Open AccessSensing and Forecasting of Pollution Data in Mexico City
Author(s) -
Elías-J. Ventura Molina,
Raúl Jiménez Cruz,
Adolfo Rangel-Díaz-de-la Vega
Publication year - 2019
Publication title -
international journal of engineering and advanced technology
Language(s) - English
Resource type - Journals
ISSN - 2249-8958
DOI - 10.35940/ijeat.a2247.129219
Subject(s) - pollution , ozone , pollutant , nox , nitrogen dioxide , environmental science , classifier (uml) , air pollution , computer science , nitrogen oxides , carbon monoxide , meteorology , data mining , artificial intelligence , engineering , geography , chemistry , waste management , ecology , biochemistry , organic chemistry , catalysis , biology , combustion
In this paper we present the characteristics of sensors used to monitor the pollution levels in Mexico City, namely sulfur dioxide (SO2), nitrogen oxides (NOx), ozone (O3), , and carbon monoxide (CO). A novel algorithm to predict contamination levels is presented: the Gamma classifier. Also, a new coding technique is introduced, allowing the conversion from a series of values taken from SIMAT databases into a set of patterns, which in turn are useful for the task of pollutant forecasting. Experimental results show a competitive performance by the Gamma classifier as a predictor, when compared to other methods.