Abstract

Canadians spend 80 to 90% of their time indoors and previous studies show that the vast majority are typically unsatisfied with their thermal comfort, especially in their workplaces. Building occupancy patterns have also dramatically changed in the past two years after the COVID-19 pandemic, given the unprecedented increase in telecommuting and the shift towards alternative office arrangements such as hot-desking, which are gaining widespread popularity. These changes pose new challenges to building operators, particularly due to larger variability in occupancy and occupant preferences compared to standard assumptions. Therefore, discovering personal comfort preference is key in optimizing room temperature for co-working spaces with variable occupancy. To this end, the goal of this research was to assess thermal comfort of occupants in a co-working space and investigate the differences in their comfort assessment under varying conditions using near real-time surveying methods. Other factors that might influence office comfort such as clothing and air velocity from ceiling diffusers were also investigated. The primary objective of this study is to leverage novel technologies such as wearables to identify thermal comfort levels in multi-occupant spaces in a continuous near real-time approach. The secondary objective is to find the statistical differences between surveyed occupants’ thermal comfort perception with respect to personal factors such as clothing, metabolic rates, and perception of air movements.
This research was conducted in the recently established living lab at Concordia university which features modern co-working spaces. Temperature ranges that correspond to survey responses continuously collected using a smartwatch have been analyzed and compared to assess if there are any statistical differences between the survey respondents when they are changing their clothing levels. Results showed statistically significant differences between respondents with regard to their thermal preferences (p-value = 2.2 *10-6), which also varied based on their clothing levels and metabolic rates. Finally, recommendations for using the results of this research to develop a control strategy for selecting optimal thermostat setpoints in response to variable occupancy were provided. This work is significant as co-working spaces with variable occupancy are on the rise. Therefore, identifying individual thermal comfort preferences can be used to formulate algorithms to satisfy most people who occupy (or are expected to occupy) these spaces while minimizing energy waste during under occupied periods.