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A Tagless Indoor Localization System Based on Capacitive Sensing Technology
Accurate indoor person localization is essential for several services, such as assisted living. We introduce a tagless indoor person localization system based on capacitive sensing and localization algorithms that can determine the location with less than 0.2 m average error in a 3 m × 3 m room and...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2016
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5038726/ https://www.ncbi.nlm.nih.gov/pubmed/27618049 http://dx.doi.org/10.3390/s16091448 |
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author | Ramezani Akhmareh, Alireza Lazarescu, Mihai Teodor Bin Tariq, Osama Lavagno, Luciano |
author_facet | Ramezani Akhmareh, Alireza Lazarescu, Mihai Teodor Bin Tariq, Osama Lavagno, Luciano |
author_sort | Ramezani Akhmareh, Alireza |
collection | PubMed |
description | Accurate indoor person localization is essential for several services, such as assisted living. We introduce a tagless indoor person localization system based on capacitive sensing and localization algorithms that can determine the location with less than 0.2 m average error in a 3 m × 3 m room and has recall and precision better than 70%. We also discuss the effects of various noise types on the measurements and ways to reduce them using filters suitable for on-sensor implementation to lower communication energy consumption. We also compare the performance of several standard localization algorithms in terms of localization error, recall, precision, and accuracy of detection of the movement trajectory. |
format | Online Article Text |
id | pubmed-5038726 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-50387262016-09-29 A Tagless Indoor Localization System Based on Capacitive Sensing Technology Ramezani Akhmareh, Alireza Lazarescu, Mihai Teodor Bin Tariq, Osama Lavagno, Luciano Sensors (Basel) Article Accurate indoor person localization is essential for several services, such as assisted living. We introduce a tagless indoor person localization system based on capacitive sensing and localization algorithms that can determine the location with less than 0.2 m average error in a 3 m × 3 m room and has recall and precision better than 70%. We also discuss the effects of various noise types on the measurements and ways to reduce them using filters suitable for on-sensor implementation to lower communication energy consumption. We also compare the performance of several standard localization algorithms in terms of localization error, recall, precision, and accuracy of detection of the movement trajectory. MDPI 2016-09-07 /pmc/articles/PMC5038726/ /pubmed/27618049 http://dx.doi.org/10.3390/s16091448 Text en © 2016 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 (CC-BY) license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Ramezani Akhmareh, Alireza Lazarescu, Mihai Teodor Bin Tariq, Osama Lavagno, Luciano A Tagless Indoor Localization System Based on Capacitive Sensing Technology |
title | A Tagless Indoor Localization System Based on Capacitive Sensing Technology |
title_full | A Tagless Indoor Localization System Based on Capacitive Sensing Technology |
title_fullStr | A Tagless Indoor Localization System Based on Capacitive Sensing Technology |
title_full_unstemmed | A Tagless Indoor Localization System Based on Capacitive Sensing Technology |
title_short | A Tagless Indoor Localization System Based on Capacitive Sensing Technology |
title_sort | tagless indoor localization system based on capacitive sensing technology |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5038726/ https://www.ncbi.nlm.nih.gov/pubmed/27618049 http://dx.doi.org/10.3390/s16091448 |
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