Sarv Sampoorna Kisan Mitra - AI Based Crop Disease Detection and Management System

Abstract

The contemporary challenge of sustainable agriculture necessitates the deployment of robust, data-driven decision support systems. This review paper details the architecture and efficacy of an integrated AI-based system, termed 'Sarv Sampoorna Kisan Mitra,' for comprehensive crop disease identification and management. The system is predicated on two core technological pillars: the use of advanced Deep Learning (DL) models, specifically Convolutional Neural Networks (CNNs), for rapid, visual diagnosis of crop diseases; and the implementation of a Knowledge Graph (KG) for prescriptive management recommendations. The paper explores the full lifecycle, from data acquisition via remote sensing and IoT, through predictive modeling for yield forecasting, and culminating in the generation of actionable, customized advice for fertilizer application and pest control. By transforming raw diagnostic data into contextualized, actionable knowledge, this integrated AI-KG framework offers a scalable solution to enhance precision farming efficiency and minimize resource wastage.

Plant phenotyping relevance

植物病害を画像から診断する手法と統合システムの構成・有効性が中心であり、病害状態の画像ベース推定を扱うレビューとして収録対象。

Code and data availability

This is a review-style paper describing a proposed AI crop disease detection architecture. No public phenotype datasets, images, code, models, or supplements with availability statements are mentioned; only generic descriptions (e.g., CNNs trained on 'a comprehensive dataset of diseased and healthy crop leaves') and a

No evidence-backed public reproduction asset is currently recorded.