Iot Data Cleaning

IoT Data Cleaning is a data preprocessing methodology that specifically addresses the identification, correction, and removal of errors, inconsistencies, and noise in raw data generated by Internet of Things devices to ensure data accuracy, completeness, and reliability for downstream analytics and decision-making.

30

Publications

872

Citations

113

Authors

60

Institutions

Publications per year

2017–2026

26

Authors

113

  1. JL
    Joohyung Lee

    Gachon University, South Korea

    1 publications · 16 citations

    1

    h-index

  2. VJ
    V.A. Jane

    1 publications · 21 citations

    1

    h-index

  3. SA
    Sarah Alkadi

    King Saud University, Saudi Arabia

    1 publications · 26 citations

    1

    h-index

  4. RR
    Ridhima Rani

    Chitkara University, India

    1 publications · 25 citations

    1

    h-index

  5. SL
    Shuangqi Li

    University of Bath, United Kingdom

    1 publications · 33 citations

    1

    h-index

1–5 of 113

Venues

  1. IEEE Internet of Things Journal

    3 publications · 148 citations

    3

    h-index

  2. Sensors

    2 publications · 121 citations

    2

    h-index

  3. 1

    h-index

  4. Intelligent and Converged Networks

    1 publications · 30 citations

    1

    h-index

  5. Applied Energy

    1 publications · 33 citations

    1

    h-index

1–5