Ontology-Driven Automation for BIM-FM Data Integration Using Neo4j, Python, and Workflow Platforms
Part Of
Computing in Civil Engineering 2025: Computational and Intelligent Technologies - Selected Papers from the ASCE International Conference on Computing in Civil Engineering 2025
Start Page
690
End Page
699
ISBN (of the container)
9780784486436
ISBN
9780784486436
Date Issued
2025
Author(s)
Huang, Chien-Pu
Abstract
This research presents an ontology-driven framework for integrating building information modeling (BIM) and facility management (FM) systems with Internet of Things (IoT) data streams to address key interoperability barriers - conceptual, semantic, organizational, and technological. Traditional approaches are limited by fragmented workflows, static data standards, and manual processes, which limit their scalability and adaptability. Leveraging Neo4j for semantic modeling, Python for automated data integration and anomaly detection, and Power Automate for real-time workflow execution, the proposed framework ensures seamless interoperability, scalability, and dynamic task automation. A simulated HVAC maintenance scenario validates its effectiveness, demonstrating 75%-90% reductions in task execution times, 81% overall time savings, and 98% semantic model accuracy. These results highlight the framework's ability to resolve interoperability challenges, automate workflows, and advance intelligent, data-driven facility management practices.
Event(s)
ASCE International Conference on Computing in Civil Engineering, i3CE 2025, New Orleans, 11 May 2025 - 14 May 2025
Publisher
American Society of Civil Engineers (ASCE)
Type
conference paper