This paper provides a systematic review on the application of Machine Learning (ML) in
thermal comfort studies to highlight the latest methods and findings and provide an agenda …

Compared with the static thermal comfort models like predicted mean vote (PMV) model,
adaptive thermal models have a wider range of adaptability. The traditional concept of …

Today's cities encounter significant challenges concerning urbanization and population
growth, resource availability, and climate change. Concurrently, unparalleled datasets are …

This study focuses on identifying individual thermal comfort requirement using infrared
images. The primary objective is to verify the feasibility of infrared images in predicting …

Urban populations face increasing heat stress in cities. However, the influence of the built
environment of new and old urban blocks on pedestrian thermal comfort remains unclear …

Indoor climate is closely related to human health, comfort and productivity. Vertical plant wall
systems, embedded with sensors and actuators, have become a promising application for …

Heating and cooling in buildings accounts for over 20% of total energy consumption in
China. Therefore, it is essential to understand the thermal requirements of building …

We analyzed the ASHRAE Global Thermal Comfort Database II to answer a fundamental but
overlooked question in thermal comfort studies: how many and which subjective metrics …

In this work, the waste heat/solar heat-driven membrane-based liquid desiccant regenerator
performance, as well as desalinated water extraction rate, are predicted and analyzed by …

Abstract ASHRAE Global Thermal Comfort Database has been extensively used for
analyzing specific thermal comfort parameters or models, evaluating subjective metrics, and …