• DocumentCode
    635998
  • Title

    Estimation of illuminance sensor positions and improvement of energy efficiency in the distributed control lighting system

  • Author

    Miki, M. ; Yoshida, Kenta ; Hirano, Yoshikuni ; Ikegami, Hiroyuki

  • Author_Institution
    Dept. of Sci. & Eng., Doshisha Univ., Kyoto, Japan
  • fYear
    2013
  • fDate
    23-25 May 2013
  • Firstpage
    137
  • Lastpage
    142
  • Abstract
    We propose a distributed control lighting system (hereafter, Intelligent Lighting System) for achieving personal illuminance. The Intelligent Lighting System changes the luminances for individual lights based on a self-distribution algorithm. It learns the influence of lights on illuminance sensors through regression analysis and controls the lighting to achieve the required illuminance in the required places. When the numbers of lights and illuminance sensors increase, however, an error in the regression coefficient becomes larger; accordingly, the influence of the lights on illuminance sensors may not be correctly estimated. To solve this problem, this study proposes a method for correcting the results of the learning of the influence of the lights on illuminance sensors by estimating the illuminance sensor positions. With the proposed method, we estimate the illuminance sensor positions and determine the distances between the individual lights and illuminance sensors to correct the results of the learning according to the distances. The method proposed in this study enables the illuminance sensor positions to be estimated with an error of less than 1 m. Moreover, the method makes it possible to appropriately control lighting luminance compared with conventional method, achieving an improvement in illuminance convergence speed as well as a 5% reduction in power consumption.
  • Keywords
    distributed control; electric sensing devices; energy conservation; intelligent control; lighting control; position control; power consumption; regression analysis; distributed control lighting system; energy efficiency; illuminance convergence speed; illuminance sensor position estimation; intelligent lighting system; power consumption; regression analysis; self-distribution algorithm; Artificial intelligence; Educational institutions; Equations; Estimation; Lighting; Mathematical model; Regression analysis; lighting control; optimization; position estimation; regression analysis;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Applied Computational Intelligence and Informatics (SACI), 2013 IEEE 8th International Symposium on
  • Conference_Location
    Timisoara
  • Print_ISBN
    978-1-4673-6397-6
  • Type

    conf

  • DOI
    10.1109/SACI.2013.6608954
  • Filename
    6608954