Hands-On Edge Analytics with Azure IoT
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To get the most out of this book

To get the most out of this book, having the following will be beneficial:

  • In Chapter 2, How Does IoT Edge Analytics Work?, we will use an ESP8266 with an RGB LED to create a weather forecasting application.
  • In Chapter 5, Using the Raspberry Pi with Azure IoT Edge, we will install Azure IoT Edge onto a Raspberry Pi 3B+. Although there is a newer version of the Raspberry Pi (the Raspberry Pi 4), the Raspberry Pi 3B+ will be needed in order to install an older version of the Raspbian operating system.
  • A computer with Windows installed will be needed to run the Microsoft Device Explorer tool that we will use in Chapter 4, Working with Microsoft Azure IoT Hub, and Chapter 5, Using the Raspberry Pi with Azure IoT Edge.
  • The purchase of an ESP32 with LoRa and the Pycom LoPy/LoPy 4 will assist in Chapter 6, Using MicroPython for Edge Analytics, as we cover MicroPython and microcontrollers.
  • A webcam will be used in Chapter 8, Designing a Smart Doorbell with Visual Recognition, as we build our smart doorbell application.
          
Software/hardware covered in the book           OS requirements
Raspberry Pi 3B+           Raspbian Stretch
Pycom LoPy / LoPy 4           Latest MicroPython firmware from Pycom
ESP32 with LoRa           Latest version of MicroPython
ESP8266           Default firmware
RGB LED
DHT11 temperature sensor
PC           Windows 10 and Node-RED

If you are using the digital version of this book, we advise you to type the code yourself or access the code via the GitHub repository (link available in the next section). Doing so will help you avoid any potential errors related to the copying and pasting of code.