Difference between revisions of "Motion recognition for the Arduino"

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In this tutorial we will be using [https://edgeimpulse.com Edge Impulse] to train a ML model  
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In this tutorial we will be using [https://edgeimpulse.com Edge Impulse] to train a ML model to recognize motion gestures that you will define using the accelerometer in your mobile phone. After successfully training the model on your motion gestures, we can then generate code for the Arduino Nano 33 BLE Sense. This will allow you to perform your trained motion gestures with the Arduino while the Arduino tries to detect what gesture is performed.
 
 
 
 
 
 
using accelerometer data. After we have succesfully trained a ML model, we can then run this model on the Arduino Nano 33 BLE Sense to detect
 

Revision as of 11:56, 24 March 2022

Intro

Edge Impulse is an free online service where you can build machine learning models to recognize certain patterns using sensor data. Think of audio, images and in case of this tutorial, motion (accelerometer). Machine learning (ML) is a way of writing computer programs. Specifically, it's a way of writing programs that process raw data and turn it into information that is useful for a specific purpose. Unlike normal computer programs, the rules of ML programs are not determined by a human programmer. Instead, ML uses specialized algorithms (sequence of instructions) to learn from data in a process known as training.

In this tutorial we will be using Edge Impulse to train a ML model to recognize motion gestures that you will define using the accelerometer in your mobile phone. After successfully training the model on your motion gestures, we can then generate code for the Arduino Nano 33 BLE Sense. This will allow you to perform your trained motion gestures with the Arduino while the Arduino tries to detect what gesture is performed.