An Intelligent Smart Farming Advisory System Using Integrating IoT Sensor Networks and Generative AI for Real-Time Crop Management and Decision Support System

Reena Thakur; Kalyani Rahate; Pradnya Borkar

An Intelligent Smart Farming Advisory System Using Integrating IoT Sensor Networks and Generative AI for Real-Time Crop Management and Decision Support System

Author(s)	Reena Thakur, Kalyani Rahate, Pradnya Borkar
Country	India
Abstract	Agriculture faces increasing pressure from population growth, climate variability, resource scarcity, and labor constraints, making traditional, experience-based farming practices insufficient for sustainable food production. While Internet of Things (IoT) and Artificial Intelligence (AI) technologies have improved precision farming through real-time monitoring and predictive analytics, most existing systems rely on static models that lack adaptability to dynamic agricultural environments. This paper proposes an Intelligent Smart Farming Advisory System that integrates IoT sensor networks, cloud–edge computing, real-time weather data, and Generative Artificial Intelligence (GenAI) to deliver adaptive, context aware, and personalized agricultural recommendations. The proposed multi-layer architecture consists of an IoT sensing layer for continuous environmental data acquisition, a data aggregation and processing layer leveraging edge and cloud computing, a Generative AI analytics layer for multimodal data fusion and scenario generation, and a decision-support layer that provides explainable, user-friendly advisories through web, mobile, and voice-based interfaces. A continuous feedback and learning loop enable system optimization using farmer responses and yield outcomes. A comprehensive literature review highlights the evolution of smart farming from basic IoT monitoring to AI-driven predictive systems and identifies the absence of real-time, adaptive GenAI-based advisory platforms as a critical research gap. The proposed methodology demonstrates how Generative AI enhances precision agriculture by enabling dynamic irrigation, fertilization, pest management, and climate adaptation strategies. The study concludes that the integration of IoT, AI/ML, and Generative AI forms a robust foundation for sustainable, scalable, and intelligent farming ecosystems capable of improving resource efficiency, crop productivity, and decision-making in modern agriculture.
Keywords	Smart Farming, IoT Sensor Networks, Generative AI, Real-Time Crop Management, Decision Support System, Precision Agriculture, Sustainable Agriculture, Crop Disease Prediction, Explainable AI (XAI), Resource Optimization.
Field	Computer Applications
Published In	Volume 7, Issue 3, May-June 2026
Published On	2026-05-08

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An Intelligent Smart Farming Advisory System Using Integrating IoT Sensor Networks and Generative AI for Real-Time Crop Management and Decision Support System

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