Artificial intelligence in cyber physical systems
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 an...
Main Authors: | , , , , |
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Format: | Journal article |
Language: | English |
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Springer
2020
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_version_ | 1826302675156729856 |
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author | Radanliev, P De Roure, D Van Kleek, M Santos, O Ani, U |
author_facet | Radanliev, P De Roure, D Van Kleek, M Santos, O Ani, U |
author_sort | Radanliev, P |
collection | OXFORD |
description | 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. |
first_indexed | 2024-03-07T05:51:09Z |
format | Journal article |
id | oxford-uuid:e8ecc2e3-cacd-43cb-ad62-a6daf2c00477 |
institution | University of Oxford |
language | English |
last_indexed | 2024-03-07T05:51:09Z |
publishDate | 2020 |
publisher | Springer |
record_format | dspace |
spelling | oxford-uuid:e8ecc2e3-cacd-43cb-ad62-a6daf2c004772022-03-27T10:50:26ZArtificial intelligence in cyber physical systemsJournal articlehttp://purl.org/coar/resource_type/c_dcae04bcuuid:e8ecc2e3-cacd-43cb-ad62-a6daf2c00477EnglishSymplectic ElementsSpringer2020Radanliev, PDe Roure, DVan Kleek, MSantos, OAni, UThis 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. |
spellingShingle | Radanliev, P De Roure, D Van Kleek, M Santos, O Ani, U Artificial intelligence in cyber physical systems |
title | Artificial intelligence in cyber physical systems |
title_full | Artificial intelligence in cyber physical systems |
title_fullStr | Artificial intelligence in cyber physical systems |
title_full_unstemmed | Artificial intelligence in cyber physical systems |
title_short | Artificial intelligence in cyber physical systems |
title_sort | artificial intelligence in cyber physical systems |
work_keys_str_mv | AT radanlievp artificialintelligenceincyberphysicalsystems AT deroured artificialintelligenceincyberphysicalsystems AT vankleekm artificialintelligenceincyberphysicalsystems AT santoso artificialintelligenceincyberphysicalsystems AT aniu artificialintelligenceincyberphysicalsystems |