Automated Rule Checking for in-house BIM Norms of Building Models

In recent years the Architectural, Engineering & construction (AEC) industry relies on different automated tools to check and validate the building design. However most of the tools are lack in interoperability, extendibility and logical compilation checks. Moreover these tools are programmed with high level programming languages. By avoiding these limitations an automated tool is beneficial for the rule checking process. Semantic web technology and Linked data approaches help to fulfill the above aim. This graduation project focuses on developing, an automated rule checker based on a Linked Data approach for in-house BIM norms. The architectural design and construction data are converted into common data format know as Resource Description Framework (RDF). The rules form the in-house BIM norm is formalized using the SPARQL query language. The results of this automated rule checking process are visualized in three dimensional view using Python libraries and modules know IfcOpenShell and python OpenCasCade. Once this in-house rule checker is developed, the end user can check multiple of design and 3D visualization of results helps for effective communication among the stakeholders involved in the construction project. It addition this it reduces the cost on investing in a commercial rule checking tools.