Most HVAC systems only use temperature sensors to control actuators like fan coil units in classrooms and offices at HKUST. However, human thermal comfort depends on many parameters, such as temperature, humidity, air speed, heat radiation, human activity level, and clothing.

The Predicted Mean Vote (PMV) is a common thermal comfort index used to predict statistical thermal comfort responses based on a seven-point thermal sensation scale according to ASHRAE Standard 55. The PMV model was established through experiments involving over 1,000 human subjects in the United States and Europe. The goals of this project are to: Conduct human subject experiments to collect thermal sensation votes from occupants at HKUST, Measure relevant environmental parameters (temperature, humidity, air speed) during the experiments, Analyze the data and compare with the standard PMV model
Propose modifications to the PMV model based on the local experimental data, Implement the modified PMV model in an HVAC controller to improve thermal comfort at HKUST, The outcomes will be a customized PMV model that more accurately predicts thermal comfort for occupants at HKUST, as well as an HVAC controller that uses the modified PMV model to achieve better thermal comfort performance.