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abstract: |
    A wireless sensor network (WSN) consists of multiple wireless sensor nodes that communicate each other to fulfill a particular task. In this paper, we emphasize on the networks whose deployments admit lower dimensional substructures, such as collinear groups in 2D, or coplanar groups in 3D. When these groups are given as a part of the input, we describe an algorithm to utilize this information to perform a low-cost localization.

    In emergency situations such as fire, earthquake etc. inside a building, wireless sensor networks might be very crucial to provide critical information and help the rescue teams to move very quickly by decreasing their burden of exploring the environment. Thus, it is very important to develop a system that provides information quickly and without consuming too much energy. We observe that in these type of environments, sensor nodes tend to form *hyperplanar groups*. A hyperplane is a subspace of one dimension less than its ambient space, and accordingly, a *hyperplanar group* of sensor nodes is a group of nodes that sit on the same hyperplane. When we consider a floor of a building, the nodes can be deployed on the corridors to form collinear groups, and when we 