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Mobile Sensing Systems
Rich-sensor smart phones have made possible the recent birth of the mobile sensing research area as part of ubiquitous sensing which integrates other areas such as wireless sensor networks and web sensing. There are several types of mobile sensing: individual, participatory, opportunistic, crowd, so...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Molecular Diversity Preservation International (MDPI)
2013
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3892889/ https://www.ncbi.nlm.nih.gov/pubmed/24351637 http://dx.doi.org/10.3390/s131217292 |
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author | Macias, Elsa Suarez, Alvaro Lloret, Jaime |
author_facet | Macias, Elsa Suarez, Alvaro Lloret, Jaime |
author_sort | Macias, Elsa |
collection | PubMed |
description | Rich-sensor smart phones have made possible the recent birth of the mobile sensing research area as part of ubiquitous sensing which integrates other areas such as wireless sensor networks and web sensing. There are several types of mobile sensing: individual, participatory, opportunistic, crowd, social, etc. The object of sensing can be people-centered or environment-centered. The sensing domain can be home, urban, vehicular… Currently there are barriers that limit the social acceptance of mobile sensing systems. Examples of social barriers are privacy concerns, restrictive laws in some countries and the absence of economic incentives that might encourage people to participate in a sensing campaign. Several technical barriers are phone energy savings and the variety of sensors and software for their management. Some existing surveys partially tackle the topic of mobile sensing systems. Published papers theoretically or partially solve the above barriers. We complete the above surveys with new works, review the barriers of mobile sensing systems and propose some ideas for efficiently implementing sensing, fusion, learning, security, privacy and energy saving for any type of mobile sensing system, and propose several realistic research challenges. The main objective is to reduce the learning curve in mobile sensing systems where the complexity is very high. |
format | Online Article Text |
id | pubmed-3892889 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2013 |
publisher | Molecular Diversity Preservation International (MDPI) |
record_format | MEDLINE/PubMed |
spelling | pubmed-38928892014-01-16 Mobile Sensing Systems Macias, Elsa Suarez, Alvaro Lloret, Jaime Sensors (Basel) Review Rich-sensor smart phones have made possible the recent birth of the mobile sensing research area as part of ubiquitous sensing which integrates other areas such as wireless sensor networks and web sensing. There are several types of mobile sensing: individual, participatory, opportunistic, crowd, social, etc. The object of sensing can be people-centered or environment-centered. The sensing domain can be home, urban, vehicular… Currently there are barriers that limit the social acceptance of mobile sensing systems. Examples of social barriers are privacy concerns, restrictive laws in some countries and the absence of economic incentives that might encourage people to participate in a sensing campaign. Several technical barriers are phone energy savings and the variety of sensors and software for their management. Some existing surveys partially tackle the topic of mobile sensing systems. Published papers theoretically or partially solve the above barriers. We complete the above surveys with new works, review the barriers of mobile sensing systems and propose some ideas for efficiently implementing sensing, fusion, learning, security, privacy and energy saving for any type of mobile sensing system, and propose several realistic research challenges. The main objective is to reduce the learning curve in mobile sensing systems where the complexity is very high. Molecular Diversity Preservation International (MDPI) 2013-12-16 /pmc/articles/PMC3892889/ /pubmed/24351637 http://dx.doi.org/10.3390/s131217292 Text en © 2013 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 | Review Macias, Elsa Suarez, Alvaro Lloret, Jaime Mobile Sensing Systems |
title | Mobile Sensing Systems |
title_full | Mobile Sensing Systems |
title_fullStr | Mobile Sensing Systems |
title_full_unstemmed | Mobile Sensing Systems |
title_short | Mobile Sensing Systems |
title_sort | mobile sensing systems |
topic | Review |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3892889/ https://www.ncbi.nlm.nih.gov/pubmed/24351637 http://dx.doi.org/10.3390/s131217292 |
work_keys_str_mv | AT maciaselsa mobilesensingsystems AT suarezalvaro mobilesensingsystems AT lloretjaime mobilesensingsystems |