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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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Formato: | Online Artículo Texto |
Lenguaje: | English |
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MDPI
2014
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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 |
collection | PubMed |
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. |
format | Online Article Text |
id | pubmed-4239898 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2014 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
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 |