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Energy Aware Object Localization in Wireless Sensor Network Based on Wi-Fi Fingerprinting

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Computer Networks (CN 2015)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 522))

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Abstract

The usage of GPS systems for indoor localization is limited, therefore multiple indirect localization techniques were proposed over the years. One of them is a localization method based on Wi-Fi (802.11) access point (AP) signal strength (RSSI) measurement. In this method, a RSSI map is constructed via Localization Fingerprinting (LF), which allows localizing object on the basis of a pattern similarity. The drawback of LF method is the need to create the RSSI map that is used as a training dataset. Therefore, in this study a Wireless Sensor Network (WSN) is used for this task. The introduced in this paper energy aware localization method allows to acquire the actual RSSI map or broadcast a localization signal, if there is not sufficient information to perform the localization by using nearby APs. To localize objects in a given cell, various classifiers were used and their localization accuracy was analyzed. Simulations were performed to compare the introduced solution with a state-of-the-art approach. The experimental results show that the proposed energy aware method extends the lifetime of WSN and improves the localization accuracy.

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Authors and Affiliations

  1. Institute of Computer Science, University of Silesia, Bedzinska 39, 41-200, Sosnowiec, Poland

    Marcin Bernas & Bartłomiej Płaczek

Authors
  1. Marcin Bernas
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  2. Bartłomiej Płaczek
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Corresponding author

Correspondence to Marcin Bernas .

Editor information

Editors and Affiliations

  1. Silesian University of Technology, Gliwice, Poland

    Piotr Gaj

  2. Silesian University of Technology, Gliwice, Poland

    Andrzej Kwiecień

  3. Silesian University of Technology, Gliwice, Poland

    Piotr Stera

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Bernas, M., Płaczek, B. (2015). Energy Aware Object Localization in Wireless Sensor Network Based on Wi-Fi Fingerprinting. In: Gaj, P., Kwiecień, A., Stera, P. (eds) Computer Networks. CN 2015. Communications in Computer and Information Science, vol 522. Springer, Cham. https://doi.org/10.1007/978-3-319-19419-6_4

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  • DOI: https://doi.org/10.1007/978-3-319-19419-6_4

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-19418-9

  • Online ISBN: 978-3-319-19419-6

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