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Domain framework for implementation of open IoT ecosystems
- Source :
- International Journal of Production Research, International Journal of Production Research, Taylor & Francis, 2018, 56 (7), pp.2552-2569. ⟨10.1080/00207543.2017.1385870⟩
- Publication Year :
- 2018
- Publisher :
- HAL CCSD, 2018.
-
Abstract
- International audience; The current Internet-of-things (IoT) hype, pushed by the unprecedented rate of the technological enablers’ innovation, is threatening to leave behind some major, not so obvious, unresolved issues. IoT platforms will extend existing enterprise information systems (EIS) infrastructures to encompass cross-domain sensing and actuating capabilities, thus introducing additional complexity and major risks to the implementation. Furthermore, IoT platforms are typically driven by models of the trivial complexity; they support very simple data structures and almost no business logic implementation. Finally, IoT systems are today managed centrally, which often means less openness, less flexibility and greater change management costs. In this article, we provide the overview of the scientific disciplines which could contribute to the resolution of the IoT implementation problem, namely requirements engineering, change management/continuous improvement, model-based systems engineering, system architecture design, interoperability and policy and regulatory aspects. Then, we identify the challenges of these contributions in the context of IoT and finally make an attempt to identify research directions which could have a significant impact. The discussion of the challenges and opportunities is illustrated by the proposed domain framework for implementation of open IoT ecosystems.
- Subjects :
- Flexibility (engineering)
Internet of things
Requirements engineering
Computer science
Strategy and Management
Interoperability
Model-based systems engineering
interoperability
maturity assessment
02 engineering and technology
Management Science and Operations Research
Industrial and Manufacturing Engineering
Change management (ITSM)
World Wide Web
[SPI]Engineering Sciences [physics]
Risk analysis (engineering)
020204 information systems
model-based systems engineering
0202 electrical engineering, electronic engineering, information engineering
Information system
Business logic
020201 artificial intelligence & image processing
multi-agent systems
requirements engineering
Enterprise information system
Subjects
Details
- Language :
- English
- ISBN :
- 978-0-321-63584-6
0-321-63584-1 - ISSN :
- 00207543 and 1366588X
- ISBNs :
- 9780321635846 and 0321635841
- Database :
- OpenAIRE
- Journal :
- International Journal of Production Research, International Journal of Production Research, Taylor & Francis, 2018, 56 (7), pp.2552-2569. ⟨10.1080/00207543.2017.1385870⟩
- Accession number :
- edsair.doi.dedup.....26597f19003c3b2ac345fa67bcaaed60
- Full Text :
- https://doi.org/10.1080/00207543.2017.1385870⟩