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Journal article

Artificial intelligence in cyber physical systems

Abstract:
This article conducts a literature review of current and future challenges in the use of artificial intelligence (AI) in cyber physical systems. The literature review is focused on identifying a conceptual framework for increasing resilience with AI through automation supporting both, a technical and human level. The methodology applied resembled a literature review and taxonomic analysis of complex internet of things (IoT) interconnected and coupled cyber physical systems. There is an increased attention on propositions on models, infrastructures and frameworks of IoT in both academic and technical papers. These reports and publications frequently represent a juxtaposition of other related systems and technologies (e.g. Industrial Internet of Things, Cyber Physical Systems, Industry 4.0 etc.). We review academic and industry papers published between 2010 and 2020. The results determine a new hierarchical cascading conceptual framework for analysing the evolution of AI decision-making in cyber physical systems. We argue that such evolution is inevitable and autonomous because of the increased integration of connected devices (IoT) in cyber physical systems. To support this argument, taxonomic methodology is adapted and applied for transparency and justifications of concepts selection decisions through building summary maps that are applied for designing the hierarchical cascading conceptual framework.
Publication status:
Published
Peer review status:
Peer reviewed

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Publisher copy:
10.1007/s00146-020-01049-0

Authors

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Institution:
University of Oxford
Division:
MPLS
Department:
Engineering Science
Sub department:
Oxford e-Research Centre
Role:
Author
ORCID:
0000-0001-9074-3016


Publisher:
Springer
Journal:
AI and Society More from this journal
Volume:
36
Issue:
3
Pages:
783–796
Publication date:
2020-08-27
Acceptance date:
2020-08-10
DOI:
EISSN:
1435-5655
ISSN:
0951-5666
Pmid:
32874020


Language:
English
Keywords:
Pubs id:
1130597
Local pid:
pubs:1130597
Deposit date:
2020-09-09
ARK identifier:

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