Connecting simple devices to IoT Central

Once you start collecting data in an IoT solution, you will need some kind of dashboard to represent the raw or aggregated data.

IoT projects typically start as a POC to validate IoT scenarios. When the POC success, a pilot project is started to check scalability, monitoring, maintainability, etc.

Microsoft provides multiple solutions for these various scenarios. The most lightweight solution is IoT Central.

Experience the simplicity of SaaS for IoT (Internet of Things), with no cloud expertise required‚ÄĒAzure IoT Central is a fully managed global IoT SaaS (software-as-a-service) solution that makes it easy to connect, monitor, and manage your IoT assets at scale. Bring your connected products to market faster while staying focused on your customers.”

You can start with a 7-day trial or with pay-as-you-go. This last option is free if you limit yourself to 5 actual or simulated devices.

At this moment, Microsoft has examples for the Raspberry Pi, the MX Chip IoT Devkit and Windows 10 IoT Core.

But what if you want to connect your own device? Is this simple to do too?

Let’s check this out.

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One Azure IoT accelerator to rule them all

The family of Azure IoT resources is very diverse. If you know what you are doing and have developers available you can have a great time with the many PaaS cloud resources.

If you have devices which need internet connectivity but you have no developers, you can check out IoT Central, the SaaS IoT solution.

Recently, Microsoft announced a very powerful integration with other leading IoT Platforms like SAP Leonardo and PTC Thingworx. Both can connect directly with the Azure IoT Hub, the cloud gateway. This opens a broad range of integration opportunities.

And last but not least, you can start with prebuild verticals, Azure IoT accelerators, formerly known as Azure IoT suites. If you have developers available but you do not want to start from scratch, check them out. You can deploy a typical accelerator in 15 minutes to see how they behave. And the smart thing is, all the code behind the logic is available for free on Github.

The most known accelerators are:

  • Remote Monitoring (version two is based on microservices)
  • Connected Factory (support OPC-UA protocol)
  • Predictive Maintenance

But there are also third-party accelerators.

If you are a developer or architect, it’s time well spend checking them out!

Remote monitoring

The remote monitoring is a good starting point, it has a lot of out-of-the-box features:

In one of our current projects, we were looking for a rule engine. And while playing with the demo of the Remote Monitoring Accelerator, we stumbled on one.

The picture shown above is not really helping to explain how this rule engine works and you can try to read about it or check out the code on GitHub.

The features of this rules engine are both simple and powerful:

  • Define rules for alarms or even actions as JSON files in blob storage
  • Bind rules to groups of devices (defined as CSV file in blob storage)
  • Rules can react to ‘instant’ messages using Javascript comparisons
  • Rules can react to time windows aggregations using Javascript comparisons

And the best feature is that the rules engine is based on Azure Stream Analytics. Therefore it’s modular and it can be separated and reused completely in your own solution.

In this blog, we will see how it’s done.

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Event Hub alerts, great for detecting drops in connectivity

If we look at the Azure IoT Reference Architecture we see how streaming data is the heart of the IoT platform:

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Data arrives at the IoT Hub and can be routed to any Azure resource using eg. the IoT Hub routing, Stream Analytics jobs and Event Hubs.

This gives us the maximum flexibility to divide the data into three major data streams or storage:

  1. Hot path – Event, Alert, Conditions
  2. Warm path – aggregated data, data for reporting
  3. Cold path – the raw data, mainly untouched and available in large quantities; great for data scientists

But there is an often unseen, even ignored forth stream. And that is the stream of data for monitoring.

In my earlier blogs, I wrote several times hoe heartbeats en watchdogs can tell the story about the quality of the data. And I have shown how eg. Azure Functions and notification services can improve the insights about the quality of the communication.

Today I want to add a little gem to that list.

Let’s check out Monitoring Alerts in Event Hubs. It’s part of the overall Monitoring service in Azure.

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Compare previous and current message in Stream Analytics

Last week I was testing the temporary storage in IoT Edge. I was interested in the stability so I wanted to know if messages were missing or maybe even coming in twice.

I have this heartbeat module which produces a counter. So I am able to generate messages which can be measured as a sequence.

One way is to check this using your eyes ūüôā

But this can be seen as a more generic issue, comparing two messages after each other. So I was thinking about Azure Stream Analytics. This should be the perfect tool for this job.

Let’s check out how we can compare subsequent messages using Stream Analytics.

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Visualize Azure IoT Edge device routes as a flowchart in Asp.Net MVC

If you look at the routes page in Azure IoT Edge configuration wizard, what do you prefer?

The current notation:

Or do you prefer a flow chart like this:

The routes in Azure IoT edge are a clever solution to describe how messages from one module are sent to another. But the JSON notation can become less readable once you add more (up to twenty) modules. That could end up eg. nineteen routes or more!

Just as an experiment I was thinking about how the ease the experience using a graphical interface.

I prefer the second solution, probably just like you.

So let’s look at how you can create the same¬†experience with your routes of your IoT Edge device.

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Integrating SQLite in Azure IoT Edge for local storage

Microsoft has opened the Azure Marketplace for IoT Edge modules. This makes it easy to find and install IoT Edge modules into your own IoT Edge devices.

At this moment a dozen or more modules are available:

We see a few well-known modules from Microsoft which support SQL Server, Modbus, OPC-UA or the Temperature sensor simulation.

One of these modules is supporting SQLite.

What is SQLite?

According to the homepage, SQLite is an in-process library that implements a self-contained, serverless, zero-configuration, transactional SQL database engine. The code for SQLite is in the public domain and is thus free for use for any purpose, commercial or private. SQLite is the most widely deployed database in the world with more applications than we can count, including several high-profile projects.

What does the module do?

This IoT Edge module is capable of accessing SQLite databases locally.

Microsoft says:

“Using this module, developers can build Azure IoT Edge solutions with the capability to access SQLite databases. The SQLite module is an Azure IoT Edge module, capable of executing SQL queries sent from other modules, and return the result to the senders or to the Azure IoT Hub via the Edge framework. Developers can modify the module tailoring to any scenario.”

The module is open source and both documentation and source code are put on GitHub.

Why should we use this module?

In the past, I checked out the SQL Server IoT module to persist IoT messages locally.

This SQLite module has a few advantages which you will like:

  • It’s lightweight
  • It’s based on a public domain framework
  • It’s integrated with the routing of IoT Edge

For me, that last item, we can integrate the module directly in the routing is interested.

So let’s check out how we can use it.

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Custom IoT Hub assignment in Device Provisioning Service

In my previous blog, I have shown how to provision a device using a real TPM using the Device Provisioning Service (DPS).

Once you are able to provision your IoT devices to the Azure IoT Platform using a DPS, a whole new world of possibilities opens up for you.

Before, you registered your device to one IoTHub. To change it, you had to go to the device and fix it. But now you are able to make a choice between multiple IoT Hubs within the cloud, dynamically!

But what strategy are you going to use?

Microsoft provides three standard strategies out of the box:

  1. Lowest latency (select the nearest IoT Hub)
  2. Evenly weighted distribution (select the IoT Hub with the least amount of devices)
  3. Static configuration (just select one yourself. This is the situation as before)

But there is a new strategy which is very flexible:

This fourth strategy makes use of a custom Azure Function which you can write yourself.

You could, for instance, access a database and read some data before you make the decision to which IoTHub you assign this device.

Let’s see how we can build a custom function ourselves and get the most out of it.

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