.png){kind=icon}
返回
Enhancing construction safety: predicting worker sleep deprivation using machine learning algorithms
.png){kind=icon}
OA
AI
DOI：10.1038/s41598-024-65568-2.png)
.png){kind=icon}
.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
Sleep deprivation is a critical issue that affects workers in numerous industries, including construction. It adversely affects workers and can lead to significant concerns regarding their health, safety, and overall job performance. Several studies have investigated the effects of sleep deprivation on safety and productivity. Although the impact of sleep deprivation on safety and productivity through cognitive impairment has been investigated, research on the association of sleep deprivation and contributing factors that lead to workplace hazards and injuries remains limited. To fill this gap in the literature, this study utilized machine learning algorithms to predict hazardous situations. Furthermore, this study demonstrates the applicability of machine learning algorithms, including support vector machine and random forest, by predicting sleep deprivation in construction workers based on responses from 240 construction workers, identifying seven primary indices as predictive factors. The findings indicate that the support vector machine algorithm produced superior sleep deprivation prediction outcomes during the validation process. The study findings offer significant benefits to stakeholders in the construction industry, particularly project and safety managers. By enabling the implementation of targeted interventions, these insights can help reduce accidents and improve workplace safety through the timely and accurate prediction of sleep deprivation.
Keyword:
Sleep deprivation
Machine learning
Construction safety
Construction workers
Safety performance
AI总结
对已上传原文的论文进行重点信息的提取，主要内容包括：简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。
期刊
IF:
3.9
论文数:
28.0W
被引数:
83.5W
机构
引用论文
Maternal sleep quality during early pregnancy, risk factors and its impact on pregnancy outcomes: a prospective cohort study孕早期孕妇睡眠质量、危险因素及其对妊娠结局影响的前瞻性队列研究.png)
SLEEP MEDICINEOAAI
SLEEP MEDICINEIF3.4
OAAI分享收藏分享收藏Social timing in fluences sleep quality in patients with sleep disorders *睡眠障碍患者的社会时机影响睡眠质量 *SLEEP MEDICINE
SLEEP MEDICINEIF3.4
PREAI
分享收藏
查看更多内容