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Using iBeacon Technology with Nearest Neighbor Algorithm to Area Positioning Systems

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Mobile Internet Security (MobiSec 2017)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 971))

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Abstract

With the advances in information and communication technologies, indoor Location Based Service (LBS) has been a hot topic of research. In a wireless positioning system, signals would be distorted and attenuated by the environment during the signal transmission. In the case, the distorted signals would degrade positioning accuracy. In order to reduce positioning errors due to bad signals, this paper uses a pattern matching approach to build environmental model. This method can reduce positioning error due to the unstable signals. We used iBeacon to build positioning environment in Wireless Sensor Networks. The K Nearest Neighbor (KNN) algorithm is used to compare the accuracy of area positioning with various environments.

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References

  1. Chen, L.H., Wu, E.H.K., Jin, M.H., Chen, G.H.: Intelligent fusion of Wi-Fi and inertial sensor-based positioning systems for indoor pedestrian navigation. IEEE Sens. J. 14(11), 4034–4042 (2014)

    Article  Google Scholar 

  2. Fang, M., Li, L., Huang, W.: Research of hybrid positioning based vehicle interactive navigation system. In: MINES, pp. 478–485 (2010)

    Google Scholar 

  3. Apple, iOS: Understanding iBeacon. https://support.apple.com/en-gb/HT202880. Accessed 5 Aug 2017

  4. Zafari, F., Papapanagiotou, I.K., Devetsikiotis, M., Hacker, T.J.: An iBeacon based Proximity and Indoor Localization System. Computing Research Repository, pp. 1–14 (2017)

    Google Scholar 

  5. Apple iBeacons Explained: Smart Home Occupancy Sensing Solved? http://www.automatedhome.co.uk/apple/apple-ibeacons-explained-smart-home-occupancy-sensing-solved.html. Accessed 3 Oct 2013

  6. Guowei, Z., Zhan, X., Dan, L.: Research and improvement on indoor localization based on RSSI fingerprint database and K-Nearest neighbor points. In: ICCCAS, pp. 68–71 (2013)

    Google Scholar 

  7. Hossain, S., Ariffin, S.H.S., Fisal, N., Neng, C.K., Hassan N.S.A., Latiff, L.A.: Accuracy enhancement of fingerprint indoor positioning system. In: ISMS, pp. 600–605 (2012)

    Google Scholar 

  8. Altman, N.S.: An introduction to kernel and nearest-neighbor nonparametric regression. Am. Stat. 46(3), 175–185 (1992)

    MathSciNet  Google Scholar 

  9. Duda, R.O., Hart, P.E., Stork, D.G.: Pattern classification, 2nd edn. Wiley, NY (2000)

    MATH  Google Scholar 

  10. Bahl, P., Padmanabhan, V.N.: RADAR: An in-building RF-based user location and tracking system. IEEE INFOCOM 2, 775–784 (2000)

    Google Scholar 

  11. Cheng, C.H., Hu C.Y., Wang, T.P., Wu, F.C.: Using iBeacon technology with a back propagation neural network to positioning systems. In: MobiSec, pp. 1–9 (2017)

    Google Scholar 

  12. Lin, S., Liu, J., Fang, Y.: ZigBee based wireless sensor networks and its applications in industrial. In: CASE, pp. 1979–1983 (2007)

    Google Scholar 

  13. Zhang, J., Song, G., Wang H., Meng, T.: Design of a wireless sensor network based monitoring system for home automation. In: ICFCSA, pp. 57–60 (2011)

    Google Scholar 

  14. What is iBeacon? A guide to iBeacon. http://www.ibeacon.com/what-is-ibeacon-a-guide-to-beacons. Accessed 20 Apr 2014

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Author information

Authors and Affiliations

  1. Department of Electrical Engineering, National Formosa University, Huwei, Taiwan

    Chia-Hsin Cheng & Chia-Yao Hu

Authors
  1. Chia-Hsin Cheng
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  2. Chia-Yao Hu
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Corresponding author

Correspondence to Chia-Hsin Cheng .

Editor information

Editors and Affiliations

  1. Department of Information Security Engineering, Soonchunhyang University, Choongchungnam-do, Korea (Republic of)

    Ilsun You

  2. Asian University Taiwan, Taichung, Taiwan

    Hsing-Chung Chen

  3. Department of Information Security, Soonchunhyang University, Seoul, Korea (Republic of)

    Vishal Sharma

  4. SPIIRAS, St. Petersburg, Russia

    Igor Kotenko

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© 2019 Springer Nature Singapore Pte Ltd.

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Cheng, CH., Hu, CY. (2019). Using iBeacon Technology with Nearest Neighbor Algorithm to Area Positioning Systems. In: You, I., Chen, HC., Sharma, V., Kotenko, I. (eds) Mobile Internet Security. MobiSec 2017. Communications in Computer and Information Science, vol 971. Springer, Singapore. https://doi.org/10.1007/978-981-13-3732-1_9

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  • DOI: https://doi.org/10.1007/978-981-13-3732-1_9

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-13-3731-4

  • Online ISBN: 978-981-13-3732-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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