Improving classroom air quality and ventilation with IoT-driven acoustic and visual CO₂ feedback system

Area of Science:

• Environmental Science
• Building Science
• Indoor Air Quality

Background:

• Classroom ventilation heavily relies on teacher behavior for window and door operation.
• Poor indoor air quality in schools is linked to health and learning outcomes.
• Existing ventilation strategies often lack real-time feedback for optimal performance.

Purpose of the Study:

• To evaluate the impact of an IoT-based CO₂ self-surveillance display system (SAVE unit) on classroom air quality and thermal comfort.
• To assess the effectiveness of visual and acoustic alarms in prompting ventilation behaviors.
• To understand the interplay between air quality, thermal comfort, and energy consumption in naturally ventilated classrooms.

Main Methods:

• Implemented an IoT-based SAVE unit with visual and acoustic alarms for CO₂ monitoring.
• Collected air quality data (CO₂, PM concentrations) across baseline, visual alarm, and visual-acoustic alarm scenarios.
• Analyzed teacher's window opening behavior in relation to CO₂ levels, temperature, and alarm triggers.

Main Results:

• The SAVE unit reduced CO₂ levels by 19-19.5% with alarm systems.
• Particulate matter (PM) concentrations increased with window openings, but remained within WHO limits.
• Teacher decisions on ventilation were primarily driven by thermal comfort, leading to higher CO₂ on colder days.

Conclusions:

• The SAVE unit effectively reduces classroom CO₂ but necessitates balancing energy efficiency and thermal comfort.
• A holistic signaling system integrating temperature and air quality is needed for optimal ventilation management.
• Real-time, data-driven ventilation strategies are crucial for healthy and comfortable learning environments.