Print Email Facebook Twitter Positive Eating: Fostering Wellbeing in Healthy Eating Experiences Supported by AI-Driven Systems Title Positive Eating: Fostering Wellbeing in Healthy Eating Experiences Supported by AI-Driven Systems Author Liu, Yi (TU Delft Industrial Design Engineering) Contributor van de Geer, S.G. (mentor) van der Maden, W.L.A. (graduation committee) Degree granting institution Delft University of Technology Corporate name Delft University of Technology Programme Integrated Product Design Date 2023-08-28 Abstract Is healthy eating simply the intake of correct quantities of certain nutrients, regardless of how and where? This project addresses improving wellbeing within the broad context of eating. Eating-related guidance products have a hyper-focus on nutrition and/or weight loss, to the detriment of a wider definition of “health”. Wellbeing is not only physical health metrics, but has a deeper psychological foundation. Eating experiences should focus on this in order to achieve a truly healthy relationship with food, and an improved level of overall wellbeing. Positive AI builds on the framework of positive design in order to do this, and this project produces a tangible example of how this can be done.This project focuses on the issue within the specific context of eating at home. The simplified context retains vital nuance, but simplifies the focus. By gaining an understanding of this and how design and AI can be applied in determined ways, actual results can be obtained. The problem is then to promote mindful home-dining experiences by providing a service in which users can feel both in control of what they eat and closer to their loved ones.The problem is addressed by designing an app-based intervention system - FoodVibe - which harnesses the power of AI to create a highly personalised recipe and experience recommendation system. It facilitates these with the goal of improving wellbeing based on a psychological wellbeing model tailored to the specific context, and learns based on user trends and past experiences. The wellbeing model, based on design analyses of various apps in the broader eating context in combination with wellbeing theories, gives initial direction. This is then thoroughly scrutinised in an evaluation section, leading to future recommendations becoming clear. Subject WellbeingArtifical Intelligencehealthy eatingAI alignmentUser ExperienceProduct Service SystemMachine LearningmindfulnessApp Design To reference this document use: http://resolver.tudelft.nl/uuid:c7933cb7-8884-43cb-9bb4-48454cdf37ac Part of collection Student theses Document type master thesis Rights © 2023 Yi Liu Files PDF Graduation_Report_Yi_Liu_ ... 570085.pdf 90.38 MB MP4 Video_showcase_Yi_Liu_5570085.MP4 113.14 MB Close viewer /islandora/object/uuid:c7933cb7-8884-43cb-9bb4-48454cdf37ac/datastream/OBJ1/view