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Air pollution poses a serious threat to urban health and safety. This paper presents an IoT-based dynamic air quality monitoring system designed for real-time tracking of pollutants such as PM2.5, PM10, CO, NO2, SO2, and O3, along with temperature and humidity. The system uses a microcontroller, gas and particulate sensors, GPS for geo-tagging, and wireless communication (Wi-Fi, LoRa, or GSM) to transmit data to the cloud. Machine learning processes the data to predict trends and issue alerts via a mobile app, supporting public awareness and smart city management. This solution promotes sustainable urban living through efficient, scalable pollution monitoring.
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