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E. Peltonen et al., "The Many Faces of Edge Intelligence," in IEEE Access, vol. 10, pp. 104769-104782, 2022, doi: 10.1109/ACCESS.2022.3210584.

The many faces of edge intelligence

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Author: Peltonen, Ella1; Ahmad, Ijaz2; Aral, Atakan3;
Organizations: 1University of Oulu, Finland
2VTT Technical Research Centre, Finland
3University of Vienna, Austria
4Business Innovation Manager, Capobianco, Italy
5TU Delft, Netherlands
6University of Vigo, Spain
7Oulu University of Applied Sciences, Finland
8University of Helsinki, Finland
9Technical University of Munich, Germany
10Poznan University of Technology, Poland
11Pengcheng Laboratory, China
Format: article
Version: published version
Access: open
Online Access: PDF Full Text (PDF, 2.2 MB)
Persistent link: http://urn.fi/urn:nbn:fi-fe2022100761313
Language: English
Published: Institute of Electrical and Electronics Engineers, 2022
Publish Date: 2022-10-07
Description:

Abstract

Edge Intelligence (EI) is an emerging computing and communication paradigm that enables Artificial Intelligence (AI) functionality at the network edge. In this article, we highlight EI as an emerging and important field of research, discuss the state of research, analyze research gaps and highlight important research challenges with the objective of serving as a catalyst for research and innovation in this emerging area. We take a multidisciplinary view to reflect on the current research in AI, edge computing, and communication technologies, and we analyze how EI reflects on existing research in these fields. We also introduce representative examples of application areas that benefit from, or even demand the use of EI.

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Series: IEEE access
ISSN: 2169-3536
ISSN-E: 2169-3536
ISSN-L: 2169-3536
Volume: 10
Pages: 104769 - 104782
DOI: 10.1109/access.2022.3210584
OADOI: https://oadoi.org/10.1109/access.2022.3210584
Type of Publication: A1 Journal article – refereed
Field of Science: 213 Electronic, automation and communications engineering, electronics
113 Computer and information sciences
Subjects:
5G
6G
Edge Computing
Edge Intelligence
Article
Funding: This paper has been written by an international expert group, led by the 6G Flagship at the University of Oulu, Finland (AoF grants 318927, 326291, 323630; Infotech Oulu grants B-TEA, TrustedMaaS). This work is partially supported by the European Union’s Horizon 2020 research and innovation programme under the grant agreement No. 101021808 and Marie Skłodowska-Curie grant agreement No. 956090, National Science Centre in Poland (grant 2018/29/B/ST7/01241), Austrian Science Fund (FWF grants Y 904-N31, I 5201-N), CHIST-ERA (grant CHIST-ERA-19-CES-005) and the City of Vienna (5G Use Case Challenge InTraSafEd 5G).
Academy of Finland Grant Number: 318927
323630
Detailed Information: 318927 (Academy of Finland Funding decision)
323630 (Academy of Finland Funding decision)
Copyright information: © 2022 Authors. This work is licensed under a Creative Commons Attribution 4.0 License. For more information, see https://creativecommons.org/licenses/by/4.0/
  https://creativecommons.org/licenses/by/4.0/