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On the Use of Perfect Sequences and Genetic Algorithms for Estimating the Indoor Location of Wireless Sensors

2015-04Journal article Open access
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datacite.subject.fosEngenharia e Tecnologia
datacite.subject.sdg09:Indústria, Inovação e Infraestruturas
dc.contributor.authorFerreira, Marco
dc.contributor.authorBagarić, J.
dc.contributor.authorLanza-Gutierrez, Jose M.
dc.contributor.authorMendes, Silvio
dc.contributor.authorPereira, João
dc.contributor.authorGomez-Pulido, Juan A.
dc.date.accessioned2025-12-15T09:23:32Z
dc.date.available2025-12-15T09:23:32Z
dc.date.issued2015-04
dc.descriptionArticle number - 720574
dc.description.abstractDetermining the indoor location is usually performed by using several sensors. Some of these sensors are fixed to a known location and either transmit or receive information that allows other sensors to estimate their own locations. The estimation of the location can use information such as the time-of-arrival of the transmitted signals, or the received signal strength, among others. Major problems of indoor location include the interferences caused by the many obstacles in such cases, causing among others the signal multipath problem and the variation of the signal strength due to the many transmission media in the path from the emitter to the receiver. In this paper, the creation and usage of perfect sequences that eliminate the signal multipath problem are presented. It also shows the influence of the positioning of the fixed sensors to the precision of the location estimation. Finally, genetic algorithms were used for searching the optimal location of these fixed sensors, therefore minimizing the location estimation error.eng
dc.description.sponsorshipFunding text This work was partially funded within the framework of the FCT/MEC (Fundação para a Ciência e a Tecnologia/Min-istério da Educação e Ciência) Project, entitled “Low-cost Indoor Positioning System (Linposys),” nationally funded by the Program PEst-OE/EEI/LA008/2013 of IT (Instituto de Telecomunicações).
dc.identifier.citationFerreira M, Bagarić J, Lanza-Gutierrez JM, Priem-Mendes S, Pereira JS, Gomez-Pulido JA. On the Use of Perfect Sequences and Genetic Algorithms for Estimating the Indoor Location of Wireless Sensors. International Journal of Distributed Sensor Networks. 2015;11(4). doi:10.1155/2015/720574
dc.identifier.doi10.1155/2015/720574
dc.identifier.issn1550-1477
dc.identifier.issn1550-1329
dc.identifier.urihttp://hdl.handle.net/10400.8/15034
dc.language.isoeng
dc.peerreviewedyes
dc.publisherSAGE Publications
dc.relation.hasversionhttps://journals.sagepub.com/doi/10.1155/2015/720574
dc.relation.ispartofInternational Journal of Distributed Sensor Networks
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/
dc.subjectIndoor locations
dc.subjectLocation estimation
dc.subjectOptimal locations
dc.subjectPerfect sequence
dc.subjectReceived signal strength
dc.subjectSignal strengths
dc.subjectTransmission media
dc.subjectTransmitted signal
dc.titleOn the Use of Perfect Sequences and Genetic Algorithms for Estimating the Indoor Location of Wireless Sensorseng
dc.typejournal article
dspace.entity.typePublication
oaire.citation.endPage12
oaire.citation.issue4
oaire.citation.startPage1
oaire.citation.titleInternational Journal of Distributed Sensor Networks
oaire.citation.volume11
oaire.versionhttp://purl.org/coar/version/c_970fb48d4fbd8a85
person.familyNameFerreira
person.familyNameLanza-Gutierrez
person.familyNameMendes
person.familyNamePereira
person.givenNameMarco
person.givenNameJose M.
person.givenNameSilvio
person.givenNameJoão
person.identifier.ciencia-id1513-13E9-C8A6
person.identifier.ciencia-idBD1E-268C-60A0
person.identifier.orcid0000-0003-2397-1697
person.identifier.orcid0000-0002-1083-5015
person.identifier.orcid0000-0002-1667-5745
person.identifier.orcid0000-0002-4303-2876
person.identifier.scopus-author-id56269586400
relation.isAuthorOfPublication190a3de4-9c64-461d-9d44-08b5f3eabf17
relation.isAuthorOfPublicationea664ff6-edc3-4da6-9b94-91d305492138
relation.isAuthorOfPublicatione23cc83a-4e70-4088-a73d-075808bda28f
relation.isAuthorOfPublicationd236a326-78d1-4be7-afca-0adcdcc4d4ae
relation.isAuthorOfPublication.latestForDiscoveryea664ff6-edc3-4da6-9b94-91d305492138

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