This project demonstrates the use of different technologies & their integration to build an intelligent system to interact with humans.
Maixduino was released to support Arduino development for Sipeed's MAix dev boards. But it's only for Linux and Windows, what about OSX?
Hack an Arduino toy car and turn it into autonomous rover searching for (and chasing) the human faces with Google Vision AIY Kit.
Using AI to detect and monitor objects, then to connect and record it on the IoT platform.
Have you ever imagined a house able to interact with its residents encouraging them to improve their habits, increase quality of life?
Objectives of this project include self-driving on track, obstacle detection, and collision avoidance.
Most home camera systems have no concept of the content of images, here we add AI to detect when people are present in images.
A fully automatic process that will generate realistic colorizations of black & white (B&W) photos and videos with OpenCV/CNN technics.
This is a bit of a fun project I’ve done in recent weeks. Actually adding machine learning for the AIY Voice kit.
This project tries to build an AI platform with Arduino.
The unit developed here makes your appliances like TV, amplifier, CD and DVD players control with voice commands using Alexa and Arduino.
Using Pynq, we can implement an accelerated AI/ML on an FPGA without writing a line of HDL! Let's take a look at how we can this...
A magic wand that uses machine learning to learn and recognize wand gestures, powered by Arduino Nano 33 BLE, TensorFlow, and PlatformIO.
Use Bolt IoT kit and Arduino Uno to make your own anomaly detection & temperature monitoring device in both modes, i. e online and offline.
The one device we all need, an AI Powered Bull**** Detector!
The M5Stick-V is an AIOT (AI + IOT) camera with machine vision capabilities.
Wouldn’t it be awesome to have a personal chatbot that will send you cool stuff throughout the day?
Microsoft Cognitive Services App Designed for Windows 10 IoT Core Devices.
Self-service checkout for vision impaired people using image recognition, and text to speech services running on Azure IoT Edge.
We can install Caffe, a commonly used deep learning framework, onto the Jetson Nano.
This demo shows an example of how to use machine learning in a decision tree concept, programmed into a smart $2 LSM6DSOX sensor.
New attempt to create a real-time speech to text and text to speech system.
Build a camera that automatically describes what it sees using AI captioning.
Robot that drives around autonomously in greenhouse environment and identifies diseases.