AI-BASED DECISION SUPPORT FOR CROP FARMING
Keywords:
Artificial Intelligence, Crop Disease Detection, Soil Fertility Estimation, Yield Prediction, Market Forecasting, Sustainable AgricultureAbstract
Agriculture plays a crucial role in ensuring food security and economic sustainability. Farm- ers face challenges such as climate variability, crop diseases, soil nutrient imbalance, and volatile market prices. Traditional decision-making methods often lead to reduced productivity and financial losses.This paper presents AgroVision, an AI-driven intelligent decision support system designed to assist farmers throughout the crop lifecycle. The system integrates Convolutional Neural Networks for crop disease detection, supervised learning models for soil fertility estimation and crop yield prediction, and time-series forecasting models for market price prediction.Unlike IoT-based systems, AgroVision operates without hardware sensors, making it cost- effective and accessible to small and medium-scale farmers.

