TRIPS: A System for Translating Raw Indoor Positioning Data into Visual Mobility Semantics

Huan Li, Hua Lu, Feichao Shi, Gang Chen, Ke Chen, Lidan Shou

Publikation: Bidrag til tidsskriftKonferenceartikel i tidsskriftForskningpeer review

3 Citationer (Scopus)
135 Downloads (Pure)

Abstrakt

The rapid accumulation of indoor positioning data is increasingly booming the interest in indoor mobility analyses. As a fundamental analysis, it is highly relevant to translate raw indoor positioning data into mobility semantics that describe what, where and when in a more concise and semantics-oriented way. Such a translation is challenging as multiple data sources are involved, raw indoor positioning data is of low quality, and translation results are hard to assess. We demonstrate a system TRIPS that streamlines the entire translation process by three functional components. The Configurator provides a standard but concise means to configure multiple input sources, including the indoor positioning data, indoor space information, and relevant contexts. The Translator cleans the indoor positioning data and exports reliable mobility semantics without manual interventions. The Viewer offers a suite of flexible operations to trace the input, output and intermediate data involved in the translation. Data analysts can interact with TRIPS to obtain the desired mobility semantics in a visual and convenient way.
OriginalsprogEngelsk
TidsskriftProceedings of the VLDB Endowment
Vol/bind11
Udgave nummer12
Sider (fra-til)1918-1921
ISSN2150-8097
DOI
StatusUdgivet - 2018
Begivenhed44th International Conference on Very Large Data Bases, VLDB 2018 - Rio de Janeiro, Brasilien
Varighed: 27 aug. 201731 aug. 2017

Konference

Konference44th International Conference on Very Large Data Bases, VLDB 2018
Land/OmrådeBrasilien
ByRio de Janeiro
Periode27/08/201731/08/2017

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