A raspberry pi project for detecting when the coffee machine in the office has finished making a fresh pot of coffee, and send a push notification on Teams.
A ThunderBoard Sense 2 with an IMU sensor is mounted on top of the coffee machine and running a machine learning binary that was trained to detect when the coffee machine is making coffee based on vibrations. The python code in this repolistory runs on a raspberry pi and starts the inference process on the ThunderBoard. The code also captures the classification outputs, makes a decision whether a new mug was made based on the classification outputs, and posts a notification to a channel on Teams together with a random quote through a webhook using a HTTP post request.
Start application by running coffee_machine.py.
For the raspberry pi in the office, the application will automatically run when the raspberry pi reboots. See /etc/rc.local.