Arduino Tiny Machine Learning (TinyML) is a technology that allows Machine Learning models to run directly on microcontrollers such as Arduino boards.
Instead of sending data to cloud servers, the device processes data locally on the hardware (edge device). This enables low-power, real-time AI applications.
The most common board used for Arduino TinyML is
Arduino Nano 33 BLE Sense
It contains multiple sensors including:
9-axis IMU (accelerometer + gyroscope + magnetometer)
microphone
temperature and humidity sensors
light and proximity sensors
These built-in sensors make it ideal for AI experiments.
The Arduino Tiny Machine Learning Kit includes:
Arduino Nano 33 BLE Sense board
OV7675 camera module
Arduino TinyML shield
Micro-USB cable
TinyML on Arduino can be used for:
Keyword spotting (voice recognition)
Gesture detection
Image classification
Sound detection
Smart IoT devices
The models typically run using TensorFlow Lite for Microcontrollers, enabling neural networks on very small devices.
✅ สรุป / Summary
| Feature | Arduino TinyML |
|---|---|
| Concept | Machine Learning on microcontrollers |
| Platform | Arduino boards |
| Tools | TensorFlow Lite Micro |
| Use cases | Voice, gesture, image recognition |
| Advantage | Real-time AI without cloud |