Design Research on an AI-Assisted Everyday Food Therapy Service System: A Case Study of the "Food Rhythm" Digital Food Therapy 4S Store

Abstract

This study addresses three problems in everyday food therapy services: insufficient explanation of recommendations, weak continuity between digital advice and offline fulfilment, and unclear boundaries of AI assistance. Taking the "Food Rhythm" Digital Food Therapy 4S Store as a design case, this research adopts a research-through-design approach that combines literature review, competitor analysis, semi-structured interviews, and service system design. The proposed system connects low-burden need expression, explainable AI recommendation, physical constraint-card interaction, offline ingredient display, open preparation, and feedback. Its core design logic is to treat AI not as a medical decision-maker, but as an auxiliary service capability that helps users understand, adjust, verify, and continue everyday food-therapy suggestions. By coordinating the mobile app, interaction terminal, physical cards, store environment, and backstage support, the design translates algorithmic output into an inspectable service journey. The study contributes a service-system framework for applying AI to daily health-related services while maintaining transparency, user control, and non-medical safety boundaries.