Air Quality Inference

Air Quality Inference is a method that employs big data and machine learning technologies to predict and evaluate air quality. Its aim is to provide accurate air quality forecasts and assessments by analyzing historical and real-time environmental data, identifying sources of pollutants and their changing trends. This method holds significant application value in environmental protection, urban planning, and public health, supporting policy-making and emergency response, and enhancing the quality of life for residents.