Aurelien Lequertier / Smoke Detector Public

Aurelien Lequertier / Smoke Detector

This is your Edge Impulse project. From here you acquire new training data, design impulses and train models.

Creating your first impulse (100% complete)

Acquire data

Every Machine Learning project starts with data. You can capture data from a development board or your phone, or import data you already collected.

Design an impulse

Teach the model to interpret previously unseen data, based on historical data. Use this to categorize new data, or to find anomalies in sensor readings.

Deploy

Package the complete impulse up, from signal processing code to trained model, and deploy it on your device. This ensures that the impulse runs with low latency and without requiring a network connection.

Download block output

Title Type Size
Raw data CO2 training data NPY file 296 windows
Raw data CO2 training labels NPY file 296 windows
Raw data CO2 testing data NPY file 76 windows
Raw data CO2 testing labels NPY file 76 windows
Raw data TVOC training data NPY file 296 windows
Raw data TVOC training labels NPY file 296 windows
Raw data TVOC testing data NPY file 76 windows
Raw data TVOC testing labels NPY file 76 windows
Raw data Humidity training data NPY file 296 windows
Raw data Humidity training labels NPY file 296 windows
Raw data Humidity testing data NPY file 76 windows
Raw data Humidity testing labels NPY file 76 windows
NN Classifier model (version #1) TensorFlow Lite (float32) 3 KB
NN Classifier model (version #1) TensorFlow Lite (int8 quantized) 3 KB
NN Classifier model (version #1) TensorFlow Lite (int8 quantized with float32 input and output) 3 KB
NN Classifier model (version #1) TensorFlow SavedModel 13 KB
NN Classifier model (version #4) TensorFlow Lite (float32) 6 KB
NN Classifier model (version #4) TensorFlow Lite (int8 quantized) 6 KB
NN Classifier model (version #4) TensorFlow Lite (int8 quantized with float32 input and output) 7 KB
NN Classifier model (version #4) TensorFlow SavedModel 18 KB

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Summary

Data collected
3m 48s

Project info

Project ID 33572
Project version 1
License No license attached