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Título
Energy Optimization Using a Case-Based Reasoning Strategy
Autor(es)
Materia
Smart building
Ubiquitous computing
Intelligent management
Case-based reasoning
Clasificación UNESCO
1203.17 Informática
Fecha de publicación
2018-03-15
Citación
González Briones, A., Prieto, J., De La Prieta, F., Herrera Viedma, E. and Corchado, J., 2018. Energy Optimization Using a Case-Based Reasoning Strategy. Sensors, 18(3), p.865.
Resumen
[EN] At present, the domotization of homes and public buildings is becoming increasingly popular. Domotization is most commonly applied to the field of energy management, since it gives the possibility of managing the consumption of the devices connected to the electric network, the way in which the users interact with these devices, as well as other external factors that influence consumption. In buildings, Heating, Ventilation and Air Conditioning (HVAC) systems have the highest consumption rates. The systems proposed so far have not succeeded in optimizing the energy consumption associated with a HVAC system because they do not monitor all the variables involved in electricity consumption. For this reason, this article presents an agent approach that benefits from the advantages provided by a Multi-Agent architecture (MAS) deployed in a Cloud environment with a wireless sensor network (WSN) in order to achieve energy savings. The agents of the MAS learn social behavior thanks to the collection of data and the use of an artificial neural network (ANN). The proposed system has been assessed in an office building achieving an average energy savings of 41% in the experimental group offices.
URI
ISSN
1424-8220
DOI
10.3390/s18030865
Colecciones
- BISITE. Artículos [290]