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Title	Building Digital Twins Of Cities Using The Inter Model Broker Framework
ID_Doc	13018
Authors	Lohman W.; Cornelissen H.; Borst J.; Klerkx R.; Araghi Y.; Walraven E.
Year	2023
Published	Future Generation Computer Systems, 148
DOI	http://dx.doi.org/10.1016/j.future.2023.06.024
Abstract	Urban areas are becoming increasingly crowded, and as a result it is challenging to ensure that these areas remain liveable and accessible. Municipalities need to make strategic long-term decisions regarding urban planning, which is often a difficult and time-consuming task. Digital twins of cities can assist policy makers during this process, providing an integral view on e.g. traffic intensities, air quality and noise. Furthermore, a digital twin enables policy makers to simulate ‘what if scenarios’ in a scenario-based analysis. Digital twins connect data, analytics and visualizations, which requires a system which integrates all these aspects in a single framework. This paper presents the Inter Model Broker framework, which is a scalable framework based on which large-scale digital twins can be built. A key property of our framework is that all connected system modules hold the relevant data locally in memory, which means that no central database is required. The effectiveness of our framework is demonstrated in a case study based on the city of Amsterdam in The Netherlands. © 2023 Elsevier B.V.
Author Keywords	Big data analytics; Digital twin; Distributed simulation; Integration framework; Smart city; Urban planning

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