ILLUMINATION ESTIMATION USING NEURAL NETWORKS
DOI:
https://doi.org/10.24867/09BE18LatinovicKeywords:
neural network, illuminance estimation, smart lighting control, LED light, spatial fieldAbstract
This paper describes a propreties of LED lights used in smart lighting systems, its alternative role in visible light communication systems and significance of these systems in localization and positioning techniques. This paper decribes a methods for illumination estimation where illumination was considered as a spatial field and the emphasis is on the indoor enviroments. The goal of this paper is to estimate the illuminance field by applying neural network using results obtained from numerical experiment implemented in MATLAB framework.
References
[1] Eva Arias–de–Reyna, Pau Closas, Davide Dardari, Petar M. Đurić, „Crowd-Based Learning of Spatial Fields for the Internet of Things“, IEEE 2018.
[2] M. Petkovic, D. Bajovic, D. Vukobratovic, G. McCutcheon, L. Stankovic, V. Stankovic: "Effect of External Daylight in Smart Dimmable LED Lighting Systems," Wireless and Optical Communications Conference WOCC 2019, Beijing, China, May 2019.
[3] Sina Afshari, Li Jia, Richard J. Radke, Sandipan Mishra, „Light Field Estimation and Control using a Graphical Rendering Engine“, ASME 2014.
[4] Casper Kofod, „Guidelines for Indoor Lighting in the Public and Private Service Sector“, Denmark, 2017.
[2] M. Petkovic, D. Bajovic, D. Vukobratovic, G. McCutcheon, L. Stankovic, V. Stankovic: "Effect of External Daylight in Smart Dimmable LED Lighting Systems," Wireless and Optical Communications Conference WOCC 2019, Beijing, China, May 2019.
[3] Sina Afshari, Li Jia, Richard J. Radke, Sandipan Mishra, „Light Field Estimation and Control using a Graphical Rendering Engine“, ASME 2014.
[4] Casper Kofod, „Guidelines for Indoor Lighting in the Public and Private Service Sector“, Denmark, 2017.
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Published
2020-08-27
Issue
Section
Electrotechnical and Computer Engineering
