Optimising Agriculture supply Chain in Sri Lanka Using Machine Learning

Abstract

Abstract AgroMate is a comprehensive agricultural management system designed to optimise agrarian processes in Sri Lanka. With a focus on enhancing productivity and efficiency, AgroMate integrates advanced machine learning algorithms and predictive analytics to forecast production accurately for farmers and provide valuable insights to agriculture officers and resellers. By leveraging historical data and adaptive neural network training, AgroMate enables precise forecasting of production weight, price, and sell weight for various stakeholders. This research explores the implementation of AgroMate's functionalities, including user interface design, backend development, and API integration. Through functional testing and evaluation, AgroMate demonstrates significant improvements in agricultural management, paving the way for enhanced decision-making and productivity in the agricultural sector.