Ekishan: Design and Implementation of an AI-Driven Agricultural Web Platform for Smart Farming and Rural Empowerment

Abstract

The agricultural sector faces unprecedented challenges including climate variability, resource inefficiency, lack of real-time market information, and limited access to precision farming technologies. This paper presents the design and implementation of Ekishan, a comprehensive AI-driven web-based agricultural platform developed using Python Flask. Ekishan integrates ten core smart farming modules including real-time weather detection, AIpowered crop recommendation, drone spraying coordination, satellite mapping, an intelligent AI assistant, pest and disease detection, live Mandi price aggregation, fertilizer optimization calculator, government scheme discovery, and GIS-based field mapping. The platform further provides a secure multi-language dashboard with role-based authentication, OTP-based password recovery, and real-time agricultural data visualization. Ekishan targets smallholder farmers, agricultural extension officers, and agribusiness professionals, offering an integrated digital ecosystem to improve decision-making, yield optimization, and rural economic empowerment.