Volume 2 - Issue 3, May - June 2026

Agriculture is one of the most crucial sectors that supports human life and economic development, particularly in developing countries like India. However, the agricultural sector is highly sensitive to environmental conditions such as temperature, rainfall, soil fertility, and climate variability. In recent years, climate change has introduced unpredictability in weather patterns, resulting in crop failures, reduced productivity, and financial losses for farmers. Traditional farming methods rely heavily on experience and intuition, which may not always be reliable under changing climatic conditions. This project proposes an AI-Based Climate-Adaptive Crop Planning & Risk Prediction System, which utilizes machine learning techniques to assist farmers in making data-driven decisions. The system analyzes various environmental parameters such as soil nutrients (Nitrogen, Phosphorus, Potassium), pH level, temperature, humidity, and rainfall to recommend the most suitable crops. Additionally, it incorporates a risk prediction module that evaluates the uncertainty associated with each recommendation and categorizes it into low, medium, or high risk. The system is designed to provide multiple crop recommendations along with confidence scores, enabling farmers to select the best option based on their preferences and local conditions. The integration of artificial intelligence not only improves prediction accuracy but also enhances agricultural productivity and sustainability. The proposed solution aims to reduce crop failure, optimize resource utilization, and support smart farming practices.

S.Harish Ragavendhar, N.Thamizharasan,"AI-Based Climate-Adaptive Crop Planning & Risk Prediction System" International Journal of Advanced Multidisciplinary Research and Educational Development, V2(3): Page(983-985) May-June 2026. ISSN: 3107-6513. www.ijamred.com. Published by Scientific and Academic Research Publishing.