Skip to main content
SpringerLink
Log in

Geofence and Network Proximity

  • Conference paper
Internet of Things, Smart Spaces, and Next Generation Networking (ruSMART 2013, NEW2AN 2013)

Part of the book series: Lecture Notes in Computer Science ((LNCCN,volume 8121))

Abstract

Many of modern location-based services are often based on an area or place as opposed to an accurate determination of the precise location. Geofencing approach is based on the observation that users move from one place to another and then stay at that place for a while. These places can be, for example, commercial properties, homes, office centers and so on. As per geofencing approach they could be described (defined) as some geographic areas bounded by polygons. It assumes users simply move from fence to fence and stay inside fences for a while. In this article we replace geo-based boundaries with network proximity rules. This new approach let us effectively deploy indoor location based services and provide a significant energy saving for mobile devices comparing with the traditional methods.

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 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

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Reclus, F., Drouard, K.: Geofencing for fleet & freight management. In: 2009 9th International Conference on Intelligent Transport Systems Telecommunications (ITST), pp. 353–356 (2009)

    Google Scholar 

  2. LaMarca, A., et al.: Place lab: Device positioning using radio beacons in the wild. In: Gellersen, H.-W., Want, R., Schmidt, A. (eds.) PERVASIVE 2005. LNCS, vol. 3468, pp. 116–133. Springer, Heidelberg (2005)

    Chapter  Google Scholar 

  3. Constandache, I., Gaonkar, S., Sayler, M., Choudhury, R.R., Cox, L.: Enloc: Energy-efficient localization for mobile phones. In: Proceedings of IEEE INFOCOM Mini Conference 2009, Rio de Janeiro, Brazil (2009)

    Google Scholar 

  4. Zhuang, Z., Kim, K.-H., Singh, J.: Singh Improving Energy Efficiency of Location Sensing on Smartphones. In: MobiSys 2010, San Francisco, California, USA, June 15-18 (2010), Copyright 2010 ACM 978-1-60558-985-5/10/06

    Google Scholar 

  5. http://forums.watchuseek.com/f296/garmin-fenix-ongoing-review-several-parts-746366-11.html (retrieved: March 2013)

  6. Hristova, N., O‘Hare, G.M.P.: Ad-me: Wireless Advertising Adapted to the User Location, Device and Emotions. In: Thirty-Seventh Hawaii International Conference on System Sciences (HICSS-37) (2004)

    Google Scholar 

  7. Lu, H., et al.: The jigsaw continuous sensing engine for mobile phone applications. In: Proc. 8th ACM Conf. Embedded Netw. Sens. Syst., SenSys 2010, pp. 71–84. ACM (2010)

    Google Scholar 

  8. Paek, J., Kim, J., Govindan, R.: Energy-efficient rate-adaptive gpsbased positioning for smartphones. In: Proc. 8th MobiSys 2010, pp. 299–314. ACM (2010)

    Google Scholar 

  9. Namiot, D.: Geo messages. In: 2010 International Congress on Ultra Modern Telecommunications and Control Systems and Workshops (ICUMT), pp. 14–19 (2010), doi:10.1109/ICUMT.2010.5676665

    Google Scholar 

  10. Priyantha, B., Lymberopoulos, D., Liu, J.: LittleRock: Enabling Energy-Efficient Continuous Sensing on Mobile Phones. IEEE Pervas. Comput. 10(2), 12–15 (2011)

    Article  Google Scholar 

  11. Song, L., Kotz, D., Jain, R., He, X.: Evaluating next-cell predictors with extensive wi-fi mobility data. IEEE Trans. Mobile Comput. 5(12), 1633–1649 (2006)

    Article  Google Scholar 

  12. Chon, Y., Talipov, E., Shin, H., Cha, H.: Mobility Prediction-based Smartphone Energy Optimization for Everyday Location Monitoring. In: SenSys 2011, Seattle, WA, USA, November 1-4 (2011), Copyright 2011 ACM 978-1-4503-0718-5/11/11

    Google Scholar 

  13. Namiot, D., Sneps-Sneppe, M.: Where Are They Now – Safe Location Sharing. In: Andreev, S., Balandin, S., Koucheryavy, Y. (eds.) NEW2AN/ruSMART 2012. LNCS, vol. 7469, pp. 63–74. Springer, Heidelberg (2012)

    Chapter  Google Scholar 

  14. Sprint Geofence API, http://developer.sprint.com/dynamicContent/geofence/ (retrived: February 2013)

  15. Open API platform, http://www2.alcatel-lucent.com/application_enablement/ (retrieved: March 2013)

  16. Namiot, D.: Context-Aware Browsing–A Practical Approach. In: 2012 6th International Conference on Next Generation Mobile Applications, Services and Technologies (NGMAST), pp. 18–23. IEEE (2012), doi:10.1109/NGMAST.2012.13

