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
Link To Document :
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