The Azure IoT Suite is a set of Azure services that provides you with a complete solution which helps with the following:

• Collecting data from devices
• Analyzing data streams in-motion
• Storing and querying large datasets
• Visualizing both real-time and historical data
• Integrating with backend systems
• Managing your devices

The Azure IoT Suite can connect with a broad range of devices with the help of IoT SDKs. The data generated by devices can be any operational data.

These devices can send that data to the Azure IoT Hub using the Azure IoT cloud gateway. The IoT solution backend receives, processes, and stores the data from these devices. The Azure IoT and Power BI enables you to analyse the data and present it in the form of dashboards or Power BI reports.

We will understand pre-configured solutions in this section:

• What is a pre-configured solution?
• How remote monitoring works
• How predictive maintenance works
• How connected factory works

Microsoft helps companies to take advantage of IoT to transform business outcomes by providing pre-configured solutions under IoT Suite, a common IoT solution pattern to reduce the time for initial base development. This is comprised of multiple Azure services which are a part of the Microsoft IoT platform. The source code is also available on GitHub, using which, one can customize the solution as per specific business scenarios.

Azure IoT Suite provides two common IoT solution patterns. Each solution is end-to-end, built along with the simulator to generate the telemetry data. These solutions give you the starting point for your IoT case, as well as a lesson on how a common IoT scenario works.

Microsoft Azure IoT provides three common scenarios in the form of pre-configured solutions with IoT Suite:

Remote monitoring: This preconfigured solution connects and monitors devices. Once we deploy the remote monitoring suite on Azure subscription, it also provides a simulator and these simulated devices will keep on generating data for these devices. Once the data is ingested, it will be processed against a set of rules and the data will then be presented on the dashboard. It uses a Bing map to show the live location of the devices.

Predictive maintenance: Predictive maintenance is another common IoT scenario. This solution, once deployed, starts automatically simulating the data. It also provides a predictive model, which is helpful in the case of asset maintenance. In Chapter 6, IoT Suite and Pre-Configured Solutions, we will be creating pre-configured solutions.

Connected factory: When you deploy the connected factory pre-configured solution, this solution is built with a common industrial scenario. In this scenario, factories can be connected to the solution, thus reporting the data values required to find out overall equipment efficiency (OEE) and key performance indicators (KPIs) for the factory operations. The following sections show you how to:

• Monitor factory, production lines, station OEE, and KPI values
• Analyze the telemetry data generated from these devices using Azure Time Series Insights
• Act on alerts to fix issues

It also provides the dashboard view for these actions and operations as a part of this solution.