Optimizing urban agriculture with digital twins: a pathway to enhanced food security and sustainability

Urban Farm DB summary

This conceptual paper proposes the Urban Agriculture Digital Twin (UA-DT), a four-layer cyber-physical framework combining IoT sensing, cloud infrastructure and hybrid mechanistic/AI models for real-time monitoring and city-scale food-system simulation, with logical feasibility demonstrated through an illustrative software simulation (Eclipse Ditto, Azure IoT, Python) for a community rooftop garden. The paper cites benchmark ranges — 20–40% water savings, 15–25% fertilizer reduction, up to 30% post-harvest loss reduction, and 3–7 day early-warning lead time — as literature-derived projections that a fully validated UA-DT deployment would be expected to approach, explicitly noting these are not empirical findings of this study.