Toward cognitive digital twins using a BIM-GIS asset management system for a diffused university - Meschini, Silvia; Pellegrini, Laura; Locatelli, Mirko; Accardo, Daniele; Tagliabue, Lavinia Chiara; Di Giuda, Giuseppe Martino; Avena, Marco (Frontiers in Built Environment, 2022)
The integrated use of BIM (Building Information Modeling) and GIS (Geographic Information System) is promising to develop Asset Management Systems (AMS) for Operation & Maintenance (O&M) in smart university campuses. The combination of BIM-GIS with Cognitive Digital Twins (CDTs) can furtherly facilitate the management of complex systems such as university building stock. CDTs enable buildings to behave as autonomous entities, dynamically reacting to environmental changes. Timely decisions based on the actual conditions of buildings and surroundings can be provided, both in emergency scenarios or when optimised and adaptive performances are required. The research aims to develop a BIM-GIS based AMS for improving user experience and enabling the optimal use of resources in the O&M phase of an Italian university. Campuses are complex assets, mainly diffused with buildings spread across the territory, managed with still document-based and fragmented databases handled by several subjects. This results in incomplete and asymmetrical information, often leading to ineffective and untimely decisions. The paper presents a methodology for the development of a BIM-GIS web-based platform (i.e. AMS-app) providing the real-time visualisation of the asset in an interactive 3D map connected to analytical dashboards for management support. Two buildings of the University of Turin are adopted as demonstrators, illustrating the development of an easy-accessible, centralised database by integrating spatial and functional data, useful also to develop future CDTs. As a first attempt to show the AMS application potentials, crowd simulations have been conducted to understand the actual buildings level of safety in case of fire emergency and demonstrate how CDTs could improve it. The identification of data needed, also gathered through the future implementation of suitable sensors and Internet of Things networks, is the core issue together with the definition of effective asset visualisation and monitoring methods. Future developments will explore the integration of Artificial Intelligence and immersive technologies to enable space use optimization and real-time wayfinding during evacuation, exploiting digital tools to alert and drive users or authorities for safety improvement. The ability to easily optimise the paths with respect to the actual occupancy and conditions of both the asset and surroundings will be enabled.