Abstract
In this paper, we propose a solution for gunshot location in national parks. In Spain there are agencies such as SEPRONA that fight against poaching with considerable success. The DiANa project, which is endorsed by Cabaneros National Park and the SEPRONA service, proposes a system to automatically detect and locate gunshots. This work presents its technical aspects related to network design and planning. The system consists of a network of acoustic sensors that locate gunshots by hyperbolic multi-lateration estimation. The differences in sound time arrivals allow the computation of a low error estimator of gunshot location. The accuracy of this method depends on tight sensor clock synchronization, which an ad-hoc time synchronization protocol provides. On the other hand, since the areas under surveillance are wide, and electric power is scarce, it is necessary to maximize detection coverage and minimize system cost at the same time. Therefore, sensor network planning has two targets, i.e., coverage and cost. We model planning as an unconstrained problem with two objective functions. We determine a set of candidate solutions of interest by combining a derivative-free descent method we have recently proposed with a Pareto front approach. The results are clearly superior to random seeding in a realistic simulation scenario.
Highlights
The Spanish SEPRONA [1] agency fights against poaching with considerable success
We provide a set of candidate solutions of interest by combining a derivative-free descent method we have recently proposed and a Pareto front approach
The results reveal that the Pareto front approach is useful
Summary
The Spanish SEPRONA [1] agency fights against poaching with considerable success. the problem remains relevant. The hyperbolic location method [17] minimizes an error measure that is a nonlinear function of the potential source location This approach is scalable, since location accuracy increases with the number of nodes that detect the gunshot (see Section 5.). The tests with our reference implementation in MICAz motes reveal that, the more sensors that detect the sound event, the greater the location precision (see Section 5.). This is due to error compensation in arrival time measures. Note that this process permits discover of optimal communication paths (in number of hops) to the root, and, it is valid for network routing
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