Have you ever wanted to perform person detection on Arduino or ESP32 boards? Found it difficult to custimize the sketch to suit your needs? Fear no more!
Person detection on Arduino and ESP32 microcontrollers doesn't have to be difficult: with the right library, you only need 3 lines of code to perform state-of-the-art person detection. You use TensorFlow Neural Networks without any boilerplate and verbose code using the EloquentTinyML library.
Are you looking for a project to get started with Machine Learning on Arduino and don't know where to start?
Do most of the tutorials on Arduino gesture recognition you found on the internet look too complicated for you?
You're in the right place!
In this tutorial I'm going to show you one of the easiest possible ways to get started with Machine Learning on Arduino boards while also creating something useful: a gesture recognition system based on an accelerometer.
You will be surprised by how much accuracy you can achieve in just a few kylobytes of resources: Decision Tree, Random Forest and XGBoost (Extreme Gradient Boosting) are now available on your microcontrollers: highly RAM-optmized implementations for super-fast classification on embedded devices.
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