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Hands-On Edge Analytics with Azure IoT

You're reading from   Hands-On Edge Analytics with Azure IoT Design and develop IoT applications with edge analytical solutions including Azure IoT Edge

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Product type Paperback
Published in May 2020
Publisher Packt
ISBN-13 9781838829902
Length 262 pages
Edition 1st Edition
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Author (1):
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Colin Dow Colin Dow
Author Profile Icon Colin Dow
Colin Dow
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Table of Contents (15) Chapters Close

Preface 1. Section 1: Getting Started with Edge Analytics
2. Introduction to Edge Analytics FREE CHAPTER 3. How Does IoT Edge Analytics Work? 4. Communications Protocols Used in Edge Analytics 5. Section 2: Understanding Edge Analytics Technologies
6. Working with Microsoft Azure IoT Hub 7. Using the Raspberry Pi with Azure IoT Edge 8. Using MicroPython for Edge Analytics 9. Machine Learning and Edge Analytics 10. Designing a Smart Doorbell with Visual Recognition 11. Section 3: The Road Ahead
12. Security and Privacy in an Edge Analytics World 13. What Next? 14. Other Books You May Enjoy

Writing the edge code

For the edge component of the Smart Doorbell application, we require two classes and a container script. The following is a diagram of the edge code:

As we can see, Camera is the container script that contains the Face and Message classes.

For our edge code, we will need to create a project folder with a subfolder called faces. The faces subfolder will store photos of people to train our program with (images available with code are in the GitHub repository).

To do this, follow these steps:

  1. In Raspbian, navigate to the home directory by clicking on the home folders icon.
  2. Right-click to create a new folder called Smart Doorbell.
  3. Open up the Smart Doorbell folder.
  1. Right-click to create a new folder called faces:
  1. In the faces folder, copy in photos of people's faces. Make sure that there is only one person per photo or the code will reject that...
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