An IoT-based environment for modeling and deploying semantic Digital Twins

The Digital Twin (DT) has emerged as a crucial component for advancing Industry 4.0, Industry 5.0, and the Metaverse, attracting substantial interest from both academia and industry. By digitalizing real-world entities, DTs enable capabilities such as monitoring, simulation, prediction, and optimization. However, accurately modeling real-world systems remains challenging due to the diversity of asset representations and the differing perspectives of stakeholders. This paper presents an integrated framework with a unified language to align these perspectives across various system levels, from individual devices to complex workflows. It introduces a methodology for semantic DT models and outlines a 4-layer architecture to clearly define system responsibilities.