iTCM : toward learning-based thermal comfort modeling via pervasive sensing for smart buildings

• Main Authors: Hu, Weizheng, Wen, Yonggang, Guan, Kyle, Jin, Guangyu, Tseng, King Jet
• Other Authors: School of Computer Science and Engineering
• Format: Article
• Language: English
• Published: 2020
• Subjects: Engineering::Computer science and engineering; Internet of Things (IoT); Machine Learning
• Online Access: https://hdl.handle.net/10356/139362
• Institution: Nanyang Technological University

For decades, ASHRAE Standard 55 has been using the Fanger's predicted mean vote (PMV) model to evaluate the indoor thermal comfort satisfaction. However, this canonical model has drawbacks in both data inadequacy and lack of inputs from test subjects. In this paper, we propose a learning-based...