This research emphasizes the importance of developing interoperable solutions that enable structural monitoring data to be directly comparable with other types of information and effectively utilized through Digital Shadow. The focus is on monuments of significant cultural and historical importance, which face threats from natural hazards such as earthquakes and environmental degradation, as well as human- induced stresses. These challenges highlight the urgent need for advanced tools and methodologies that enable the continuous and reliable assessment of their structural integrity, ensuring their preservation for future generations. This study presents a comprehensive and integrated approach to information modeling methods for data management, specifically tailored for monitoring and preserving culturally significant structures. The Roman Arena in Verona serves as the case study, demonstrating how Building Information Modeling (BIM) systems and sensor networks can be integrated to assess structural health and manage large datasets efficiently. The study explores the use of open data standards, such as IFC, to ensure interoperability and facilitate seamless integration of different data sources. It also highlights the application of SQL databases for handling real-time sensor data, enabling a dynamic and detailed digital shadow of the monitored structure. By combining cutting-edge digital tools, including BIM, remote sensing technologies, and environmental sensors, the proposed methodology provides a comprehensive system that not only facilitates real-time data analysis but also offers insights for conservation and restoration efforts. A framework that organizes monitoring data into an SQL database, which is subsequently linked to a specific database for Industry Foundation Classes (IFC) files is proposed. This linkage enables the real-time visualization and dynamic updating of the structure’s digital representation. An online platform is introduced to allow users to view and interact with the updated IFC model and query the database to monitor sensor data trends over time. This platform moves beyond traditional visualization tools by integrating monitoring data with actionable insights, offering advanced capabilities such as the identification of specific areas requiring intervention based on sensor readings. By providing decision-makers with a comprehensive view that combines real-time monitoring with historical and predictive data, the system supports more effective conservation and restoration strategies. This research demonstrates how modern data management techniques and digital tools can be leveraged to enhance the long-term preservation of cultural heritage assets. The proposed framework is scalable and adaptable, offering a model that can be applied to other heritage sites facing similar challenges. By offering a robust and flexible framework for the interoperable use of data generated through structural health monitoring, enabling seamless integration with other information types, this work aims to contribute to the global effort towards preserving cultural heritage in the face of growing environmental and societal pressures.
Marcellino et al. (Tue,) studied this question.