Redundant positioning architecture

Positioning has been a driving factor in the development of ubiquitous computing applications throughout the past two decades. Numerous devices and techniques have been developed-few of them are actually used commercially. The precision is limited to specific applications, the availability limited to the provider of specific services. Occasionally, few methods have been combined to recalibrate each other by means of data fusion. We present a novel architecture for processing the vast amount of data from pervasive devices penetrating everyday objects to the cheapest level. Location information can be inferred from infrastructure deployed for different purposes, only partly designed for positioning in the first place. The massive redundancy of such nodes and the synergetic heterogeneity of completely different recognition principles allows to tailor the perceived positioning probability to the specific requirements of the target application. A self-learning and self-healing approach to misleading, wrong and outdated pieces of information provides a new quality of interworking position and context aware systems.

[1]  Axel Küpper,et al.  Quality of Context: What It Is And Why We Need It , 2004 .

[2]  F. Livesey,et al.  The ORL active floor [sensor system] , 1997, IEEE Wirel. Commun..

[3]  Jeff Magee,et al.  Multi-sensor location tracking , 1998, MobiCom '98.

[4]  Walter Hirt.  Ultra-wideband radio technology: overview and future research , 2003 .

[5]  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).

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

[7]  A. Harter,et al.  A distributed location system for the active office , 1994, IEEE Network.

[8]  Alois Ferscha,et al.  Coordination in pervasive computing environments , 2003, WET ICE 2003. Proceedings. Twelfth IEEE International Workshops on Enabling Technologies: Infrastructure for Collaborative Enterprises, 2003..

[9]  Henk L. Muller,et al.  Low Cost Indoor Positioning System , 2001, UbiComp.

[10]  Michael Rohs,et al.  Social, Economic, and Ethical Implications of Ambient Intelligence and Ubiquitous Computing , 2005, Ambient Intelligence.

[11]  F. Livesey,et al.  The ORL Acfive Floor , 1997 .

[12]  Gaetano Borriello,et al.  The location stack , 2004 .

[13]  Gregory D. Abowd,et al.  The smart floor: a mechanism for natural user identification and tracking , 2000, CHI Extended Abstracts.

[14]  Seth J. Teller,et al.  The cricket compass for context-aware mobile applications , 2001, MobiCom '01.

[15]  Gaetano Borriello,et al.  Real-world implementation of the location stack: the universal location framework , 2003, 2003 Proceedings Fifth IEEE Workshop on Mobile Computing Systems and Applications.

[16]  Gaetano Borriello,et al.  The location stack: a layered model for location in ubiquitous computing , 2002, Proceedings Fourth IEEE Workshop on Mobile Computing Systems and Applications.

[17]  Gregory D. Abowd,et al.  Rapid prototyping of mobile context-aware applications: the Cyberguide case study , 1996, MobiCom '96.

[18]  Radu Popescu-Zeletin,et al.  A modular location-aware service and application platform , 1999, Proceedings IEEE International Symposium on Computers and Communications (Cat. No.PR00250).

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

[20]  Matthias Jarke,et al.  DAIDA: an environment for evolving information systems , 1992, TOIS.