Author(s)

Zhinian Hong

Corresponding Author

Zhinian Hong

Abstract

Traditional safety supervision methods have some problems, such as lagging information acquisition and insufficient risk identification, which can not meet the needs of modern complex construction environment. This paper proposes to build a digital early warning and decision support system based on the Internet of Things (IoT), big data, AI and BIM to realize real-time monitoring, data analysis and intelligent decision-making. The system collects construction site data by deploying sensors, cameras and other equipment, uses big data analysis and AI algorithm for risk identification and early warning, and pushes early warning information to relevant personnel through visual interface and mobile terminal. In addition, the system also provides a decision support module, which constructs a decision support model based on historical data and real-time data to provide scientific decision-making basis for safety supervisors. The research shows that the digital early warning and decision support system can effectively improve the efficiency and accuracy of safety supervision, reduce the accident rate and ensure the safety of the construction site.

Keywords

Digital Early Warning, Decision Support, Construction Safety Supervision