A new approach has been proposed to improve the performance of the in-telligent lighting system by estimating personal illuminance and desired color temperature at the workplace. We are considering the problem of using the sensing devices manually for the intelligent lighting system. The lighting control system has not become useful without sensing devices to measure the provided illuminance and color temperature. In this paper, we have used the property of light for the color temperature to estimate the level of color temperature for each user at the workplace. The new method will give personal illuminance for each user at the workplace and decrease the power consumption of the environment as well. As a result, the proposed method of the intelligent lighting system has realized the target of illuminance and color temperature for each user at the workplace by adapting dimming levels using illuminance sensing information for each user. Thus, the energy of the workplace has reduced by using a distributed luminance to realize the target for each user.
References
[1]
Castillo-Martinez, A., Medina-Merodio, J.-A., Gutierrez-Martinez, J.-M., Aguado-Delgado, J., de Pablos-Heredero, C. and Otón, S. (2018) Evaluation and Improvement of Lighting Efficiency in Working Spaces. Sustainability, 10, 1110. https://doi.org/10.3390/su10041110
[2]
Cadena, R. (2006) Automated Lighting: The Art and Science of Moving Light in Theatre, Live Performance, Broadcast, and Entertainment. Taylor & Francis, Thames.
[3]
Mills, P.R., Tomkins, S.C. and Schlangen, L.J. (2007) The Effect of High Correlated Colour Temperature Office Lighting on Employee Wellbeing and Work Performance. Journal of Circadian Rhythms, 5, 2. https://doi.org/10.1186/1740-3391-5-2
[4]
Noguchi, H. and Sakaguchi, T. (1999) Effect of Illuminance and Color Temperature on Lowering of Physiological Activity. Applied Human Science, 18, 117-123. https://doi.org/10.2114/jpa.18.117
[5]
Pandharipande, A. and Newsham, G. (2018) Lighting Controls: Evolution and Revolution. Lighting Research & Technology, 50, 115-128. https://doi.org/10.1177/1477153517731909
[6]
Tanaka, S., Yoshikata, M., Miki, M. and Hiroyasu, T. (2009) An Evolutional Optimization Algorithm to Provide Individual Illuminance in Workplaces. 2009 IEEE International Conference on Systems, Man and Cybernetics, San Antonio, 11-14 October 2009, 941-947. https://doi.org/10.1109/ICSMC.2009.5346094
[7]
Borile, S., Pandharipande, A., Caicedo, D., Schenato, L. and Cenedese, A. (2017) A Data-Driven Daylight Estimation Approach to Lighting Control. IEEE Access, 5, 21461-21471.
[8]
Tomishima, C., Miki, M., Ashibe, M., Hiroyasu, T. and Yoshimi, M. (2010) Distributed Control of Illuminance and Color Temperature in Intelligent Lighting System. International Conference on Artificial Intelligence and Soft Computing, Springer, New York, 411-419. https://doi.org/10.1007/978-3-642-13232-2_50
[9]
Taniguchi, Y., Miki, M., Hiroyasu, T. and Yoshimi, M. (2011) Preferred Illuminance and Color Temperature in Creative Works. 2011 IEEE International Conference on Systems, Man, and Cybernetics, Anchorage, 9-12 October 2011, 3255-3260. https://doi.org/10.1109/ICSMC.2011.6084171
[10]
Miki, M., Motoya, Y., Ikegami, H. and Fujimoto, S. (2013) Combination of Preferred Illuminance and Preferred Color Temperature for Work. 2013 IEEE International Conference on Systems, Man, and Cybernetics, Manchester, 13-16 October 2013, 4577-4582.
[11]
Xinping, B., Guanglei, Z. and Jichuan, Z. (2014) Illuminance and Color Temperature Control in Intelligent Lighting System. Ricoh Software Research Center (Beijing) Co., Ltd., Beijing.
[12]
Ikegami, H., Kuwajima, S., Miki, M. and Aida, H. (2014) An Extraction Method of Influential Lightings for Illuminance Sensors on an Intelligent Lighting System in Large Office. Proceedings on the International Conference on Artificial Intelligence (ICAI), Las Vegas, 21-24 July 2014, 1.
