Impact Prediction of Climate Change on Crop Yield and It’s Solutions
Impact Prediction of Climate Change on Crop Yield and It’s Solutions
Vivek Bhosale,Tejas Nirmal,Aayush Bhakare,Prof. Manoj Kharde
TLDR
Economic analysis predicts 20–25% income loss under moderate warming, half recoverable via the AI-IoT solutions, and Adaptive strategies include crop recommendations, optimized sowing, disease alerts, and conversational guidance.
Abstract
Climate change (temperature rise, erratic rainfall, humidity swings) threatens yields of wheat, rice, maize, cotton and sugarcane in Maharashtra. We integrate 25+ years of historical yield & weather data (State Ag. Dept.), IoT sensing (NodeMCU ESP8266 + DHT11 + soil-moisture + NEO-6M GPS) and AI (Random Forest Regressor, CNN disease detection, Gemini chatbot). The Random Forest model achieved R² ≈0.91 (rice), 0.93 (cotton); RMSE ~0.3 t/ha. IoT-driven irrigation alerts saved 12–15% water; pilot trials showed 6–8% yield gains. Economic analysis predicts 20–25% income loss under moderate warming, half recoverable via our AI-IoT solutions. Adaptive strategies include crop recommendations, optimized sowing, disease alerts, and conversational guidance