Development of an Indoor Air Quality Monitoring System

This project aims to develop an internet-of- things-based air quality monitoring system for indoor use, specifically in a university health clinic. The project includes the following hardware materials: PPD42 particulate matter detector, MQ-9 gas sensor, MiCS-6814 gas sensor, DHT11 temperature and humidity sensor, and NodeMCU ESP8266. The sensors and microcontroller were programmed using C++ to get the raw carbon monoxide, nitrogen dioxide, particulate matter 2.5 and 10, LPG, and temperature and humidity data from the indoor environment. Then, they were processed and sent to Firebase. The materials were merged inside a case using wires, lead, and PCB. The application was developed in Android Studio using Java as the backend language. The application displays an air quality index based on the information gathered in the database through the sensor. The website, using JavaScript, also fetches data from the database to display the gathered air information. The machine collected air quality data every 30 minutes, which the application displays in numerical form along with its index. The website serves as the data analytics module to monitor anomalies in the air quality of an indoor area. Based on the testing, the sensors could have accurate readings and produced an accurate output, which the participants strongly agreed.