Productivity Improvement with Generative AI Framework for Data Enrichment in Agriculture

Abstract

The improvement in agricultural sector is essential for ensuring food security. Sector faces a multitude of challenges like climate change, resource limitations, and heightened food demand. To meet these challenges, there is an increasing demand for innovative solutions to enhance agricultural productivity, sustainability, and efficiency. This study presents an innovative framework that harnesses Generative Artificial Intelligence (GAI) to revolutionize agriculture. The objective is to conceptualize framework that integrates state-of-the-art AI techniques, encompassing deep learning and generative models, to provide farmers and stakeholders with data-driven insights and decision support tools. By leveraging GAI capabilities, study aims to address key agricultural issues, providing prototype implementation. Study concludes with various possible solution including crop yield prediction, disease identification, soil analysis, and resource optimization and future direction.