Identyfikatory
Warianty tytułu
Języki publikacji
Abstrakty
In this work, an application of adaptive lighting system is proposed for smart homes. In this paper, it is suggested that, an intelligent lighting system with outdoor adaptation can be realized via a real fisheye image. During the implementation of the proposed method, the fuzzy c-means method, which is a commonly used data clustering method, has been used. The input image is divided into three different regions according to its brightness levels. Then, the RGB image is converted to CIE 1931 XYZ color space; and the obtained XYZ values are converted to x and y values. The parameters of x and y values are shown in CIE Chromaticity Diagram for different regions in the sky. Thereafter, the coordinate values are converted to Correlated Color Temperature by using two different formulas. Additionally, the conversion results are examined with respect to actual and estimated CCT values.
Słowa kluczowe
Wydawca
Rocznik
Tom
Strony
172--178
Opis fizyczny
Bibliogr. 23 poz., fig., tab.
Twórcy
autor
- Fırat University, Faculty of Engineering, Department of Electrical and Electronics Engineering, 23200, Elazığ, Turkey
Bibliografia
- 1. Arecchi A. V., Koshel R. J. and Messadi T. Field guide to illumination. SPIE. 2007.
- 2. Baniya R., Maksimainen, M., Sierla, S., Pang, C., Yang, C. W., & Vyatkin, V. Smart indoor lighting control: Power, illuminance, and colour quality. In Industrial Electronics (ISIE), 2014 IEEE 23rd International Symposium on, 2014, 1745-1750.
- 3. Berman S. M., Navvab M., Martin M. J., Sheedy, J., & Tithof W. A comparison of traditional and high colour temperature lighting on the near acuity of elementary school children. Lighting Research & Technology, 38(1), 2006, 41-49.
- 4. Breteau, Jean-Marc, Colorimetry, Optical Metrology, [Online] http://www.optique-ingenieur.org/ en/courses/OPI_ang_M07_C02/co/Contenu_07. html, [Last Accessed:28.04.2017]
- 5. Cai W., Chen S., & Zhang, D. Fast and robust fuzzy c-means clustering algorithms incorporating local information for image segmentation. Pattern recognition, 40(3), 2007, 825-838.
- 6. Ceriotti M., Corrà, M., D’Orazio L., Doriguzzi R., Facchin D., Jesi G. P., ... & Picco G. P. (2011, April). Is there light at the ends of the tunnel? Wireless sensor networks for adaptive lighting in road tunnels. In Information Processing in Sensor Networks (IPSN), 10th International Conference on, 2011, 187-198.
- 7. Colour Management for Beginners – Profiles Explained, [Online] http://www.sant-media. co.uk/2010/06/color-management-for-beginners-profiles-explained/ [Last Accessed:28.04.2017].
- 8. Ford A. and Roberts, A. Colour space conversions. Westminster University, London, 1998, 1-31.
- 9. Han Dae-Man and Jae-Hyun Lim. Smart home energy management system using IEEE 802.15. 4 and zigbee. IEEE Transactions on Consumer Electronics 56.3, 2010.
- 10. Hernández-Andrés J., Lee R. L., & Romero J. Calculating correlated color temperatures across the entire gamut of daylight and skylight chromaticities. Applied optics, 38(27), 1999, 5703-5709.
- 11. Lee A. T., Chen H., Tan S. C., & Hui S. R. Precise dimming and color control of LED systems based on color mixing. IEEE Transactions on Power Electronics, 31(1), 2016, 65-80.
- 12. McCamy C. S. Correlated color temperature as an explicit function of chromaticity coordinates. Color Research & Application, 17(2), 1992, 142-144.
- 13. Miki M., Kasahara Y., Hiroyasu T., & Yoshimi M. Construction of illuminance distribution measure-ment system and evaluation of illuminance convergence in intelligent lighting system. In Sensors, 2010, 2431-2434.
- 14. Nayak J., Naik B., & Behera H. S. Fuzzy C-means (FCM) clustering algorithm: a decade review from 2000 to 2014. In Computational Intelligence in Data Mining-Volume 2, 2015, 133-149.
- 15. Pathak P. H., Feng X., Hu P., & Mohapatra, P. Visible light communication, networking, and sensing: A survey, potential and challenges. IEEE communications surveys & tutorials, 17(4), 2015, 2047-2077.
- 16. Reinhard E., Adhikhmin M., Gooch B., & Shirley P. Color transfer between images. IEEE Computer graphics and applications, 21(5), 2001, 34-41.
- 17. Schanda J. (Ed.). Colorimetry: understanding the CIE system. John Wiley & Sons, 2007.
- 18. Smith J. Calculating color temperature and illuminance using the TAOS TCS3414CS digital color sensor. Designer’s Notebook, 2009, 1-7.
- 19. Thattai K., Manikanta, K. B., Chhawchharia, S., & Marimuthu, R. ZigBee and ATmega32 based wireless digital control and monitoring system For LED lighting. In Information Communication and Embedded Systems (ICICES), International Conference on, 2013, 878-881.
- 20. Van Bommel I. W., van den Beld, I. G., & van Ooyen, I. M. Industrial lighting and productivity. Philips Lighting, The Netherlands, 2002.
- 21. Van Bommel W. J. M., & Van den Beld, G. J. Lighting for work: a review of visual and biological ef-fects. Lighting Research & Technology, 36(4), 2004, 255-266.
- 22. Vujović V., & Maksimović, M. Raspberry Pi as a Sensor Web node for home automation. Computers & Electrical Engineering, 44, 2015, 153-171.
- 23. Wei M., Houser, K. W., Orland, B., Lang, D. H., Ram, N., Sliwinski, M. J., & Bose, M. Field study of office worker responses to fluorescent lighting of different CCT and lumen output. Journal of Environmental Psychology, 39, 2014, 62-76.
Uwagi
Opracowanie ze środków MNiSW w ramach umowy 812/P-DUN/2016 na działalność upowszechniającą naukę (zadania 2017)
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-edb19a87-1a19-47d4-bc37-3d3b614a6b36