Qingdao Middle School Classroom Environmental Monitoring and Window-Opening Behavior Dataset
Description
This dataset comprises high-resolution environmental monitoring and window-opening behavior data collected from a middle school classroom in Qingdao, China (cold-climate region), over four seasons in 2025. The monitoring campaign covered 84 school days across spring (April, 22 days), summer (June, 21 days), autumn (October, 18 days), and winter (December, 23 days), yielding a total of 120,960 raw data records. The dataset includes continuous measurements of indoor and outdoor air temperature (°C), relative humidity (%), indoor CO₂ concentration (ppm), indoor and outdoor PM₂.₅ (μg/m³), indoor and outdoor PM₁₀ (μg/m³), outdoor CO₂ concentration (ppm), and window-opening status (binary: open/closed). Environmental parameters were recorded at 1-minute intervals using Xingzong Intelligent AM308-470M industrial-grade sensors for indoor monitoring and HOBO U12-012 data loggers for outdoor measurements. Window status was tracked via magnetic contact switches mounted on the classroom's exterior windows. The merged Excel file contains 10 worksheets: (1) All_Raw_Data: 56,760 rows of merged raw monitoring data from all four seasons with a 'Season' identifier column (sampling interval: 1 minute during school hours, 6:30–18:30). (2) All_Calculated_Data: 2,640 rows of aggregated statistical summaries (hourly and daily averages) with a 'Season' identifier column. (3–10) Season-specific sheets (Spring_Raw, Spring_Calculated, Summer_Raw, Summer_Calculated, Autumn_Raw, Autumn_Calculated, Winter_Raw, Winter_Calculated) preserving original file structure for reproducibility. This dataset supports machine learning-based analysis of window-opening behavior as a climate-resilient adaptive mechanism under institutionalized teaching schedules. It has been used to train a Random Forest model (AUC-ROC = 0.897, F1-score = 0.749) with SHAP (SHapley Additive exPlanations) analysis to identify threshold-driven behavioral patterns across four daily activity phases: arrival, break, class, and leaving. Variable list (All_Raw_Data sheet): - Season: Spring / Summer / Autumn / Winter - Timestamp: Date and time (YYYY-MM-DD HH:MM:SS) - Indoor_Temperature_C: Indoor air temperature (°C) - Outdoor_Temperature_C: Outdoor air temperature (°C) - Indoor_CO2_ppm: Indoor CO₂ concentration (ppm) - Outdoor_CO2_ppm: Outdoor CO₂ concentration (ppm) - Indoor_PM2_5_ugm3: Indoor PM₂.₅ concentration (μg/m³) - Outdoor_PM2_5_ugm3: Outdoor PM₂.₅ concentration (μg/m³) - Indoor_PM10_ugm3: Indoor PM₁₀ concentration (μg/m³) - Outdoor_PM10_ugm3: Outdoor PM₁₀ concentration (μg/m³) - Indoor_RH_percent: Indoor relative humidity (%) - Outdoor_RH_percent: Outdoor relative humidity (%) - Window_Status: Window opening state (1 = open, 0 = closed)
Files
Institutions
- Qingdao University of TechnologyShandong, Qingdao