Recent advances in IoT-driven crop monitoring and precision irrigation: Technologies, models, and future challenges

Abstract

The application of Internet of Things (IoT) technologies to agriculture is converting traditional decision-making models from being retrospective and subjective to real-time and data-driven. This paper provides an in-depth and structured review of recent developments in the Verizon Smart Crop systems for precision irrigation and crop monitoring, highlighting the importance of wireless communication protocols, sensor networks, and artificial intelligence (AI) for early intervention monitoring as a proactive, adaptive approach to changing field conditions. It also explores mathematical modeling approaches and vegetation indices, to inform irrigation scheduling and crop stress detection. A tiered system architecture framework has been developed, and case studies illustrate how these technologies can address resource usage and improve yield outcomes. The review also comments on some of the challenges such as interoperability, data overload and cost, and suggests future research directions that would improve sustainability, scalability and efficiency of smart agriculture.

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