Transforming Agriculture with Cyber-Physical Systems: An Insight into Future Smart Farming

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Authors: Muhammad Ahsan Waseem, Hamna Batool, Tanzeel U. Rehman, Yaqoob Majeed, Faraz Ahmad, Hamid Habib Syed, Tayyaba Nadeem
Cited by: 1

Abstract

Agriculture is going through transformations by leveraging the advancements in technological practices including the implementation of Cyber-physical systems (CPS), a centralized system encompassing highly integrated computational and physical elements. It consists of the interconnected web of physical elements in the form of wired and/or wireless field sensors (e.g., moisture sensors, temperature sensors, pH sensors, humidity sensors, etc.), and computational and control elements in the form of artificial intelligence enhanced processing algorithms (e.g., machine learning and deep learning models) CPS allows farmers to, manage irrigation, dispense fertilizers and pesticides meticulously, and anticipate crop yield and market demand. Conventional labor-intensive procedures can be eliminated with these technologies, which can automate all crop-growing activities from field preparation to harvesting. The objective of the perspective is to give an insight into CPS in agriculture, their use, implementation, current challenges, and future recommendations while highlighting the benefits of carrying out CPS in agriculture, such as improved efficiency, enhanced productivity, and minimal resource wastage. It discusses key components and technologies involved, such as sensor networks, Internet of Things (IoT) appliances, cloud driven computing, and data analytical frameworks. Furthermore, challenges and limitations of CPS implementation, including high upfront costs, infrastructure requirements, and data privacy concerns, are also discussed. Future directions and research opportunities in precision farming, predictive analytics, and resource allocation optimization are explored.

Fields of Study & Subjects

Smart Agriculture and AI Greenhouse Technology and Climate Control Remote Sensing in Agriculture

Publication details

Journal / source
Preprints.org
Publisher
MDPI AG
Publication date
15 June 2026
Document type
Preprint