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Big-Data framework-based visualization solution for performance analysis of positioning systems in railway environments

Authors: Zheng Liu; Iñigo Adin; Saioa Arrizabalaga; Jon Goya; Javier Añorga; Sijia Yang;

Big-Data framework-based visualization solution for performance analysis of positioning systems in railway environments

Abstract

The on-board positioning system provides not only the location estimation but also additional information about the certainty or quality of the provided estimation. Additionally, when developing the positioning system itself and evaluating the performance of the system, it is useful to thoroughly analyze the input parameter values used by the positioning system for each of the location estimates. A visualization platform based on Big-Data frameworks was highly demanded in this context and several alternatives were analyzed. This paper describes the approaches that have been tested and implemented, describes the difficulties and advantages of the alternatives and provides detailed steps for adapting the open-source Big-Data framework-based solutions to other application areas.

Keywords

Big Data, Positioning, GNSS, multisensorial, visualization, dashboard application, ELK stack

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selected citations
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This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
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