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International Symposium on Ambient Intelligence

ISAmI 2016: Ambient Intelligence- Software and Applications – 7th International Symposium on Ambient Intelligence (ISAmI 2016) pp 161–166Cite as

Preliminary Study of Classifier Fusion Based Indoor Positioning Method

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Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 476))

Abstract

Indoor positioning technology is commercially available now, however, the positioning accuracy is not sufficient in the current technologies. Currently available indoor positioning technologies differ in terms of accuracy, costs and effort, but have improved quickly in the last couple of years. It has been actively conducted research for estimating indoor location using RSSI (Received Signal Strength Indicator) level of Wi-Fi access points or BLE (Bluetooth Low Energy) tags. WiFi signal is commonly used for the indoor positioning technology. However, It requires an external power source, more setup costs and expensive. BLE is inexpensive, small, have a long battery life and do not require an external energy source. Therefore, by adding some BLE tags we might be able to enhance the accuracy inexpensive way. In this paper, we propose a new type of indoor positioning method based on WiFi-BLE fusion with Fingerprinting method. WiFi RSSI and BLE RSSI are separately processed each one by a Naive Bayes Classifier. Then, Multilayer Perceptron(MLP) is used as the fusion classifier. Preliminary experimental result shows 2.55m error in case of the MLP output. Since the result is not as good as the ones using conventional method, further test and investigation needs to be performed.

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Author information

Authors and Affiliations

  1. Department of Engineering, Osaka Institute of Technology, 5-16-1 Omiya, Asahi Ward, Osaka, 535-0002, Japan

    Yuki Miyashita & Kenji Matsui

  2. Department of Information Science and Technology, Osaka Institute of Technology, 1-79-1 Kitayama, Hirakata City, Osaka, 573-0196, Japan

    Mahiro Oura

  3. BISITE Research Group, University of Salamanca, Edificio I+D+I, 37008, Salamanca, Spain

    Juan F. De Paz, Gabriel Villarrubia & Juan M. Corchado

Authors
  1. Yuki Miyashita
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  2. Mahiro Oura
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  3. Juan F. De Paz
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  4. Kenji Matsui
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  5. Gabriel Villarrubia
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  6. Juan M. Corchado
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Corresponding author

Correspondence to Yuki Miyashita .

Editor information

Editors and Affiliations

  1. Plan 4 MIT-huset C435, University of Umea, Umea, Sweden

    Helena Lindgren

  2. Dept de Info y Automática, Universidad de Salamanca, Salamanca, Spain

    Juan F. De Paz

  3. Department of Informatics, Universidade do Minho, Braga, Portugal

    Paulo Novais

  4. Departamento de Sistemas Informáticos, University of Castilla-La Mancha, Albacete, Spain

    Antonio Fernández-Caballero

  5. Dept. of Information and Communication, Sunchon National University, 540-742, Korea (Republic of)

    Hyun Yoe

  6. ETS Ingeniería Informática, University of Sevilla, Sevilla, Spain

    Andres Jiménez Ramírez

  7. Departamento de Informática y Automática, Universidad de Salamanca, Salamanca, Spain

    Gabriel Villarrubia

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© 2016 Springer International Publishing Switzerland

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Miyashita, Y., Oura, M., De Paz, J.F., Matsui, K., Villarrubia, G., Corchado, J.M. (2016). Preliminary Study of Classifier Fusion Based Indoor Positioning Method. In: Lindgren, H., et al. Ambient Intelligence- Software and Applications – 7th International Symposium on Ambient Intelligence (ISAmI 2016). ISAmI 2016. Advances in Intelligent Systems and Computing, vol 476. Springer, Cham. https://doi.org/10.1007/978-3-319-40114-0_18

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  • DOI: https://doi.org/10.1007/978-3-319-40114-0_18

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-40113-3

  • Online ISBN: 978-3-319-40114-0

  • eBook Packages: EngineeringEngineering (R0)

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