Semantic Enrichment for Building Information Modeling: Procedure for Compiling Inference Rules and Operators for Complex Geometry

Rafael Sacks,Uri Kattel,Simon Daum,Raz Yosef,Andre Borrmann,Ling Ma

doi:10.1061/(asce)cp.1943-5487.0000705

Abstract

Semantic enrichment of building models adds meaningful domain-specific or application-specific information to a digital building model. It is applicable to solving interoperability problems and to compilation of models from point cloud data. The SeeBIM (Semantic Enrichment Engine for BIM) prototype software encapsulates domain expert knowledge in computer readable rules for inference of object types, identity and aggregation of systems. However, it is limited to axis-aligned bounding box geometry and the adequacy of its rule-sets cannot be guaranteed. This paper solves these drawbacks by (1) devising a new procedure for compiling inference rule sets that are known a priori to be adequate for complete and thorough classification of model objects, and (2) enhancing the operators to compute complex geometry and enable precise topological rule processing. The procedure for compiling adequate rule sets is illustrated using a synthetic concrete highway bridge model. A real-world highway bridge model, with 333 components of 13 different types and compiled from a laser scanned point cloud, is used to validate the approach and test the enhanced SeeBIM system. All of the elements are classified correctly, demonstrating the efficacy of the approach to semantic enrichment.

Highlights

Semantic enrichment of building models refers to the automatic or semiautomatic addition of meaningful information to a digital model of a building or other structure by software that can deduce new information by processing rules (Belsky et al 2016)
Development of semantic enrichment for models is motivated by the information interoperability problem (Eastman et al 2011), which hampers the use of building information modeling (BIM), 1Associate Professor, Faculty of Civil and Environmental Engineering, Technion, Haifa 3200003, Israel
Semantic enrichment is an important process that can relieve the problem of information interoperability and greatly improve the functionality of BIM models throughout a facility’s lifecycle

Summary

Introduction

Semantic enrichment of building models refers to the automatic or semiautomatic addition of meaningful information to a digital model of a building or other structure by software that can deduce new information by processing rules (Belsky et al 2016). The rules use the existing information and evaluate the topological, spatial, geometric, and other relationships between the model’s objects. Development of semantic enrichment for models is motivated by the information interoperability problem (Eastman et al 2011), which hampers the use of building information modeling (BIM), and by the difficulties faced by vendors of commercial BIM software in implementing the standard solution—exchanges based on the industry foundation classes (IFC) (BuildingSmart 2013). Semantic enrichment draws on the foundations laid by research of semantic query languages for BIM (Mazairac and Beetz 2013), semantic rule-checking systems for BIM (Eastman et al 2009; Pauwels et al 2011), and BIM model query using spatial and topological relationships (Borrmann and Rank 2009; Daum and Borrmann 2014)

Methods

Discussion

Conclusion