부산대학교 도서관

With the continuous development of human society, air pollution has become a global concern. For elderly people with respiratory diseases such as asthma and COPD, the danger of air pollution is not to be underestimated. In this study, we use a number of public datasets and LSTM, SVM, DT, and SHAP models to analyze and predict air quality data and explore the effects of different air environment changes on the occurrence of asthma, in an attempt to find the main sources of pollution for asthma. In addition, this study uses the Internet of Things technology to develop an air quality sensor box to collect data and an information platform to calculate various air quality related data using machine learning models and data to provide efficient control methods to help the elderly avoid dangerous spaces and reduce the risk of asthma in order to create a safe and healthy living space.