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Mexican Conference on Pattern Recognition

MCPR 2022: Pattern Recognition pp 127–136Cite as

Indoor Air Pollution Forecasting Using Deep Neural Networks

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Part of the Lecture Notes in Computer Science book series (LNCS,volume 13264)

Abstract

Atmospheric pollution components have negative effects in the health and life of people. Outdoor pollution has been extensively studied, but a large portion of people stay indoors. Our research focuses on indoor pollution forecasting using deep learning techniques coupled with the large processing capabilities of the cloud computing. This paper also shares the implementation using an open source approach of the code for modeling time-series of different sources data. We believe that further research can leverage the outcomes of our research.

Keywords

  • Air quality index forecast
  • Deep learning
  • Public data

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Acknowledgements

We thank the Asociación Mexicana de Cultura A.C., for its support. We also thank Montserrat Altamirano-Astorga for her valuable help proofreading this manuscript.

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Authors and Affiliations

  1. Instituto Tecnológico Autónomo de México, Mexico City, Mexico

    Jorge Altamirano-Astorga, Ita-Andehui Santiago-Castillejos, Luz Hernández-Martínez & Edgar Roman-Rangel

Authors
  1. Jorge Altamirano-Astorga
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  2. Ita-Andehui Santiago-Castillejos
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  3. Luz Hernández-Martínez
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  4. Edgar Roman-Rangel
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Corresponding authors

Correspondence to Jorge Altamirano-Astorga , Ita-Andehui Santiago-Castillejos , Luz Hernández-Martínez or Edgar Roman-Rangel .

Editor information

Editors and Affiliations

  1. Universidad Autónoma de Ciudad Juárez, Ciudad Juárez, Mexico

    Prof. Dr. Osslan Osiris Vergara-Villegas

  2. Universidad Autónoma de Ciudad Juárez, Ciudad Juárez, Mexico

    Vianey Guadalupe Cruz-Sánchez

  3. Instituto Politécnico Nacional, Mexico City, Mexico

    Juan Humberto Sossa-Azuela

  4. Instituto Nacional de Astrofísica, Óptica y Electrónica, Puebla, Mexico

    Dr. Jesús Ariel Carrasco-Ochoa

  5. Instituto Nacional de Astrofísica, Óptica y Electrónica, Puebla, Mexico

    José Francisco Martínez-Trinidad

  6. Autonomous University of Puebla, Puebla, Mexico

    José Arturo Olvera-López

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Altamirano-Astorga, J., Santiago-Castillejos, IA., Hernández-Martínez, L., Roman-Rangel, E. (2022). Indoor Air Pollution Forecasting Using Deep Neural Networks. In: Vergara-Villegas, O.O., Cruz-Sánchez, V.G., Sossa-Azuela, J.H., Carrasco-Ochoa, J.A., Martínez-Trinidad, J.F., Olvera-López, J.A. (eds) Pattern Recognition. MCPR 2022. Lecture Notes in Computer Science, vol 13264. Springer, Cham. https://doi.org/10.1007/978-3-031-07750-0_12

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  • DOI: https://doi.org/10.1007/978-3-031-07750-0_12

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