Christopher Mendez / AI Meter
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About this project
Brief
This project consists on a "Smart Energy Meter" that is capable to identify and segregate loads and appliances connected to our house grid by analysing their harmonics behaviour extracted from their current and voltage raw signals, also, with some custom code, the microcontroller shares the inferences results and energy measurements to a server in the cloud using a WiFi Notecard
Hardware used
- YHDC CT 100A:50mA
- YHDC PT 230-9 VAC
- ST Nucleo-F767ZI Dev Board
- Custom PCB
Hackster project guide
Download block output
| Title | Type | Size | |
|---|---|---|---|
| Spectral features training data | NPY file | 133760 windows | |
| Spectral features training labels | NPY file | 133760 windows | |
| Spectral features testing data | NPY file | 3415 windows | |
| Spectral features testing labels | NPY file | 3415 windows | |
| Flatten training data | NPY file | 133760 windows | |
| Flatten training labels | NPY file | 133760 windows | |
| Flatten testing data | NPY file | 3415 windows | |
| Flatten testing labels | NPY file | 3415 windows | |
| NN Classifier model | TensorFlow Lite (float32) | 18 KB | |
| NN Classifier model | TensorFlow Lite (int8 quantized) | 7 KB | |
| NN Classifier model | TensorFlow Lite (int8 quantized with float32 input and output) | 7 KB | |
| NN Classifier model | TensorFlow SavedModel | 28 KB | |
| Anomaly detection model | JSON | 144 KB |
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Summary
Data collected
2h 12m 9sProject info
| Project ID | 26079 |
| Project version | 13 |
| License | Apache 2.0 |
