Does historical data still count? Exploring the applicability of smart building applications in the post-pandemic period
Sustainable Cities and Society
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Xie, X., Lu, Q., Herrera Fernandez, A., Yu, Q., Parlikad, A., & Schooling, J. Does historical data still count? Exploring the applicability of smart building applications in the post-pandemic period. Sustainable Cities and Society https://doi.org/10.17863/CAM.65155
The emergence of COVID-19 pandemic is causing tremendous impact on our daily lives, including the way people interact with buildings. Leveraging the advances in machine learning and other supporting digital technologies, recent attempts have been sought to establish exciting smart building applications that facilitates better facility management and higher energy efficiency. However, relying on the historical data collected prior to the pandemic, the resulting smart building applications are not necessarily effective under the current ever-changing situation due to the drifts of data distribution. This paper investigates the bidirectional interaction between human and buildings that leads to dramatic change of building performance data distributions post-pandemic, and evaluates the applicability of typical facility management and energy management applications against these changes. According to the evaluation, this paper recommends three mitigation measures to rescue the applications and embedded machine learning algorithms from the data inconsistency issue in the post-pandemic era. Among these measures, incorporating occupancy and behavioural parameters as independent variables in machine learning algorithms is highlighted. Taking a Bayesian perspective, the value of data is exploited, historical or recent, pre- and post-pandemic, under a people-focused view.
This research forms part of the Centre for Digital Built Britain’s (CDBB) work at the University of Cambridge within the Construction Innovation Hub (CIH). The Construction Innovation Hub is funded by UK Research and Innovation through the Industrial Strategy Fund.
Technology Strategy Board (920035)
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This record's DOI: https://doi.org/10.17863/CAM.65155
This record's URL: https://www.repository.cam.ac.uk/handle/1810/318040
Attribution-NonCommercial-NoDerivatives 4.0 International
Licence URL: https://creativecommons.org/licenses/by-nc-nd/4.0/