Skip to main content
SpringerLink
Log in

The Improved Algorithm Based on DFS and BFS for Indoor Trajectory Reconstruction

  • Conference paper
  • First Online:
Wireless Algorithms, Systems, and Applications (WASA 2016)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 9798))

  • 1615 Accesses

Abstract

The trajectory of moving objects in large spaces is important, as it enables a range of applications related to security, guidance and so on. Trajectory reconstruction is the process which uses searching algorithms to find a reasonable trajectory. Due to the complexity of indoor environment and the larger area which multi-floor causes, it exits the problem of low searching efficient. To solve the problem, this paper proposes the improved algorithm which combines the Branch and Bound method based on Depth-First-Search(DFS) and Breadth-First-Search(BFS). It helps construct the trajectory quickly on topological map. Experimental results validate the improved algorithm is effective by comparing other algorithms.

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 39.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
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. Huang, W.Q., Ding, C., Wang, S.Y., Jing, X., Luo, Y.J., Zhang, Y.F., Zhang, Z.J.: An efficient visualization method of RFID indoor positioning data. In: 2nd International Conference on Systems and Informatics (ICSAI), pp. 497–504. IEEE, Shang Hai (2014)

    Google Scholar 

  2. Kang, H.Y., Kim, J.S., Li, K.J.: STrack: tracking in indoor symbolic space with RFID sensors. In: Proceedings of the 18th SIGSPATIAL International Conference on Advances in Geographic Information Systems (GIS 2010), pp. 502–505. ACM, San Jose (2010)

    Google Scholar 

  3. Yang, M.: The Research and Achievement of Visualization of indoor location data. Shanghai Jiaotong University (2012)

    Google Scholar 

  4. Huang, Y., Du, J., Chen, H.: Construct three-dimensional route from blueprint. J. Beijing JiaoTong Univ. Image Build. 34(2), 80–83 (2010)

    Google Scholar 

  5. Li, Z.: The optimization of Trajectory Reconstruction of Indoor Location System. G01C21/32GK102521328SQ201110400719 (2012)

    Google Scholar 

  6. Wang, R., Shroff, R., Zha, Y., Seshan, S., Veloso, M.: Indoor trajectory identification: snapping with uncertainty. In: IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), pp. 4901–4906 (2015)

    Google Scholar 

  7. Zheng H, Peng C.: Collaboration and fairness in opportunistic spectrum access. In: IEEE ICC, pp. 3132–3136 (2005)

    Google Scholar 

  8. Randria, I., Khelifa, M.M.B., Bouchouicha, M., Abellard, P.: A comparative study of six basic approaches for path planning towards an autonomous navigation. In: 33rd Annual Conference of the IEEE Industrial Electronics Society, IECON 200, pp. 2730–2735. IEEE, Taipei (2007)

    Google Scholar 

  9. Lutvica, K., Velagić, J., Kadić, N., Osmić, N., Džampo, G., Muminović, H.: Remote path planning and motion control of mobile robot within indoor maze environment. In: IEEE International Symposium on Intelligent Control, pp. 1596–1601. IEEE, Antibes (2014)

    Google Scholar 

  10. Gao, P., Shi, W., Zhou, W., Li, H., Wang, X.: A location predicting method for indoor mobile target localization in wireless sensor networks. Int. J. Distrib. Sens. Netw. 2013, Article ID 949285, 11pages (2013)

    Google Scholar 

  11. Yuan, W., Schneider, M.: iNav: an indoor navigation model supporting length-dependent optimal routing. Geospatial Thinking. Lecture Notes in Geoinformation and Cartography, pp. 299–313. Springer, Heidelberg (2010)

    Chapter  Google Scholar 

  12. Yuan W, Schneider M.: Supporting continuous range queries in indoor space. In: IEEE Eleventh International Conference on Mobile Data Management (MDM 2010), pp. 209–214 (2010)

    Google Scholar 

Download references

Acknowledgement

This work was supported in part by the Innovation Program of Institute of Information Engineering Chinese Academy of Sciences (Grant No. Y5Z0151104).

Author information

Authors and Affiliations

  1. Institute of Information Engineering, CAS, Beijing, China

    Min Li, Jingjing Fu, Yanfang Zhang, Zhujun Zhang & Siye Wang

  2. University of Chinese Academy of Sciences, Beijing, China

    Jingjing Fu

  3. Beijing Jiaotong University, Beijing, China

    Siye Wang

Authors
  1. Min Li
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Jingjing Fu
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Yanfang Zhang
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Zhujun Zhang
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Siye Wang
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Yanfang Zhang .

Editor information

Editors and Affiliations

  1. Montana State University , Bozeman, USA

    Qing Yang

  2. Dept of Computer & Information Sci, Towson University, Towson, Maryland, USA

    Wei Yu

  3. Laboratoire de Méthodes de Conception de , Algiers, Algeria

    Yacine Challal

Rights and permissions

Reprints and permissions

Copyright information

© 2016 Springer International Publishing Switzerland

About this paper

Cite this paper

Li, M., Fu, J., Zhang, Y., Zhang, Z., Wang, S. (2016). The Improved Algorithm Based on DFS and BFS for Indoor Trajectory Reconstruction. In: Yang, Q., Yu, W., Challal, Y. (eds) Wireless Algorithms, Systems, and Applications. WASA 2016. Lecture Notes in Computer Science(), vol 9798. Springer, Cham. https://doi.org/10.1007/978-3-319-42836-9_41

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-42836-9_41

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-42835-2

  • Online ISBN: 978-3-319-42836-9

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation