Improving Wi-Fi Based Indoor Positioning Using Bluetooth Add-Ons

Location-Based Services (LBSs) constitutes one of the most popular classes of mobile services. However, while current LBSs typically target outdoor settings, we lead large parts of our lives indoors. The availability of easy-to-use and low-cost indoor positioning services is essential in also enabling indoor LBSs. Existing indoor positioning services typically use a single technology such as Wi-Fi, RFID or Bluetooth. Wi-Fi based indoor positioning is relatively easy to deploy, but does often not offer good positioning accuracy. In contrast, the use of RFID or Bluetooth for positioning requires considerable investments in equipment in order to ensure good positioning accuracy. Motivated by these observations, we propose a hybrid approach to indoor positioning. In particular, we introduce Bluetooth hotspots into an indoor space with an existing Wi-Fi infrastructure such that better positioning is achieved than what can be achieved by each technology in isolation. We design a flexible and extensible system architecture with an effective online position estimation algorithm for the hybrid system. The system is evaluated empirically in the building of our department. The results show that the hybrid approach improves positioning accuracy markedly.

[1]  Mikkel Baun Kjærgaard,et al.  A Taxonomy for Radio Location Fingerprinting , 2007, LoCA.

[2]  Paramvir Bahl,et al.  RADAR: an in-building RF-based user location and tracking system , 2000, Proceedings IEEE INFOCOM 2000. Conference on Computer Communications. Nineteenth Annual Joint Conference of the IEEE Computer and Communications Societies (Cat. No.00CH37064).

[3]  Kyandoghere Kyamakya,et al.  An Indoor Bluetooth-Based Positioning System: Concept, Implementation and Experimental Evaluation , 2003, International Conference on Wireless Networks.

[4]  Hao Wang,et al.  A wireless LAN-based indoor positioning technology , 2004, IBM J. Res. Dev..

[5]  Tsung-Nan Lin,et al.  Performance comparison of indoor positioning techniques based on location fingerprinting in wireless networks , 2005, 2005 International Conference on Wireless Networks, Communications and Mobile Computing.

[6]  Steven K. Feiner,et al.  Coarse, inexpensive, infrared tracking for wearable computing , 2003, Seventh IEEE International Symposium on Wearable Computers, 2003. Proceedings..

[7]  Andy Hopper,et al.  The active badge location system , 1992, TOIS.

[8]  Giuseppe Anastasi,et al.  Experimenting an indoor bluetooth-based positioning service , 2003, 23rd International Conference on Distributed Computing Systems Workshops, 2003. Proceedings..

[9]  Mikkel Baun Kjærgaard,et al.  Hyperbolic Location Fingerprinting: A Calibration-Free Solution for Handling Differences in Signal Strength (concise contribution) , 2008, 2008 Sixth Annual IEEE International Conference on Pervasive Computing and Communications (PerCom).

[10]  Hua Lu,et al.  Graph Model Based Indoor Tracking , 2009, 2009 Tenth International Conference on Mobile Data Management: Systems, Services and Middleware.

[11]  Myong-Soon Park,et al.  An indoor localization mechanism using active RFID tag , 2006, IEEE International Conference on Sensor Networks, Ubiquitous, and Trustworthy Computing (SUTC'06).

[12]  Yunhao Liu,et al.  LANDMARC: Indoor Location Sensing Using Active RFID , 2004, Proceedings of the First IEEE International Conference on Pervasive Computing and Communications, 2003. (PerCom 2003)..

[13]  Paul J. M. Havinga,et al.  Towards Smart Surroundings: Enabling Techniques and Technologies for Localization , 2005, LoCA.

[14]  Bent Thomsen,et al.  Efficient and Accurate WLAN Positioning with Weighted Graphs , 2009, MOBILIGHT.

[15]  Scott Bell,et al.  WiFi-based enhanced positioning systems: accuracy through mapping, calibration, and classification , 2010, ISA '10.

[16]  Jing Liu,et al.  Survey of Wireless Indoor Positioning Techniques and Systems , 2007, IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews).