Architectural Engineering Assistant Professor James Lo, PhD has received a National Science Foundation (NSF) award titled “Collaborative Research: Living Building Information Model (BIM): A Layered Approach for Automatic and Continuous Built Environment Model Update.” This project is led by Lo in conjunction with Associate Professor Ko Nishino, PhD from the Department of Computer Science, as well as collaboration with Assistant Professor Fernanda Leite, PhD from the Cockrell School of Engineering at the University of Texas at Austin. The total award amount is $399,924 over a duration of three years.
Buildings and related infrastructure are designed to have long life spans. As advancements and renovations are made to buildings over time, information regarding maintenance and operation needs to be kept up-to-date so that a building can operate at its maximum potential. Building Information Models (BIMs) can aid in this effort. A BIM is a digital representation of the physical and functional characteristics of a building. A BIM data model can store all operational data of a specific building, but BIM models are challenging to maintain due to the fact that updates to the data are currently done manually; a difficult process to streamline over the lifespan of a given building.
This project will develop an automated system to update and maintain BIMs in order to reduce the maintenance challenges previously mentioned. To successfully automate these models, a machine vision based concept system will be developed at Drexel and field tested on an indoor renovation project at the University of Austin, Texas. Computer programs that "see" using cameras and/or sensing techniques are defined as machine vision. This machine vision process will systematically analyze a building during construction and renovation phases to detect changes from the previous analysis. Critical building information is then captured and updated with minimal human error or effort. This project will yield a fundamental transformation in how construction records are kept. Building operators will benefit from increased accuracy of this data; therefore maintenance and renovation activities can be planned more easily throughout a building’s lifecycle.
These efforts will leverage multidisciplinary research to establish an interface between computer science and civil engineering. This automated system will be adaptable to other fields of engineering. The investigative team also intends to translate this research into mentoring and training opportunities for both undergraduate and graduate students as well as STEM outreach activities for grades K thru 12.