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An Expert System for Building Energy Management Through the Web of Things

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Hybrid Artificial Intelligent Systems (HAIS 2020)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 12344))

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Abstract

Managing energy consumption in buildings is of utmost importance given the fact that 20% of the total energy consumed worldwide comes from the buildings sector. The miniaturization of electronic and mechanical systems, together with low-power wireless communications, facilitate the development and deployment of building energy management systems (BEMS) based on Internet of Things (IoT) platforms. It is well known that IoT solutions create silos suffering from interoperability issues. In this paper, we propose an expert system based on the W3C Web of Things (WoT), a paradigm that seeks to counter the interoperability issues in the IoT. The proposed system implements a set of rules, fed by a time series database, that mange several sensors and actuators addressed through Web technologies using WoT. The goal of this expert system is to be the core of a BEMS, and thus, it will be able to optimize energy consumption as well as to enable smart retrofit of existing buildings. In addition, the expert system is combined with a graphical user interface featuring several web-based dashboards, making it possible for an administrator to remotely supervise the operation of the whole building.

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Notes

  1. 1.

    https://www.influxdata.com/products/influxdb-overview/.

  2. 2.

    https://pypi.org/project/experta/.

  3. 3.

    http://www.clipsrules.net.

References

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Acknowledgments

This work has been funded by the European Union’s Horizon 2020 Framework Program for Research and Innovation under grant agreement No. 768921 and by the University of Oviedo under project 2018/00061/012.

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Authors and Affiliations

  1. CTIC Technological Centre, Gijón, Spain

    Daniel Ibaseta, Martín Álvarez & Fidel Díez

  2. Department of Computer Science and Engineering, University of Oviedo, Oviedo, Spain

    Julio Molleda

Authors
  1. Daniel Ibaseta
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  2. Julio Molleda
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  3. Martín Álvarez
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  4. Fidel Díez
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Corresponding author

Correspondence to Daniel Ibaseta .

Editor information

Editors and Affiliations

  1. University of Oviedo, Oviedo, Spain

    Enrique Antonio de la Cal

  2. University of Oviedo, Oviedo, Spain

    José Ramón Villar Flecha

  3. University of A Coruña, Ferrol, Spain

    Héctor Quintián

  4. University of Salamanca, Salamanca, Spain

    Emilio Corchado

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Ibaseta, D., Molleda, J., Álvarez, M., Díez, F. (2020). An Expert System for Building Energy Management Through the Web of Things. In: de la Cal, E.A., Villar Flecha, J.R., Quintián, H., Corchado, E. (eds) Hybrid Artificial Intelligent Systems. HAIS 2020. Lecture Notes in Computer Science(), vol 12344. Springer, Cham. https://doi.org/10.1007/978-3-030-61705-9_39

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  • DOI: https://doi.org/10.1007/978-3-030-61705-9_39

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-61704-2

  • Online ISBN: 978-3-030-61705-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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