Edge-enabled real-time framework for context-aware data acquisition and hazard alerting in smart construction sites
Journal
Automation in Construction
Journal Volume
181
Start Page
106642
ISSN
09265805
Date Issued
2026-01
Author(s)
Lee, Chiu-Ming
Abstract
Smart construction sites are dynamic and risk-prone, requiring intelligent systems for continuous monitoring, contextual understanding, and autonomous hazard mitigation. Addressing the inherent limitations of centralized cloud-based systems, such as latency, scalability, and fragmented decision-making, remains a key challenge. This paper introduces an edge-enabled framework for real-time, context-aware hazard alerting, enabling efficient on-site data acquisition and predictive safety management. The framework shifts data processing from the cloud to the edge, leveraging distributed edge-enabled processing, autonomous event triggering, and queue-based data prioritization to achieve an unprecedented level of real-time responsiveness. The framework's effectiveness was validated through a simulation-based approach, utilizing both on-site sensor data (e.g., temperature, worker ID) and external datasets (e.g., PM2.5 indices, weather forecasts). This validates the system's ability to enhance predictive logic and adaptive decision-making. The proposed solution provides a scalable and robust foundation for next-generation management systems, significantly enhancing safety and operational efficiency in complex construction environments.
Subjects
Context-aware alerting
Edge computing
IoT integration
Open data
Smart construction
SDGs
Publisher
Elsevier B.V.
Type
journal article