The SkyLoc Floor Localization System

When a mobile user dials 911, a key to arriving to the emergency scene promptly is knowing the location of the mobile user. This paper presents SkyLoc, a GSM fingerprinting-based localization system that runs on a mobile phone and identifies the current floor of a user in tall multi-floor buildings. Knowing the floor in a tall building significantly reduces the area that emergency service personnel have to canvas to locate the individuals in need. We evaluated our system in three multi-floor buildings located in Washington DC, Seattle and Toronto. Our system identifies the floor correctly in up to 73% of the cases and is within 2 floors in 97% of the cases. The system is robust as it works for different network operators, when the training and testing sets were collected with different hardware and up to one month apart. In addition, we show that feature selection techniques that select a subset of highly relevant radio sources for fingerprint matching nearly double the localization accuracy of our system

[1]  Andy Hopper,et al.  The active badge system (abstract) , 1993, INTERCHI.

[2]  Kostas E. Bekris,et al.  Robotics-Based Location Sensing Using Wireless Ethernet , 2002, MobiCom '02.

[3]  Moustafa Youssef,et al.  WLAN location determination via clustering and probability distributions , 2003, Proceedings of the First IEEE International Conference on Pervasive Computing and Communications, 2003. (PerCom 2003)..

[4]  Gergely V. Záruba,et al.  A Bayesian sampling approach to in-door localization of wireless devices using received signal strength indication , 2005, Third IEEE International Conference on Pervasive Computing and Communications.

[5]  H. Laitinen,et al.  Database correlation method for GSM location , 2001, IEEE VTS 53rd Vehicular Technology Conference, Spring 2001. Proceedings (Cat. No.01CH37202).

[6]  Mika Raento,et al.  Adaptive On-Device Location Recognition , 2004, Pervasive.

[7]  Eyal de Lara,et al.  Accurate GSM Indoor Localization , 2005, UbiComp.

[8]  Mike Y. Chen,et al.  Practical Metropolitan-Scale Positioning for GSM Phones , 2006, UbiComp.

[9]  Andy Hopper,et al.  A new location technique for the active office , 1997, IEEE Wirel. Commun..

[10]  Andreas Haeberlen,et al.  Practical robust localization over large-scale 802.11 wireless networks , 2004, MobiCom '04.

[11]  S. Ahonen,et al.  Database correlation method for UMTS location , 2001, The 57th IEEE Semiannual Vehicular Technology Conference, 2003. VTC 2003-Spring..

[12]  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).

[13]  Bill N. Schilit,et al.  Place Lab: Device Positioning Using Radio Beacons in the Wild , 2005, Pervasive.

[14]  Eric Horvitz,et al.  RightSPOT: A Novel Sense of Location for a Smart Personal Object , 2003, UbiComp.

[15]  Hari Balakrishnan,et al.  6th ACM/IEEE International Conference on on Mobile Computing and Networking (ACM MOBICOM ’00) The Cricket Location-Support System , 2022 .

[16]  Pat Langley,et al.  Selection of Relevant Features and Examples in Machine Learning , 1997, Artif. Intell..

[17]  Lamb Harmon client Shreve,et al.  Empire State Building , 1931 .