What question did this study set out to answer?

The aim is to enhance agricultural decision-making through predictive analytics using AI and ML.

April 3, 2026Open Access

KrishiConnect: An Intelligent Agriculture Prediction System using AI and ML

Key Points

The aim is to enhance agricultural decision-making through predictive analytics using AI and ML.
Developed a system integrating real-time data on weather, soil, and market conditions.
Implemented predictive algorithms to analyze the data.
Provided recommendations for crops, yield predictions, and price forecasts.
Showed significant improvements in decision-making for farmers.
Increased productivity by recommending optimal crops based on data.
Enhanced farmers' income through accurate price forecasting.

Abstract

Agriculture faces major challenges such as unpredictable weather, soil degradation, and fluctuating market prices. This research proposes KrishiConnect, an intelligent agriculture support system enhanced with Artificial Intelligence (AI) and Machine Learning (ML) models. The system integrates real-time data (weather, soil, and market) and applies predictive algorithms to provide crop recommendations, yield prediction, and price forecasting. The objective is to improve decision-making, increase productivity, and maximize farmers’ income.

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