A Novel for Light-Weighted Indoor Positioning Algorithm with Hybridizing Trilateration and Fingerprinting Method Considering Bluetooth Low Energy Environment

  • Jaeho Lee
  • Bong-Ki SonEmail author
Conference paper
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 474)


IPS (Indoor Positioning System) has been considered as one of mostly challengeable technical issues at the focus of accuracy and differentiation even though it has been researched long times ago, and many of researches found that fingerprinting approach can show better accuracy comparing with previous trilateration-based schemes. However, regarding huge indoor place, there can be significant calculation problem issue due to a lot of cells to be pre-surveyed radio map and the great number of location anchor point such as beacon device. Furthermore, this can aggregate life time of user handheld devices which would be generally tiny shape and insufficient energy resource. In this paper, we present a new scheme which was researched with a unique goal for improving calculational computing power, with hibridizing traditional trilateration and recently issued fingerprinting approaches under the Bluetooth low energy environment. In addition, we also present experiment results with analytical evaluations to prove the performance of proposed scheme.


Indoor positioning system Bluetooth low energy  Fingerprinting Localization Trilateration 


  1. 1.
    Oh, J.: 3D indoor positioning system based on smartphone. J. Korea Inf. Commun. Soc. (KICS) 38C(12), 1126–1133 (2013)Google Scholar
  2. 2.
    Hyun, N., Lim, I., Lee, J.: Location estimation method of positioning system utilizing the iBeacon. J. Korea Inst. Inf. Commun. Eng. 19(4), 925–932 (2015)CrossRefGoogle Scholar
  3. 3.
    Yoon, C., Hwang, C.: Efficient indoor positioning systems for indoor location-based service provider. J. Korea Inst. Inf. Commun. Eng. 19(6), 1368–1373 (2015)CrossRefGoogle Scholar
  4. 4.
    Palumbo, F., Barsocchi, P., Chessa, S.: A stigmergic approach to indoor localization using Bluetooth low energy beacons. In: IEEE International Conference, pp. 1–6, August 2015Google Scholar
  5. 5.
    Huh, J., Lee, C., Kim, J.: A study of beacon delivery characteristics in BLE based fingerprinting indoor positioning system. Korea Inf. Sci. Soc. 2015(6), 1612–1614 (2015)Google Scholar
  6. 6.
    Sung, K., Ryoo, J., Kim, H.: Design and implementation of location determination technology based on RSSI and trilateration over smart-phone. In: Proceedings of Symposium of the Korean Institute of Communications and Information Sciences, pp. 969–970 (2010)Google Scholar
  7. 7.
    Thaljaoui, A., Val, T., Nasri, N., Brulin, D.: BLE localization using RSSI measurements and iRingLA. In: 2015 IEEE International Conference on Industrial Technology (ICIT), pp. 2178–2183, 17–19 March 2015Google Scholar
  8. 8.
    Kim, S., Son, H., Kim, S., Lee, C.: Fingerprint-based indoor location tracking application development and performance analysis. In: Proceedings of Symposium of Institute of Electronics Engineers of Korea, pp. 677–680, November 2014Google Scholar
  9. 9.
    Ramsey, F., Harle, R.: An analysis of the accuracy of bluetooth low energy for indoor positioning applications. In: Proceedings of the 27th International Technical Meeting of the Satellite Division of the Institute of Navigation, (ION GNSS+2014) (2014)Google Scholar

Copyright information

© Springer Nature Singapore Pte Ltd. 2018

Authors and Affiliations

  1. 1.Department of Information and Communications EngineeringSeowon UniversityCheongjuKorea
  2. 2.Department of Computer EngineeringSeowon UniversityCheongjuKorea

Personalised recommendations