AI-BASED AIR QUALITY AND POLLUTION MONITORINGS SYSTEM FOR SMART CITY

  Air pollution has become a major environmental and public health concern in modern urban areas. Rapid industrialization, increasing vehicular traffic, and population growth have significantly contributed to the deterioration of air quality in many cities. Continuous monitoring and early prediction of pollution levels are essential to control environmental damage and protect public health. The proposed AI-Based Air Quality and Pollution Monitoring Systemprovides an intelligent and efficient solution for addressing these challenges through the integration of advanced technologies such as Artificial Intelligence, Internet of Things (IoT), and cloud computing. The system successfully collects environmental data from IoT-based sensors that measure various air quality parameters including particulate matter (PM2.5 and PM10), carbon monoxide, carbon dioxide, nitrogen dioxide, sulfur dioxide, temperature, and humidity. These sensors continuously monitor environmental conditions and transmit real-time data to a centralized cloud platform. The collected data is then processed and analyzed using machine learning algorithms implemented in Python, which helps in identifying pollution patterns and predicting the Air Quality Index (AQI).

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