Vision-based user-centric light control for smart environments
Smart homes are conceptualized as environments responsive to a users presence and actions, and adaptive to user preferences and context. Visual information plays an enabling role in smart home applications such as interfaces and gesture control. This paper reports on the use of cameras and a distributed processing method for automated control of lights in a smart home. The proposed optimization formulations maintain the users comfort while reducing the energy cost of lights. Information from camera sensors provides occupancy reasoning and human activity analysis. By detecting the users position and activity, and employing light utility functions as constraints, the system optimizes the light setting for the users satisfaction in the occupied area. Additionally, to reduce the transmission energy and bandwidth, we also propose an ellipsoid approximation (EA) method for occupancy reasoning by a camera network. By applying the EA method, the network nodes can aggregate the observed data progressively and maintain a fixed transmitted data length. Simulations on the occupancy results from experiments are provided to verify the proposed algorithms.
smart environments energy-efficient light control camera sensor networks