Research on the Information Integration Model of Prefabricated Buildings Based on BIM Technology

This paper constructs a multi-dimensional information integration framework based on building information modeling (BIM) technology, aiming to integrate data flows at all stages of the building life cycle and realize efficient information sharing and collaborative management. The framework adopts an improved semantic integration algorithm, and by optimizing data matching rules and semantic parsing models, it effectively improves the compatibility and interaction efficiency between heterogeneous data sources, and solves the problems of data islands, semantic conflicts and inefficiency in the traditional information integration process. In order to verify the actual application effect of the framework, an actual prefabricated building project was selected as a case, and performance tests were carried out in the design data interaction, construction plan integration and operation and maintenance information sharing links. The simulation results show that the framework significantly improves the data interaction speed and the information integration efficiency by about 28%. At the same time, it ensures the consistency of key node data, and the error rate is controlled within 1.5%. In addition, the experiment also shows that in the multi-stage collaborative work scenario, the framework has high stability and scalability, providing an efficient information management solution for prefabricated building projects.

Authors

Institutions

Publication Details

Published
2025-03-17
DOI
https://doi.org/10.1109/eespe63401.2025.10987181
Primary Topic
Regional Development and Environment
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Research on the Information Integration Model of Prefabricated Buildings Based on BIM Technology

Xin Jing, Yunfen Wu
Regional Development and Environment
article

Research on the Information Integration Model of Prefabricated Buildings Based on BIM Technology

Xin Jing, Yunfen Wu
article en

Abstract

This paper constructs a multi-dimensional information integration framework based on building information modeling (BIM) technology, aiming to integrate data flows at all stages of the building life cycle and realize efficient information sharing and collaborative management. The framework adopts an improved semantic integration algorithm, and by optimizing data matching rules and semantic parsing models, it effectively improves the compatibility and interaction efficiency between heterogeneous data sources, and solves the problems of data islands, semantic conflicts and inefficiency in the traditional information integration process. In order to verify the actual application effect of the framework, an actual prefabricated building project was selected as a case, and performance tests were carried out in the design data interaction, construction plan integration and operation and maintenance information sharing links. The simulation results show that the framework significantly improves the data interaction speed and the information integration efficiency by about 28%. At the same time, it ensures the consistency of key node data, and the error rate is controlled within 1.5%. In addition, the experiment also shows that in the multi-stage collaborative work scenario, the framework has high stability and scalability, providing an efficient information management solution for prefabricated building projects.

Shandong University of Technology (CN)
Sustainable cities and communities
Openalex Percentile: Top 86%
Regional Development and Environment
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.