Intelligent light control using sensor networks

Increasing user comfort and reducing operation costs have always been two primary objectives of building operations and control strategies. Current building control strategies are unable to incorporate occupant level comfort and meet the operation goals simultaneously. In this paper, we present a novel utility-based building control strategy that optimizes the tradeoff between meeting user comfort and reduction in operation cost by reducing energy usage. We present an implementation of the proposed approach as an intelligent lighting control strategy that significantly reduces energy cost. Our approach is based on a principled, decision theoretic formulation of the control task. We demonstrate the use of mobile wireless sensor networks to optimize the trade-off between fulfilling different occupants' light preferences and minimizing energy consumption. We further extend our approach to optimally exploit external light sources for additional energy savings, a process called daylight harvesting. Also we demonstrate that an active sensing approach can maximize the mobile sensor network's lifetime by sensing only during most informative situations. We provide efficient algorithms for solving the underlying complex optimization problems, and extensively evaluate our proposed approach in a proof-of-concept testbed using MICA2 motes and dimmable lamps. Our results indicate a significant improvement in user utility and reduced energy expenditure.