Kutluhan Aktar / IoT AI-driven Yogurt Processing Public

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.

home_1.jpg

Thinner.sample_32
Optimum.sample_34
Optimum.sample_16
Optimum.sample_4
Curdling.sample_6
Thinner.sample_13
Thinner.sample_27
Curdling.sample_28

Run this model

On any device

Dataset summary

Data collected
2m 0s
Sensors
temperature, humidity, pressure, milk_temperature, starter_weight @ 1Hz
Labels
Curdling, Optimum, Thinner

Project info

Project ID 159184
Project version 1
License Apache 2.0
No. of views 15,550
No. of clones 12