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Multi-cell Based UWB Indoor Positioning System

  • JaeMin Hong
  • ShinHeon Kim
  • KyuJin Kim
  • ChongGun KimEmail author
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11432)

Abstract

Indoor positioning is a big issue to trace or navigate for a moving object. Methods using Wi-Fi have been widely studied even though Wi-Fi has a lot of problems. UWB is an alternative indoor positioning method. But indoor positioning using UWB has lots of problems to solve. At an indoor environment like hospitals, many pathways like a maze is an important target for positioning. For monitoring an active moving object in some period, continuous tracking is needed. A cell system is proposed to overcome limitation of UWB modules on continuous indoor position tracking during some period. The proposed system can be used for analyzing staff workload at hospitals and for real time monitoring. Measuring nursing activities is critical steps to understand relationship between nursing practices, workload and patient safety.

Keywords

Cells Wi-Fi UWB BLE Indoor positioning Workload monitoring 

Notes

Acknowledgement

This research was supported by The Leading Human Resource Training Program of Regional Neo industry through the National Research Foundation of Korea (NRF) funded by the Ministry of Science, ICT and future Planning, and the BK21 Plus Program funded by the Ministry of Education (MOE, Korea) and National Research Foundation of Korea (NRF).

References

  1. 1.
    Hong, J., Kim, K., Kim, C.: Comparison of indoor positioning system using Wi-Fi and UWB. In: Nguyen, N.T., Hoang, D.H., Hong, T.-P., Pham, H., Trawiński, B. (eds.) ACIIDS 2018. LNCS (LNAI), vol. 10751, pp. 623–632. Springer, Cham (2018).  https://doi.org/10.1007/978-3-319-75417-8_58CrossRefGoogle Scholar
  2. 2.
    Hong, J., Kim, S., Lee, J., Kim, K., Kim, C.: Indoor position monitoring system using UWB module. In: 2018 International Conference on Applied Mechanics, Mechatronics and Materials (2018)Google Scholar
  3. 3.
    Di Benedetto, M.-G.: UWB communication systems: a comprehensive over-view, vol. 5. Hindawi Publishing Corporation, New York (2006)CrossRefGoogle Scholar
  4. 4.
    Dong, Q., Dargie, W.: Evaluation of the reliability of RSSI for indoor localization. In: 2012 International Conference on Wireless Communications in Unusual and Confined Areas (ICWCUCA), pp. 1–6. IEEE (2012)Google Scholar
  5. 5.
    Zhou, Y., Law, C.L., Chin, F.: Construction of local anchor map for indoor position measurement system. IEEE Trans. Instrum. Measur. 59(7), 1986–1988 (2010)CrossRefGoogle Scholar
  6. 6.
    Kim, K., Hong, J., Kim, C.: An alarm and response tracking system for the patient-centric perspective. J. Med. Imaging Health Inform. 8, 190–195 (2018)CrossRefGoogle Scholar
  7. 7.
    Ingram, S.J., Harmer, D., Quinlan, M.: UltraWideBand indoor positioning systems and their use in emergencies. In: Position Location and Navigation Symposium, PLANS 2004, pp. 706–715. IEEE (2004)Google Scholar
  8. 8.
    Saksvik-Lehouillier, I., et al.: Individual, situational and lifestyle factors related to shift work tolerance among nurses who are new to and experienced in night work. J. Adv. Nurs. 69(5), 1136–1146 (2013)CrossRefGoogle Scholar
  9. 9.
    Duffield, C., et al.: Nursing staffing, nursing workload, the work environment and patient outcomes. Appl. Nurs. Res. 24, 244–255 (2011)CrossRefGoogle Scholar
  10. 10.
    Myny, D., et al.: Determining a set of measurable and relevant factors affecting nursing workload in the acute care hospital setting: a cross-sectional study. Int. J. Nurs. Stud. 49, 427–436 (2012)CrossRefGoogle Scholar
  11. 11.
    OnkarPathak, P.P., Palkar, R., Tawari, M.: Wi-Fi indoor positioning system based on RSSI measurements from Wi-Fi access points –a trilateration approach. Int. J. Sci. Eng. Res. 5(4), 1234–1238 (2014)Google Scholar
  12. 12.
    Vasisht, D., Kumar, S., Katabi, D.: Decimeter-level localization with a single WiFi access point. In: 13th USENIX Symposium on Networked Systems Design and Implementation (NSDI 2016) (2016)Google Scholar
  13. 13.
    Kong, I.-Y., Kim, H.-J.: Experiments and its analysis on the Identification of indoor location by visible light communication using LED lights. J. Korea Inst. Inf. Commun. Eng. 15(5), 1045–1052 (2011)CrossRefGoogle Scholar
  14. 14.
    Bluetooth Indoor Localization System: Gunter FISCHER, Burkhart DIETRICH, Frank WINKLERGoogle Scholar

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • JaeMin Hong
    • 1
  • ShinHeon Kim
    • 1
  • KyuJin Kim
    • 2
  • ChongGun Kim
    • 1
    Email author
  1. 1.Department of Computer EngineeringYeungnam UniversityGyeongsanKorea
  2. 2.College of NursingKyungpook National UniversityDaeguKorea

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