Integrated IoT-Based Air Quality Monitoring and Prediction System: A Hybrid Approach

Abstract

Air pollution remains a global concern, leading to approximately 7 million annual deaths from prolonged exposure to harmful pollutants, causing chronic illnesses like respiratory diseases, cardiovascular problems, and cancer. It also has adverse effects on ecosystems due to climate changes. Governments rely on air quality monitoring systems to regulate toxic gas emissions, safeguarding public health and supporting agriculture and industry. Recent years have seen increased interest in air quality measurement and prediction. By connecting sensors in different locations, It is simpler to detect air pollution thanks to the Internet of Things (IoT). In order to conduct a full analysis, our research simulates air quality patterns in specific regions using an assortment of stationary and portable IoT sensors. We demonstrate the effectiveness of this method for detecting and forecasting air quality, offering efficient monitoring, particularly for smart cities and businesses, using machine learning algorithms and data from the real world.