Energy consumption is one of the primary concerns\udin a resource-constrained visual sensor network (VSN). The existing VSN design solutions under particular resource-constrained scenarios are application specific, whereas the degree of sensitivity of the resource constraints varies from one application to another. This limits the implementation of the existing energy efficient solutions within a VSN node, which may be considered to\udbe a part of a heterogeneous network. The heterogeneity of image capture and processing within a VSN can be adaptively reflected with a dynamic field-of-view (FoV) realization. This is expected to allow the implementation of a generalized energy efficient solution to adapt with the heterogeneity of the network. In this paper, an energy efficient FoV characterization framework is proposed,\udwhich can support a diverse range of applications. The context of adaptivity in the proposed FoV characterization framework is considered to be: 1) sensing range selection; 2) maximizing spatial coverage; 3) adaptive task classification; and 4) minimizing the number of required nodes. Soft decision criteria is exploited, and it is observed that for a given detection reliability, the proposed\udframework provides energy efficient solutions, which can be\udimplemented within heterogeneous networks. It is also found that the proposed design solution for heterogeneous networks leads to 49.8% energy savings compared with the trivial design solution.
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