Non-intrusive physiological parameters sensing for personalized human thermal comfort prediction
Sep 20, 2025·,,,·
1 min read
Mohamad Rida
Mohamed Abdelfattah
Alexandre Alahi
Dolaana Khovalyg
A non-intrusive physiological sensing approach for personalized thermal comfort prediction.
One-Sentence Summary
In this study, we applied multi-modal non-intrusive computer vision algorithms to extract personal features such as clothing ensemble, activity level, posture, sex, age, and skin temperature as thermal comfort defining parameters.
BibTeX
@article{rida2023toward,
title={Toward contactless human thermal monitoring: A framework for Machine Learning-based human thermo-physiology modeling augmented with computer vision},
author={Rida, Mohamad and Abdelfattah, Mohamed and Alahi, Alexandre and Khovalyg, Dolaana},
journal={Building and Environment},
volume={245},
pages={110850},
year={2023},
publisher={Elsevier}
}