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RSSI Fingerprinting Techniques for Indoor Localization Datasets

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Internet of Things, Infrastructures and Mobile Applications (IMCL 2019)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1192))

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Abstract

Indoor localization techniques using Received Signal Strength Indicator (RSSI) is attractive in the Internet of Things domain due to its simplicity and cost-effectiveness. However, there are many different approaches proposed in and there is not a common, widely acceptable solution in the research community. This is mainly due to the limited number of publicly available datasets and that the multi-effect signal phenomenon limits each dataset to its gathering testbed. In this paper, we tested several fingerprinting methods in a publicly available dataset and we compared them against the RSSI regression approach, which is considered as the most prominent one in certain domains, such as indoor and outdoor localization.

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Notes

  1. 1.

    http://desmos-project.gr/en/datasets-2.

  2. 2.

    http://desmos-project.gr/en/homepage-en.

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Acknowledgement

This research has been co-financed by the European Union and Greek national funds through the Operational Program Competitiveness, Entrepreneurship and Innovation, under the call RESEARCH-CREATE-INNOVATE (project code: T1EDK-03487).

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Authors and Affiliations

  1. Information Technologies Institute, Center for Research and Technology Hellas, 6th km Charilaou-Thermi Road, Thessaloniki, Greece

    Angelos Chatzimichail, Athina Tsanousa, Georgios Meditskos, Stefanos Vrochidis & Ioannis Kompatsiaris

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  1. Angelos Chatzimichail
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  2. Athina Tsanousa
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  3. Georgios Meditskos
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  4. Stefanos Vrochidis
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  5. Ioannis Kompatsiaris
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Corresponding author

Correspondence to Angelos Chatzimichail .

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Editors and Affiliations

  1. Carinthia University of Applied Sciences, Villach, Austria

    Michael E. Auer

  2. Department of Informatics, Aristotle University of Thessaloniki, Thessaloniki, Greece

    Thrasyvoulos Tsiatsos

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Chatzimichail, A., Tsanousa, A., Meditskos, G., Vrochidis, S., Kompatsiaris, I. (2021). RSSI Fingerprinting Techniques for Indoor Localization Datasets. In: Auer, M.E., Tsiatsos, T. (eds) Internet of Things, Infrastructures and Mobile Applications. IMCL 2019. Advances in Intelligent Systems and Computing, vol 1192. Springer, Cham. https://doi.org/10.1007/978-3-030-49932-7_45

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  • DOI: https://doi.org/10.1007/978-3-030-49932-7_45

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