Digital Twin and Predictive Maintenance in Cultural Heritage: A Multidisciplinary Educational Experience with HBIM and IoT

This Research to Practice Full Paper describes a project that combines different fields to include Heritage Building Information Modelling (HBIM), Internet of Things (IoT) sensor systems, and the digital twin (DT) concept into the hands-on learning experiences for construction engineering and architecture students at the university. This methodology was used in the 'Computer Graphics' course at the University of Salerno, where third-year students engaged in a data-driven digital workflow concerning the genuine case study of Villa Regina, a Roman rural villa situated inside the archaeological site of Pompeii. The students engaged thoroughly in the complete digitization process, encompassing 3D surveying through terrestrial laser scanning and aerial photogrammetry and culminating in the development of HBIM models augmented with semantic and degradation metadata. Subsequently, they developed and executed IoT-based monitoring systems utilizing Raspberry Pi and Arduino platforms and constructed DT simulations to investigate predictive maintenance tactics. An interdisciplinary collaboration between architecture, computer science, and conservation supported the course, which was structured on a project-based learning framework. The assessment, which was conducted through structured surveys and project analysis, demonstrated substantial improvements in technical proficiency, data literacy, and systems thinking. Despite their little prior experience, the students have effectively learned the fundamentals of sensor integration and real-time data processing and indicated greater enthusiasm for using smart technologies in cultural heritage contexts. The results demonstrate the usefulness of combining digital heritage methods with practical engineering training for large-scale teaching. Authentic, cross-disciplinary, and digitally-based learning experiences can be used in a variety of academic and cultural settings that want to change their program.