Analysing the Low Quality of the Data in Lighting Control Systems

  • Jose R. Villar
  • Enrique de la Cal
  • Javier Sedano
  • Marco García-Tamargo
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6076)


Energy efficiency represents one of the main challenges in the engineering field, i.e., by means of decreasing the energy consumption due to a better design minimising the energy losses. This is particularly true in real world processes in the industry or in business, where the elements involved generate data full of noise and biases. In other fields as lighting control systems, the emergence of new technologies, as the Ambient Intelligence can be, degrades the quality data introducing linguistic values. The presence of low quality data in Lighting Control Systems is introduced through an experimentation step, in order to realise the improvement in energy efficiency that its of managing could afford. In this contribution we propose, as a future work, the use of the novel genetic fuzzy system approach to obtain classifiers and models able to deal with the above mentioned problems.


Step Response Lighting System Light Sensor Ambient Intelligence Fuzzy Random Variable 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • Jose R. Villar
    • 1
  • Enrique de la Cal
    • 1
  • Javier Sedano
    • 2
  • Marco García-Tamargo
    • 1
  1. 1.Computer Science DepartmentUniversity of OviedoGijónSpain
  2. 2.Instituto Tecnológico de Castilla y León, Lopez BravoBurgosSpain

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