Computational Intelligence for Evaluating the Air Quality in the Center of Madrid, Spain

  • Jamal ToutouhEmail author
  • Irene Lebrusán
  • Sergio Nesmachnow
Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 1173)


This article presents the application of data analysis and computational intelligence techniques for evaluating the air quality in the center of Madrid, Spain. Polynomial regression and deep learning methods to analyze the time series of nitrogen dioxide concentration, in order to evaluate the effectiveness of Madrid Central, a set of road traffic limitation measures applied in downtown Madrid. According to the reported results, Madrid Central was able to significantly reduce the nitrogen dioxide concentration, thus effectively improving air quality.


Smart cities Air pollution Computational intelligence 



I. Lebrusán has been partially funded by RCC Harvard program. J. Toutouh has been partially funded by EU’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No 799078; and by the Spanish MINECO and FEDER projects TIN2017-88213-R, RTI2018-100754-B-I00, and UMA18-FEDERJA-003.


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Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  1. 1.CSAILMassachusetts Institute of TechnologyCambridgeUSA
  2. 2.IGLPHarvard UniversityCambridgeUSA
  3. 3.Universidad de la RepúblicaMontevideoUruguay

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