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Meta-Model and Tool Support for the Organizational Aspects of Internet-of-Things Development Methods
The University of Rostock, Faculty of Computer Science and Electrical Engineering, Germany.
Jönköping University, School of Engineering, JTH, Department of Computer Science and Informatics. The University of Rostock, Faculty of Computer Science and Electrical Engineering, Germany.ORCID iD: 0000-0002-7431-8412
2021 (English)In: AISS 2021: 2021 3rd International Conference on Advanced Information Science and System (AISS 2021) / [ed] K. Sandkuhl, New York, NY, USA: ACM Digital Library, 2021, article id Article no. 27Conference paper, Published paper (Refereed)
Abstract [en]

The Internet-of-Things (IoT) has long become reality and contributes to the digital transformation of many industrial domains. IoT technologies are at the core of industry 4.0 application scenarios, contribute to cyber-physical system implementation, smart connected products and new business models exploiting their potential. There is plenty of work on how to specify, design and implement IoT solutions, but a lot of enterprises struggle to create business value from IoT technology because they have difficulties to define the organizational integration. Methodologies for model-driven engineering (MDE) of IoT solutions should encompass both, organizational and system development and integration, but existing model-based approaches focus on the technical perspective. The paper proposes a modeling approach integrated into enterprise modeling techniques to compensate for this lack. The enterprise modeling language 4EM is extended by adding a method component for IoT modeling. The main contributions of this paper are (a) a summary of the state-of-research in the field, (b) an industrial case for model-based IoT development, and (c) a meta-model and tool support for IoT modelling.

Place, publisher, year, edition, pages
New York, NY, USA: ACM Digital Library, 2021. article id Article no. 27
National Category
Computer and Information Sciences
Identifiers
URN: urn:nbn:se:hj:diva-55870DOI: 10.1145/3503047.3503077ISBN: 978-1-4503-8586-2 (electronic)OAI: oai:DiVA.org:hj-55870DiVA, id: diva2:1637289
Conference
AISS 2021: 2021 3rd International Conference on Advanced Information Science and System, Sanya, China, November 26 - 28, 2021
Available from: 2022-02-13 Created: 2022-02-13 Last updated: 2022-02-13Bibliographically approved

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