Skip to main content
SpringerLink
Log in

Research on Indoor Location Method Based on WLAN Signal Location Fingerprints

  • Conference paper
  • First Online:
Advances in Internet, Data & Web Technologies (EIDWT 2018)

Part of the book series: Lecture Notes on Data Engineering and Communications Technologies ((LNDECT,volume 17))

Abstract

Since the outdoor positioning technology has matured, people pay more attention to the development of indoor positioning technology in recent years. The use of existing WLAN signal for indoor positioning is a convenient way to realize. Aiming at the location fingerprint location algorithm based on WLAN signal, an in-depth study has been carried out in this paper. The K-means clustering algorithm and fuzzy logic are used to optimize the traditional algorithms in off-line database creation and on-line location phrase, which is expected to reduce the positioning error while improving the positioning efficiency. In the field simulation experiment, the actual effect of several similar algorithms is analyzed and compared, which proves that the research of this paper is effective for the optimization of indoor location algorithm.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 169.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 219.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Wan, Q., Guo, X., Chen, Z.: Theory, Method and Application of Indoor Positioning Method. Electronic industry press, Beijing (2012)

    Google Scholar 

  2. Wang, Y., Zhao, H.-D.: Overview and prospect of indoor location techniques. Meas. Control Technol. 35(07), 1–3+8 (2016)

    Google Scholar 

  3. Wang, S.: Research on the application of hybrid wireless positioning technology. Informatization Res. 36(3), 43–45, 48 2010

    Google Scholar 

  4. Shi, G., Wang, B., Wu, B.: Overview of indoor localization method based on WiFi and mobile smart terminal. Comput. Eng. 41(09), 39–44+50 (2015)

    Google Scholar 

  5. Dong, Y., Zhang, H., Chen, J.: Location fingerprint algorithm based on Wi-Fi indoor positioning. Ind. Control Comput. 28(1), 72–74 (2015)

    Google Scholar 

  6. Du, S.: Research and Implementation of Indoor Positioning Technology based on Location Fingerprint. Yunnan University (2013)

    Google Scholar 

  7. Lei, L.: Application on Positioning Technology Based on RFID in Warehouse Management. HuaZhong University of Science and Technology (2012)

    Google Scholar 

  8. Wu, D.: Tourist Attractions Mobile Phone Intelligent Navigation System Based on WIFI Scan. Jilin Agricultural University (2016)

    Google Scholar 

  9. Tang, N., Xiao, X., Chen, Z.: A method of multi-mode switching for SVC based on Sugeno Fuzzy Inference. Power Syst. Technol. 35(08), 140–143 (2011)

    Google Scholar 

  10. Yang, M., Liu, K., Shao, D.: PCA clustering algorithm for indoor positioning in WLAN. Telecommun. Sci. 32(07), 21–26 (2016)

    Google Scholar 

  11. Wang, Y., Ba, B., Cui, W., et al.: Indoor positioning algorithm based on Markov Monte Carlo. J Xidian Univ. (Sci. edn.) 43(02), 145–149 (2016)

    Google Scholar 

  12. Miao, H., Wang, J., Li, C., et al.: A fuzzy logic-based indoor location approach. Control Instrum. Chem. Ind. 41(04), 387–391+396 (2014)

    Google Scholar 

  13. Mao, Q., Zeng, B., Ye, L.-F.: Research on improved indoor mobile robot fuzzy position fingerprint localization. Comput. Sci. 42(11), 170–173 (2015)

    Google Scholar 

  14. Cai, Z., Xia, X., Hu, B., et al.: Improvement of indoor signal strength fingerprint localization algorithm. Comput. Sci. 41(11), 178–181 (2014)

    Google Scholar 

  15. Guo, W.: Research on Indoor Positioning Algorithm Based on Fuzzy Inference. University of Electronic Science and Technology of China (2015)

    Google Scholar 

Download references

Acknowledgments

The authors thank all the reviewers and editors for their valuable comments and works. This research is Supported by the Key research and development plan of Shandong Province (Major key technology) (No. 2016ZDJS02A12), the Major scientific and technological innovation project of Shandong Province (No. 2017CXGC0603).

Author information

Authors and Affiliations

  1. School of Information and Electrical Engineering, Shandong Jianzhu University, Jinan, 250101, Shandong, China

    Tao Wang, Tan Wang, Huanbing Gao & Yanping Li

Authors
  1. Tao Wang
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Tan Wang
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Huanbing Gao
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Yanping Li
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Tao Wang .

Editor information

Editors and Affiliations

  1. Department of Information and Communication Engineering, Fukuoka Institute of Technology, Fukuoka-shi, Japan

    Leonard Barolli

  2. Technical University of Catalonia, Barcelona, Spain

    Fatos Xhafa

  3. Department of Computer Science, COMSATS Institute of Information Technology, Islamabad, Pakistan

    Nadeem Javaid

  4. Polytechnic University of Tirana, Tirana, Albania

    Evjola Spaho

  5. Polytechnic University of Tirana, Tirana, Albania

    Vladi Kolici

Rights and permissions

Reprints and permissions

Copyright information

© 2018 Springer International Publishing AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Wang, T., Wang, T., Gao, H., Li, Y. (2018). Research on Indoor Location Method Based on WLAN Signal Location Fingerprints. In: Barolli, L., Xhafa, F., Javaid, N., Spaho, E., Kolici, V. (eds) Advances in Internet, Data & Web Technologies. EIDWT 2018. Lecture Notes on Data Engineering and Communications Technologies, vol 17. Springer, Cham. https://doi.org/10.1007/978-3-319-75928-9_75

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-75928-9_75

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-75927-2

  • Online ISBN: 978-3-319-75928-9

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics

Search

Navigation