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Using the BBC micro:bit and TinyML to sense and respond to the world

Supervisor

Suitable for

MSc in Advanced Computer Science

Abstract

Co supervised by Johnny Austin Jonny@microbit.org

At www.microbit.org

"The BBC micro:bit V2 is capable of running TinyML workloads, and there have been some interesting demo applications. However, little work has been done to push the limits of what is possible with the device's built in motion sensor and microphone. This is an open-ended project to look at pushing the envelope of the machine learning tasks possible on the micro:bit. Because the device is widely available and inexpensive, it makes an excellent and accessible platform for datascience and TinyML work. For example, could the micro:bit be used as a wrist-worn device to recognise different activity types, or could it be trained to distinguish bat species, or birdsong? Could we teach it to recognise a range of 'command keywords' for controlling other projects? By demonstrating creative and effective uses for machine learning with the micro:bit you will be feeding into the future feature roadmap of the Micro:bit Educational Foundation as we work out how to teach students around the world about AI and ML with physical computing"

Prerequisites Digital Systems (or equivalent)