ACCES: Offline Accuracy Estimation for Fingerprint-Based Localization

Artyom Nikitin, Christos Laoudias, Georgios Chatzimilioudis, Panagiotis Karras, Demetrios Zeinalipour-Yazti

Research output: Contribution to book/anthology/report/conference proceedingArticle in proceedingResearchpeer-review

1 Citation (Scopus)
301 Downloads (Pure)

Abstract

In this demonstration we present ACCES, a novel framework that enables quality assessment of arbitrary fingerprint maps and offline accuracy estimation for the task of fingerprint-based indoor localization. Our framework considers collected fingerprints disregarding the physical origin of the data. First, it applies a widely used statistical instrument, namely Gaussian Process Regression (GPR), for interpolation of the fingerprints. Then, to estimate the best possibly achievable localization accuracy at any location, it utilizes the Cramer-Rao Lower Bound (CRLB) with interpolated data as an input. Our demonstration entails a standalone version of the popular and open-source Anyplace Internet-based indoor navigation service in which the software modules of ACCES are integrated. At the conference, we will present the utility of our method in two modes: (i) Collection Mode, where attendees will be able to use our service directly to collect signal measurements over the venue using an Android smartphone; and (ii) Reflection Mode, where attendees will be able to observe the collected measurements and the respective ACCES accuracy estimations in the form of an overlay heatmap.
Original languageEnglish
Title of host publication18th IEEE International Conference on Mobile Data Management (MDM)
Number of pages2
PublisherIEEE
Publication date30 May 2017
Pages358-359
ISBN (Electronic)978-1-5386-3932-0
DOIs
Publication statusPublished - 30 May 2017
Event18th IEEE International Conference on Mobile Data Management - KAIST, Daejeon, Korea, Republic of
Duration: 29 May 20171 Jun 2017
Conference number: 18
http://mdmconferences.org/mdm2017/

Conference

Conference18th IEEE International Conference on Mobile Data Management
Number18
LocationKAIST
CountryKorea, Republic of
CityDaejeon
Period29/05/201701/06/2017
Internet address
SeriesIEEE International Conference on Mobile Data Management (MDM)
ISSN2375-0324

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