Introduction to Machine Learning with Arduino

By Anthony Aiyedun, Mechanical Engineering Student at The University of Texas at Arlington

Machine learning is a useful tool that can be used to help automate tasks, make predictions, and improve decision-making. As a mechanical engineering student, I have not had the ability to be exposed to this cutting-edge tool yet so I have decided to make it my goal this summer to learn machine learning using Arduino.

Arduino is an open-source platform for electronics that can be used to create interactive projects. By combining machine learning and Arduino, I will be able to create projects that can sense and respond to their environment. The specific Arduino hardware I shall use is the Arduino Nano 33 BLE Sense Rev2, which is a board specifically designed for machine learning applications and also equipped with a variety of sensors, including a microphone, accelerometer, gyroscope, magnetometer, and light sensor. It also has a built-in Bluetooth Low-Energy (BLE) radio, which allows it to connect to other devices. I plan to have the board delivered by the beginning of June.

Arduino Nano 33 BLE Sense Rev2

Guide

I will be following the examples found on the Get Started With Machine Learning on Arduino website page in order to better understand the hardware and software, allowing me to create my own projects and devices later on.

Hardware

In terms of hardware materials, I will attempt to recycle my former Arduino projects in addition to purchasing the Arduino Nano 33 BLE Sense Rev2.

Software

In terms of software, I will use Arduino Create web editor, Arduino IDE, and Google Colab.