Applying IoT and Data Analytics to Thermal Comfort: A Review

Application of machine learning in thermal comfort studies: A review of methods, performance and challenges

“…There are some publicly accessible thermal comfort datasets, such as ASHRAE global thermal comfort database II, the scales project, Langevin Longitudinal dataset, ERA5-Heat, and Winter Thermal Comfort and health for the elderly that can be used, which contain 107584, 8226, 678621, not mentioned, and 424 records, respectively [68]. Therefore, some studies used existing data from ASHRAE databases ( [26], [28], [59], [60], [34], [61], [62], [63], [35]) while others collected data for their specific studies.…”

“…In a recent review study, Khalil et al [68] concluded that ML model selection, data privacy and security, and Federated Learning are the major challenges in the field of thermal comfort IoT data analytics. More comprehensively, the present review introduces some challenges relating to the process of all ML applications in thermal comfort studies.…”