Event statistics and criticality-aware bitrate allocation to minimize energy consumption of memory-constrained wireless surveillance system

An event criticality-aware wireless surveillance system tries to minimize the energy consumption by adjusting the image distortion (or quality) requirement according to event criticality. In this paper, we present a novel video encoding method which scales bitrate so as to minimize the energy consumption of the wireless surveillance system while satisfying the given memory constraint. Given event statistics, memory size, and distortion requirement, the presented method gives an energy-optimal bitrate based on an analytic formulation of energy-rate-distortion (E-R-D) relationship for the target system consisting of H.264 video encoder, event detector, transceiver and memory. Experimental results show that the proposed method offers up to 59.6% (29.1% on average) energy savings compared to an existing bitrate allocation method which does not consider event statistics.