Artificial intelligence in cyber physical systems
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Artificial intelligence in cyber physical systems Petar Radanliev1 · David De Roure1 · Max Van Kleek2 · Omar Santos3 · Uchenna Ani4 Received: 19 April 2020 / Accepted: 10 August 2020 © The Author(s) 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 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. Keywords Artificial cognition · Industrial internet of things · Cyber physical systems · Industry 4.0 · Artificial intelligence · Anomaly detection
1 Introduction
* Petar Radanliev [email protected] David De Roure [email protected] Max Van Kleek [email protected] Omar Santos [email protected] Uchenna Ani [email protected] 1
Engineering Science Department, Oxford e-Research Centre, University of Oxford, 7 Keble Road, Oxford OX1 3QG, England, UK
2
Department of Computer Science, University of Oxford, Oxford, England, UK
3
Cisco Research Centre, Research Triangle Park, NC, USA
4
Faculty of Engineering Science, STEaPP, University College London, London, England, UK
Artificial intelligence (AI) is already changing our economy and society, and the increased AI decision making has triggered debated on the potential harms and the need to make AI decision making more transparent (de Fine Licht et al. 2020, forthcoming). Even with our current technological progress, self-building technologies are possible (Kammerer 2020, forthcoming). Cognitive architectures representing truly intelligent human-like performance, that includes ‘motivation, emotion, personality, and other relevant aspects,’ are also possible (Sun 2020). Such findings trigger concerns on the creation of collective ‘Borg–eye and the We–I’ subjects, by merging the desires of many subjects, e.g. th
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