Edge Impulse Experts / AI-Based Mechanical Anomaly Detector (Audio)
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About this project
This neural network model detects sound-based mechanical anomalies:
- normal
- anomaly
After building my neural network model, I deployed my model as a fully optimized and customizable Arduino library and uploaded it to Beetle ESP32-C3. Also, I developed an Android application from scratch to notify the user of the detected anomalies.
Download block output
| Title | Type | Size | |
|---|---|---|---|
| MFE training data | NPY file | 100 windows | |
| MFE training labels | NPY file | 100 windows | |
| MFE testing data | NPY file | 35 windows | |
| MFE testing labels | NPY file | 35 windows | |
| Classifier model | TensorFlow Lite (float32) | 15 KB | |
| Classifier model | TensorFlow Lite (int8 quantized) | 8 KB | |
| Classifier model | Model evaluation metrics (JSON file) | 2 KB | |
| Classifier model | TensorFlow SavedModel | 20 KB | |
| Classifier model | Keras h5 model | 14 KB |
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Summary
Data collected
2m 8sProject info
| Project ID | 336608 |
| Project version | 1 |
| License | Apache 2.0 |
