ShawnHymel / perfect-toast-machine Public

perfect-toast-machine

About this project

The Perfect Toast Machine

This project attempts to toast bread using odor and temperature data (rather than relying on a simple timer). Using this data, we attempt to predict the "time remaining before burnt" using regression. From this, we can estimate a level of "doneness" e.g. by saying that "toast will be perfect 40 seconds before being burned." By hacking a toaster to cancel the toasting process at this point, we should, in theory, be able to perfectly make toast regardless of starting temperature and bread thickness or composition.

Gas and odor data collected from various types of bread over a Black and Decker simple two-slot toaster. Data was standardized before being uploaded to Edge Impulse. The original dataset, curation script, and inference code can be found here: https://github.com/ShawnHymel/perfect-toast-machine.

A full tutorial showing how to build this AI-powered toaster can be found here: https://www.digikey.com/en/maker/projects/how-to-build-an-ai-powered-toaster/2268be5548e74ceca6830bf35f0f0f9e.

88.5a09c32a5ad643c4ab564e2d9bf56d08
7.6b034b1b110a4065a8d8d14b30afd5e4
44.0d194994d5d84006b33b2ec1259c1f15
-39.89b1f371a3ec497a934622832fb1708a
80.b6e19b2318ec4704913d5d8367672aef
26.bb6b5eb7e5094957acff228a8bae6af1
21.8f5be9ccd7104af2b16ad455ed93b013
84.a7d29de13c52480a98347669ed2739c9

Run this model

On any device

Dataset summary

Data collected
18h 15m 50s
Sensors
temp, humd, co2, voc1, voc2, no2, eth, co, nh3 @ 2Hz
Labels
-68 .. 202

Project info

Project ID 129477
Project version 2
License Apache 2.0
No. of views 298,660
No. of clones 16