An automated system for personalized nutrition via 3D food printing

This project presents an innovative approach to personalized nutrition using 3D food printing technology. It comprises two key components. Firstly, a decision-support system is designed to evaluate the feasibility of turning a 3D food design into a tangible, edible product. This system helps ensure that the food is not only nutritious but also practical to create with the 3D printer. Secondly, a user-friendly algorithm is developed to offer customized dietary recommendations after users input their personal data. By considering factors like individual health goals, dietary restrictions, and preferences, this algorithm generates tailored nutritional plans, making it easier for individuals to maintain a balanced and personalized diet.

Faculty Supervisor:

Rafiq Ahmad

Student:

Partner:

North Forge

Discipline:

Engineering

Sector:

Education; Management of companies and enterprises; Professional, scientific and technical services

University:

University of Alberta

Program: