Toward intelligent cyber-physical systems: Digital twin meets artificial intelligence

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dc.contributor.author Groshev, Milan
dc.contributor.author Magalhaes Guimaraes, Carlos Eduardo
dc.contributor.author Martín Pérez, Jorge
dc.contributor.author Oliva Delgado, Antonio de la
dc.date.accessioned 2022-01-19T11:52:40Z
dc.date.available 2022-01-19T11:52:40Z
dc.date.issued 2021-08
dc.identifier.bibliographicCitation Groshev, M., Guimaraes, C., Martín-Pérez, J. & de la Oliva, A. (2021). Toward Intelligent Cyber-Physical Systems: Digital Twin Meets Artificial Intelligence. IEEE Communications Magazine, 59(8), 14–20.
dc.identifier.issn 0163-6804
dc.identifier.uri http://hdl.handle.net/10016/33912
dc.description.abstract Industry 4.0 aims to support smarter and autonomous processes while improving agility, cost efficiency, and user experience. To fulfill its promises, properly processing the data of the industrial processes and infrastructures is required. Artificial intelligence (AI) appears as a strong candidate to handle all generated data, and to help in the automation and smartification process. This article overviews the digital twin as a true embodiment of a cyber-physical system (CPS) in Industry 4.0, showing the mission of AI in this concept. It presents the key enabling technologies of the digital twin such as edge, fog, and 5G, where the physical processes are integrated with the computing and network domains. The role of AI in each technology domain is identified by analyzing a set of AI agents at the application and infrastructure levels. Finally, movement prediction is selected and experimentally validated using real data generated by a digital twin for robotic arms with results showcasing its potential.
dc.description.sponsorship This work has been (partially) funded by the H2020 EU/TW joint action 5G-DIVE (Grant #859881) and the H2020 5Growth project (Grant #856709). It has also been funded by the Spanish State Research Agency (TRUE5G project, PID2019-108713RB-C52/AEI/10.13039/501100011033).
dc.format.extent 7
dc.language.iso eng
dc.publisher IEEE
dc.rights © 2021 IEEE.
dc.subject.other Program processors
dc.subject.other Service robots
dc.subject.other 5G mobile communication
dc.subject.other Digital twin
dc.subject.other Cyber-physical systems
dc.subject.other Manipulators
dc.subject.other User experience
dc.subject.other Artificial intelligence
dc.subject.other Fourth Indusrial Revolution
dc.title Toward intelligent cyber-physical systems: Digital twin meets artificial intelligence
dc.type article
dc.subject.eciencia Telecomunicaciones
dc.identifier.doi https://doi.org/10.1109/MCOM.001.2001237
dc.rights.accessRights openAccess
dc.relation.projectID info:eu-repo/grantAgreement/EC/H2020/856709/5Growth
dc.relation.projectID info:eu-repo/grantAgreement/EC/H2020/859881/5G-DIVE
dc.relation.projectID Gobierno de España. PID2019-108713RB-C52
dc.type.version acceptedVersion
dc.identifier.publicationfirstpage 14
dc.identifier.publicationissue 8
dc.identifier.publicationlastpage 20
dc.identifier.publicationtitle IEEE Communications Magazine
dc.identifier.publicationvolume 59
dc.identifier.uxxi AR/0000029341
dc.contributor.funder European Commission
dc.contributor.funder Agencia Estatal de Investigación (España)
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