Climate-Resilient Agriculture: Systems, Science and Solutions for a Warming World

Agricultural climate resilience increasingly depends on the capacity to detect environmental change early, interpret it correctly and respond before stress becomes irreversible. Internet of Things (IoT) technologies promise to strengthen this capacity by linking field sensors, communication networks, edge or cloud computing, analytics, decision support and automated actuators. Yet much of the smart-farming literature evaluates connectivity, prediction accuracy or input efficiency rather than resilience itself. This critical narrative review examines how IoT-enabled smart farming can contribute to climate-resilient agriculture and where the evidence remains insufficient. Peer-reviewed literature published principally from 1 January 2015 to 14 June 2026 was selected through searches of agricultural, biomedical and multidisciplinary scholarly sources, supplemented by citation tracing and bibliographic verification. Evidence was synthesised across system architecture, irrigation and microclimate management, artificial intelligence integration, reliability, governance and adoption. The strongest operational evidence concerns soil- and plant-informed irrigation, where multi-season orchard trials and recent field comparisons show that sensor-driven scheduling can reduce water application while maintaining commercially relevant crop performance. IoT-controlled protective structures and irrigation can also buffer heat and excess-rainfall exposure, but such studies remain geographically and technologically narrow. Across the wider literature, resilience claims are often inferred from technical performance, resource efficiency or short-duration prototypes rather than tested through multi-season exposure to drought, heat, flooding or compound extremes. Network outages, power failure, sensor drift, model transferability, cybersecurity, data governance and affordability can themselves become points of vulnerability. Artificial intelligence can improve anticipatory decision support, but historical predictive accuracy does not guarantee performance under climate non-stationarity. IoT should therefore be understood not as a resilience intervention in isolation, but as an enabling infrastructure whose value depends on reliable closed-loop operation, agronomic validity and institutional capacity. Progress requires field trials designed around resilience outcomes, stress-tested architectures, uncertainty-aware analytics, interoperable data systems and business models accessible to small and resource-constrained farms.