Artificial Intelligence and Smart Sensor–Driven Systems for Climate-Resilient, Safe, and Sustainable Food Systems from Farm to Industry

Global food systems face escalating threats from climate change, population growth, environmental degradation, and stringent demands for safety and sustainability. This study synthesizes recent advancements in artificial intelligence (AI), smart sensors, and Internet of Things (IoT) integrations to foster climate-resilient, efficient, and secure food production from farm to industry. Employing a hybrid methodology that combines conceptual framework design with simulation-based evaluations, we assess end-to-end cyber-physical systems incorporating modular architectures for data acquisition, analytics, and adaptive decision-making. Simulation results across baseline, partial digitalization, and fully integrated AI–IoT scenarios reveal substantial gains: yield variability reduced by up to ۴۱% under high climate stress, recovery times shortened by ۳۰–۴۵%, water savings of ۳۲–۴۸%, energy intensity lowered by ۱۸–۲۶%, food waste decreased by ۲۵–۳۷%, and contamination detection accuracies exceeding ۹۳%. These findings underscore the synergistic potential of AI–IoT systems in enhancing resilience, resource optimization, and traceability, while addressing key gaps in integration, generalizability, metrics, and governance. By quantifying multidimensional benefits, this work provides a replicable blueprint for transforming food systems to meet global challenges.

کلیدواژه ها:

AI-driven agriculture ، Smart sensing and IoT integration ، Climate-smart food systems ، Digital agriculture transformation ، Precision farming analytics ، Food system resilience ، Sustainable agri-food supply chains ، Intelligent cyber-physical systems