Empowering Small Landowner Farmers with Real-time Data and AI: Enhancing Precision Agriculture
Year: 2025
Type: article
Abstract: This paper presents a modular, low-cost Internet of Things (IoT) and Artificial Intelligence (AI) frame work designed to assist small landowner farmers with real-time environmental monitoring and decision support. The proposed system integrates field sensors, a local gateway, and cloud-based AI analytics to provide irrigation recommendations, pest alerts, and yield predictions. The architecture emphasizes af fordability, offline capability through gateways, and a farmer-friendly mobile dashboard for actionable insights. We describe the overall architecture, hardware components, AI model design, and the planned pilot deployment strategy. Evaluation metrics include sensor accuracy, water conservation, yield im provement, and farmer adoption rate. While Phase I focuses on system design and pilot preparation, Phase II will report empirical field results. The framework provides a scalable blueprint for precision agriculture solutions in resource-constrained environments.
Authors: B.Prabhakar B, P.Jyothisri P, D.Sai Prasanth D, P.Balagajaraj P
Language: English
Topic: Smart Agriculture and AI
Subfield: Plant Science
Domain: Life Sciences
Open Access status: hybrid
OpenAlex ID: W4415115152
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