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Applying digital twins for the management of information in turnaround event operations in commercial airports
Univ Politecn Madrid, Dept Ingn Sistemas Telemat, Escuela Tecn Super Ingenieros Telecomunicac, Madrid, Spain..
Univ Politecn Madrid, Dept Ingn Sistemas Telemat, Escuela Tecn Super Ingenieros Telecomunicac, Madrid, Spain..
KTH, Skolan för elektroteknik och datavetenskap (EECS), Datavetenskap, Beräkningsvetenskap och beräkningsteknik (CST).ORCID-id: 0000-0003-4616-189X
Ferrovial, Madrid, Spain..
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2022 (engelsk)Inngår i: Advanced Engineering Informatics, ISSN 1474-0346, E-ISSN 1873-5320, Vol. 54, s. 101723-, artikkel-id 101723Artikkel i tidsskrift (Fagfellevurdert) Published
Abstract [en]

The aerospace sector is one of the many sectors in which large amounts of data are generated. Thanks to the evolution of technology, these data can be exploited in several ways to improve the operation and management of industrial processes. However, to achieve this goal, it is necessary to define architectures and data models that allow to manage and homogenise the heterogeneous data collected. In this paper, we present an Airport Digital Twin Reference Conceptualisation's and data model based on FIWARE Generic Enablers and the Next Generation Service Interfaces-Linked Data standard. Concretely, we particularise the Airport Digital Twin to improve the efficiency of flight turnaround events. The architecture proposed is validated in the Aberdeen International Airport with the aim of reducing delays in commercial flights. The implementation includes an application that shows the real state of the airport, combining two-dimensional and three-dimensional virtual reality representations of the stands, and a mobile application that helps ground operators to schedule departure and arrival flights.

sted, utgiver, år, opplag, sider
Elsevier BV , 2022. Vol. 54, s. 101723-, artikkel-id 101723
Emneord [en]
Aviation, Flight turnaround events, Digital twin, Internet of Things, Data modelling, Big data
HSV kategori
Identifikatorer
URN: urn:nbn:se:kth:diva-319468DOI: 10.1016/j.aei.2022.101723ISI: 000857299300004Scopus ID: 2-s2.0-85137651694OAI: oai:DiVA.org:kth-319468DiVA, id: diva2:1699961
Merknad

QC 20220929

Tilgjengelig fra: 2022-09-29 Laget: 2022-09-29 Sist oppdatert: 2022-09-29bibliografisk kontrollert

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Romero, Mario

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