An IoT-Based Intelligent Air Quality Monitoring System

ABSTRACT

Air pollution imposes a big environmental and health hazard challenge in the world. This necessitates a tool to be developed that can measure and analyze air quality in real time. This is also essential in quick restoration and assessment of lungs during the prevailing COVID pandemics. The real-time air quality indexes of gases like carbon monoxide, ozone, SO2, NO2, etc., are collected and sent to the cloud (firebase). The collected data is analyzed using machine learning algorithms which leads to the prediction of severity of air quality contamination. Further in this paper, we propose an analysis of location wise air pollution measurement and accuracy in the prediction of air quality.