Lighting in commercial office environments is a major factor in workplace comfort, productivity, and stress. Modern work environments strive to improve these conditions by better selection of luminaires (fixtures), wall, floor, and furniture colour and texture, and intelligent lighting control that ensures that occupants each receive the proper amount of light needed at their workstations for the task at hand. Daylight infiltration is generally good for occupant comfort, and provides opportunities to "harvest" this daylight and save energy on electric lighting, provided that it is harnessed in a way that it does not over illuminate or cause glare. Building an intelligent lighting control system is challenging due to incompatible or sometimes conflicting lighting preferences from adjacent people or areas. Some office environments can be additionally challenging because of complex geometries, time-varying nondeterministic daylight contributions through windows, and glare. Here we address the challenges of meeting users' individual lighting preferences using a highly accurate illumination model to enable balancing the various lighting requirements among spatially grouped task areas, while minimizing the energy needed to do so (and in the future, minimizing the number of wireless sensors needed for this application). We propose an illumination model-based method and algorithm for intelligent open-loop lighting control, and present the results of a simulation study using a simplistic virtual room model to demonstrate the validity of our method. Daylight infiltration is to be addressed in future work.
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