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TinyML Keyword Detection for Controlling RGB Lights

Train a TensorFlow model to recognize certain keywords and control an RGB light strip using an Arduino Nano 33 BLE Sense.

The Premise
Machine learning at the edge is extremely useful for creating devices that can accomplish “intelligent” tasks with far less programming and logical flow charts compared to traditional code. That’s why I wanted to incorporate at-the-edge keyword detection that can recognize certain words and then perform a task based on what was said.

This project just has one component: an Arduino Nano 33 BLE Sense. The actual magic happens in the machine learning model. The Arduino Nano 33 BLE Sense is full of sensors, including a microphone, 9-axis IMU, environmental sensor, and a gesture/proximity/color/ambient light sensor (APDS-9960). The microcontroller on it is an nRF52840 that runs at 64MHz and contains 1MB of flash memory and 256KB of RAM. This project also uses its onboard RGB LED to display the current color.”

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