IoT Air Quality Monitoring and Alert System

This project was developed as a collaborative IoT solution designed to monitor environmental conditions and air quality in real time. The core system integrates a Raspberry Pi with various sensors, including a DHT22 for temperature and humidity, and an MQT5 sensor for air quality, to continuously collect vital environmental data. The collected sensor readings are processed by Python applications running on the Raspberry Pi. This data is then reliably transmitted to Google Firebase for robust cloud-based storage and synchronization. To ensure user accessibility, a responsive web application was developed to display live environmental metrics, historical readings, and the current air quality status through an intuitive dashboard interface. A key feature of the system is the automated alert mechanism. This system proactively notifies users whenever the measured air quality levels exceed predefined safety thresholds, enabling immediate and informed action regarding unhealthy environmental conditions. Overall, this project served as an intensive, hands-on learning experience, covering the entire stack from IoT device integration and hardware interfacing to cloud databases, web development, and real-time data processing. The collaborative nature of the development process allowed us to exchange knowledge across hardware configuration, backend development, frontend design, and cloud infrastructure deployment.

Integrating multiple sensors with Raspberry Pi hardware; establishing reliable communication between IoT devices and cloud infrastructure; configuring Firebase for real-time data synchronization; ensuring data accuracy through sensor calibration; and developing a responsive web dashboard capable of handling live updates.

We utilized Python scripts to efficiently collect, process, and transmit sensor data. Firebase Realtime Database was implemented for robust cloud storage. A Bootstrap-powered responsive web dashboard was developed for cross-device accessibility. Threshold-based alert logic was established to notify users of poor air quality, and a modular architecture was designed for future scalability.