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Relocatable, Automated Cost-Benefit Analysis for Marine Sensor Network Design
When designing sensor networks, we need to ensure they produce representative and relevant data, but this must be offset by the financial cost of placing sensors. We describe a novel automated method for generating and combining cost and benefit values to decide on the best sensor locations using in...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Molecular Diversity Preservation International (MDPI)
2012
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3376612/ https://www.ncbi.nlm.nih.gov/pubmed/22736982 http://dx.doi.org/10.3390/s120302874 |
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author | D’Este, Claire de Souza, Paulo Sharman, Chris Allen, Simon |
author_facet | D’Este, Claire de Souza, Paulo Sharman, Chris Allen, Simon |
author_sort | D’Este, Claire |
collection | PubMed |
description | When designing sensor networks, we need to ensure they produce representative and relevant data, but this must be offset by the financial cost of placing sensors. We describe a novel automated method for generating and combining cost and benefit values to decide on the best sensor locations using information about the specific constraints available in most coastal locations. Costs in maintenance, negotiation, equipment, exposure and communication are estimated using hydrodynamic models and Electronic Navigation Charts. Benefits in maximum coverage and reducing overall error are also determined using model output. This method demonstrates equivalent accuracy at predicting the whole system to expert-chosen locations, whilst significantly reducing the estimated costs. |
format | Online Article Text |
id | pubmed-3376612 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2012 |
publisher | Molecular Diversity Preservation International (MDPI) |
record_format | MEDLINE/PubMed |
spelling | pubmed-33766122012-06-25 Relocatable, Automated Cost-Benefit Analysis for Marine Sensor Network Design D’Este, Claire de Souza, Paulo Sharman, Chris Allen, Simon Sensors (Basel) Article When designing sensor networks, we need to ensure they produce representative and relevant data, but this must be offset by the financial cost of placing sensors. We describe a novel automated method for generating and combining cost and benefit values to decide on the best sensor locations using information about the specific constraints available in most coastal locations. Costs in maintenance, negotiation, equipment, exposure and communication are estimated using hydrodynamic models and Electronic Navigation Charts. Benefits in maximum coverage and reducing overall error are also determined using model output. This method demonstrates equivalent accuracy at predicting the whole system to expert-chosen locations, whilst significantly reducing the estimated costs. Molecular Diversity Preservation International (MDPI) 2012-03-02 /pmc/articles/PMC3376612/ /pubmed/22736982 http://dx.doi.org/10.3390/s120302874 Text en © 2012 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/3.0/). |
spellingShingle | Article D’Este, Claire de Souza, Paulo Sharman, Chris Allen, Simon Relocatable, Automated Cost-Benefit Analysis for Marine Sensor Network Design |
title | Relocatable, Automated Cost-Benefit Analysis for Marine Sensor Network Design |
title_full | Relocatable, Automated Cost-Benefit Analysis for Marine Sensor Network Design |
title_fullStr | Relocatable, Automated Cost-Benefit Analysis for Marine Sensor Network Design |
title_full_unstemmed | Relocatable, Automated Cost-Benefit Analysis for Marine Sensor Network Design |
title_short | Relocatable, Automated Cost-Benefit Analysis for Marine Sensor Network Design |
title_sort | relocatable, automated cost-benefit analysis for marine sensor network design |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3376612/ https://www.ncbi.nlm.nih.gov/pubmed/22736982 http://dx.doi.org/10.3390/s120302874 |
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