González-Figueredo, CarlosEgurrola-Hernández, E.A.DeAlba-Martínez, HugoRamírez-Briseño, R.L.Magaña-Villegas, Elizabeth2019-08-282019-08-282018-03González-Figueredo, C., Egurrola-Hernández, E. A., DeAlba-Martínez, H., Ramírez-Briseño, R. L., & Magaña-Villegas, E. (2018). Mobile App for Air Quality Guadalajara, Mexico. In Proceedings of Abstracts 11th International Conference on Air Quality Science and Application, University of Hertfordshire.978-1-5272-2150-5http://hdl.handle.net/11117/5990AireAMG is a mobile app for air quality forecasting in the Guadalajara Metropolitan Area in Mexico. This app uses real-time air quality measurements of five criteria pollutants, along with meteorological data, to forecast air pollution concentration. A novel scheme of Artificial Neural Networks (ARN) coupled to Kalman filters is used to generate air quality predictions for up to 24 hours for each of the monitoring stations locations. We used these predictions to generate ozone and particulate matter dispersion maps, by interpolating with the Inverse Distance Weighted (IDW) method. AireAMG updates these forecasts and dispersion maps every hour, and is available for Android and iOS systems.engCalidad del AireApplicaciones MóvilesRedes Neuronales Artificialesinfo:eu-repo/semantics/conferencePaper