The data inherent in building automation systems, computerized maintenance management systems, security and access control systems, and IT networks represent an untapped opportunity to improve the operation and maintenance (O&M) of buildings. This paper reports the findings of a critical review of the literature regarding the use of data analytics in building O&M applications, and a two-day stakeholder's workshop titled Big Data in Building Operations. Building on the discussions at the workshop and the literature survey, the current state of the O&M related decision-making process was identified: the data availability in existing buildings was discussed; the challenges related with accessing and processing these datasets were examined; and emerging sensing technologies were presented. Further, the research fields applying data analytics in O&M were introduced, the barriers to their widespread use in practice were discussed, future work recommendations were developed; and the need for semantic models of O&M data and comprehensive open O&M datasets was identified for the development and assessment of data analytics-driven energy and comfort management algorithms.

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Automation in Construction
Department of Civil and Environmental Engineering

Gunay, H.B, Shen, W. (Weiming), & Newsham, G. (Guy). (2019). Data analytics to improve building performance: A critical review. Automation in Construction (Vol. 97, pp. 96–109). doi:10.1016/j.autcon.2018.10.020