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A Calibration-Free Crowdsourcing-Based Indoor Localization Solution

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Advances in Services Computing (APSCC 2016)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 10065))

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Abstract

Researches on crowdsourcing-based localization systems have been attracting much attention. It is a main problem that device diversity and short-duration signal strength measurement significantly degrade the localization accuracy in crowdsourcing-based systems. In this paper, we analyze underlying relationships between detected wireless Access Points (AP) and received signal strength (RSS), which are relatively invariable over devices and measurement times. Then we present a novel solution which uses these underlying relationships as key values for location determination. We use the first publicly available database in this field to evaluate this solution. The experimental results confirm that this solution provides high success rate and acceptable localization accuracy.

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Correspondence to Ying Wu .

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Yin, J., Wu, Y., Zhang, X., Lu, M. (2016). A Calibration-Free Crowdsourcing-Based Indoor Localization Solution. In: Wang, G., Han, Y., Martínez Pérez, G. (eds) Advances in Services Computing. APSCC 2016. Lecture Notes in Computer Science(), vol 10065. Springer, Cham. https://doi.org/10.1007/978-3-319-49178-3_5

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  • DOI: https://doi.org/10.1007/978-3-319-49178-3_5

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-49177-6

  • Online ISBN: 978-3-319-49178-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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