Advances in Precision Agriculture Using AI

Abstract

Precision agriculture (PA) is revolutionizing modern farming by integrating advanced digital technologies to optimize agricultural productivity, resource efficiency, and environmental sustainability. The infusion of artificial intelligence (AI), particularly machine learning (ML) and deep learning (DL) algorithms, has further transformed PA, enabling real-time decision-making, predictive analytics, and automation across the agricultural value chain. This chapter presents an in-depth overview of the core technologies that underpin AI-driven PA, including ML techniques, deep neural networks, Internet of Things (IoT), edge computing, blockchain, and remote sensing. Further, this chapter explores how these technologies converge to support critical agricultural applications such as precision sowing, smart spraying, harvest optimization, pest and disease control, and crop health monitoring. Further, interoperability standards and the need for cohesive data frameworks are examined to ensure seamless integration of diverse PA tools. Challenges related to adoption, cost, data governance, algorithmic bias, and geospatial disparities are discussed, along with strategies for equitable technology deployment. The chapter also highlights participatory innovation models like Living Labs and User-Centered Design to promote inclusive development. Two case studies are also discussed that demonstrate practical AI applications in the field. Finally, the chapter underscores the transformative potential of AI in reshaping agriculture for a sustainable and food-secure future.