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dc.contributor.authorGeorgiou, K.en
dc.contributor.authorConstambeys, T.en
dc.contributor.authorLaoudias, Christosen
dc.contributor.authorPetrou, L.en
dc.contributor.authorChatzimilioudis, Georgiosen
dc.contributor.authorZeinalipour-Yazdi, Constantinos D.en
dc.creatorGeorgiou, K.en
dc.creatorConstambeys, T.en
dc.creatorLaoudias, Christosen
dc.creatorPetrou, L.en
dc.creatorChatzimilioudis, Georgiosen
dc.creatorZeinalipour-Yazdi, Constantinos D.en
dc.description.abstractPeople do most of their activities, business, commerce, entertainment and socializing indoors. As all of these are increasingly aided by online services and indoor spaces are becoming bigger and more complex, there is a growing need for cost-effective indoor localization, mapping, navigation and information services. In this paper, we present a complete Indoor Information Service, coined Anyplace, which has an open, modular, extensible and scalable architecture, making it ideal for a wide range of applications. Our service features three highly desirable properties, namely crowd sourcing, scalability and accuracy. Anyplace implements a set of crowd sourcing-supportive mechanisms to handle the enormous amount of crowd-sensed data, filter incorrect user contributions and exploit Wi-Fi data from heterogeneous mobile devices. Moreover, it uses a big-data architecture for efficient storage and retrieval of localization and mapping data. Finally, our service relies on the abundance of sensory data on smartphones (e.g., Wi-Fi signal strength and inertial measurements) to deliver reliable indoor geolocation information that received several international awards. © 2015 IEEE.en
dc.publisherInstitute of Electrical and Electronics Engineers Inc.en
dc.sourceProceedings - IEEE International Conference on Mobile Data Managementen
dc.source16th IEEE International Conference on Mobile Data Management, MDM 2015en
dc.subjectInformation servicesen
dc.subjectCost effectivenessen
dc.subjectDigital storageen
dc.subjectInformation managementen
dc.subjectMobile devicesen
dc.subjectBig dataen
dc.subjectHeterogeneous mobile devicesen
dc.subjectIndoor positioning systemsen
dc.subjectInertial measurementsen
dc.subjectInternational awardsen
dc.subjectLocalization and mappingsen
dc.subjectScalable architecturesen
dc.subjectStorage and retrievalsen
dc.titleAnyplace: A Crowdsourced Indoor Information Serviceen
dc.description.endingpage294 Σχολή Θετικών και Εφαρμοσμένων Επιστημών / Faculty of Pure and Applied SciencesΤμήμα Πληροφορικής / Department of Computer Science
dc.type.uhtypeConference Objecten
dc.description.notes<p>Sponsors: Aalborg Universityen
dc.description.noteset al.en
dc.description.notesIEEE Computer Societyen
dc.description.notesIEEE Technical Committee on Data Engineeringen
dc.description.notesThe National Science Foundationen
dc.description.notesUniversity of Pittsburghen
dc.description.notesConference code: 118117en
dc.description.notesCited By :5</p>en
dc.contributor.orcidZeinalipour-Yazdi, Constantinos D. [0000-0002-8388-1549]
dc.contributor.orcidLaoudias, Christos [0000-0002-2907-7488]

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