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Towards a Reference Architecture for Future Industrial Internet of Things Networks

Martin, Dominik ORCID iD icon; Kühl, Niklas ORCID iD icon; Schwenk, Marcel

Abstract:

With the continuing decrease of sensor technology prices as well as the increase of communication and analytical capabilities of modern internet of things devices, the continuously generated amount of data is constantly growing. Various use cases show the untapped potential of this data for new business models. However, conventional industrial IT networks of traditional manufacturing companies can hardly meet the modern requirements emerging with today's and future industrial internet of things applications. Outdated and rigid network infrastructures are one of the main reasons for hesitant innovation efforts and cross-organizational collaborations as well as the slow adoption of modern business models by traditional manufacturing companies.
Following the design science research paradigm, our work contributes by elaborating on a comprehensive list of requirements for future industrial internet of things networks from a theoretical and practical perspective as well as a proposed reference architecture acting as a blueprint for future implementations.


Preprint §
DOI: 10.5445/IR/1000137118
Originalveröffentlichung
DOI: 10.1109/CBI52690.2021.10049
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Zitationen: 1
Cover der Publikation
Zugehörige Institution(en) am KIT Institut für Wirtschaftsinformatik und Marketing (IISM)
Karlsruhe Service Research Institute (KSRI)
Publikationstyp Proceedingsbeitrag
Publikationsdatum 01.09.2021
Sprache Englisch
Identifikator ISBN: 978-1-6654-2069-3
ISSN: 2378-1971
KITopen-ID: 1000137118
Erschienen in Proceedings : 2021 IEEE 23rd Conference on Business Informatics, CBI 2021, Virtual Conference 1-3 September 2021, Volume 2 – CBI Forum and Workshop Papers. Ed.: J.P.A. Almeida
Veranstaltung 23rd IEEE Conference on Business Informatics (IEEE CBI 2021), Online, 01.09.2021 – 03.09.2021
Verlag Institute of Electrical and Electronics Engineers (IEEE)
Seiten 1-9
Projektinformation bi.smart; TP (BMBF, 02J19B041)
Nachgewiesen in Scopus
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arXiv
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