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Intelligent Luminance Control of Lighting Systems Based on Imaging Sensor Feedback

1
School of Biological Science and Medical Engineering, Beihang University, Beijing 100191, China
2
Astronaut Research and Training Center of China, Beijing 100094, China
*
Author to whom correspondence should be addressed.
Academic Editor: Vittorio M. N. Passaro
Sensors 2017, 17(2), 321; https://doi.org/10.3390/s17020321
Received: 7 January 2017 / Revised: 1 February 2017 / Accepted: 3 February 2017 / Published: 9 February 2017
(This article belongs to the Section Physical Sensors)
An imaging sensor-based intelligent Light Emitting Diode (LED) lighting system for desk use is proposed. In contrast to the traditional intelligent lighting system, such as the photosensitive resistance sensor-based or the infrared sensor-based system, the imaging sensor can realize a finer perception of the environmental light; thus it can guide a more precise lighting control. Before this system works, first lots of typical imaging lighting data of the desk application are accumulated. Second, a series of subjective and objective Lighting Effect Evaluation Metrics (LEEMs) are defined and assessed for these datasets above. Then the cluster benchmarks of these objective LEEMs can be obtained. Third, both a single LEEM-based control and a multiple LEEMs-based control are developed to realize a kind of optimal luminance tuning. When this system works, first it captures the lighting image using a wearable camera. Then it computes the objective LEEMs of the captured image and compares them with the cluster benchmarks of the objective LEEMs. Finally, the single LEEM-based or the multiple LEEMs-based control can be implemented to get a kind of optimal lighting effect. Many experiment results have shown the proposed system can tune the LED lamp automatically according to environment luminance changes. View Full-Text
Keywords: intelligent lighting; luminance control; vision effect; environment perception; imaging sensor intelligent lighting; luminance control; vision effect; environment perception; imaging sensor
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Liu, H.; Zhou, Q.; Yang, J.; Jiang, T.; Liu, Z.; Li, J. Intelligent Luminance Control of Lighting Systems Based on Imaging Sensor Feedback. Sensors 2017, 17, 321.

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