Personal comfort models have shown to predict specific thermal comfort requirements more
accurately than aggregate models, increasing occupant acceptability and associated energy …

Human individual differences widely and markedly affect thermal comfort and should be
carefully considered in the design and operation of the built environment. This paper aims to …

Develo** functional textiles with a cooling effect is important for personal comfort in
human life and activities. Although existing passive cooling fabrics exhibit promising cooling …

The predicted mean vote (PMV) and predicted percentage of dissatisfied (PPD) are the most
widely used thermal comfort indices. Yet, their performance remains a contested topic. The …

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 …

Fueled by big data, powerful and affordable computing resources, and advanced algorithms,
machine learning has been explored and applied to buildings research for the past decades …

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 …

Buildings have a significant impact on global sustainability. During the past decades, a wide
variety of studies have been conducted throughout the building lifecycle for improving the …

The emerging concept of smart buildings, which requires the incorporation of sensors and
big data (BD) and utilizes artificial intelligence (AI), promises to usher in a new age of urban …

A personal comfort model is an approach to thermal comfort modeling, for thermal
environmental design and control, that predicts an individual's thermal comfort response …