It’s a tale as old as time: start cooking food on the stove. Leave stove to scroll through YouTube for the perfect video to watch while eating said food. Food burns on the stove because you didn’t keep an eye on it. If this sounds like you, then you need this project to let Raspberry Pi Pico keep an eye on it for you.

How does it work?

Raspberry Pi Pico runs Edge Impulse’s Sensor Fusion software to read data from gas, temperature, and humidity sensors. The data is then run through a neural network model that warns you if food is burning on the stove. It’s a machine learning-trained babysitter for your cooking.

This project is built around Raspberry Pi Pico, but you can recreate it with any RP2040-compatible board.

Three states of cooking

The setup is trained to detect three different atmosphere conditions around the stove: idle, active cooking, and burning.

The inspiration for this project came from the knowledge that unattended cooking is by far the leading cause of kitchen fires.

The project video is particularly helpful because it walks you through software download, setup, and deployment on screen. It’s super easy to follow if you’re interested in building your own stove monitor.

Volatile organic compounds

The Grove – HCHO Sensor used in this project detects the concentration of gases known as VOCs (volatile organic compounds) in the air. VOCs are emitted by everything from fresh paint to new furniture, and some can damage health, so if high levels of VOCs are detected in your home then you need better ventilation to keep you safe.

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