Biological Rhythm Aware Office Lighting Control

We formulate the lighting control system as a mathematical optimization problem which is highly nonlinear and acts of a longer time interval. To this end we introduce an iterative optimization algorithm to achieve a solution. This method can be used to develop scalable human-centric smart lighting control systems centered towards bringing support to the biological rhythm of individual employees. We test the inter-person variability of the optimum light exposure, and concluded that theory predicts that there is no one-size-fits-all light recipe. In particular, individual differences in late-evening light exposure require differentiation in the late afternoon.
Humans are different. Our evaluations show that standard deviations in biological difference (intrinsic period) and social behavior require different light recipes. That is, human centric lighting control based on population averages have much less effect, compared to algorithms that take human variation into account. Possible one-size-fits-all human centric lighting is inadequate to achieve the desired impact or may be counterproductive for specific humans.