Smart Agriculture for Hilly and Terraced Farming: A Literature Review and Decision-Support System Design

Abstract

Hilly agriculture presents conditions that are not adequately represented by uniform-field assumptions, including slope-dependent water movement, fragmented terraces, elevation variation, and difficult physical access. This paper reviews fifteen verified scholarly sources, including eight focal works on agricultural sensing, irrigation scheduling, machine learning, remote sensing, unmanned aerial systems, and conversational access. Seven supporting sources provide context on precision agriculture, data-intensive farming, decision-support adoption, digital-agriculture governance, and edge computing. The synthesis identifies design needs concerning input reliability, spatial interpretation, terrain-sensitive analysis, user access, and intermittent connectivity. These needs inform an Intelligent Smart Agriculture Platform for Hilly Cultivation that combines quality-aware ingestion, structured storage, Python analytics, FastAPI services, constrained LangChain/Gemini orchestration, and React-based chart and contour-map presentation. Numerical results originate from deterministic retrieval and analytics rather than the language model. The paper specifies a conceptual analytical framework and prospective evaluation protocol without claiming field validation, measured performance, or agronomic benefit.