Acoustic sensor planning for gunshot location in national parks: a pareto front approach
| Autor: | J. Alonso, Enrique Costa-Montenegro, Francisco J. González-Castaño, S. Costas-Rodriguez, Francisco Vicente-Carrasco, Felipe Gil-Castineira, Pablo López-Matencio, Francisco J. Parrado-Garcia |
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| Přispěvatelé: | Grupo Ingeniería Telemática (GIT) |
| Jazyk: | angličtina |
| Rok vydání: | 2009 |
| Předmět: |
Sensor network planning
Sound location Operations research Computer science lcsh:Chemical technology Biochemistry Multi-objective optimization Acoustic sensing Article Clock synchronization Analytical Chemistry sensor synchronization sensor network planning Ubicación del sonido lcsh:TP1-1185 Electrical and Electronic Engineering Instrumentation Protocol (object-oriented programming) derivative-free optimization Ingeniería Telemática acoustic sensing Sensor de sincronización Derivative-free optimization Estimator sound location Detección acústica Pareto front Atomic and Molecular Physics and Optics Network planning and design Optimización de derivados libres Sensor de planificación de la red Pareto frontal Sensor synchronization Wireless sensor network |
| Zdroj: | Repositorio Digital de la Universidad Politécnica de Cartagena instname Sensors; Volume 9; Issue 12; Pages: 9493-9512 Sensors (Basel, Switzerland) Sensors, Vol 9, Iss 12, Pp 9493-9512 (2009) |
| Popis: | 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 Caba˜neros 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. This work has been partly supported by Spanish grants DEP2006-56158-C03-01/02/03 andTEC2007-67966-C03-01/02 (CON-PARTE). |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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