Iot Data Mining

IoT Data Mining is a computational process that systematically extracts hidden patterns, correlations, and knowledge from large-scale, heterogeneous, and real-time sensor-derived data generated by interconnected devices within the Internet of Things, distinguished from general data mining by its focus on streaming, context-aware, and geographically distributed IoT-generated datasets.

282

Publications

18.5K

Citations

975

Authors

493

Institutions

Publications per year

2017–2026

239

Authors

975

  1. VR
    Vangipuram Radhakrishna

    Vignana Jyothi Institute of Management, India

    5 publications · 433 citations

    5

    h-index

  2. LT
    Laurence T. Yang

    St. Francis Xavier University, Canada

    4 publications · 753 citations

    4

    h-index

  3. VJ
    V. Janaki

    Osmania University, India

    4 publications · 320 citations

    4

    h-index

  4. SA
    Shadi Aljawarneh

    Jordan University of Science and Technology, Jordan

    4 publications · 396 citations

    4

    h-index

  5. AV
    Athanasios V. Vasilakos

    Luleå University of Technology, Sweden

    4 publications · 1.2K citations

    4

    h-index

1–5 of 975

Venues

  1. Future Generation Computer Systems

    FGCS · 16 publications · 1.5K citations

    16

    h-index

  2. The Journal of Supercomputing

    7 publications · 475 citations

    8

    h-index

  3. IEEE Internet of Things Journal

    8 publications · 1.2K citations

    8

    h-index

  4. IEEE Access

    8 publications · 1.9K citations

    8

    h-index

  5. Computer Communications

    7 publications · 179 citations

    7

    h-index

1–5