Matching Real-World Facilities to Building Information Modeling Data Using Natural Language Processing

Qingsheng Xie,Xinao Gao,Jia Wang,Liu Chun,Xi Chen,Xiaoping Zhou

doi:10.1109/access.2019.2937219

Abstract

Building Information Modeling (BIM) is a promising technology for building informatics. Currently, an increasing number of applications adopt BIM to improve the building operations and facility management. In these applications, matching real-world facilities to the corresponding BIM items is a fundamental yet challenging task. This study addresses this issue using Natural Language Processing. Firstly, a novel BIM hierarchy tree (HiTree) is proposed to model the original spatial structure relationships of a BIM. Then, the locations of facilities are extracted from natural language through processes of word segmentation, keyword extraction, and semantic disambiguation. Thirdly, an algorithm that matches real-world facilities to the BIM data is developed using the HiTree and the extracted locations. Finally, a concrete case for a 35,000 m 2 library is presented to verify the effectiveness of the proposed solution. BIM has become a common paradigm in the construction industry, and our scheme can facilitate more applications of BIM in building operations and facility management. One of the most representative applications is integrating the BIM data and information within IoT (Internet of Things) system intelligently by matching the BIM data to real-world facilities.

Highlights

Building Information Modeling (BIM) is a digital representation of physical and functional characteristics of a facility [1]
OVERALL FRAMEWORK The matching solution proposed in this study can be divided into three steps, namely the construction of the hierarchy tree (HiTree); the LIEModel combined with natural language segmentation, keyword extraction and semantic disambiguation; and the matching scheme between the location information of realworld facilities and BIM data
Since each node on the HiTree is named according to the pre-built building information thesaurus Q0, in order to achieve an accurate matching between the natural language information from the Real-world Facility installation information Table (RFT) and the construction equipment information, the extracted keyword sequence is Q = {library, one layer, The aisle, fire hydrant} and it is converted into a consistent expression with the pre-built building information thesaurus Q0

Summary

INTRODUCTION

Building Information Modeling (BIM) is a digital representation of physical and functional characteristics of a facility [1]. B. OVERALL FRAMEWORK The matching solution proposed in this study can be divided into three steps, namely the construction of the HiTree; the LIEModel combined with natural language segmentation, keyword extraction and semantic disambiguation; and the matching scheme between the location information of realworld facilities and BIM data. Layer nodes represent the building equipment distributed in the corresponding subspace

KEYWORD EXTRACTION AND SEMANTIC DISAMBIGUATION

CONCLUSION