Title: Advancing Precision Agriculture Through Digital Twins and Smart Farming Technologies: A Review
Journal: AgriEngineering
DOI: https://doi.org/10.3390/agriengineering7050137
Abstract: The agricultural sector is evolving with the adoption of smart farming technologies, where Digital Twins (DTs) offer new possibilities for real-time monitoring, simulation, and decision-making. While previous research has explored the Internet of Things (IoT), UAVs, machine learning (ML), and remote sensing (RS) in enhancing agricultural efficiency, a systematic approach to integrating these technologies within a DTs ecosystem remains underdeveloped. This paper presents a systematic review of 167 studies published between 2018 and 2025. The objective of this study is to examine recent advancements in DTs-enabled precision agriculture and propose a comprehensive framework for designing, integrating, and optimizing DTs in smart farming. The study systematically examines the current state of DT adoption, identifies key barriers, and computational efficiency challenges, and provides a step-by-step methodology for DT implementation. The review sheds light on potential future research direction and implications for policy, with the aim to speed up the adoption of DTs-based farm management systems in their operational success and commercial viability through analysis of practical applications and future perspectives. This study presents an innovative strategy for integrating digital and physical systems into agriculture and is an important contribution to existing literature.
CLISA is the first multi-institutional training program in Canada towards climate smart agriculture to help address the need for HQPs who possess appropriate knowledge and expertise in climate change, precision agriculture, water and soil management, sustainable food production and food value chains, and climate-smart financing and policies to promote the development and application of innovative technologies and strategies in Canadian farming practices.
