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Automation in Construction· 2026Q1

Database-driven IFC framework for digital twins of existing structures

Jiangpeng Shu, Yuhang Luo, Jiawang Song, Congguang Zhang et al.

Short summary

A new database-driven IFC framework integrates heterogeneous operational data (SHM, inspection) with IFC models, enabling traceable associations for digital twins of existing structures.

AI-generated from the title and abstract; the full text is not read.

Key points

  • Presents a database-driven IFC framework to integrate operational data (SHM, inspection) with IFC models.
  • Extends IFC representation to enable traceable associations between monitoring records and IFC components.
  • Utilizes a structured database and RESTful API for efficient data access.
  • Validated on an office building and a bridge, demonstrating performance gains in queries.

AI-generated from the title and abstract; the full text is not read.

Abstract

Industry Foundation Classes (IFC) is an open standard for representing geometric and semantic information in building information modeling (BIM), which is widely used to support the development of digital twins (DTs). However, IFC has limited capabilities for handling heterogeneous operational data, hindering the integration of DTs into workflows such as structural health monitoring (SHM). This paper presents a database-driven IFC framework that stores IFC models and semantic data in a structured database. The IFC representation is extended to incorporate SHM and inspection information, enabling traceable associations between monitoring records and their corresponding IFC components, with data access provided through a RESTful API. The framework is validated using an office building and a simply supported bridge. Benchmarks demonstrate the relational approach’s efficiency in global counts, property retrieval, and sensor-oriented queries. The framework has the potential to provide a unified, extensible data foundation for lifecycle-oriented digital twins of existing structures.

The authors' abstract, as published at the source. Automation in Construction, 2026 · DOI ↗

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Field: Industrial and Manufacturing Engineering

Industrial and Manufacturing EngineeringEngineering