The DOI matches its Crossref record; 6 of the 6 references it cites were found in a registry or an index.
Artificial intelligence in cyber physical systems
Open accessAbstract
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.
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Cites
The Discovery of Grounded Theory; Strategies for Qualitative Research
Glaser, B. G., Strauss, A. L., & Strutzel, E. (1968) · Nursing Research · doi:10.1097/00006199-196807000-00014 · Cited by 39,449
The Discovery of Grounded Theory: Strategies for Qualitative Research
Glaser, B. G., & Strauss, A. L. (2017) · Aldine (Routledge reprint) · doi:10.4324/9780203793206 · Cited by 25,789
Recommender systems and their ethical challenges
Milano, S., Taddeo, M., & Floridi, L. (2020) · AI & SOCIETY · doi:10.1007/s00146-020-00950-y · Cited by 556
de Fine Licht, K., & de Fine Licht, J. (2020) · AI & SOCIETY · doi:10.1007/s00146-020-00960-w · Cited by 334
Future developments in cyber risk assessment for the internet of things
Radanliev, P., De Roure, D. C., Nicolescu, R., Huth, M., Montalvo, R. M., Cannady, S., & Burnap, P. (2018) · Computers in Industry · doi:10.1016/j.compind.2018.08.002 · Cited by 162
Self-citationCan a machine think (anything new)? Automation beyond simulation
Fazi, M. B. (2019) · AI & SOCIETY · doi:10.1007/s00146-018-0821-0 · Cited by 62 · cited 2×
“…Agent-ori-ented Architecture (Ribeiro et al. 2010), Object-oriented Architecture (Thramboulidis 2015), Cloud optimised Virtual Object Architecture (Giordano et al. 2016), supported with Virtual Engineering Objects and Virtual Engineering Processes with Internet Protocol version 6 (IPv6) connected…”
Cited by
Zuiderwijk, A., Chen, Y.-C., & Salem, F. (2021) · Government Information Quarterly · doi:10.1016/j.giq.2021.101577 · Cited by 795
Role of Artificial Intelligence in the Internet of Things (IoT) cybersecurity
Kuzlu, M., Fair, C., & Guler, O. (2021) · Discover Internet of Things · doi:10.1007/s43926-020-00001-4 · Cited by 259
Artificial Intelligence in Government: Taking Stock and Moving Forward
Medaglia, R., Gil-Garcia, J. R., & Pardo, T. A. (2023) · Social Science Computer Review · doi:10.1177/08944393211034087 · Cited by 159
A Review of Anomaly Detection Strategies to Detect Threats to Cyber-Physical Systems
Jeffrey, N., Tan, Q., & Villar, J. R. (2023) · Electronics · doi:10.3390/electronics12153283 · Cited by 160
Future developments in standardisation of cyber risk in the Internet of Things (IoT)
Radanliev, P., De Roure, D. C., Nurse, J. R. C., Mantilla Montalvo, R., Cannady, S., Santos, O., Maddox, L., Burnap, P., & Maple, C. (2020) · SN Applied Sciences · doi:10.1007/s42452-019-1931-0 · Cited by 91
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Metadata
- Authors
- Radanliev, P., De Roure, D., Van Kleek, M., Santos, O., & Ani, U.
- Venue
- AI & SOCIETY
- Published
- 2020-08-27
- Volume
- 36
- Issue
- 3
- Pages
- 783-796
- ISSN
- 0951-5666 (ISSN-L)
- 1435-5655
- OpenAlex
- W3081880709
- Cited by
- 199
- References
- 6
- FWCI
- 23.25
- Type
- journal article
- Language
- en
- Open access
- hybrid
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- Radanliev, P., De Roure, D., Van Kleek, M., Santos, O., & Ani, U. (2021). Artificial intelligence in cyber physical systems. AI & SOCIETY. https://doi.org/10.1007/s00146-020-01049-0
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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.