Digital Twins for Mission-Critical Infrastructures: A BIM-Based Framework for Real-Time Monitoring and Decision Support

Authors: Viviana Vaccaro, Lavinia Chiara Tagliabue, Robert Birke, Marco Aldinucci and Silvia Meschini.

Abstract: Digital Twins are increasingly adopted to support the operational management of complex and energy-intensive infrastructures, yet their practical implementation often remains fragmented across heterogeneous platforms and proprietary monitoring systems. In data center environments, this fragmentation limits the interpretability of real-time data and weakens the connection between operational measurements, spatial context, and asset-level decision-making. This paper presents a BIM-based Digital Twin architecture developed for the HPC4AI (High-Performance Computing for Artificial Intelligence) data center, hosted at the University of Turin's Computer Science Department, within the framework of the DYMAN project, which aims to develop advanced solutions to reduce the impact of thermal energy management in high-performance computing installations and data server rooms. The proposed approach integrates real-time IoT monitoring with Building Information Modelling through a modular layered architecture that decouples sensing, time-series data management, and digital representation. Sensor data are stored in a time-series database and synchronized into the BIM environment via automated Dynamo workflows and embedded Python scripts, where shared parameters enable semantic mapping to building elements. This supports near real-time spatial contextualization, rule-based alerting, and native BIM visualisation without reliance on external dashboards. The case study demonstrates how the BIM model evolves from a static geometric artifact into an operational interface capable of supporting situational awareness, diagnostics, and integration with predictive analytics and energy optimization strategies. The paper discusses system architecture, data synchronization mechanisms, and transferability to other mission-critical infrastructures, highlighting the role of data-driven integration strategies in advancing scalable and interoperable Digital Twins for smart and sustainable built environments.

Keywords: Digital Twin, BIM–IoT Integration, Data Centers, Real-Time Monitoring, Facility, Management, Data-Driven Operation, Model Predictive Control.