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Information Fusion for Edge Intelligence: A Survey
Information Fusion
  • Yin Zhang, University of Electronic Science and Technology of China
  • Chi Jiang, Zhongnan University of Economics and Law
  • Binglei Yue, Zhongnan University of Economics and Law
  • Jiafu Wan, South China University of Technology
  • Mohsen Guizani, Mohamed Bin Zayed University of Artificial Intelligence
Document Type

Edge intelligence capability is expected to enable the development of a new paradigm integrated with edge computing and artificial intelligence. However, due to the multisource nature, heterogeneity, and a large scale of the sensory data, it is necessary to improve the data processing and decision-making capacity for the edges. Hence, this paper asserts that information fusion is an important technique to power the capacity of edge intelligence in terms of collection, communication, computing, caching, control and collaboration. Specifically, it provides a comprehensive investigation of four representative scenarios assisted by information fusion at the edge, i.e., multisource information fusion, real-time information fusion, event-driven information fusion, and context-aware information fusion. Moreover, it discusses the future directions and open issues in this field.

Publication Date
  • Context-aware,
  • Event-driven,
  • Information fusion,
  • Multisource,
  • Real-time

IR deposit conditions:

  • OA version (accepted version) - pathway b
  • 24 month embargo
  • Must link to publisher version with DOI
Citation Information
Y. Zhang, C. Jiang, B. Yue, J. Wan, and M. Guizani, “Information fusion for edge intelligence: A survey,”Information Fusion, vol. 81, pp. 171–186, May 2022, doi: 10.1016/J.INFFUS.2021.11.018.