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Concepts

1. Gesture Recognition and Machine Learning: you will explore how the
Google Teachable Machine uses machine learning to recognise and categorise
different hand gestures. This helps you understand how computers learn

from data and apply what they’ve learned to real-world tasks, connecting to
the science of artificial intelligence (AI) and pattern recognition.

2. Programming and Device Control: By programming the micro:bit, you will
see how the model’s predictions trigger certain actions, such as displaying

specific patterns on the LED display. This integrates concepts of programming
and automation and demonstrates how humans can interact with computers

through gestures, much like touchless control systems or gesture-based
interfaces.

3. Human-Computer Interaction: The activity introduces you to how humans
can communicate with machines using non-verbal commands (gestures).

This links to real-world applications like gesture-controlled devices or
gaming systems that respond to body movements.

Observations

In the Hand Gesture Recognition and Pattern Display activity, you will
observe how their micro:bit responds to the trained model recognising their

hand gestures. They will see how quickly the device processes the gesture
and displays the corresponding pattern on the LED display. This hands-on
experience allows you to understand the process of machine learning, from

training a model to using it for real-time predictions. They will also learn how
computers can interpret human movements and respond in meaningful ways.

Application

Hand gesture recognition has many real-world applications. Here are a few

examples:

Fun and Creative AI Concepts 133