Perform gesture recognition on the SAMD21 ML Eval Kit using the SensiML Toolkit.
Speech recognition model deployment to resource-limited devices
Automatic FOMO-based people counting using computer vision to increase elevator safety.
Children with ADHD can have difficulties in learning and this project focuses on this problem
A proof-of-concept that uses an Arduino to listen for anomolies in the sound of a running motor.
Detection of cracked road to help wheelchair user travel better
Classify a fan's operational state on the SAMD21 ML Eval Kit using the SensiML Toolkit.
Making a cup of coffee/tea on a Sunday morning is really hard. I would like to make a fully automated coffee/tea maker
This blog contains all the necessary info to optimize your TinyML applications
Digital Screen Scraping on edge devices
A toothbrush timer that uses an accelerometer to measure motion, and analyzes it using a simple machine learning model. Hit 2 minutes!
This project allows the user to control the device they are looking at, through voice commands.
Secure, robust, tinyML based delivery of agricultural products to its valid consumers is the most important step for our AREC.
A compact ESP32 edge-AI and AR module powering a rover with audio, vision, and offline ML for hands-on robotics projects.
Creating a TinyML classification model to identify the correct execution of gym exercises
This project is used to monitor patient's activity and alerts if fall is detected.
Getting started with custom computer vision for your project is a snap using the Remyx Engine and Arduino Portenta H7
To tackle dorm laundry hassles, we took pics and trained models to monitor washers using the Seeed Vision AI Module v2 & Xiao ESP32S3.
Use an Arduino Nicla Vision to determine and alert if a driver's eyes are closed for more than 2 seconds.
ultra-low power keyword detection on Avnet's RASynBoard
Train a wake word model by using tensflow machine learning and deploy to microcontrolloer as Arduino Nano BLE 33 Sense
An overview: Setting up DPU-PYNQ on the Ultra96-V2 board.
Audio classification with an Arduino Nano 33 BLE Sense to detect the sound of glass breaking.
An Edge-AI-powered, solar-run wildlife alert system that uses LoRa and intelligent signage to protect both elephants and people.
