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oapen-20.500.12657-890912024-04-03T02:23:25Z Chapter BIM-GIS and BI Integration for Facility and Occupancy Management of University Assets: The UNITO Pilot Case Di Giuda, Giuseppe Martino Accardo, Daniele Gasbarri, Paola Meschini, Silvia Tagliabue, Lavinia Chiara Scomparin, Laura Asset Management System BIM-GIS integration Business Intelligence Information management thema EDItEUR::U Computing and Information Technology::UT Computer networking and communications::UTV Virtualization The integration of Building Information Modelling (BIM) and Geographic Information System (GIS) with Business Intelligence (BI) is promising for managing vast and diffused assets. It enables valuable insights into asset performance and resource uses, supporting savings, improved efficiency, and sustainability. The research proposes a web-based Asset Management System application (AMS-app) via BIM-GIS-BI integration, providing an updated digital representation of university assets by combining spatial, performance, and operation data with related analytics. The AMS-app was developed in the context of the University of Turin's strategic plan as a pilot case to improve asset management procedures through a data-driven approach. Indeed, campuses are complex assets managed by multiple actors through still document-based and fragmented databases, often leading to ineffective and untimely decision-making processes. The AMS-app represents a valuable decision support system for facility managers aimed at asset monitoring and user experience improving through better and more sustainable decisions concerning space, occupancy, and indoor environmental quality (IEQ). To demonstrate the effectiveness of the BIM-GIS-BI integration through the AMS-app, several case studies were implemented with the following objectives: (i) the digitalization of university building data, (ii) the optimization of courses timetables according to space availability, (iii) the optimal workstations management, and (iv) the analysis, monitoring and optimizing of IEQ and comfort via IoT networks. The paper illustrates the advantages and applicability of the developed methodology through the case studies, and further developments in university asset management 2024-04-02T15:46:14Z 2024-04-02T15:46:14Z 2023 chapter ONIX_20240402_9791221502893_60 2704-5846 9791221502893 https://library.oapen.org/handle/20.500.12657/89091 eng Proceedings e report application/pdf n/a 9791221502893_41.pdf https://books.fupress.com/doi/capitoli/979-12-215-0289-3_41 Firenze University Press 10.36253/979-12-215-0289-3.41 10.36253/979-12-215-0289-3.41 bf65d21a-78e5-4ba2-983a-dbfa90962870 9791221502893 137 12 Florence open access
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The integration of Building Information Modelling (BIM) and Geographic Information System (GIS) with Business Intelligence (BI) is promising for managing vast and diffused assets. It enables valuable insights into asset performance and resource uses, supporting savings, improved efficiency, and sustainability. The research proposes a web-based Asset Management System application (AMS-app) via BIM-GIS-BI integration, providing an updated digital representation of university assets by combining spatial, performance, and operation data with related analytics. The AMS-app was developed in the context of the University of Turin's strategic plan as a pilot case to improve asset management procedures through a data-driven approach. Indeed, campuses are complex assets managed by multiple actors through still document-based and fragmented databases, often leading to ineffective and untimely decision-making processes. The AMS-app represents a valuable decision support system for facility managers aimed at asset monitoring and user experience improving through better and more sustainable decisions concerning space, occupancy, and indoor environmental quality (IEQ). To demonstrate the effectiveness of the BIM-GIS-BI integration through the AMS-app, several case studies were implemented with the following objectives: (i) the digitalization of university building data, (ii) the optimization of courses timetables according to space availability, (iii) the optimal workstations management, and (iv) the analysis, monitoring and optimizing of IEQ and comfort via IoT networks. The paper illustrates the advantages and applicability of the developed methodology through the case studies, and further developments in university asset management
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