windows device (IPC, VM) connected to both the local network and the cloud (using a secured outbound connection). Check out this MS Learn training module for more details.

Your device needs to connect with the edge device using communication on the local network. The Edge device will translate the local protocol (eg MQTT, OPC-UA) to messages sent to the cloud.

From there, your IoT Hub messages need to be transferred to your Azure Digital Twins solution.

A common solution is introducing an Azure Function to update Digital Twins living inside your Azure Digital Twin environment.

Notice that Azure Digital Twins is not a database. It only stores the last known values of twin properties.

You can however connect Azure Data Explorer (which is a TimeSeries database) to Azure Digital Twin to record historical values.

If you want to make use of the ADT History connection, you need to create a full Azure Data Explorer cluster.

You could however also export the raw IoT Hub data directly (so ignoring ADT output) into the free ADX cluster using an EventHub data import connection.

This could also be your stepping stone for anomaly detection and forecasting.

It's up to you if you want to integrate other Machine learning tools.

I recommend the free MS Learn training paths for Azure Digital Twins and Azure Data Explorer and machine learning.

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