AGRISHAKTI: KNOWLEDGE & DIRECT MARKET FOR FARMERS USING AI & SATELLITE IMAGE FOR PADDY CULTIVATION

Authors:

SHIVAM KUMAR, SANKET SUMAN, SUDHANSHU RANJAN

ABSTRACT:

This project proposes a smart agriculture system for paddy disease detection and direct market selling using machine learning and satellite weather forecasting. A convolutional neural network (CNN) model is used to classify paddy leaf diseases from images uploaded by farmers. Weather forecasting is integrated using satellite-derived meteorological parameters. The system also provides a digital marketplace where farmers can sell paddy directly to buyers, eliminating middlemen and improving profit margins. Mathematical modeling is used for image classification, loss optimization, probability prediction, and weather prediction modeling.

Keywords: Paddy Disease Detection, Convolutional Neural Network, Machine Learning, Satellite Weather Forecasting, Image Classification, Precision Agriculture, Mathematical Modeling, Direct Market Selling.