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This is a public Edge Impulse project, use the navigation bar to see all data and models in this project; or clone to retrain or deploy to any edge device.
This is a public Edge Impulse project, use the navigation bar to see all data and models in this project; or clone to retrain or deploy to any edge device.
IoT AI-driven Yogurt Processing
About this project
Project Description
This model detects yogurt consistency (texture) classes before fermentation based on temperature, humidity, pressure, milk temperature, and culture weight measurements:
- Thinner
- Optimum
- Curdling
After building my neural network model, I deployed my model as an Arduino library and uploaded it to XIAO ESP32C3. Also, I employed XIAO ESP32C3 to communicate with the Blynk application I designed to run the neural network model remotely and transmit the collected data.
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Dataset summary
Data collected
2m 0sSensors
temperature, humidity, pressure, milk_temperature, starter_weight @ 1HzLabels
Curdling, Optimum, ThinnerProject info
| Project ID | 159184 |
| Project version | 1 |
| License | Apache 2.0 |
| No. of views | 15,550 |
| No. of clones | 12 |
