TR233: IFC-Enabled Site-to-BIM Automation: An Interoperable Approach Toward the Integration of Unmanned Aerial Vehicle (UAV)-Captured Reality into BIM

<a href="https://embed.stanford.edu/iframe/?url=https%3A%2F%2Fpurl.stanford.edu%2Fgf324nd7978" class="su-underline">Show Content</a>

Abstract/Contents

Abstract: This technical report elaborates on the design of an industry foundation classes (IFC)-enabled smart, robotic, and interoperable construction and facility monitoring solution. It summarizes the research project conducted by Hesam Hamledari, PhD student at Stanford University. This document focuses primarily on motivations, achievements, and challenges with regard to this student project’s novel IFC use for achieving site-to-BIM automation. A series of techniques have been proposed and implemented to 1) automatically develop multi-dimensional as-built and as-is IFCbased BIMs using data collected at construction sites and facilities by robotic technologies such as drones; and 2) enable the automated in-BIM documentation of inspection data using IFC schema. The proposed solution has been tested in real-life scenarios, and the resulting updated BIMs have been verified for conformance to IFC schema using IFC validating tools. This work’s focus on IFC and its practical schema use for enabling site-to-model automation promotes the application of bSI standards among industry practitioners. Further, it romotes OpenBIM and interoperability, a core challenge in the construction information modeling domain.

Type of resource	text
Date created	2017

Author	Hamledari, Hesam

Subject	Industry Foundation Classes
Subject	IFC
Subject	Interoperability
Subject	Building Information Modeling
Subject	BIM
Subject	Automation
Subject	Robotics
Subject	Unmanned Aerial Vehicles
Subject	UAV
Subject	Computer Vision
Subject	Construction Progress Monitoring
Subject	Facility Management
Subject	OpenBIM
Subject	As-Built Modeling
Subject	Artificial Intelligence
Genre	Technical report

Related Publication	BuildingSMART International Award 2017
Location	https://purl.stanford.edu/gf324nd7978

Use and reproduction: User agrees that, where applicable, content will not be used to identify or to otherwise infringe the privacy or confidentiality rights of individuals. Content distributed via the Stanford Digital Repository may be subject to additional license and use restrictions applied by the depositor.

CIFE Publications

Loading usage metrics...