Thermal Comfort Modeling Dataset: Climatic and Biological Data collected in Santa Maria, RS, Brazil

This dataset was collected in Santa Maria, RS, Brazil, as part of a study aimed at evaluating human thermal comfort using machine learning models. The data includes both climatic and biological variables, as well as subjective responses on thermal sensation and preference. Climatic data includes air temperature (°C), relative humidity (%), wind speed (m/s), and solar radiation (W/m²). Biological data covers height (m), weight (kg), biological sex, and clothing insulation (Clo). Subjective responses include Thermal Sensation Vote (TSV, -3 to +3) and thermal preference. The data was collected over multiple sessions between 2017 and 2019, combining real-time environmental measurements from a local weather station with questionnaire responses. This dataset is suitable for personalized thermal comfort modeling, climate-adaptive building design, and urban microclimate analysis. It has been previously used to recalibrate analytical comfort models for subtropical climates and to develop machine learning algorithms for thermal comfort prediction. CSV Schema/Format: Encoding = Unicode (UTF-8) Column Separator = ; Quote Character = "