Research Project

AI in Construction Code Compliance

Research Team

Lead Researchers:

Dr. Shawn Sun, Civil Engineering & Construction Management
Dr. Bingbing Li, Manufacturing Systems Engineering and Management

Collaborators:

Dr. Maged Elaasar, JPL

Student Team:

Summayah Waseem, MS Software Engineering

Funding

Funding Organization:
Funding Program:

Abstract

Automate Building Information Model (BIM) checking processes.
Use SPARQL queries and rule-based systems to extract and analyze building data.
Aimed at improving accuracy and efficiency in the BIM validation workflow.

Motivation/Research Problem

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Research Questions and Research Objectives

Develop an intelligent system for automating BIM validation.
Focus on creating a system independent of specific BIM software by using IFC files.
Implement rules from the International Building Code (IBC) to validate building designs.
Generate comprehensive reports accessible via a website.

Research Methods

Utilize IFC files for universal compatibility across BIM software.
Convert IFC to RDF format to query using SPARQL.
Use SmartReview as a research tool to guide the generation of accurate reports.
Leverage Jupyter Notebooks for advanced rule visualization and HTML report generation.

Research Results and Deliverables

Automated BIM validation using SPARQL queries and Python rules.
IFC compatibility ensures the system can work with any software.
Creation of HTML reports for easy review of BIM validation reports.

Commercialization Opportunities

Application: Universal BIM validation tool applicable across multiple platforms via IFC standardization.
Key Values: Automation reduces manual errors, accelerates compliance checks, and enhances review efficiency.
Potential Customers: Developers, building authorities, and BIM software users looking to streamline validation processes.

Research Timeline

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