Artículo
Rule-based system to detect energy efficiency anomalies in smart buildings, a data mining approach
Autor/es | Peña Muñoz, Manuel
Biscarri Triviño, Félix Guerrero Alonso, Juan Ignacio Monedero Goicoechea, Iñigo Luis León de Mora, Carlos |
Departamento | Universidad de Sevilla. Departamento de Tecnología Electrónica |
Fecha de publicación | 2016 |
Fecha de depósito | 2018-07-05 |
Publicado en |
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Resumen | The rapidly growing world energy use already has concerns over the exhaustion of energy resources andheavy environmental impacts. As a result of these concerns, a trend of green and smart cities has beenincreasing. To ... The rapidly growing world energy use already has concerns over the exhaustion of energy resources andheavy environmental impacts. As a result of these concerns, a trend of green and smart cities has beenincreasing. To respond to this increasing trend of smart cities with buildings every time more complex,in this paper we have proposed a new method to solve energy inefficiencies detection problem in smartbuildings. This solution is based on a rule-based system developed through data mining techniques andapplying the knowledge of energy efficiency experts. A set of useful energy efficiency indicators is alsoproposed to detect anomalies. The data mining system is developed through the knowledge extracted bya full set of building sensors. So, the results of this process provide a set of rules that are used as a partof a decision support system for the optimisation of energy consumption and the detection of anomaliesin smart buildings. |
Agencias financiadoras | European Union (UE). FP7 |
Identificador del proyecto | FP7-285229 |
Cita | Peña Muñoz, M., Biscarri Triviño, F., Guerrero Alonso, J.I., Monedero Goicoechea, I.L. y León de Mora, C. (2016). Rule-based system to detect energy efficiency anomalies in smart buildings, a data mining approach. Expert Systems with Applications, 56 (september 2016), 242-255. |
Ficheros | Tamaño | Formato | Ver | Descripción |
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Rule-based system.pdf | 3.787Mb | [PDF] | Ver/ | |