    Google Scholar 

  17. Namiot, D., Schneps-Schneppe, M.: About location-aware mobile messages. In: NGMAST 2011, pp. 48–53 (2011), doi:10.1109/NGMAST.2011.19

    Google Scholar 

  18. Namiot, D., Sneps-Sneppe, M.: Proximity as a Service. In: 2012 2nd Baltic Congress on Future Internet Communications (BCFIC), pp. 199–205 (2012), doi:10.1109/BCFIC.2012.6217947

    Google Scholar 

  19. Rekimoto, J., Miyaki, T., Ishizawa, T.: LifeTag: WiFi-Based Continuous Location Logging for Life Pattern Analysis. In: Hightower, J., Schiele, B., Strang, T. (eds.) LoCA 2007. LNCS, vol. 4718, pp. 35–49. Springer, Heidelberg (2007)

    Chapter  Google Scholar 

  20. Azizyan, M., Constandache, I., Roy, R.: SurroundSense: mobile phone localization via ambience fingerprinting. In: Proceedings of the 15th Annual International Conference on Mobile Computing and Networking (MobiCom 2009), pp. 261–272 (2009), doi:10.1145/1614320.1614350

    Google Scholar 

  21. Chen, Y., Chawathe, Y., LaMarca, A., Krumm, J.: Accuracy characterization for metropolitan-scale Wi-Fi localization. In: ACM MobiSys (2005)

    Google Scholar 

  22. Stuart, A.: The correlation between variate-values and ranks in samples from a continous distribution. British Journal of Statistical Psychology 7(1), 37–44

    Google Scholar 

  23. Kjaergaard, M., Wirz, M., Roggen, D., Troster, G.: Mobile sensing of pedestrian flocks in indoor environments using WiFi signals. In: 2012 IEEE International Conference on Pervasive Computing and Communications (PerCom), pp. 95–102 (2012)

    Google Scholar 

  24. Janga, W., Healyb, W.: Wireless sensor network performance metrics for building applications. Energy and Buildings 42(6), 862–868, doi:10.1016/j.enbuild.2009.12.008

    Google Scholar 

  25. Chandra, R., Padhye, J., Ravindranath, L., Wolman, A.: A Beacon-Stuffing: Wi-Fi without Associations. In: Eighth IEEE Workshop on Mobile Computing Systems and Applications, HotMobile 2007, pp. 53–57 (2007)

    Google Scholar 

  26. Smartphones movement track, http://www.technologyreview.com/view/427687/if-you-have-a-smart-phone-anyone-can-now-track/ (retrieved: April 2013)

  27. Meshlium Xtreme, http://www.libelium.com/products/meshlium (retrived: April 2013)

  28. Hansen, J., Gronli, T., Ghinea, G.: Cloud to Device Push Messaging on Android: A Case Study. In: 2012 26th International Conference on Advanced Information Networking and Applications Workshops (WAINA), pp. 1298–1303 (2012)

    Google Scholar 

  29. Sneps-Sneppe, M., Namiot, D.: Spotique: A New Approach to Local Messaging. In: Tsaoussidis, V., Kassler, A.J., Koucheryavy, Y., Mellouk, A. (eds.) WWIC 2013. LNCS, vol. 7889, pp. 192–203. Springer, Heidelberg (2013)

    Chapter  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Faculty of Computational Mathematics and Cybernetics, Lomonosov Moscow State University, Moscow, Russia

    Dmitry Namiot

  2. M2M Competence Center, ZNIIS, Moscow, Russia

    Manfred Sneps-Sneppe

Authors
  1. Dmitry Namiot
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Manfred Sneps-Sneppe
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Editors and Affiliations

  1. FRUCT Oy, Kissankellontie 20B, 00930, Helsinki, Finland

    Sergey Balandin

  2. Department of Electronics and Communications Engineering, Tampere University of Technology, Korkeakoulunkatu 1, 33720, Tampere, Finland

    Sergey Andreev  & Yevgeni Koucheryavy  & 

Rights and permissions

Reprints and permissions

Copyright information

© 2013 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Namiot, D., Sneps-Sneppe, M. (2013). Geofence and Network Proximity. In: Balandin, S., Andreev, S., Koucheryavy, Y. (eds) Internet of Things, Smart Spaces, and Next Generation Networking. ruSMART NEW2AN 2013 2013. Lecture Notes in Computer Science, vol 8121. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-40316-3_11

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-40316-3_11

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-40315-6

  • Online ISBN: 978-3-642-40316-3

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation