Computer Vision-based Safety Monitoring

Computer Vision-Based Safety Monitoring is a computational methodology within mine safety automation that employs image and video analysis through artificial intelligence to detect hazards, monitor compliance with safety protocols, and enable real-time risk assessment in underground and surface mining environments.

163

Publications

8.3K

Citations

550

Authors

184

Institutions

Publications per year

2017–2026

142

Authors

550

  1. CP
    Chansik Park

    Chung-Ang University, South Korea

    6 publications · 180 citations

    6

    h-index

  2. DL
    Doyeop Lee

    Chung-Ang University, South Korea

    4 publications · 128 citations

    4

    h-index

  3. BE
    Bahaa Eddine Mneymneh

    American University of Beirut, Lebanon

    3 publications · 244 citations

    3

    h-index

  4. HL
    Heng Li

    Hong Kong Polytechnic University, Hong Kong SAR China

    3 publications · 411 citations

    3

    h-index

  5. ZZ
    Zhenhua Zhu

    Nanjing University of Chinese Medicine, China

    3 publications · 337 citations

    3

    h-index

1–5 of 550

Venues

  1. Sensors

    9 publications · 680 citations

    11

    h-index

  2. Automation in Construction

    9 publications · 709 citations

    9

    h-index

  3. Journal of Computing in Civil Engineering

    8 publications · 807 citations

    8

    h-index

  4. 5

    h-index

  5. Applied Sciences

    5 publications · 143 citations

    5

    h-index

1–5