• Dr. M.K. Jayanthi Kannan
• Om Kumar Singh
• Roshmik Agrawal
• Aadish Chaturvedi
• Harshit Tiwari, Abhyanand Sharma

Agriculture is a critical pillar of global food security but faces persistent threats from plant diseases that cause significant crop losses and economic instability. Traditional methods of diagnosing and managing plant diseases are often slow, inaccurate, and reliant on expert intervention, posing challenges for smallholder farmers. This paper introduces Krishi Care, an AI-powered system for plant disease detection and management, designed to provide accurate and timely solutions. By analysing leaf images, the system uses deep learning models to identify plant diseases and offers actionable recommendations tailored to the detected issue. The system incorporates a recommendation engine to guide farmers on the appropriate use of fertilizers, pesticides, and preventive measures, with real-time weather integration ensuring context-aware advice. The solution is accessible through an intuitive web interface, empowering farmers and agricultural professionals to make informed decisions with minimal technical expertise. Trained on the PlantVillage dataset, the system demonstrates an accuracy exceeding 96%, highlighting its potential for scalable, efficient, and sustainable agricultural management. Future developments aim to expand its functionality by incorporating multilingual support, IoT integration, and dataset generalization, making it adaptable to diverse farming contexts.

Plant Disease Detection, AI in Agriculture, Recommendation System, Sustainable Farming, Context-Aware Solutions, Streamlit

"KrishiCare @ AI based Plant Disease Detection and Fertilizer Recommendation System using Image Classification", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.11, Issue 12, page no.b191-b200, December-2024, Available :http://www.jetir.org/papers/JETIR2412111.pdf

"KrishiCare @ AI based Plant Disease Detection and Fertilizer Recommendation System using Image Classification", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.11, Issue 12, page no. ppb191-b200, December-2024, Available at : http://www.jetir.org/papers/JETIR2412111.pdf