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Demonstration abstract: Crowdsourced indoor localization and navigation with Anyplace

dc.contributor.authorPetrou, L.en
dc.contributor.authorLarkou, G.en
dc.contributor.authorLaoudias, Christosen
dc.contributor.authorZeinalipour-Yazdi, Constantinos D.en
dc.contributor.authorPanayiotou, Christos G.en
dc.creatorPetrou, L.en
dc.creatorLarkou, G.en
dc.creatorLaoudias, Christosen
dc.creatorZeinalipour-Yazdi, Constantinos D.en
dc.creatorPanayiotou, Christos G.en
dc.date.accessioned2019-11-13T10:41:58Z
dc.date.available2019-11-13T10:41:58Z
dc.date.issued2014
dc.identifier.isbn978-1-4799-3146-0
dc.identifier.urihttp://gnosis.library.ucy.ac.cy/handle/7/54830
dc.description.abstractIn this demonstration paper, we present the Anyplace system that relies on the abundance of sensory data on smartphones (e.g., WiFi signal strength and inertial measurements) to deliver reliable indoor geolocation information. Our system features two highly desirable properties, namely crowdsourcing and scalability. Anyplace implements a set of crowdsourcing-supportive mechanisms to handle the enormous amount of crowdsensed data, filter incorrect user contributions and exploit WiFi data from heterogeneous mobile devices. Moreover, Anyplace follows a big-data architecture for efficient and scalable storage and retrieval of localization and mapping data. © 2014 IEEE.en
dc.publisherIEEE Computer Societyen
dc.sourceIPSN 2014 - Proceedings of the 13th International Symposium on Information Processing in Sensor Networks (Part of CPS Week)en
dc.source13th IEEE/ACM International Conference on Information Processing in Sensor Networks, IPSN 2014en
dc.source.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-84904627358&doi=10.1109%2fIPSN.2014.6846788&partnerID=40&md5=285f9484ba584fedf91448b2a0e0c016
dc.subjectSensor networksen
dc.subjectData processingen
dc.subjectDigital storageen
dc.subjectMobile devicesen
dc.subjectCrowdsourcingen
dc.subjectHeterogeneous mobile devicesen
dc.subjectInertial measurementsen
dc.subjectLocalization and mappingsen
dc.subjectnavigationen
dc.subjectIndoor geolocationen
dc.subjectindoor localizationen
dc.subjectIndoor localization and navigationsen
dc.subjectWifi signal strengthsen
dc.titleDemonstration abstract: Crowdsourced indoor localization and navigation with Anyplaceen
dc.typeinfo:eu-repo/semantics/conferenceObject
dc.identifier.doi10.1109/IPSN.2014.6846788
dc.description.startingpage331
dc.description.endingpage332
dc.author.faculty002 Σχολή Θετικών και Εφαρμοσμένων Επιστημών / Faculty of Pure and Applied Sciences
dc.author.departmentΤμήμα Πληροφορικής / Department of Computer Science
dc.type.uhtypeConference Objecten
dc.description.notes<p>Sponsors: ACM SIGBEDen
dc.description.notesIEEE Computer Societyen
dc.description.notesConference code: 106452en
dc.description.notesCited By :7</p>en
dc.contributor.orcidPanayiotou, Christos G. [0000-0002-6476-9025]
dc.contributor.orcidZeinalipour-Yazdi, Constantinos D. [0000-0002-8388-1549]
dc.contributor.orcidLaoudias, Christos [0000-0002-2907-7488]
dc.gnosis.orcid0000-0002-6476-9025|0000-0002-8388-1549
dc.gnosis.orcid0000-0002-2907-7488


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