Design and Implementation of a Low-Cost IoT-Based Air Quality Monitoring System Using Raspberry Pi and Cloud Integration

Abstract

Air quality deterioration is a prominent pollution issue that raises the need for continuous and localized air quality monitoring. Conventional air quality monitoring systems provide precise results but are quite expensive and scarce devices. A low-cost IoT air quality monitoring system using Raspberry Pi as an edge device with Real-time cloud integration has been designed and implemented in this paper. The system is designed to detect carbon monoxide, ammonia, carbon dioxide, temperature, and humidity with MQ series gas sensors and a DHT22 sensor. An MCP 3008 Analog-to-Digital Converter helps in successfully obtaining the analog output of sensors. The Raspberry Pi performs edge computations and sends the processed information to a Firebase Realtime Database using wireless communication. Simulation modeling with Proteus helps to demarcate sensor connections and information flow prior to implementation. The hardware for the air quality monitoring system designed in this paper provides scalable, cost-effective, and efficient means to achieve real-time air quality measurements in smart homes, labs in academic institutes, and small-scale cities.