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학술대회 Autonomous Lighting Control Based on Adjustable Illumination Model
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저자
김현석, 김유진, 김대호, 김현종, 강태규, 장성주, 서동준
발행일
201306
출처
International Conference on Information Science and Applications (ICISA) 2013, pp.1-3
DOI
https://dx.doi.org/10.1109/ICISA.2013.6579496
협약과제
13IC1400, 쌍방향 정보 교환기반 인텔리전트 복합공간용 IT 조명 시스템 기술 개발, 강태규
초록
Autonomous lighting control systems require a numerical illumination model in which the light level output in a room can be expected according to given dimming control inputs. Stationary illumination models, such as the zonal cavity method and the point by point method, might be difficult to adjust the model to on-site environments in which are suffused with various shading artifacts unconsidered in a preceding simulation stage. Thus, this paper suggests an adjustable illumination model through Neural Network which can fit the model to the environments by a learning technology. Secondly, the autonomous lighting control can be realized by using the inverse of the illumination model. A small-sized replica of an actual lighting space is used for evaluation of our approach. © 2013 IEEE.
키워드
lighting control, lighting emitting diodes, neural network
KSP 제안 키워드
Cavity method, Dimming Control, Emitting diodes, Illumination model, Neural networks, On-Site, Point method, Small-sized, learning technology, lighting control system