BIM, GIS and BI Tools for a university asset management system supporting space management, occupancy evaluation and optimization strategies

Integrating Building Information Modelling (BIM) and Geographic Information System (GIS) into Business Intelligence (BI) tools is promising for developing Asset Management Systems (AMS), especially for large and widespread building assets, such as university campuses. The AMS can provide valuable insights about asset performance and resource uses, improving cost and time savings, sustainability, and overall efficiency. A web- based AMS application (AMS-App) via BIM-GIS-BI integration is proposed, enabling the reliable digital representation of university assets by combining spatial, performance, and operational data with the related analytics and visualization dashboards. The AMS-App was developed under the umbrella of the University of Turin's strategic plan as a pilot case to apply a data-driven approach aimed at improving asset management procedures. Indeed, the managerial complexity of university campuses involves multiple actors exchanging information through still document-based and fragmented databases, often leading to untimely and ineffective decision-making processes. The AMS-App represents a valuable decision support system aimed at monitoring and improving the users' experience living in the asset, providing better and more sustainable decisions concerning spaces, occupancy flows, and indoor environmental quality (IEQ) in the learning environments. Aiming at demonstrating the effectiveness of the BIM-GIS-BI integration through the AMS-App, several topics were implemented with the following objectives: (i) the digitalization and georeferencing of the university building stock; (ii) the optimization of courses timetables according to spaces availability; (iii) the optimal management of workstations; and (iv) the monitoring, analysis and optimizing of IEQ and user comfort via IoT sensing. The paper presents the developed methodology and its applicability and replicability, illustrating the implemented topics on selected pilot buildings and discussing the results underlining advantages, challenges, and further developments needed for improved efficient and scalable university asset management.