Soft Computing

, Volume 20, Issue 5, pp 1749–1762

Big data: the key to energy efficiency in smart buildings

  • M. Victoria Moreno
  • Luc Dufour
  • Antonio F. Skarmeta
  • Antonio J. Jara
  • Dominique Genoud
  • Bruno Ladevie
  • Jean-Jacques Bezian
Focus

Abstract

Due to the high impact that energy consumption by buildings has at global scale, energy-efficient buildings to reduce \(\mathrm{CO}_2\) emissions and energy consumption are needed. In this work we present a novel approach to energy saving in buildings through the identification of the relevant parameters and the application of Soft Computing techniques to generate predictive models of energy consumption in buildings. Using such models it is possible to define strategies for optimizing the day-to-day energy consumption of buildings. To verify the feasibility of this proposal, we apply our approach to a reference building for which we have contextual data from a complete year of monitoring. First, we characterize the building in terms of its contextual features and energy consumption, and then select the most appropriate techniques to generate the most accurate model of our reference building charged with estimating the energy consumption, given a concrete set of inputs. Finally, considering the energy usage profile of the building, we propose specific control actions and strategies to save energy.

Keywords

Internet of things Big data Smart buildings Energy efficiency 

Copyright information

© Springer-Verlag Berlin Heidelberg 2015

Authors and Affiliations

  • M. Victoria Moreno
    • 1
  • Luc Dufour
    • 2
  • Antonio F. Skarmeta
    • 1
  • Antonio J. Jara
    • 2
  • Dominique Genoud
    • 2
  • Bruno Ladevie
    • 3
  • Jean-Jacques Bezian
    • 3
  1. 1.Department of Information and Communications EngineeringUniversity of MurciaMurciaSpain
  2. 2.Institute of Information SystemsUniversity of Applied Sciences Western Switzerland (HES-SO)SierreSwitzerland
  3. 3.Mines TelecomAlbiFrance

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