Learn to build and program a Quarky Intellio Obstacle Avoider Robot using PictoBlox Python and OpenCV.
An experimental language model I trained from scratch, running offline on ESP32-S3 with a touchscreen chat interface.
WaterLens combines four water sensors, Arduino UNO Q and local Edge AI to recognize patterns and flag changes from a tap-water reference.
Our pets deserve more to stay active. A tinyML model predicts activities based on the data coming from 3 Axis IMU.
Building an inclination estimator system with Arduino Nicla Sense ME and Neuton TinyML
Predict the possibility of arrhythmias on an 8- bit Microcontroller, without sending the corresponding sensor data to the cloud.
Learning Image Classification on embedding devices (ESP32-CAM)
Developing a TinyML solution for the Shipping Industry that allows users to track the status of a shipment/package in real time.
Creating a faster, smaller, and more accurate magic wand than the famous experiment provided in Arduino Sketch, given the same hardware.
Implementing sensor fusion to detect smoke and reduce false alarms.
Collecting and analyzing data to predict which F1 car will finish the race first.
Experimenting with air-writing recognition on Arduino’s smallest board
Applying sensor fusion with RSL10 and Bosch sensors to run a TinyML model for predictive maintenance of compressor water pumps.
Detect spoiled products using the Tiny Machine Learning approach.
Exploring Machine Learning on the tiny device of the Seeed XIAO family, the ESP32S3 Sense and SenseCraft-Web-Toolkit
A sealed ±32 g edge-AI node plus the whole stack — firmware, OTA, cloud, API, dashboards. You build only what makes your product yours.
Amateur's Guide: Comparing Vision AI MCUs on Ease & Speed
A fun and simple project that uses TinyML to detect and respond to dog barks.
How to apply the TinyML approach to detect truck failure related to the Air Pressure System (APS) in a timely manner.
Play Tic-Tac-Toe (also known as Xs and Os) using handwritten digits recognized with the help of TinyML techniques.
Classificate gestures using an Esp32, MPU6050 and Edge Impulse.
Using data from different sensors and ML on the edge, this device can detect early sign of algae bloom and notify authorities or citizens.
A tiny DIY cam built with Xiao ESP32S3 Sense. Captures images with a button press and saves them to an SD card.
Exploring Computer Vision applications such as Image Classification, Object Detection, and Pose estimation.
