A Semantic Approach for Automated Rule Compliance Checking in Construction Industry
Dongming Guo, Erling Onstein, Angela Daniela La Rosa
Abstract
Automated Compliance Checking (ACC) of building/construction projects is one of important applications in Architecture, Engineering and Construction (AEC) industry, because it provides the checking processes and results of whether a building design complies with relevant laws, policies and regulations. Currently, Automated Compliance Checking still involves lots of manual operations, massive time and cost consumption. Additionally, some sub-tasks of ACC have been researched, while few studies can automatically implement the whole ACC process. To solve related issues, we proposed a semantic approach to implement the whole ACC process as automatically as possible, in which Natural Language Processing (NLP) is used to extract rule terms and logic relationships among these terms from text regulatory documents. Rule terms are mapped to keywords (concepts or properties) in BIM data through term matching and semantic similarity analysis. After that, according to the mapped keywords in BIM and logic relationships among keywords, a corresponding SPARQL query is automatically generated. The query results can be non-compliance or compliance with rules based on the generated SPARQL query and requirements of stakeholders. The cases study proves the proposed approach can provide the flexible and effective rule checking for BIM data. In addition, based on the proposed approach, we also further develop a semantic framework to implement automated rule compliance checking in construction industry.