Overview

As children spend increasingly more time with screen-based devices, they are losing out on the developmental benefits offered by outdoor play and fail to develop a positive relationship with nature. This project explores how advances in machine learning on mobile devices can enable children to explore the natural world around them and rekindle that dwindling interest in nature. Oof is a screen-less companion toy that uses machine learning and object-classification to create a scavenger hunt for children to explore their surroundings.

My role

I was responsible for fabricating and prototyping the machine learning components of the toy and contributed actively to the user research and design activities.

Team

Veronica Alfaro

Lydia Jessup

Key Technologies

ml5.js, p5.js

Process

The user interactions were prototyped using Vuforia and Unity and deployed the Microsoft HoloLens.