Justin Lutz / Rower Public

Justin Lutz / Rower

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.


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
Spectral features training data NPY file 7370 windows
Spectral features training labels NPY file 7370 windows
Spectral features testing data NPY file 4202 windows
Spectral features testing labels NPY file 4202 windows
NN Classifier model TensorFlow Lite (float32) 6 KB
NN Classifier model TensorFlow Lite (int8 quantized) 4 KB
NN Classifier model TensorFlow SavedModel 12 KB
NN Classifier model Keras h5 model 6 KB
Anomaly detection model JSON 7 KB

Clone project

You are viewing a public Edge Impulse project. Clone this project to add data or make changes.


Data collected
18m 26s

Project info

Project ID 90788
Project version 1
License No license attached