ABSTRACT

This study introduced an IoT-based air quality monitoring system for checking meticulous environmental evaluation, mainly focusing on monitoring capabilities. The system was meticulously designed to detect and analyze an array of air pollutants, including PM1.0, PM2.5, PM10, NO2, SO2, O3, CO, and CO2. Central to this research is the system’s precision in monitoring, data acquisition, and seamless integration with cloud-based platforms. These data points were seamlessly transmitted to the ThingSpeak platform, the central hub for data storage, in-depth analysis, and visual representation. The IoT-enabled air quality monitoring system offered multifaceted advantages. It presented a comprehensive view of air quality by encompassing diverse pollutants with varied sources and effects and enables immediate detection of pollution surges and hazardous conditions, prompting timely interventions. Furthermore, the integration with ThingSpeak ensured that the collected data could be accessed from any location, enabling remote monitoring and informed decision-making. This study showcased the successful implementation of an IoT air quality monitoring system that not only detects pollutants with accuracy but is also integrated with cloud technologies for comprehensive environmental assessment.

College of Engineering and Computer Studies Bachelor of Science in Electronics Engineering