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Article . Conference object . 2017 . 2016
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Conference object . 2017
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Data sources: Datacite
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Conference object . 2017
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Visual Comfort and Energy Efficiency for User Centric Lighting Control

Authors: Tsatsakis Konstantinos; Tsitsanis Anastasios; Malavazos;

Visual Comfort and Energy Efficiency for User Centric Lighting Control

Abstract

Energy consumption for lighting constitutes a sizable portion of the overall energy consumption of commercial office buildings. Many smart lighting control products are already available in the market, but their penetration has been limited and even installed systems have had limited use. One of the main reasons is that they tend to control lighting based on universal set-points which are agnostic to the individual preferences of the occupants thus hampering their comfort. The paper will present an automated lighting control framework which dynamically learns the lighting preferences of each user, models his visual comfort and controls the light dimming in a truly personalized manner so as to always control the comfort vs. energy efficiency trade-off. This approach effectively removes the single most important complaint of occupants when using such systems, loss of comfort, and paves the way for their wide scale adoption in order to untap the energy reduction potential of commercial lighting.

Abushakra, B., Sreshthaputra, A., Haberl, J., & Claridge, D. (2001). Compilation of diversity factors and schedules for energy and cooling load calculations. ASHRAE research project 1093-RP. Texas, USA.

Bourgeois, D. (2005). Detailed occupancy prediction, occupancy-sensing control & advanced behavioral modelling within whole-building energy simulation. Univ. Laval, Canada.

Chen, H., Chou, P., Duri, S., Lei, H., & Reason, J. (2009). The design and implementation of a smart building control system. In IEEE International Conference on e-Business Engineering, pp. 255-262.

Clevenger, C., Haymaker, J. (2006). The Impact of the Building Occupant on Energy Modeling Simulations. In Joint International Conference on Computing and Decision Making in Civil ad Building Engineering, Montreal, Canada.

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    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Average
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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download
citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
views
OpenAIRE UsageCountsViews provided by UsageCounts
downloads
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0
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208
327
Funded by
EC| MOEEBIUS
Project
MOEEBIUS
Modelling Optimization of Energy Efficiency in Buildings for Urban Sustainability
  • Funder: European Commission (EC)
  • Project Code: 680517
  • Funding stream: H2020 | IA
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