Version 1
: Received: 11 March 2019 / Approved: 13 March 2019 / Online: 13 March 2019 (09:06:29 CET)
Version 2
: Received: 12 September 2020 / Approved: 14 September 2020 / Online: 14 September 2020 (05:47:48 CEST)
Radanliev, Petar., De Roure, David., Van Kleek, Max., Santos, Omar., and Ani, Uchenna, “Artificial intelligence in cyber physical systems,” AI Soc., vol. 1, p. 1-14, Aug. 2020.
Radanliev, Petar., De Roure, David., Van Kleek, Max., Santos, Omar., and Ani, Uchenna, “Artificial intelligence in cyber physical systems,” AI Soc., vol. 1, p. 1-14, Aug. 2020.
Radanliev, Petar., De Roure, David., Van Kleek, Max., Santos, Omar., and Ani, Uchenna, “Artificial intelligence in cyber physical systems,” AI Soc., vol. 1, p. 1-14, Aug. 2020.
Radanliev, Petar., De Roure, David., Van Kleek, Max., Santos, Omar., and Ani, Uchenna, “Artificial intelligence in cyber physical systems,” AI Soc., vol. 1, p. 1-14, Aug. 2020.
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 methodol- ogy 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.
Keywords
Industrial Internet of Things; Cyber Physical Systems; Internet of Everything; Industry 4.0; Digital Industry; Digital Economy
Subject
Engineering, Control and Systems Engineering
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Commenter: Petar Radanliev
Commenter's Conflict of Interests: Author