Artificial Intelligence Based Air Quality Prediction Using IoT Sensor Data

Continuous air quality monitoring is important for protecting human health and ensuring environmental sustainability. Recent advances in sensor technologies, the Internet of Things (IoT) and artificial intelligence have led to innovative solutions that allow environmental parameters to be monitored and analyzed in real time. For this study, an IoT-based data collection system was designed that integrates environmental sensors to record meteorological data such as temperature, humidity and precipitation, as well as a gas sensor which is sensitive to a range of pollutants such as carbon monoxide (CO), nitrogen oxides (NOx), and ozone(O3). Based on the ESP32 microcontroller platform, the system has been used to create artificial intelligence models that can predict air quality with high accuracy. The main objective of this research is to evaluate the extent to which the developed models can successfully predict complex environmental relationships.