Abstract: Air quality is crucial for the environment and the life quality of citizens. Therefore, in the present study a software application is developed to predict air quality on the basis of 2.5 particulate matter (〖PM〗_(2.5)) and 10particulate matter (〖PM〗_10), in the city of Upper Hunter, Australia, as it is considered to be one of the cities with the lowest air quality levels worldwide. For this purpose, it has been decided to use the methodology of long-short term memory (LSTM) from data collected by NSW department of planning industry and environment during the period of 30 September 2012 to 30 September 2019, to predict the behavior of the mentioned particulate matter during the month of October 2019. A comparison between the average and maximum values suggested by the software and the actual values has been made and it is shown that the predicted results of the study are quite close to reality. Finally, the results obtained in this study may serve as a basis for local authorities to proceed with the necessary protocols and measures in case an alarming prediction occurs.

Alexi Delgado, Ramiro Ricardo Maque Acuña and Chiara Carbajal, “Air Quality Prediction (PM2.5 and PM10) at the Upper Hunter Town - Muswellbrook using the Long-Short-Term Memory Method” International Journal of Advanced Computer Science and Applications(IJACSA), 11(4), 2020. http://dx.doi.org/10.14569/IJACSA.2020.0110443

@article{Delgado2020,
title = {Air Quality Prediction (PM2.5 and PM10) at the Upper Hunter Town - Muswellbrook using the Long-Short-Term Memory Method},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2020.0110443},
url = {http://dx.doi.org/10.14569/IJACSA.2020.0110443},
year = {2020},
publisher = {The Science and Information Organization},
volume = {11},
number = {4},
author = {Alexi Delgado and Ramiro Ricardo Maque Acuña and Chiara Carbajal}
}