Metaverse-driven Digital Twin Architectures for Low-latency Smart Agriculture IoT: A PRISMA-based Structured Scoping Review and Simulation Framework

Abstract

Given the wide adoption of IoT in agriculture, real-time monitoring of crop yield can now be performed thanks to cloud-based systems. Traditional cloud computing systems have high latency compared to the required demands, limiting their use in agriculture. This research explores the extent to which the metaverse and digital twins can reduce data distribution latency in a hybrid cloud-edge-fog computing environment. This structured scoping review follows the PRISMA 2020 method. Studies were first collected through searches within the Scopus database. Subsequent selection criteria included language, document type, and year (papers published between 2020 and 2026). Next, 106 studies were selected using keywords, such as "metaverse," "digital twin," and "smart agriculture." A total of 24 papers were selected for further analysis. The application of hybrid computing environments is common practice in present-day agriculture. Digital twins, combined with metaverse simulation tools, allow for real-time operation of agricultural enterprises through prediction and process synchronization. Future improvements can be achieved through innovations in 5G/6G wireless networking and artificial intelligence. Nonetheless, many problems arise when implementing them, especially in rural areas. Combining metaverse simulation capabilities and advanced distributed computing environments provides an efficient solution for the implementation of smart agriculture. Concerns about compatibility, scalability, and potential differences between models and reality still exist. Moreover, the issue of the digital divide may be addressed through decentralized computing architectures. Metaverse technology, coupled with digital twins and distributed computing infrastructure, is a promising strategy for minimizing the data distribution latency in smart agriculture.