Occupant Profiling Based On Thermal Comfort Preference

Abstract

As occupants are the end-users of buildings, it is important that their comfort is well taken care of. Thermal comfort plays a huge role in achieving high levels of occupant comfort levels, especially in tropical climates. However, thermal comfort is subjective and not everyone would feel comfortable in a shared space. The aim of this study was to better understand various thermal profiles and test the feasibility of thermal clustering. Furthermore, this paper aims to simulate how higher thermal comfort can be achieved by means of a reorganisation of occupant’s sitting arrangement. Thermal comfort feedback data obtained from a 30-day experiment with 30 participants were used for analysis on the Python programming language. Individual thermal profiles were created, and two clusters were formed based on their similarities. Both clusters were analysed further to understand their thermal preferences. Following which, simulation-based testing showed that thermal clustering improved the overall thermal comfort level from 60 per cent to 90 per cent. While clustering showed to improve thermal comfort level, it was also noted that there are other aspects affecting an individual’s overall comfort level. Furthermore, clustering might reduce the overall flexibility within a working space.