Mckee, DW orcid.org/0000-0002-9047-7990, Clement, SJ, Almutairi, J et al. (1 more author) (2018) Survey of advances and challenges in intelligent autonomy for distributed cyber-physical systems. CAAI Transactions on Intelligence Technology, 3 (2). pp. 75-82. ISSN 2468-2322
Abstract
With the evolution of the Internet of things and smart cities, a new trend of the Internet of simulation has emerged to utilise the technologies of cloud, edge, fog computing, and high-performance computing for design and analysis of complex cyber-physical systems using simulation. These technologies although being applied to the domains of big data and deep learning are not adequate to cope with the scale and complexity of emerging connected, smart, and autonomous systems. This study explores the existing state-of-the-art in automating, augmenting, and integrating systems across the domains of smart cities, autonomous vehicles, energy efficiency, smart manufacturing in Industry 4.0, and healthcare. This is expanded to look at existing computational infrastructure and how it can be used to support these applications. A detailed review is presented of advances in approaches providing and supporting intelligence as a service. Finally, some of the remaining challenges due to the explosion of data streams; issues of safety and security; and others related to big data, a model of reality, augmentation of systems, and computation are examined.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | This is an open access article published by the IET, Chinese Association for Artificial Intelligence and Chongqing University of Technology under the Creative Commons Attribution License (https://creativecommons.org/licenses/by/3.0/). |
Keywords: | smart cities; Big Data; energy conservation; cloud computing; service-oriented architecture; intelligent manufacturing systems; security of data; Internet of Things; production engineering computing; cyber-physical systems |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Engineering & Physical Sciences (Leeds) > School of Computing (Leeds) |
Funding Information: | Funder Grant number EPSRC EP/K014226/1 |
Depositing User: | Symplectic Publications |
Date Deposited: | 14 Mar 2018 16:51 |
Last Modified: | 25 Jun 2023 21:16 |
Status: | Published |
Publisher: | IET |
Identification Number: | 10.1049/trit.2018.0010 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:128485 |