Risk factors and emerging technologies for preventing falls from heights at construction sites

M Khan, C Nnaji, MS Khan, A Ibrahim, D Lee… - Automation in …, 2023 - Elsevier
Falls at construction sites account for approximately 50% of all accidents reported in the US
annually, making them the leading cause of injuries and fatalities. Although there have been …

A Review of Computer Vision-Based Monitoring Approaches for Construction Workers' Work-Related Behaviors

J Li, Q Miao, Z Zou, H Gao, L Zhang, Z Li… - IEEE Access, 2024 - ieeexplore.ieee.org
Construction workers' behaviors directly affects labor productivity and their own safety,
thereby influencing project quality. Recognizing and monitoring the construction-related …

Construction work-stage-based rule compliance monitoring framework using computer vision (CV) technology

N Khan, SFA Zaidi, J Yang, C Park, D Lee - Buildings, 2023 - mdpi.com
Noncompliance with safety rules is a major cause of unsatisfactory performance in
construction safety worldwide. Although some research efforts have focused on using …

[HTML][HTML] Exploring construction workers' attention and awareness in diverse virtual hazard scenarios to prevent struck-by accidents

R Hussain, SFA Zaidi, A Pedro, H Lee, C Park - Safety science, 2024 - Elsevier
Repetitive tasks in construction reduce workers' attentiveness of hazards on sites. This
decline in attentiveness can be influenced by their situation awareness level. However …

Real-time monitoring unsafe behaviors of portable multi-position ladder worker using deep learning based on vision data

M Park, J Bak, AS Kulinan, S Park - Journal of safety research, 2023 - Elsevier
Introduction: Fatal fall from height accidents, especially on construction sites, persist,
underscoring the importance of monitoring and managing worker behaviors to enhance …

Secure Your Steps: A Class-Based Ensemble Framework for Real-Time Fall Detection Using Deep Neural Networks

MM Kabir, J Shin, MF Mridha - IEEE Access, 2023 - ieeexplore.ieee.org
Falls represent a significant public health concern, particularly concerning vulnerable
populations such as older adults. Accurate detection and classification of falls are critical for …

Computer vision-based hazard identification of construction site using visual relationship detection and ontology

Y Li, H Wei, Z Han, N Jiang, W Wang, J Huang - Buildings, 2022 - mdpi.com
Onsite systematic monitoring benefits hazard prevention immensely. Hazard identification is
usually limited due to the semantic gap. Previous studies that integrate computer vision and …

Rotation error detection of gallium nitride (GaN) substrate in MBE utilizing ensemble learning

S Anjum, HY Lee, HK Noh - Crystal Growth & Design, 2023 - ACS Publications
A rotating substrate is essential for achieving high-quality and uniform growth of gallium
nitride (GaN) thin films in molecular beam epitaxy (MBE). By rotating the substrate during …

Human risky behaviour recognition during ladder climbing based on multi-modal feature fusion and adaptive graph convolutional network

W Zhu, D Shi, R Cheng, R Huang, T Hu… - Signal, Image and Video …, 2024 - Springer
Human falls during ladder climbing are typically instantaneous, making the timely and
accurate determination of security risks during ladder climbing a challenging engineering …

Vision-Based Construction Safety Monitoring Utilizing Temporal Analysis to Reduce False Alarms

SFA Zaidi, J Yang, MS Abbas, R Hussain, D Lee… - Buildings, 2024 - mdpi.com
Construction safety requires real-time monitoring due to its hazardous nature. Existing vision-
based monitoring systems classify each frame to identify safe or unsafe scenes, often …