Year: 2025
Type: conference-paper
Abstract: Scaffolding safety is a significant concern in the construction industry. To address this, researchers have proposed various safety monitoring approaches. However, current intelligent monitoring systems fall short of fully integrating real-time data, and predictive capabilities, reducing their overall effectiveness in ensuring scaffolding safety. Therefore, this study aims to develop a conceptual framework to advance the intelligent scaffolding monitoring system based on cyber-physical systems (CPS) and digital twins (DT) integration. The framework focuses on developing a DT-enabled scaffolding risk assessment model (SRAM), a sensor-based real-time data collection system, and an intelligent cyber-physical scaffolding risk alert. This research provides essential insights for more accurate accident risk assessments, more efficient data collection system, and faster warning mechanisms for construction safety.
Source: CIB Conferences
Authors: Xiaowei Wang, Chien-Ho Ko, John A Haug
Institution: University of Kansas
Language: English
Subfield: Civil and Structural Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: bronze
OpenAlex ID: W4411472833