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Active Sensing and Its Application to Sensor Node Reconfiguration

This paper presents a perturbation/correlation-based active sensing method and its application to sensor node configuration for environment monitoring. Sensor networks are widely used as data measurement tools, especially in dangerous environments. For large scale environment monitoring, a large num...

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Detalles Bibliográficos
Autor principal: Lee, Sooyong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4239898/
https://www.ncbi.nlm.nih.gov/pubmed/25299949
http://dx.doi.org/10.3390/s141018484
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author Lee, Sooyong
author_facet Lee, Sooyong
author_sort Lee, Sooyong
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description This paper presents a perturbation/correlation-based active sensing method and its application to sensor node configuration for environment monitoring. Sensor networks are widely used as data measurement tools, especially in dangerous environments. For large scale environment monitoring, a large number of nodes is required. For optimal measurements, the placement of nodes is very important. Nonlinear spring force-based configuration is introduced. Perturbation/correlation-based estimation of the gradient is developed and it is much more robust because it does not require any differentiation. An algorithm for tuning the stiffness using the estimated gradient for node reconfiguration is presented. The performance of the proposed algorithm is discussed with simulation results.
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spelling pubmed-42398982014-11-21 Active Sensing and Its Application to Sensor Node Reconfiguration Lee, Sooyong Sensors (Basel) Article This paper presents a perturbation/correlation-based active sensing method and its application to sensor node configuration for environment monitoring. Sensor networks are widely used as data measurement tools, especially in dangerous environments. For large scale environment monitoring, a large number of nodes is required. For optimal measurements, the placement of nodes is very important. Nonlinear spring force-based configuration is introduced. Perturbation/correlation-based estimation of the gradient is developed and it is much more robust because it does not require any differentiation. An algorithm for tuning the stiffness using the estimated gradient for node reconfiguration is presented. The performance of the proposed algorithm is discussed with simulation results. MDPI 2014-10-08 /pmc/articles/PMC4239898/ /pubmed/25299949 http://dx.doi.org/10.3390/s141018484 Text en © 2014 by the authors; licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Lee, Sooyong
Active Sensing and Its Application to Sensor Node Reconfiguration
title Active Sensing and Its Application to Sensor Node Reconfiguration
title_full Active Sensing and Its Application to Sensor Node Reconfiguration
title_fullStr Active Sensing and Its Application to Sensor Node Reconfiguration
title_full_unstemmed Active Sensing and Its Application to Sensor Node Reconfiguration
title_short Active Sensing and Its Application to Sensor Node Reconfiguration
title_sort active sensing and its application to sensor node reconfiguration
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4239898/
https://www.ncbi.nlm.nih.gov/pubmed/25299949
http://dx.doi.org/10.3390/s141018484
work_keys_str_mv AT leesooyong activesensinganditsapplicationtosensornodereconfiguration