Personal and Ubiquitous Computing

, Volume 18, Issue 2, pp 271–285 | Cite as

Hybrid indoor and outdoor location services for new generation mobile terminals

  • Massimo Ficco
  • Francesco Palmieri
  • Aniello Castiglione
Original Article

Abstract

In the last years, an increasing interest in location services characterized the market of mobile ubiquitous devices (smartphones, handhelds, etc.). Several technologies and solutions have been developed to determine the position of mobile devices in their operating space, each with its specific degree of precision and accuracy. In this scenario, the ideal location service should be able of tracking the mobile terminal in any place it moves to, both indoors and outdoors. However, while outdoor location services have already achieved a satisfactory degree of technological maturity and effectiveness, a really ubiquitous location service that works satisfactorily in both indoor and outdoor scenarios is not yet available. In order to cope with the above challenge, this work proposes a hybrid location approach designed to choose and switch among multiple positioning technologies supported by the mobile device and available in the surrounding environment, in a dynamic and transparent way during the user movement. It combines signal strength–based fingerprinting techniques for indoor positioning together with traditional GPS-based positioning for the outdoor localization and performs opportunistic technology switching according to a count-and-threshold mechanism. The resulting solution is able to leverage the different features of the wireless networks and of the global positioning technologies, in order to provide ubiquitous location services across indoor and outdoor scenarios, as well as to minimize power consumption of the mobile device.

