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

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

*Corresponding author for this work

Research output: Contribution to journalReview articlepeer-review

4 Citations (Scopus)

Abstract

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.

Original languageEnglish
Article number2239
JournalElectronics (Switzerland)
Volume11
Issue number14
DOIs
Publication statusPublished - Jul 2022

Keywords

  • edge AI
  • edge computing
  • edge multimedia
  • edge multimedia analytics
  • intelligence edge
  • multimedia processing

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