A science map**-based review of work-related musculoskeletal disorders among construction workers

MF Antwi-Afari, H Li, AHS Chan, JO Seo, S Anwer… - Journal of safety …, 2023 - Elsevier
Introduction: Work-related musculoskeletal disorders (WMSDs) are recognized as a leading
cause of nonfatal injuries in construction, but no review of existing studies has systematically …

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 …

Integrating feature engineering, genetic algorithm and tree-based machine learning methods to predict the post-accident disability status of construction workers

K Koc, Ö Ekmekcioğlu, AP Gurgun - Automation in Construction, 2021 - Elsevier
The construction industry is among the riskiest industries around the world. Hence, the
preliminary studies exploring the consequences of occupational accidents have received …

Scenario-based automated data preprocessing to predict severity of construction accidents

K Koc, AP Gurgun - Automation in Construction, 2022 - Elsevier
Occupational accidents are common in the construction industry, therefore develo**
prediction models to detect high severe accidents would be useful. However, existing …

Automated detection of construction work at heights and deployment of safety hooks using IMU with a barometer

H Choo, B Lee, H Kim, B Choi - Automation in Construction, 2023 - Elsevier
An automated system that identifies work at height and the fastening state of safety hooks
using wearable sensors was developed to prevent falls from height (FFH). This system …

Assessing occupational risk of heat stress at construction: A worker-centric wearable sensor-based approach

S Shakerian, M Habibnezhad, A Ojha, G Lee, Y Liu… - Safety science, 2021 - Elsevier
Construction workers are at a high risk of exposure to excessive heat generated by several
factors such as intensive physical activities, personal protective clothing, and frequent heat …

Machine learning-based identification and classification of physical fatigue levels: A novel method based on a wearable insole device

MF Antwi-Afari, S Anwer, W Umer, HY Mi, Y Yu… - International Journal of …, 2023 - Elsevier
Construction is known for being a labor-intensive and risky industry. Within various
occupational settings such as construction, physical fatigue is an underlying health condition …

Cyber physical system for safety management in smart construction site

W Jiang, L Ding, C Zhou - Engineering, Construction and …, 2021 - emerald.com
Purpose Construction safety has been a long-term problem in the development of the
construction industry. An increasing number of smart construction sites have been designed …

Smart Personal Protective Equipment (PPE) for construction safety: A literature review

S Rasouli, Y Alipouri, S Chamanzad - Safety science, 2024 - Elsevier
Construction projects are risky environments which can increase the number of fatal and
non-fatal accidents. The development of Personal Protective Equipment (PPE) is one of the …

Effective inertial sensor quantity and locations on a body for deep learning-based worker's motion recognition

K Kim, YK Cho - Automation in Construction, 2020 - Elsevier
Construction tasks involve various activities composed of one or more body motions. As
construction projects are labor-intensive and heavily rely on manual tasks, understanding …