Integrating Edge Computing and Cloud BIM for Enhanced Real-Time Safety Monitoring in Construction Sites: Reducing Time-Latency and Improving Data Accessibility

Abstract

Purpose

This study aims to reduce time latency and improve data integration in Proximity Warning Systems (PWS) used for construction safety monitoring. Traditional systems often suffer from delays that compromise worker safety, highlighted the need for a more responsive and integrated approach.

Methodology

This research proposes a hybrid PWS architecture that integrates edge computing with Industry Foundation Classes (IFC) to enhance real-time performance and data accessibility. The system was implemented and tested in a controlled laboratory setting, where its performance was compared to both local and centralized processing systems. Key performance metrics, such as latency and reliability, were measured over multiple iterations.

Findings

The hybrid system demonstrated latency comparable to local processing but significantly lower than centralized systems. It also maintained reliable performance with minimal variability and remained resilient to network disconnections. These characteristics make the proposed hybrid system highly effective for real-time monitoring in dynamic construction environments.

Originality

This study presents a novel hybrid architecture that uniquely combines the strengths of both local and centralized PWS, offering an optimal balance between real-time responsiveness and robust data integration. The integration of edge computing with combination with IFC for construction safety monitoring is an innovative approach that has not been previously studied.

Research limitations

Further research is required to validate the system in real-world construction sites and to address potential time delays in cross-system data access.