Artificial Neural Network Based Early Warning System For Aydin Province Towards Air Factors Which Primarily Affect Human Health

Abstract

Temperature, air quality index and ultraviolet index, which are basic air parameters, affect human health significantly. It is important to inform people about the precautions to be taken for these factors affecting human health at the primary level using today's technology. In this study, a software was developed for increasing the awareness of the people living in Aydın and informing them about these three important parameters. The obtained data was showed in an accessible website for the users and an informing message and an electronic mail are sent to the users according to predetermined conditions. Besides, air parameters, which were collected for Aydin province, are analyzed with artificial neural network for predicting of forward-looking these parameters. The result of analysis of the relationship between the predicted and real data has been observed to yield highly efficient results in the prediction of air quality index and ultraviolet index.

Keywords

• Air quality index
• ultraviolet index
• temperature
• early warning system
• artificial neural network