Book Image

The Azure IoT Handbook

By : Dan Clark
Book Image

The Azure IoT Handbook

By: Dan Clark

Overview of this book

With the rise of cloud-based computing, deploying IoT systems has become more cost-effective for businesses. This transformation has led to developers and architects shouldering the responsibility of creating, managing, and securing these systems, even if they are new to the IoT technology. The Azure IoT Handbook is a comprehensive introduction to quickly bring you up to speed in this rapidly evolving landscape. Starting with the basic building blocks of any IoT system, this book guides you through mobile device management and data collection using an IoT hub. You’ll explore essential tools for system security and monitoring. Following data collection, you’ll delve into real-time data analytics using Azure Stream Analytics and view real-time streaming on a Power BI dashboard. Packed with real-world examples, this book covers common IoT use as well. By the end of this IoT book, you’ll know how to design and develop IoT solutions leveraging intelligent edge-to-cloud technologies implemented on Azure.
Table of Contents (18 chapters)
1
Part 1: Capturing Data from Remote Devices
7
Part 2: Processing the Data
12
Part 3: Processing the Data

Lab – creating an ADX dashboard

In this lab, we will explore how to consume and analyze IoT data using ADX. We will then leverage ADX’s capabilities to create a real-time dashboard that visualizes the IoT data:

  1. Set up IoT Hub and a device capturing data from the Raspberry Pi online simulator (https://azure-samples.github.io/raspberry-pi-web-simulator/#getstarted).
  2. Verify that the signal is being sent to IoT Hub.
  3. Set up an SDX cluster and make sure you enable streaming data.
  4. Create a database and a table in ADX to capture the data.
  5. Define the table mapping between the incoming messages and the table columns.
  6. Create a new dashboard and enter the following KQL using your table name:
    Telemetry
     | where IotHubEnqueuedTime between (['_startTime'] .. ['_endTime']) // Time range filtering
  7. After a few minutes, you should see results when you run the KQL.
  8. Select Add visual next to the Results tab.
  9. Add a line chart showing...