ITcon Vol. 23, pg. 259-284,

Big data in building design: a review

submitted:October 2017
revised:November 2018
published:November 2018
editor(s):Amor R
authors:Mauricio Loyola
Princeton University
summary:Compared with other industries, the use of big data is substantially less developed in the architecture, construction, engineering, and operation (AECO) industry. Available examples are mostly experimental, limited in scope, and without an obvious transfer to practice. Yet, a substantial number of academics and practitioners envision that the use of big data will have a significant impact on how decisions are made in the building design process, providing designers with an unprecedented amount of exceptionally detailed data on buildings and their occupants that is redefining what can be observed, modeled, simulated, predicted and measured in the industry. We first review the main concepts and technologies that shape this technological phenomenon, and then, based on the survey of around 100 cases of applications of big data and machine learning throughout all phases of building design we identify 12 clusters of applications where the technology seems to be more disruptive. The discussion then focuses on the transformative impacts of the technology on three niches where further research is more urgently needed: 1) understanding the design problem; 2) simulating and predicting the holistic performance of the design solution; 3) evaluating integrally and continuously the design product during its complete lifecycle.
keywords:Big Data, Building Design, Machine Learning, Architecture
full text: (PDF file, 0.535 MB)
citation:Loyola M (2018). Big data in building design: a review, ITcon Vol. 23, pg. 259-284,