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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...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer London
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7451704/ https://www.ncbi.nlm.nih.gov/pubmed/32874020 http://dx.doi.org/10.1007/s00146-020-01049-0 |
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author | Radanliev, Petar De Roure, David Van Kleek, Max Santos, Omar Ani, Uchenna |
author_facet | Radanliev, Petar De Roure, David Van Kleek, Max Santos, Omar Ani, Uchenna |
author_sort | Radanliev, Petar |
collection | PubMed |
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. |
format | Online Article Text |
id | pubmed-7451704 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Springer London |
record_format | MEDLINE/PubMed |
spelling | pubmed-74517042020-08-28 Artificial intelligence in cyber physical systems Radanliev, Petar De Roure, David Van Kleek, Max Santos, Omar Ani, Uchenna AI Soc Open Forum 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. Springer London 2020-08-27 2021 /pmc/articles/PMC7451704/ /pubmed/32874020 http://dx.doi.org/10.1007/s00146-020-01049-0 Text en © The Author(s) 2020 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Open Forum Radanliev, Petar De Roure, David Van Kleek, Max Santos, Omar Ani, Uchenna 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 |
topic | Open Forum |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7451704/ https://www.ncbi.nlm.nih.gov/pubmed/32874020 http://dx.doi.org/10.1007/s00146-020-01049-0 |
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