AgroVision-A multi agentic AI system for sustainable farming

Agriculture, the backbone of India’s economy, is currently facing multiple challenges such as soil degradation, excessive use of fertilizers, water scarcity, unpredictable weather patterns, and unstable market prices. These factors not only reduce productivity but also increase the economic risks faced by farmers. To address these issues, we propose a Multi-Agentic AI System for Smart and Sustainable Farming, an intelligent decision-support framework designed to assist farmers in making data-driven agricultural decisions. The proposed system employs a multi-agent architecture, where four specialized agents — the Farmer Agent, Environment Monitoring Agent, Agriculture Expert Agent, and Market Researcher Agent — work collaboratively to analyze diverse data sources and generate actionable insights. The Farmer Agent collects local farm information and maintains historical records, while the Environment Monitoring Agent tracks real-time parameters such as soil health, temperature, humidity, and rainfall. The Agriculture Expert Agent provides scientific recommendations for optimal crop selection, water usage, and fertilizer application, ensuring environmental sustainability. Simultaneously, the Market Researcher Agent analyzes market trends and forecasts demand to help farmers choose the most profitable crops. By integrating machine learning and data analytics, this system provides personalized recommendations that promote sustainable practices, efficient resource use, and better alignment with market needs. The modular design ensures scalability, adaptability, and long-term impact, ultimately empowering farmers to make smarter and more sustainable farming decisions.