The intelligent control of lighting has the potential to bring benefits in energy consumption, human comfort and well-being, and worker productivity. Existing systems have various drawbacks including: (1) they often only detect the presence of people, and not their number and spatial distribution in the room; and (2) they typically use cameras or other high resolution sensors, which create high computational loads for real time operation and may present significant privacy or security concerns. A smart lighting system and method was developed that estimates occupancy using perturbation-modulated light and distributed non-imaging color sensors. The system includes color controllable lighting and non-imaging color sensors distributed throughout a space to estimate the spatial distribution of people in the space in order to make real time lighting adjustments. small perturbations onto the color-controllable light are introduced. These perturbations are designed and sequenced to be imperceptible to humans, but are accurately measurable by the color sensors. A rapid series of measurements is made with the sensors under different perturbations in the lighting, and these measurements are used to estimate a light transport model. The light transport model contains a measure of the light flux between each fixture-sensor pair, as a function of color, e.g., red, green, blue (RGB). This is done in such a way that the ambient lighting (from a window, for example) is subtracted from the model, leaving only the linear (controllable) part of the relationship. With the light transport model determined, various options are provided for estimating the occupancy pattern in the room.

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Natasha Sanford