HealthHub: A Hybrid?Intelligence Meta?App for Personalized, Sustainable Food Choices with Adaptive Nudging

Abstract

Consumers today navigate fragmented food services (such as recipes, grocery shopping, and delivery) without unified, health/sustainability-aware guidance. Existing recommender systems often prioritize clicks over long-term personal well-being and global sustainability goals. We introduce HealthHub, a scalable meta-platform that (1) aggregates real-time data from recipes, retailers, and restaurants, (2) employs a multimodal, multi-objective AI engine (optimizing for taste, health, and sustainability) enhanced by wearable sensing, (3) leverages LLM-powered, explainable nudges, and (4) incorporates gamified behavior-change mechanics. By integrating cross-service infrastructure with hybrid-intelligence framework, HealthHub illustrates how ubiquitous and wearable computing (via always-on wristband sensing, context-aware notifications, and on-device AI) can adapt recommendations in real time to a user's physiological and situational context. It transparently justifies each suggestion and fosters lasting shifts toward healthier, more sustainable and lower-carbon diets.