Food waste has a significant negative impact on the environment. A recent EU-project states that 89 million tons of food are wasted each year, and the total amount of food waste for 2020 could rise by an additional 40%. Although food waste occurs throughout the entire food system, households make the most considerable contribution.

This project reflects on the potential of tackling food waste in the home through the development of an artificial intelligence (AI)-application. The application gives the user dinner recommendations to address underlying issues such as lack of skill and poor storage management. Therefore, the objective of this application is to design an AI-driven system that allows the user to get their favorite recipe(s) while maximizing the number of pantry ingredients used and minimizing the amount of effort.

In the first phase, a data collection application utilizing third-party APIs is employed to collect personal information, contextual data, and user interaction data. Machine learning algorithms are then employed on the data through Weka to establish a prediction model suitable for integration in the final interactive application. The final prototype presents users with personalized recipe recommendations after submission of a personal profile and furthermore offers functionalities to filter the dataset on ingredients available in their pantry and fridge
Course                   Designing with Advanced AI (DPM120), Quartile 2, 2020-2021
Grade                     8
Tools                       Weka, Invision, Processing
Team members     Chantal Vriens, Danvy Vu, Olaf Adan, X

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