Analyzing the Impact of Occupancy Patterns on Indoor Air Quality in University Classrooms Using a Real-Time Monitoring System

Abstract

Indoor air quality (IAQ) in universities is of concern because it directly affects students’ health and performance. This study presents an IoT-based system for real-time monitoring of IAQ in university classrooms. The system uses MQ-7 and MQ-135 sensors to monitor CO and CO2 pollution parameters. The data is then processed by the ESP32 microcontroller, displayed on the LCD screen, and responded to immediately in the mobile application. The system's real-time monitoring capabilities, data display, and alert mechanism provide valuable insights to improve the classroom environment. The sensors used in the system achieved an accuracy of 97.17% for five people and 93.96% for ten people's scenarios. This study investigates the relationship between human behavior, classroom activities, and occupancy impacts the IAQ. The results show a strong positive correlation between occupancy rates and CO2 levels, indicating the importance of ventilation in densely populated classrooms. The correlation coefficient between the number of students and the CO2 levels is 0.982. This coefficient is remarkably close to 1, indicating a strong positive correlation. In other words, as the number of students in the classroom increases, the CO2 levels also increase significantly. The high correlation coefficient suggests a direct relationship between the number of students and the CO2 levels. This IoT-based system will facilitate a data-driven approach to improving indoor environmental conditions, supporting healthier and more effective learning environments in educational institutions.