The objective of this project is to design a smart air quality monitoring system that collects, analyzes, and visualizes pollution data in real time. The system helps authorities and citizens understand air pollution levels and supports data-driven environmental protection measures.
Study air pollutants such as CO₂, NO₂, SO₂, PM2.5, and PM10 and their health effects.
Research existing air quality monitoring systems and government standards.
Design a system architecture integrating IoT sensors (real or simulated).
Develop a database to store pollution data with timestamps and locations.
Implement data preprocessing techniques to handle noisy or missing data.
Create algorithms to calculate Air Quality Index (AQI) values.
Develop a web dashboard to visualize pollution levels using graphs and charts.
Implement alert notifications when AQI exceeds safe limits.
Analyze historical pollution trends using statistical methods.
Conduct testing using simulated environmental data.
Evaluate system accuracy and scalability.
Document findings and propose enhancements like predictive pollution modeling.
