Protecting cultural heritage buildings poses significant research challenges. Effective damage prevention hinges on a thorough understanding of structural behavior and the continuous monitoring of its changes over time. Advanced visualization tools are essential to provide adequate awareness of the monitoring systems installed over the years while guaranteeing a quick, basic analysis of their data. This paper addresses a crucial gap in structural health monitoring (SHM), particularly in managing complex structures and systems, by responding to the growing need for tools that not only represent 3D models enriched with heterogeneous data and metadata but also facilitate detailed analysis of sensor recordings. In response to this challenge, it proposes the integration of a 3D informational model and an interactive web-based platform for monitoring data, creating a comprehensive management tool. Piazza del Duomo UNESCO Site in Pisa serves as an ideal test case due to its historical significance, structural complexity, and the wealth of monitoring data collected over time. With their interactive architecture, the two developed integrated visualization tools that could offer an effective solution for data management and visualization in other heritage contexts, particularly in cases where the monitoring system consists of numerous sensors and has evolved substantially over the years.

The structural diagnosis of monumental buildings necessitates organizing diverse cross-disciplinary data. The H-BIM procedure employs 3D digital models to create a comprehensive virtual repository, offering advantages in documentation access, interoperability, intervention design, cost evaluation, and maintenance management. This work proposes an approach to combining different models while addressing interoperability challenges by best exploiting their positive characteristics. After evaluating the advantages and limitations of textured-mesh and NURBS-based models, and virtual reality environments based on specific comparison criteria, an integrated system of these models within the H-BIM framework is proposed. The latter is applied to study the relevant case of the Baptistery of San Giovanni in Pisa, Italy. The integrated H-BIM model is designed primarily to facilitate the structural diagnosis of the monument, and illustrates how combining different 3D representations, each providing multiple information with different levels of detail, enhances its capabilities. This integration results in a more effective tool for the multidisciplinary conservation of cultural heritage, accommodating a wide range of data beyond structural aspects, thus fostering collaboration among professionals from various fields of expertise.

Numerical models play a crucial role in the study and understanding of cultural heritage structures, serving as valuable tools for predicting their behavior under diverse and prospective scenarios. They are however affected by various uncertainties, which impact can be mitigated through the calibration of model parameters. For heritage structures, where testing is usually restricted to the use of non-destructive techniques, and often unable to directly assess the inherent heterogeneity of the materials, a calibration approach can prove particularly useful to obtain a working model. This work applies a Bayesian model updating procedure to material-related uncertainties affecting a recently developed finite element model of the Leaning Tower of Pisa also comprising the underlying soil layers. A general Polynomial Chaos Expansion-based surrogation of the model was employed to evaluate the sensitivity of modal properties and ease the computational burden that comes with the probabilistic framing of the updating problem. Material property distributions were then updated, taking advantage of modal data from a newly installed sensor network which allowed the most up-to-date dynamic identification of the monument. The results represent the first probabilistic model-based assessment of material uncertainties in a three-dimensional finite element model of the Leaning Tower of Pisa. They shed some light into the value of specific modal information, while the use of analytical surrogation paves the way for the future design of a real-time updating procedure for monitoring and damage detection.