Build a fruit quality detector

Instructions

Build the fruit quality detector!

Take everything you have learned so far and build the prototype fruit quality detector. Trigger image classification based off proximity using an AI model running on the edge, store the results of the classification in storage, and control an LED based off the ripeness of the fruit.

You should be able to piece this together using code you have previously written in all the lessons so far.

Rubric

Criteria	Exemplary	Adequate	Needs Improvement
Configure all the services	Was able to set up an IoT Hub, Azure functions application and Azure storage	Was able to set up the IoT Hub, but not either the Azure functions app or Azure storage	Was unable to set up any internet IoT services
Monitor proximity and send the data to IoT Hub if an object is closer than a pre-defined distance and trigger the camera via a command	Was able to measure distance and send a message to an IoT Hub when an object is close enough, and have a command send to trigger the camera	Was able to measure proximity and send to IoT Hub, but unable to get a command sent to the camera	Was unable to measure distance and send a message to IoT Hub, or trigger a command
Capture an image, classify it and send the results to IoT Hub	Was able to capture an image, classify it using an edge device and send the results to IoT Hub	Was able to classify the image but not using an edge device, or was unable to send the results to IoT Hub	Was unable to classify an image
Turn the LED on or off depending on the results of the classification using a command sent to a device	Was able to turn an LED on via a command if the fruit was unripe	Was able to send the command to the device but not control the LED	Was unable to send a command to control the LED