Automated Construction and Semantic Interoperability for Digital Twins: Integrating Heterogeneous Data with Large Language Models

Digital twins are increasingly used, as they allow the creation of detailed virtual representations of physical products and systems. They face, however, significant challenges such as heterogeneous data integration and high costs. This article presents an innovative methodology that uses Large Language Models to unify information and automate the generation of Digital Twin models. The proposal comprises several modules, covering the stages of data collection, semantic processing, modular construction and validation of the Digital Twin. In this way, the proposed model guarantees interoperability, efficiency and scalability for various domains.