Ai-powered Smart Agriculture
Year: 2026
Type: article
Abstract: Agriculture is influenced by changing weather, soil conditions, crop selection, plant disease, and market variability. Farmersmay need to consult multiple sources to obtain timely and understandable guidance. This paper presents a proposed AIpowered smart agriculture framework that combines farmer-provided information with weather services, crop and soilknowledge, plant-health image analysis, and market information. A web or mobile interface collects a location, crop details,and the farmer’s concern. An application layer validates the inputs and coordinates the available services. Therecommendation module then presents context-sensitive suggestions with their data sources, confidence indicators wheresupported, and appropriate cautions. The design emphasizes explainability, accessibility, privacy, and the involvement oflocal agricultural experts for consequential decisions. A prototype may be implemented using a REST API, a structuredknowledge base, and separately deployable analytical services. Evaluation should measure functional correctness, responsetime, recommendation relevance, usability, and robustness under missing or outdated data. Because this paper proposes aframework rather than reporting completed field trials, no experimental accuracy or yield improvement is claimed.
Author: Khandarkar, Aditya
Language: English
Topic: Smart Agriculture and AI
Subfield: Plant Science
Domain: Life Sciences
SDG: Zero hunger
Open Access status: green
OpenAlex ID: W7223555321