Keywords

Location-based services Hybrid positioning Mobile devices RSS fingerprinting 

References

  1. 1.
    Aitenbichler E, Mhlhuser M (2003) An IR local positioning system for smart items and devices. In: Proceedings of the 23rd IEEE international conference on distributed computing systems (IWSAWC03), pp 334–339. http://doi.ieeecomputersociety.org/10.1109/IMIS.2012.202
  2. 2.
    Aparicio S, Perez J, Bernardos AM, Casar JR (2008) A fusion method based on Bluetooth and WLAN technologies for indoor location. In: IEEE international conference on multisensor fusion and integration for intelligent systems, IEEE, pp 487–491. http://dx.doi.org/10.1016/j.diin.2008.06.003
  3. 3.
    Aversa R, Di Martino B, Ficco M, Venticinque S (2011) A simulation model for localization of pervasive objects using heterogeneous wireless networks. J Simul Model Pract Theory 19(8):1758–1772CrossRefGoogle Scholar
  4. 4.
    Baus J, Krüger A, Wahlster W (2002) A resource-adaptive mobile navigation system. In: Proceedings of the 7th international conference on intelligent user interfaces, pp 15–22. ACMGoogle Scholar
  5. 5.
    Becker C, Dürr F (2005) On location models for ubiquitous computing. Pers Ubiquit Comput 9(1):20–31CrossRefGoogle Scholar
  6. 6.
    Bohn J (2007) IPOS: a fault-tolerant and adaptive multi-sensor positioning architecture with QoS guarantees. Sens Rev 27(3):239–249CrossRefGoogle Scholar
  7. 7.
    Bowen CL, Martin TL (2006) Combining position estimates to enhance user localization. In: Proceeding of the 9th international symposium on wireless personal multimedia communications (WPMC06), pp 648–652Google Scholar
  8. 8.
    Bowen CL, Martin TL (2007) A survey of location privacy and an approach for solitary users. In: Proceedings of the 40th annual Hawaii international conference on system sciences, p 163cGoogle Scholar
  9. 9.
    Chai X, Yang Q (2007) Reducing the calibration effort for probabilistic indoor location estimation. IEEE Trans Mob Comput 6(6):649–662CrossRefGoogle Scholar
  10. 10.
    Cotroneo D, Russo S, Cornevilli F, Ficco M, Vecchio V (2004) Implementing positioning services over an ubiquitous infrastructure. In: Proceedings of the 2nd IEEE workshop on software technologies for future embedded and ubiquitous systems, IEEE, pp 14–18Google Scholar
  11. 11.
    Di Flora C, Ficco M, Russo S (2006) An architecture for providing Java applications with indoor and outdoor hybrid location sensing. In: Proceedings of the IEEE international workshop on software technology for future embedded and ubiquitous systems, IEEE, pp 37–42Google Scholar
  12. 12.
    Di Martino B, Ficco M, Aversa R, Venticinque S (2010) A positioning service for pervasive objects in dynamic environments. In: Proceedings of the IEEE 5th international symposium on wireless pervasive computing, IEEE, pp 244–249Google Scholar
  13. 13.
    Esposito C, Cotroneo D, Ficco M (2009) Calibrating RSS-based indoor positioning systems, IEEE, pp 1–6Google Scholar
  14. 14.
    Esposito C, Ficco M (2011) Deployment of RSS-based indoor positioning systems. J Wirel Inf Netw 18(4):224–242CrossRefGoogle Scholar
  15. 15.
    Feldmann S, Kyamakya K, Zapater A, Lue Z (2003) An indoor Bluetooth-based positioning system: concept, implementation and experimental evaluation. In: Proceedings of the international conference on wireless networks (ICWN 03), pp 109–113Google Scholar
  16. 16.
    Fernandez-Madrigal JA, Cruz-Martin E, Gonzalez J, Galindo C, Blanco JL (2007) Application of UWB and GPS technologies for vehicle localization in combined indoor-outdoor environments. In: 9th international symposium on signal processing and its applications, IEEE, pp 1–4Google Scholar
  17. 17.
    Ficco M, Piatrantuono R, Russo S (2010) Supporting ubiquitous location information in interworking 3G and wireless networks. Commun ACM 53(11):116–123CrossRefGoogle Scholar
  18. 18.
    Ficco M, Russo S (2009) A hybrid positioning system for technology-independent location-aware computing. Softw Pract Exp 39(13):1095–1125CrossRefGoogle Scholar
  19. 19.
    Focken D, Stiefelhagen R (2002) Towards vision-based 3-D people tracking in a smart room. In: Proceedings of the 4th IEEE international conference on multimodal interfaces (ICMI’02), pp 400–405Google Scholar
  20. 20.
    Gartner G, Frank A, Retscher G (2004) Pedestrian navigation system in mixed indoor/outdoor environment–the navio project. In: Proceedings of the CORP 2004 and geomultimedia04 symposium, pp 24–27Google Scholar
  21. 21.
    Gonzalez J, Blanco JL, Galindo C, Ortiz-de Galisteo A, Fernández-Madrigal JA, Moreno FA, Martinez JL (2007) Combination of UWB and GPS for indoor-outdoor vehicle localization. In: IEEE international symposium on intelligent signal processing, IEEE, pp 1–6Google Scholar
  22. 22.
    Gu Y, Lo A, Niemegeers I (2009) A survey of indoor positioning systems for wireless personal networks. IEEE Commun Surv Tutor 11(1):13–32CrossRefGoogle Scholar
  23. 23.
    Hightower J, Borriello G (2001) Location systems for ubiquitous computing. IEEE Comput Mag 34(8):57–66CrossRefGoogle Scholar
  24. 24.
    Ingram SJ, Harmer D, Quinlan M (2004) Ultrawideband indoor positioning systems and their use in emergencies. In: Proceedings of the IEEE conference on position location and navigation symposium, pp 706–715Google Scholar
  25. 25.
    LaMarca A, Chawathe Y, Consolvo S, Hightower J, Smith I, Scott J, Sohn T, Howard J, Hughes J, Potter F et al (2005) Place lab: device positioning using radio beacons in the wild. Pervasive Computing, vol 3468. LNCS, pp 301–306. http://dx.doi.org/10.1007/11428572_8
  26. 26.
    Lane ND, Miluzzo E, Lu H, Peebles D, Choudhury T, Campbell AT (2010) A survey of mobile phone sensing. IEEE Commun Mag 48(9):140–150CrossRefGoogle Scholar
  27. 27.
    Liu H, Darabi H, Banerjee P, Liu J (2007) Survey of wireless indoor positioning techniques and systems. IEEE Trans Syst Man Cybern C Appl Rev 37(6):1067–1080CrossRefGoogle Scholar
  28. 28.
  29. 29.
    Nord J, Synnes K, Parnes P (2002) An architecture for location aware applications. In: Proceedings of the 35th annual Hawaii international conference on system sciences, IEEE, pp 3805–3810Google Scholar
  30. 30.
    Pandya D, Jain R, Lupu E (2003) Indoor location estimation using multiple wireless technologies. In: 14th IEEE proceedings on personal, indoor and mobile radio communications, vol. 3, IEEE, pp 2208–2212Google Scholar
  31. 31.
    Pfeifer T (2005) Redundant positioning architecture. Comput Commun 28(13):1575–1585CrossRefGoogle Scholar
  32. 32.
    Raab F, Blood EB, Steiner TO, Jones HR (1979) Magnetic position and orientation tracking system. IEEE Trans Aerosp Electron Syst AES 15(5):709–718CrossRefGoogle Scholar
  33. 33.
    Rao B, Minakakis L (2003) Evolution of mobile location-based services. Commun ACM 46(12):61–65CrossRefGoogle Scholar
  34. 34.
    Son LT, Orten P (2007) Enhancing accuracy performance of bluetooth positioning. In: Proceedings of the IEEE wireless communications and networking conference (WCNC 07), pp 2726–2731Google Scholar
  35. 35.
    Spinella SC, Iera A, Molinaro A (2010) On potentials and limitations of a hybrid WLAN-RFID indoor positioning technique. Int J Navig Obs 2010:1–11. doi: 10.1155/2010/397467
  36. 36.
    Vegni AM, Esposito F (2009) Location aware mobility assisted services for heterogeneous wireless technologies. In: IEEE MTT-S international microwave workshop on wireless sensing, local positioning, and RFID, IEEE, pp 1–4Google Scholar
  37. 37.
    Vossiek M, Wiebking L, Gulden P, Wieghardt J, Hoffmann C, Heide P (2003) Wireless local positioning. Microw Mag IEEE 4(4):77–86CrossRefGoogle Scholar
  38. 38.
    Want R, Hopper A, Falcao V, Gibbons J (1992) The active badge location system. ACM Trans Inf Syst 10(1):91–102CrossRefGoogle Scholar
  39. 39.
    Wireless S, Skyhook CEO undaunted by mobile giants. http://www.crunchbase.com/company/skyhook-wireless

Copyright information

© Springer-Verlag London 2013

Authors and Affiliations

  • Massimo Ficco
    • 1
  • Francesco Palmieri
    • 1
  • Aniello Castiglione
    • 2
  1. 1.Dipartimento di Ingegneria Industriale e dell’InformazioneSeconda Università degli Studi di NapoliAversaItaly
  2. 2.Dipartimento di Informatica “R.M. Capocelli”Università degli Studi di SalernoFiscianoItaly

Personalised recommendations