Does historical data still count? Exploring the applicability of smart building applications in the post-pandemic period.

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.

Infrastructure sensing.

Design, construction, maintenance and upgrading of civil engineering infrastructure requires fresh thinking to minimize use of materials, energy and labour. This can only be achieved by understanding the performance of the infrastructure, both during its construction and throughout its design life, through innovative monitoring. Advances in sensor systems offer intriguing possibilities to radically alter methods of condition assessment and monitoring of infrastructure. In this paper, it is hypothesized that the future of infrastructure relies on smarter information; the rich information obtained from embedded sensors within infrastructure will act as a catalyst for new design, construction, operation and maintenance processes for integrated infrastructure systems linked directly with user behaviour patterns. Some examples of emerging sensor technologies for infrastructure sensing are given. They include distributed fibre-optics sensors, computer vision, wireless sensor networks, low-power micro-electromechanical systems, energy harvesting and citizens as sensors.