AI-Enabled Smart Air Quality Monitoring and Short-Term AQI Prediction System

Air pollution is an important environmental concernthat affects public health and urban living conditions. Conventional monitoring stations provide valuable measurements, butlimited monitoring coverage can make it difficult to observelocal variations in air quality. This paper proposes an Internet ofThings (IoT)-enabled framework for monitoring environmentalconditions and estimating short-term changes in the Air QualityIndex (AQI). The proposed system connects environmental sensors to a microcontroller, transfers measurements to a processingplatform, and prepares the collected data for forecasting. Historical observations and relevant environmental variables can beused to investigate suitable prediction methods. A dashboard candisplay current measurements, historical trends, forecasts, andwarning messages. The design also considers missing readings,communication failures, and the need to distinguish measuredvalues from predictions. This framework provides a basis forfuture implementation and evaluation; its actual forecastingperformance must be established through experiments usingsuitable data.