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Simulation-Based Predictive Analytics for Construction Safety Incidents

  • 2025
  • OriginalPaper
  • Chapter
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Abstract

The chapter addresses the critical challenge of enhancing construction productivity by focusing on safety-related incidents. It introduces the concept of the construction productivity safety incidence rate (CPSIR) as a metric to quantify productivity loss due to safety incidents. The study proposes a distributed simulation model using the High Level Architecture (HLA) framework, which integrates independent simulators to predict safety incidents and their severity levels. The safety federate, a key component of this model, utilizes a Fuzzy Inference System (FIS) to process vague and dynamic input variables, generating realistic safety incidents and their impact on project performance. The chapter also discusses the synchronization points and communication protocols within the HLA framework, ensuring seamless interaction among federates. The development of the safety federate is detailed, highlighting its role in receiving updates from other simulators, generating predictions, and contributing to a holistic understanding of safety incidents. The use of FIS for handling low-resolution information and mapping relationships between variables is a significant aspect of the study, enabling a more accurate and comprehensive simulation of safety incidents and their impact on productivity. The chapter concludes with a discussion on the future development and refinement of the predictive simulation model, emphasizing the need for expanding influence factors and validating the model with real-case datasets.

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Title
Simulation-Based Predictive Analytics for Construction Safety Incidents
Authors
Abbey Dale Abellanosa
Hamidreza Golabchi
Stephen Hague
Simaan AbouRizk
Yasser Mohamed
Copyright Year
2025
DOI
https://doi.org/10.1007/978-3-031-87364-5_38
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