A dynamic adaptive light field sampling approach for smart lighting control

Abstract

Smart lighting is used to provide the right light to meet occupants’ needs for efficiency, productivity and health. The development of adaptive control in smart lighting requires advanced real-time sensing technologies for monitoring the generated light field. This paper introduces a systematic approach to dynamic light field sampling using a distributed sensor network. A dynamic adaptive sampling algorithm is introduced to guide the adaptive selection and real-time reallocation of sample locations to track and estimate the generated light field and the daylight field. This approach generates a multi-scale functional representation of the light field, which can be an effective basis for lighting control. Experimental results have shown that a systematic dynamic selection of sensor locations can significantly reduce the error in representation of the light field with corresponding improvement in the lighting control.