vendor independent TinyML deep learning library, compiler and inference framework microcomputers and micro-controllers

Lego Technik Hub Remote Control

Mind the “Uuh” – Train yourself to avoid using uuh fill words

Wearable gait event detection device with real-time gait event-dependent feedback. Heel-strike events accuracy was validated with floor-embedded force plates.

The ALL Arduino Nano 33 BLE Sense Classifier is an experiment to explore how low powered microcontrollers, specifically the Arduino Nano 33 BLE Sense, can be used to detect Acute Lymphoblastic Leukemia.

This repo contains all the necessary files to build a MNIST TinyML application, that works with an OV7670 camera module and TFT LCD module.

🤖 Internet Of Things (CCF 351)

Enhance your LED hula hoop performances with OpenHoop, an open-source Arduino Nano 33 BLE Sense Rev2 project. Immerse yourself in captivating pixel art displays powered by NeoPixel LEDs and controlled via Bluetooth HID protocol. Join our vibrant community and start your LED hula hoop journey now!

A holistic device for safer and smarter contactless elevator system using Embedded Machine Learning on an Arduino Nano 33 BLE Sense, complete with a deployable PCB and fire safety system pipeline.

This repository showcases different methods to create a wireless communication between the Arduino 33 BLE/IoT boards and a PC.

Embedded machine learning for gesture recognition using Arduino Nano 33 BLE Sense. Includes source code for programming the board and notebooks for training the model.

A wrist-worn device and monitoring system implements user-file-memory management system for a person with Body-focused Repetitive Behavior

Demostration for a low-power Wake-on-LAN solution using Arduino Nano and Raspberry Pi

Quadcopter flight controller

TinyML project. This system monitors your room or surrounding with an onboard microphone of Arduino nano BLE sense. Still Under Developement

MoonMakers-Pinball in a game that works in the browser, where we use our Arduino Nano 33 BLE Sense, as a command to control the imposition of our ball thanks to AI.

Este repositorio presenta una variedad de proyectos que cubren aspectos fundamentales de la electrónica moderna, desde el uso de microcontroladores hasta la implementación de comunicaciones inalámbricas y el desarrollo de firmware. Cada proyecto aborda desafíos específicos y tecnologías relevantes.

Arduino TinyML project that uses a ML model to recognize 2 keywords, "yes" and "no", from speech data

Arduino TinyML project that uses a ML model to recognize digits in the camera feed, the model was trained using the MNIST dataset