Kutluhan Aktar / IoT AI-driven Food Irradiation Classifier
This is your Edge Impulse project. From here you acquire new training data, design impulses and train models.
About this project
Project Description
This artificial neural network model (ANN) makes predictions on food irradiation dose levels (classes) based on ionizing radiation, weight, and visible light (color) measurements:
- Regulated
- Unsafe
- Hazardous
After building my neural network model, I deployed my model as an Arduino library and uploaded it to Beetle ESP32-C3 so as to run inferences.
Download block output
| Title | Type | Size | |
|---|---|---|---|
| Raw data training data | NPY file | 486 windows | |
| Raw data training labels | NPY file | 486 windows | |
| Raw data testing data | NPY file | 54 windows | |
| Raw data testing labels | NPY file | 54 windows | |
| NN Classifier model | TensorFlow Lite (float32) | 13 KB | |
| NN Classifier model | TensorFlow Lite (int8 quantized) | 5 KB | |
| NN Classifier model | TensorFlow SavedModel | 18 KB | |
| NN Classifier model | Keras h5 model | 13 KB |
Clone project
You are viewing a public Edge Impulse project. Clone this project to add data or make changes.
Summary
Data collected
9m 0sProject info
| Project ID | 109647 |
| Project version | 1 |
| License | No license attached |
