Shu, L, Rodrigues, JJPC, Cohn, AG orcid.org/0000-0002-7652-8907 et al. (2 more authors) (2022) Editor’s Note. International Journal of Interactive Multimedia and Artificial Intelligence, 7 (5). p. 4. ISSN 1989-1660
Abstract
As the Internet of Things (IoT) further develops and expands to the Internet of Everything (IoE), high-speed multimedia streaming data processing, analysis, and shorter response times are increasingly becoming the demands of today. Driven by the Internet of Things (IoT), a new computing paradigm, Edge computing, is currently developing rapidly. Compared with traditional centralized generalpurpose computing, Edge computing is a distributed architecture. The operations of applications, data and services are moved from the central node of the network to the edge nodes on the network logic for processing. Under this structure, the analysis of data and the generation of knowledge are closer to the source of the data, so it is more suitable for processing. However, with the rapid development of 5G, IoT and other services and scenarios, there are more and more intelligent terminal devices. Multimedia streaming processing in IoT becomes a very prominent problem. To overcome this problem, the adoption of intelligent Edge or Artificial Intelligence (AI) powered Edge computing (Edge-AI) can achieve the goals of lower cost, higher security, lower latency, and ease of management.
Recently, many network modeling methods, computing algorithms, and signal processing technologies have been successfully developed and applied to multimedia streaming processing in IoT with Edge Intelligence. A total of 13 papers are presented in this special issue for the purpose of collecting the latest developments and results on this research topic. We divide them into three categories: production and life applications, security, and text and image processing.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | This item is protected by copyright. This is an open access article under the terms of the Creative Commons Attribution License (CC-BY). |
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) |
Depositing User: | Symplectic Publications |
Date Deposited: | 11 Oct 2022 10:19 |
Last Modified: | 11 Oct 2022 10:19 |
Status: | Published |
Publisher: | Universidad Internacional de La Rioja (UNIR) |
Identification Number: | 10.9781/ijimai.2022.08.010 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:191394 |