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International Symposium on Distributed Computing and Artificial Intelligence

DCAI 2018: Distributed Computing and Artificial Intelligence, 15th International Conference pp 61–68Cite as

AllergyLESS. An Intelligent Recommender System to Reduce Exposition Time to Allergens in Smart-Cities

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Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 800))

Abstract

Allergic rhinitis affects between 10% and 30% of the worldwide population. It reduces the quality of life of the individuals and causes losses in the local economy due to absenteeism. AllergyLESS is a recommendation system to solve mobility issues of the citizens by informing them which walking routes minimizes the exposure time to allergens. The system collects air-quality and allergens metrics from wireless pollution stations and open-data sources. In the cases when the pollution stations do not cover the whole area of interest, an ontology for the healthcare domain along with a set of data mining processes are used to forecast the presence of allergens. The system was validated by carrying out a number of controlled simulations of real situations.

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Notes

  1. 1.

    http://www.aemet.es.

  2. 2.

    https://openweathermap.org/.

  3. 3.

    https://www.apixu.com/.

  4. 4.

    http://aber-owl.net/ontology/AO/#/.

  5. 5.

    https://www.iso.org/standard/62436.html.

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Acknowlegements

This work has been supported by the Comunidad Autónoma de la Región de Murcia (CARM) and the European Regional Development Fund (FEDER/ERDF) through project 2I16SAE00025 under the RIS3MUR program.

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Authors and Affiliations

  1. Department of Informatics and Systems, Universidad de Murcia, Murcia, Spain

    José Antonio García-Díaz, María Luisa Hernández-Alcaraz, Francisco García-Sánchez & Rafael Valencia-García

  2. Proyectos y soluciones tecnológicos avanzadas, SLP (Proasistech), Avda. Primero de Mayo, nº2, Torres Azules. Torre A, 4ª Planta, Drcha, Murcia, Spain

    José Ángel Noguera-Arnaldos & Isabel María Robles-Marín

Authors
  1. José Antonio García-Díaz
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  2. José Ángel Noguera-Arnaldos
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  3. María Luisa Hernández-Alcaraz
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  4. Isabel María Robles-Marín
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  5. Francisco García-Sánchez
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  6. Rafael Valencia-García
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Corresponding author

Correspondence to José Antonio García-Díaz .

Editor information

Editors and Affiliations

  1. BISITE Digital Innovation Hub. Edificio Multimedia I+D+i, University of Salamanca, Salamanca, Spain

    Fernando De La Prieta

  2. Faculty of Engineering, Department of Electronics, Information and Communication, Osaka Institute of Technology, Osaka, Osaka, Japan

    Sigeru Omatu

  3. Department of Computing Systems, School of Industrial Engineers at Albacete, University of Castilla-La Mancha, Albacete, Spain

    Antonio Fernández-Caballero

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García-Díaz, J.A., Noguera-Arnaldos, J.Á., Hernández-Alcaraz, M.L., Robles-Marín, I.M., García-Sánchez, F., Valencia-García, R. (2019). AllergyLESS. An Intelligent Recommender System to Reduce Exposition Time to Allergens in Smart-Cities. In: De La Prieta, F., Omatu, S., Fernández-Caballero, A. (eds) Distributed Computing and Artificial Intelligence, 15th International Conference. DCAI 2018. Advances in Intelligent Systems and Computing, vol 800. Springer, Cham. https://doi.org/10.1007/978-3-319-94649-8_8

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