Real-time monitoring of work-at-height safety hazards in construction sites using drones and deep learning.

Journal: Journal of safety research
PMID: 36481029

Abstract

INTRODUCTION: The construction field is considered one of the most dangerous industries. Accidents and fatalities take place on a daily basis in construction projects. Globally, different levels of government have implemented strict rules and regulations to protect workers on job sites. However, despite the efforts to implement the rules and regulations, accidents occur frequently. Falling from heights is considered the most common cause of death in construction. This study developed a novel system integrating deep learning and drones to monitor workers in real-time when performing at-height activities.

Authors

  • Mohammad Z Shanti
    Department of Civil, Infrastructure and Environmental Engineering, Khalifa University of Science and Technology, Abu Dhabi 127788, United Arab Emirates.
  • Chung-Suk Cho
    Department of Civil, Infrastructure and Environmental Engineering, Khalifa University of Science and Technology, Abu Dhabi 127788, United Arab Emirates. Electronic address: chung.cho@ku.ac.ae.
  • Borja Garcia de Soto
    Department of Civil and Urban Engineering, S.M.A.R.T. Construction Research Group, Division of Engineering, New York University Abu Dhabi (NYUAD), Saadiyat Island, Abu Dhabi 129188, United Arab Emirates.
  • Young-Ji Byon
    Department of Civil, Infrastructure and Environmental Engineering, Khalifa University of Science and Technology, Abu Dhabi 127788, United Arab Emirates.
  • Chan Yeob Yeun
    Department of Electrical Engineering and Computer Science, Khalifa University of Science and Technology, Abu Dhabi 127788, United Arab Emirates.
  • Tae Yeon Kim
    Department of Civil, Infrastructure and Environmental Engineering, Khalifa University of Science and Technology, Abu Dhabi 127788, United Arab Emirates.

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