Edge-ai Integration

Edge–AI Integration is a framework-level academic concept that denotes the seamless incorporation of artificial intelligence models and algorithms into multi-access edge computing environments, distinguished by its emphasis on enabling real-time, low-latency, and context-aware intelligent processing directly at the network edge.

257

Publications

26.6K

Citations

1.2K

Authors

489

Institutions

Publications per year

2017–2026

255

Authors

1.2K

  1. DN
    Dusit Niyato

    Nanyang Technological University, Singapore

    13 publications · 3.2K citations

    12

    h-index

  2. GZ
    Guangxu Zhu

    Shenzhen Research Institute of Big Data, China

    10 publications · 1.4K citations

    10

    h-index

  3. ZX
    Zehui Xiong

    Nanyang Technological University, Singapore

    10 publications · 1.7K citations

    10

    h-index

  4. JK
    Jiawen Kang

    Guangdong University of Technology, China

    9 publications · 1.5K citations

    9

    h-index

  5. XS
    Xuemin Shen

    University of Waterloo, Canada

    7 publications · 1.4K citations

    7

    h-index

1–5 of 1.2K

Venues

  1. IEEE Network

    16 publications · 1.9K citations

    14

    h-index

  2. arXiv (Cornell University)

    Repository · 13 publications · 545 citations

    11

    h-index

  3. IEEE Internet of Things Journal

    10 publications · 2.5K citations

    10

    h-index

  4. IEEE Access

    10 publications · 621 citations

    10

    h-index

  5. IEEE Wireless Communications

    9 publications · 600 citations

    9

    h-index

1–5