Sensing and Forecasting of Pollution Data in Mexico City

  • et al.
Citations of this article
Mendeley users who have this article in their library.
Get full text


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.




Molina, E.-J. V., Cruz, R. J., & Vega, A. R.-D. (2019). Sensing and Forecasting of Pollution Data in Mexico City. International Journal of Engineering and Advanced Technology, 9(2), 2372–2378.

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free