Author(s)

Hongmei Zhang

Corresponding Author

Hongmei Zhang

Abstract

As the scale and complexity of China's construction projects continue to expand, construction safety issues have become increasingly prominent. Traditional safety supervision methods exhibit significant shortcomings in real-time responsiveness, accuracy, and preventative capabilities. To enhance construction safety management, this paper focuses on dynamic monitoring and early warning technologies. It systematically analyzes the current status and primary challenges of construction safety supervision, establishes a dynamic monitoring system based on IoT and big data, and incorporates multi-source data fusion with intelligent algorithms to develop risk early warning models. Building upon this foundation, a dynamic linkage strategy integrating monitoring data with safety supervision mechanisms is proposed, enabling real-time identification and tiered early warning of accident hazards. Research findings indicate that this technological framework effectively enhances the informatization and intelligence of safety supervision, improves accident prevention capabilities, and holds significant theoretical and practical value for optimizing construction safety management models.

Keywords

Construction safety, Safety supervision, Dynamic monitoring, Early warning technology, Construction engineering, Internet of Things, Big data