This project focuses on real-time air pollution monitoring and prediction using machine learning techniques. The core idea is to collect live data from various gas sensors, preprocess this data, and use it to train a machine learning model capable of predicting pollution levels. The project leverages Arduino for data acquisition and Python for data processing and model training.