SDG HACKATHON CODE for a CAUSE 3.0

Using IoT for Classroom Air Quality Monitoring

Introduction

Indoor air quality (IAQ) plays a critical role in students’ health, concentration, and academic performance. Classrooms, often densely packed and poorly ventilated, can accumulate pollutants like CO₂, dust, and volatile organic compounds (VOCs). With the advancement of the Internet of Things (IoT), real-time monitoring of IAQ is now practical, affordable, and scalable.

Why Air Quality Monitoring Matters in Classrooms
Poor air quality can cause fatigue, headaches, allergies, and long-term health issues. Studies have shown that high CO₂ levels correlate with reduced cognitive function and decision-making abilities. In developing countries, many classrooms lack basic ventilation standards, making it even more urgent to implement real-time monitoring solutions.

System Overview
Our IoT-based air quality monitoring system focuses on creating a smart, connected classroom environment. The system consists of:

• Sensors:

  • CO₂ Sensor (e.g., MG-811, MH-Z19)

  • PM2.5/PM10 Sensor (e.g., PMS5003)

  • Temperature & Humidity Sensor (e.g., DHT22)

  • VOC Sensor (e.g., CCS811)

• Microcontroller:

  • NodeMCU (ESP8266) for WiFi-based data transmission.

• Cloud Platform:

  • Data is sent to ThingSpeak or Firebase Realtime Database for visualization and logging.

• Dashboard:

  • A simple web/mobile interface shows air quality trends over time, with alert thresholds for unsafe conditions.

How It Works

1. Sensors collect air quality data every 30 seconds.

2. Data is transmitted via WiFi to a cloud platform.

3. The system triggers alerts (email/SMS/notification) when pollution crosses thresholds.

4. Teachers or school staff can take corrective actions like increasing ventilation or adjusting schedules.

Results & Observations
During a pilot test in a Dhaka classroom over 3 weeks:

• CO₂ levels spiked above 1000 ppm during peak hours.

• PM2.5 levels were higher in morning sessions near open windows facing roads.

• VOC levels increased significantly after cleaning sessions using chemical agents.

Benefits

• Low-cost and scalable solution for urban schools.

• Real-time alerts help maintain a safe learning environment.

• Historical data allows school management to optimize ventilation systems and cleaning schedules.

Challenges

• Maintaining sensor accuracy over time in dusty or humid conditions.

• WiFi instability in remote areas.

• Lack of awareness among school staff about IAQ metrics.

Future Improvements

• Integration with AI to predict air quality trends.

• Automated ventilation control based on sensor data.

• Solar-powered deployment for energy efficiency.

Conclusion
This IoT-based classroom air quality monitoring system demonstrates how low-cost technology can address critical health and learning challenges. With further refinement and support, such systems can be deployed across schools to ensure healthier environments for students.