  Wireless sensor networks are dynamically formed over the varying topologies.
Wireless sensor networks can assist in conducting the rescue operations and can
provide search in timely manner. Long time monitoring applications are
environment monitoring, security surveillance and habitat monitoring. Further,
where it can be deployed in time critical situations when disaster happens. As
we are dealing with the human lives here, we can not just rely on the
localization schemes that depend upon the connectivity information Rf i.e.
range-free algorithms only. Further, rescue operations are carried out in
highly noisy environments, so distance based Rb(range-based) localization
algorithms generate high error in distance measurements. An efficient algorithm
is needed that can measure the location of the sensor nodes near to the living
being or being attached to them in 3-D space with a high accuracy. To achieve
such kind of accuracy a combination of both the strategies is required. The
proposed method which incorporates both the Rb(range-based)&Rfrange-free
strategies that successfully localizes nodes in a sensor network with noisy
distance measurements. We also have depicted the effect of scalability on the
performance of the algorithm. Results show that as the scalability of the
network increases with the number of beacon nodes; the performance of the
algorithm goes high above 90 percent . The granularity of the areas estimated
may be easily adjusted by changing the system parameters which makes the
proposed algorithm flexible.
