Context-Aware Indoor Navigation

Over the past few years, several technological advances have been made to enable locating people in indoor settings, where way finding is something we do on a daily basis. In a similar way as it happened with GPS and today's popular outdoor navigation systems, indoor navigation is set to become one of the first, truly ubiquitous services that will make our living and working environments intelligent. Two critical characteristics of human way finding are destination choice and path selection. This work focuses on the latter, which traditionally has been assumed to be the result of minimizing procedures such as selecting the shortest path, the quickest or the least costly path. However, this path approximations are not necessarily the most natural paths. Taking advantage of context-aware information sources, this paper presents an easy to deploy context-aware indoor navigation system, together with an efficient spatial representation, and novel approach for path adaptation to help people find their destination according to their preferences and contextual information. We tested our system in one building with several users to estimate first an assessment of preference values, and later to compare how the paths suggested by our system correspond to those people would actually follow. The positive results of this evaluation confirm the suitability of our models and algorithms.

[1]  Abdelsalam Helal,et al.  Drishti: an integrated indoor/outdoor blind navigation system and service , 2004, Second IEEE Annual Conference on Pervasive Computing and Communications, 2004. Proceedings of the.

[2]  Stephan Winter,et al.  Spatial Information Theory, 8th International Conference, COSIT 2007, Melbourne, Australia, September 19-23, 2007, Proceedings , 2007, COSIT.

[3]  Yao-Jen Chang,et al.  A novel wayfinding system based on geo-coded qr codes for individuals with cognitive impairments , 2007, Assets '07.

[4]  Dragos-Anton Manolescu,et al.  Workflow enactment with continuation and future objects , 2002, OOPSLA '02.

[5]  Bing Liu Intelligent Route Finding: Combining Knowledge and Cases and an Efficient Search Algorithm , 1996, ECAI.

[6]  Reginald G. Golledge,et al.  Path Selection and Route Preference in Human Navigation: A Progress Report , 1995, COSIT.

[7]  Max Mühlhäuser,et al.  An IR local positioning system for smart items and devices , 2003, 23rd International Conference on Distributed Computing Systems Workshops, 2003. Proceedings..

[8]  Stathes Hadjiefthymiades,et al.  A human-centered semantic navigation system for indoor environments , 2005, ICPS '05. Proceedings. International Conference on Pervasive Services, 2005..

[9]  Lynn A. Streeter,et al.  How to Tell People Where to Go: Comparing Navigational Aids , 1985, Int. J. Man Mach. Stud..

[10]  W. Edwards,et al.  Decision Analysis and Behavioral Research , 1986 .

[11]  Stephen C. Hirtle,et al.  The Nature of Landmarks for Real and Electronic Spaces , 1999, COSIT.

[12]  Hanan Samet,et al.  The Quadtree and Related Hierarchical Data Structures , 1984, CSUR.

[13]  Andrew U. Frank,et al.  Pedestrian Navigation System in Mixed Indoor/Outdoor Environment - The NAVIO Project , 2004 .

[14]  Andreas Butz,et al.  A hybrid indoor navigation system , 2001, IUI '01.

[15]  O Svestková,et al.  International classification of functioning, disability and health of World Health Organization (ICF). , 2008, Prague medical report.

[16]  Matthias Dehmer,et al.  Information theoretic measures of UHG graphs with low computational complexity , 2007, Appl. Math. Comput..

[17]  Max Mühlhäuser,et al.  MundoCore: A light-weight infrastructure for pervasive computing , 2007, Pervasive Mob. Comput..

[18]  Kai-Florian Richter,et al.  Simplest Instructions: Finding Easy-to-Describe Routes for Navigation , 2008, GIScience.

[19]  Max Mühlhäuser,et al.  CoINS: Context Sensitive Indoor Navigation System , 2006, Eighth IEEE International Symposium on Multimedia (ISM'06).

[20]  Edsger W. Dijkstra,et al.  A note on two problems in connexion with graphs , 1959, Numerische Mathematik.

[21]  Andreas Hartl A provider-independent, proactive service for location sensing in cellular networks , 2005 .

[22]  Max Mühlhäuser,et al.  Designing and Implementing Smart Spaces , 2007 .

[23]  Christian Freksa,et al.  Spatial Information Theory. Cognitive and Computational Foundations of Geographic Information Science , 1999, Lecture Notes in Computer Science.

[24]  Matthias Dehmer,et al.  Structural similarity of directed universal hierarchical graphs: A low computational complexity approach , 2007, Appl. Math. Comput..