dc.creator | Salazar González, Jose Luis | es |
dc.creator | Soria Morillo, Luis Miguel | es |
dc.creator | Álvarez García, Juan Antonio | es |
dc.creator | Enríquez de Salamanca Ros, Fernando | es |
dc.creator | Jiménez Ruíz, Antonio R. | es |
dc.date.accessioned | 2021-09-08T10:53:14Z | |
dc.date.available | 2021-09-08T10:53:14Z | |
dc.date.issued | 2019 | |
dc.identifier.citation | Salazar González, J.L., Soria Morillo, L.M., Álvarez García, J.A., Enríquez de Salamanca Ros, F. y Jiménez Ruíz, A.R. (2019). Energy-Efficient Indoor Localization WiFi-Fingerprint System: An Experimental Study. IEEE Access, 7, 162664-162682. | |
dc.identifier.issn | 2169-3536 | es |
dc.identifier.uri | https://hdl.handle.net/11441/125569 | |
dc.description.abstract | In order to apply indoor localization systems in real environments it is necessary to provide an
accurate location without implying a high impact on the user's normal behaviour. To achieve this goal, in this
paper, a combination of battery saving techniques with a system based on WiFi ngerprinting is proposed.
This is done by transferring the location calculation workload to the server, leaving user's mobile devices
the only responsibility of making periodic WiFi network scans at dynamic intervals based on user activity,
through an application running on background. There are not many studies analyzing energy consumption
of existing localization systems, even though it is an important factor in real applications. In this paper, both
energy consumption and accuracy are analyzed, having an energy consumption of only 0.8 Wh (having a
3.7 V battery) during a 24-hour cycle and an average localization error of 4.51 meters. Worth to mention
that as computation is done on server side the system can be expanded to multiple buildings and oors.
Finally, the dataset used in this paper has been published making possible to test new algorithms in the same
environment. | es |
dc.description.sponsorship | Ministerio de Economía y Competitividad TIN2017-82113-C2-1-R | es |
dc.description.sponsorship | Ministerio de Ciencia, Innovación y Universidades RTI2018-095168-B-C55 | es |
dc.format | application/pdf | es |
dc.format.extent | 18 | es |
dc.language.iso | eng | es |
dc.publisher | IEEE Computer Society | es |
dc.relation.ispartof | IEEE Access, 7, 162664-162682. | |
dc.rights | Attribution-NonCommercial-NoDerivatives 4.0 Internacional | * |
dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/4.0/ | * |
dc.subject | Indoor localization | es |
dc.subject | WiFi ngerprinting | es |
dc.subject | RSSI | es |
dc.subject | battery life | es |
dc.subject | KNN | es |
dc.subject | naive Bayes | es |
dc.subject | dataset | es |
dc.title | Energy-Efficient Indoor Localization WiFi-Fingerprint System: An Experimental Study | es |
dc.type | info:eu-repo/semantics/article | es |
dcterms.identifier | https://ror.org/03yxnpp24 | |
dc.type.version | info:eu-repo/semantics/publishedVersion | es |
dc.rights.accessRights | info:eu-repo/semantics/openAccess | es |
dc.contributor.affiliation | Universidad de Sevilla. Departamento de Lenguajes y Sistemas Informáticos | es |
dc.relation.projectID | TIN2017-82113-C2-1-R | es |
dc.relation.projectID | RTI2018-095168-B-C55 | es |
dc.relation.publisherversion | https://ieeexplore.ieee.org/document/8894078 | es |
dc.identifier.doi | 10.1109/ACCESS.2019.2952221 | es |
dc.contributor.group | Universidad de Sevilla. TIC134: Sistemas Informáticos | es |
dc.journaltitle | IEEE Access | es |
dc.publication.volumen | 7 | es |
dc.publication.initialPage | 162664 | es |
dc.publication.endPage | 162682 | es |
dc.contributor.funder | Ministerio de Economía y Competitividad (MINECO). España | es |
dc.contributor.funder | Ministerio de Ciencia, Innovación y Universidades (MICINN). España | es |