IoT Environmental Monitoring - Student Mental Health Dataset
Abstract
"IoT-based environmental perception data studying impact on university students' mental health. Integrates temperature, humidity, noise, and air quality sensors."
Description
Research Focus
This innovative dataset explores the relationship between environmental factors measured by IoT sensors and mental health outcomes in university students.
Sensor Data Collected
- Temperature sensors - Indoor/outdoor readings
- Humidity monitors - Relative humidity %
- Noise level detectors - dB measurements
- Air quality sensors - PM2.5, CO2, VOCs
- Light intensity - Lux readings
Mental Health Correlations
Data includes survey responses on stress levels, sleep quality, concentration ability, and overall well-being, correlated with environmental sensor readings.
Research Applications
Supports studies in environmental psychology, smart campus initiatives, IoT healthcare (IoMT), and data-driven mental health interventions.
📊 View Data Structure
To explore column names, data types, and sample rows, visit the official dataset page on Kaggle.
Preview on Kaggle
Cite This Dataset
Ziya (2025). IoT Environmental Monitoring - Student Mental Health Dataset. [Dataset]. Kaggle. https://www.kaggle.com/datasets/ziya07/iot-based-environmental-dataset
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Original source: Kaggle (2025). Visit official page for more details.
Indexed by IoTDataset.com on Jan 21, 2026
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