Computer vision and long short-term memory: Learning to predict unsafe behaviour in construction
Predicting unsafe behaviour in advance can enable remedial measures to be put in place to
mitigate likely accidents on construction sites. Prevailing safety studies in construction tend …
mitigate likely accidents on construction sites. Prevailing safety studies in construction tend …
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 …
thereby influencing project quality. Recognizing and monitoring the construction-related …
Deep learning–based building attribute estimation from google street view images for flood risk assessment using feature fusion and task relation encoding
Floods are the most common and damaging natural disaster worldwide in terms of both
economic losses and human casualties. Currently, policymakers rely on data collected …
economic losses and human casualties. Currently, policymakers rely on data collected …
A Systematic Review of Biometric Monitoring in the Workplace: Analyzing Socio-technical Harms in Development, Deployment and Use
Modern advances in AI have increased employer interest in tracking workers' biometric
signals—eg, their brainwaves and facial expressions—to evaluate and make predictions …
signals—eg, their brainwaves and facial expressions—to evaluate and make predictions …
FedHIP: Federated learning for privacy-preserving human intention prediction in human-robot collaborative assembly tasks
Human-robot collaboration is a promising solution to relieve construction workers from
repetitive and physically demanding tasks, thus improving construction safety and …
repetitive and physically demanding tasks, thus improving construction safety and …
Personal Protective Equipment Detection for Construction Workers: A Novel Dataset and Enhanced YOLOv5 Approach
L Yipeng, W Junwu - IEEE Access, 2024 - ieeexplore.ieee.org
Current research on personal protective equipment (PPE) detection has mainly focused on
hard hats, overlooking the detection of reflective clothing. Therefore, this study aims to …
hard hats, overlooking the detection of reflective clothing. Therefore, this study aims to …
Construction worker ergonomic assessment via LSTM-based multi-task learning framework
Work-related musculoskeletal disorder (WMSD) is a critical occupational hazard and among
the leading causes of nonfatal injuries in construction. Rapid ergonomic assessment is …
the leading causes of nonfatal injuries in construction. Rapid ergonomic assessment is …
An Efficient Deep Learning-Based High-Definition Image Compressed Sensing Framework for Large-Scene Construction Site Monitoring
T Zeng, J Wang, X Wang, Y Zhang, B Ren - Sensors, 2023 - mdpi.com
High-definition images covering entire large-scene construction sites are increasingly used
for monitoring management. However, the transmission of high-definition images is a huge …
for monitoring management. However, the transmission of high-definition images is a huge …
Construction Activity Recognition Method Based on Object Detection, Attention Orientation Estimation, and Person Re-Identification
J Li, X Zhao, L Kong, L Zhang, Z Zou - Buildings, 2024 - mdpi.com
Recognition and classification for construction activities help to monitor and manage
construction workers. Deep learning and computer vision technologies have addressed …
construction workers. Deep learning and computer vision technologies have addressed …
Multi-Task Deep Learning-Based Human Intention Prediction for Human-Robot Collaborative Assembly
Construction robots have great potential to serve as assistants to relieve construction
workers from repetitive and physically demanding tasks. It is essential for robots to …
workers from repetitive and physically demanding tasks. It is essential for robots to …