The advent of state-of-the-art technology ranging from Building Information Modeling (BIM) to machine learning has improved building operation efficiencies. In particular, such technology helps stakeholders achieve data-driven decision-making based on multiple objective data sources from BIM, embedded sensors in a building, and building management software platforms such as Building Management System (BMS) and Integrated Workplace Management System (IWMS). Such data are utilized in machine learning model building, visualization for insight, and comparison to benchmark tests to measure and improve building performance and management process.
Publications
- Hong, S., Kim, H., & Yang, E. (2021). Automated text classification of maintenance data of higher education buildings using text mining and machine learning techniques. Journal of Architectural Engineering, 28(1), 04021045. https://doi.org/10.1061/(ASCE)AE.1943-5568.0000522.
- Yang, E., & Bayapu, I. (2019). Big data analytics and facilities management: A case study. Facilities, 38(3/4), 268-281. https://doi.org/10.1108/F-01-2019-0007
- Williams, B., Haines, B., Roper, K., & Yang, E. (2019). Building Information Modelling (BIM) for Facility Management (FM): Industry survey of building assets. Journal of Facility Management Education and Research, 3(1), 18-26. https://doi.org/10.22361/jfmer/112195
- Zhao, C., Yang, E., Nie, Y., & Russo, J. (2019). Facility decision making process with modified value engineering approach. Journal of Corporate Real Estate, 21(2), 112-129. https://doi.org/10.1108/JCRE-01-2018-0002
- Yang, E., Lee, Y. C., & Li, Q. (2018). Energy disclosure law in New York City: Building energy performance benchmarking progress. Facilities, 36(11/12), 571-583. https://doi.org/10.1108/F-08-2017-0090