Void detection on Edge devices with Live Video Analytics using own images and video

AI Edge Engineer
Azure IoT Hub

Use a Live Video Analytics module on IoT Edge and deploy a Custom Vision machine learning solution to an IoT Edge device. The solution will identify void spaces in shelves. Check that the solution is successfully deployed and test your solution from a web application.

Learning objectives

In this module, you will:

  • Use Live Video Analytics to build video analytics solution with Custom Vision
  • Deploy a set of modules to an IoT Edge virtual machine using the installer
  • Set up an application that uses the virtual device for rapid inference at the edge
  • Deploy a solution that will enable you to watch images with defects through a web application

"Produced in partnership with the University of Oxford – Ajit Jaokar, Artificial Intelligence: Cloud and Edge Implementations course."


  • An Azure subscription
  • Ability to use Azure Cloud Shell
  • Basic knowledge of Azure IoT Edge
  • Basic knowledge of Custom Vision
  • Basic knowledge of Live Video Analytics