This project focuses on predicting air quality in smart cities using machine learning. The system collects data from various environmental sensors placed around the city, processes the data, and predicts future air quality conditions. By utilizing machine learning algorithms like Decision Trees, the system can provide forecasts that help city planners optimize pollution management.
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