Combined visual comfort and energy efficiency through true personalization of automated lighting control

Abstract

Lighting consumes a sizable portion of the energy consumed in office buildings. Smart lighting control products exist in the market, but their penetration is limited and even installed systems see limited use. One of the main reasons is that they control lighting based on universal set-points agnostic to individual human preferences, thus hampering their comfort. This paper presents an automated lighting control framework which dynamically learns user lighting preferences, models human visual comfort and controls light dimming in a truly personalized manner so as to always control the comfort vs. energy efficiency trade-off. It effectively removes the most important complaint when using such systems — loss of comfort — and paves the way for their wider scale adoption in order to untap the energy reduction potential of commercial lighting.