Artificial Intelligence (AI) and Machine Learning for Multimedia and Edge Information Processing

Jasmine Kah Phooi Seng; Kenneth Li-minn Ang; Eno Peter; Anthony Mmonyi

doi:10.3390/electronics11142239

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Artificial Intelligence (AI) and Machine Learning for Multimedia and Edge Information Processing

Journal article

Open access

Peer reviewed

Artificial Intelligence (AI) and Machine Learning for Multimedia and Edge Information Processing

Jasmine Kah Phooi Seng, Kenneth Li-minn Ang, Eno Peter and Anthony Mmonyi

Electronics, Vol.11(14), pp.1-39

2022

DOI: https://doi.org/10.3390/electronics11142239

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Abstract

edge AI

edge computing

edge multimedia

edge multimedia analytics

intelligence edge

multimedia processing

The advancements and progress in artificial intelligence (AI) and machine learning, and the numerous availabilities of mobile devices and Internet technologies together with the growing focus on multimedia data sources and information processing have led to the emergence of new paradigms for multimedia and edge AI information processing, particularly for urban and smart city environments. Compared to cloud information processing approaches where the data are collected and sent to a centralized server for information processing, the edge information processing paradigm distributes the tasks to multiple devices which are close to the data source. Edge information processing techniques and approaches are well suited to match current technologies for Internet of Things (IoT) and autonomous systems, although there are many challenges which remain to be addressed. The motivation of this paper was to survey these new paradigms for multimedia and edge information processing from several technological perspectives including: (1) multimedia analytics on the edge empowered by AI; (2) multimedia streaming on the intelligent edge; (3) multimedia edge caching and AI; (4) multimedia services for edge AI; and (5) hardware and devices for multimedia on edge intelligence. The review covers a wide spectrum of enabling technologies for AI and machine learning for multimedia and edge information processing.

Details

Title: Artificial Intelligence (AI) and Machine Learning for Multimedia and Edge Information Processing
Authors: Jasmine Kah Phooi Seng (Corresponding Author) - Xi’an Jiaotong-Liverpool University
Kenneth Li-minn Ang (Author) - University of the Sunshine Coast, Queensland, School of Science, Technology and Engineering
Eno Peter (Author) - Federal University Oye Ekiti
Anthony Mmonyi (Author) - Afe Babalola University
Publication details: Electronics, Vol.11(14), pp.1-39
Publisher: MDPI AG
Date published: 2022
DOI: 10.3390/electronics11142239
ISSN: 2079-9292
Copyright note: © 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
Organisation Unit: University of the Sunshine Coast, Queensland; School of Science, Technology and Engineering; Engage Research Lab
Language: English
Record Identifier: 99663998202621
Output Type: Journal article

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Collaboration types: Domestic collaboration; International collaboration
Web Of Science research areas: Computer Science, Information Systems; Engineering, Electrical & Electronic; Physics, Applied

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