AI for Inclusivity

Designing AI-powered tools that support visually impaired users in cooking and play.

Tools & Methods

Arduino, Processing, SolidWorks, Computer Vision.

Industry

AI & Inclusive Design

Duration

Team (4) & Solo, 2.5 months

Project Overview

This project investigates how Artificial Intelligence can be utilised to enhance accessibility for visually impaired users in their daily routines. Two AI-powered prototypes were developed: ChefMate, a kitchen assistant that promotes safer cooking by providing real-time audio cues in case of dangerous cutting position; and DAiCE, a computer vision-enabled device that identifies dice outcomes and communicates them through auditory feedback, allowing visually impaired users to engage independently in dice-based games.

Design Challenge

Design AI-driven solutions to increase inclusivity in daily contexts.

Project Overview

Design Challenge

Design AI-driven solutions to increase inclusivity in daily contexts.

Design Process

ChefMate (Solo): Problem identification, defining requirement, collect data and train the model, and designing the electronics hardware with Arduino and Processing.
DAiCE (Team): Decide on the target user, defining product features, making the design of the product, collect data and train the model with computer vision, and lastly, test and evaluate the final prototype.

Key Learnings

Gained hands-on experience in technical problem-solving through rapid prototyping and parallel hardware-software development.
Deepened understanding of inclusive design principles.
Learned how to translate user challenges into practical AI-driven solutions by training and integrating machine learning models.

Key Learnings

Gained hands-on experience in technical problem-solving through rapid prototyping and parallel hardware-software development.
Deepened understanding of inclusive design principles.
Learned how to translate user challenges into practical AI-driven solutions by training and integrating machine learning models.