The deterioration of human and environmental conditions caused by air pollution is seriously affecting worldwide. Several countries have been taken urgent action to improve air quality to achieve sustainable development goals proposed by the United Nations. Some pollutants, in particular, tropospheric ozone is a major component of smog. It can worsen plant growth limitations, respiratory and cardiovascular problems along with premature deaths. In order to build a tool to support public health planning and management, as well as being one way to achieve the UN Sustainable Development goal 11.6 in cities, our goal is to develop a neuro-fuzzy model to predict the concentration of ozone in the city of Sorocaba. By local data collected on the CETESB website, neuro-fuzzy models of ANFIS architecture will be proposed. The best model option will be chosen based on performance metrics between the actual data collected and those predicted by the model. This project will contribute to the development of sustainable plans regarding air quality in Sorocaba, as well as the knowledge generated will support the construction of accurate and reliable forecasting models.
News published in Agência FAPESP Newsletter about the scholarship: