Smart AI Farmer- A Scalable AI-Based Web Application to Solve Real- World Agricultural Challenges Without IoT Dependency
Year: 2025
Type: article
Abstract: Agriculture remains the primary source of income for many developing countries, but farmers have enduring challenges such as climate unpredictability, crop diseases, water mismanagement, and inadequate tailored guidance. This paper presents a smart AI-powered web application developed specifically for small and marginal farmers that enables efficient farming decision-making without requiring expensive IoT gadgets. Important aspects are included such as a crop recommendation system, image-based disease and pest recognition, smart irrigation, weather forecasting, and answer chatbots that respond to various farming queries. It can take input in different forms, supporting various languages, and even voice commands for those who are illiterate or uneducated. The solution is scientifically and economically tested, user-friendly, and accessible to all intended users. The application is constructed in Python and employs real-time AI models tested extensively for precision. More features are planned in the future, such as AI-driven market price forecasting, personal dashboards for farmers, AI-driven crop rotation scheduling, entrepreneur networks for farmers, an AI-driven subsidy and loan advisory system, a digital crop calendar with AI, and numerous other features. This specific project can expect a positive impact on food production, improving its quality, raising the income of farmers, and even advancing agriculture in India. The solution is practical, affordable, and incorporates the advantages of artificial intelligence.
Authors: Sumit Kurre, Payal Chandrakar, Sudhanshu S Dadsena
Language: English
Topic: Smart Agriculture and AI
Subfield: Plant Science
Domain: Life Sciences
Open Access status: gold
OpenAlex ID: W4410825981