Integrated Agriculture Management with IoT, AIoT, and Mobile Decision Support: An Analytical Review and Design

Abstract

The paper is an overview of the shift in the agricultural IoT research focus away from isolated monitoring prototypes to management systems that are capable of facilitating timely action, traceability, and accountability of operations. Instead of viewing smart farming as a scattering of scattered sensors, the discussion is bracketed in terms of the decisions that the farm managers need to make: at what times and at what points do they receive the first signal, how to verify the field work and how to maintain the operation in case of poor connectivity. One years of literature are reviewed by combining the author analysis, comparison by system-layer analysis, and mapping of management-functions in order to synthesise a representative body of literature between 2020 and early 2026. A clear shift in the types of device-centric studies to architectures that bring sensing, edge coordination, analytics, and mobile workflows in addition to more digital-twin or AIoT components can be seen in the review. The paper suggests a visionary framework, AgriTwinOps, as a connection between field telemetry, a farm digital twin, decision intelligence, and proof-of-completion work flows, enclosed within a single implementable operating model, based on that shift. The value is thus two-fold; a realistic literature review on the basis of realistic agriculture, and a blueprint of future readiness design to scientists or creators who desire to construct the following generation of farm management websites.