Air Quality Monitoring System

Project Overview

This project is an IoT-driven Air Quality Monitoring System designed to measure and track environmental conditions in real-time. Using a Raspberry Pi as the central hub, the system integrates a DHT22 temperature and humidity sensor and an MQ135 air quality sensor to collect data on temperature, humidity, and air pollutants. The data is continuously uploaded to Google Firebase, providing a reliable cloud-based storage solution and enabling seamless access for users. A responsive web application, built with Bootstrap and Python, displays the live sensor readings and notifies users when air quality drops to unsafe levels. Beyond coding, the project served as a peer-learning experience, where setup, Python scripting, network integration, and cloud database management were collaboratively handled. The system not only highlights environmental awareness but also demonstrates practical IoT application and cloud integration skills.

The Challenge

Ensuring accurate sensor readings and maintaining reliable real-time data uploads to Firebase was difficult due to environmental fluctuations, sensor limitations, and potential network interruptions. Designing a responsive web interface, setting proper alert thresholds, and coordinating tasks during peer collaboration added complexity and required careful planning and communication.

The Solution

The sensors were calibrated and validated, and efficient Python scripts with error handling ensured continuous, accurate data uploads to Firebase. Bootstrap was used to create a responsive dashboard, dynamic logic handled alert notifications, and clear task division improved collaboration and workflow efficiency.

Key Features

• Real-Time Air Quality Monitoring
• Cloud Integration
• Responsive Web Application
• Alerts & Notifications
• Collaborative Build
• Open Source