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Sensor-based safety management
DOI:10.1016/j.autcon.2020.103128.png)
摘要
En 中文
The construction industry has one of the most hazardous working environments worldwide, which accounts for about 1 in every 5 occupational fatalities. The high rates of workplace injuries, illnesses and fatalities cause irreversible harm to workers and are often the source of delays and additional project costs. Improvements in sensor technologies, wireless communication, the processing power of computers, and advancements in machine learning and computer vision are now enabling the development of sensor-based safety management systems. The rapid growth of Building Information Modelling (BIM) has also created opportunities for improving safety management. While considerable progress has been made to improve construction safety, few studies have focused on the integration of sensor-based systems and BIM. This research, which is motivated by the development of such integrated methods, carries out a systematic review of the relevant literature, summarising recent developments of sensor-based safety management systems and advancements in safety management through BIM. The research gaps are identified and an outline for potential future research is provided. The results of the review reveal the potential of combining sensor-driven systems with BIM for improving safety management in construction.
Keyword:
INTELLIGENT VIDEO SURVEILLANCE
INFORMATION MODELING BIM
CONSTRUCTION SAFETY
KNOWLEDGE MANAGEMENT
VISUALIZATION TECHNOLOGY
SPATIOTEMPORAL ANALYSIS
PROCESS INTEGRATION
AUTOMATED DETECTION
NEURAL-NETWORKS
WORKER SAFETY
AI总结
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期刊
IF:
11.5
论文数:
6.3K
被引数:
4.2W
机构
引用论文
A deep learning-based method for detecting non-certified work on construction sites一种基于深度学习的建筑工地非认证工作检测方法

