TY - JOUR
AU - 
AB - fbuil-06-00136 September 22, 2020 Time: 19:47 # 1 ORIGINAL RESEARCH published: 24 September 2020 doi: 10.3389/fbuil.2020.00136 Detection of Personal Protective Equipment (PPE) Compliance on Construction Site Using Computer Vision Based Deep Learning Techniques Venkata Santosh Kumar Delhi*, R. Sankarlal and Albert Thomas Construction Technology and Management Division, Civil Engineering Department, Indian Institute of Technology Bombay, Mumbai, India Construction safety is a matter of great concern for practitioners and researchers worldwide. Even after risk assessments have been conducted and adequate controls have been implemented, workers are still subject to safety hazards in construction work environments. The need for personal protective equipment (PPE) is important in this context. Automatic and real-time detection of the non-compliance of workers in using PPE is an important concern. Developments in the field of computer vision and data analytics, especially using deep learning algorithms have the potential to address this challenge in construction. This study developed a framework to sense in Edited by: real-time, the safety compliance of construction workers with respect to PPE, which is Dryver R. Huston, University of Vermont, United States intended to be integrated into the safety workflow of an organization. The study makes Reviewed by: use of the Convolutional Neural Networks 
TI - Detection of Personal Protective Equipment (PPE) Compliance on Construction Site Using Computer Vision Based Deep Learning Techniques
JF - Frontiers in Built Environment
DO - 10.3389/fbuil.2020.00136
DA - 2020-09-24
UR - https://www.deepdyve.com/lp/unpaywall/detection-of-personal-protective-equipment-ppe-compliance-on-Wm1eSPV1WA
DP - DeepDyve
ER -