Dr. Dipti Chauhan, Dr.Pritika Bahad

Prestige Institute of Engineering Management and Research, Indore, Madhya Pradesh
452010, India

Abstract

Recent years have seen a significant increase in interest in digital twin technology, which presents a promising method for simulating and replicating real-world entities in a virtual setting. By developing virtual representations of the agricultural industry’s physical assets, systems, and processes, it has the potential to revolutionize farming methods. To simulate and improve agricultural operations, they use real-time data from numerous sources, including sensors, satellites, and farm management systems. It’s very exciting to think about how digital twins could take productive and sustainable farming to new heights. Farmers can maximize resource allocation, monitor crops in real-time, and make data-driven decisions by utilizing the power of digital twins, which will ultimately result in increased productivity, decreased environmental impact, and improved sustainability in agricultural practices. Digital twins have the potential to revolutionize farming practices and contribute to the creation of a more sustainable and effective agricultural ecosystem given the rapid advancements in technology and data-driven decision-making. The chapter discusses the advantages, difficulties, and case studies that highlight its practical application as it explores the various elements and technologies involved in creating a Digital Twins enabled model for smart farming. This study aims to investigate and explore the potential applications and benefits of digital twins in transforming farming practices, with a focus on enhancing livestock operations, crop management, and overall agricultural sustainability. Future prospects and potential developments in this field are also covered in this chapter. The results of this study will be useful to farmers, researchers, policymakers, and other stakeholders in the agricultural industry, facilitating informed decision-making and promoting efficient and long-lasting smart farming methods.

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