OntoNav: A Semantic Indoor
Navigation System
C. Anagnostopoulos, V. Tsetsos, P. Kikiras, and S.
Hadjiefthymiades
Pervasive Computing Research Group,
Communication Networks Laboratory (CNL),
Dept. of Informatics & Telecommunications, University of Athens
1st Workshop on Semantics in Mobile Environments - SME’05
(in conjunction with MDM’05)
May 9 2005
Ayia Napa, Cyprus
Presentation Structure
 Introduction
 System Design
 Conclusions
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Indoor Location Based Services
 Traditional LBS
 Navigation, find nearest POIs, etc.
 Based on geometric location modeling
 Semantic LBS
 Intelligent service provisioning based on
ontological knowledge representation
and hybrid location modeling
 Human-centered services, suitable for
people with disabilities
 Can be deployed to “pervasive
environments”
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Motivation
 Complex and unknown built environments
cannot be easily explored
 People with disabilities face additional
difficulties and put increased effort when
following paths that eventually become
non-traversable
 Built environments are associated with rich
semantics which may lead to intelligent
services if exploited appropriately
 OntoNav’s goal: to assist the path selection
and end-to-end guidance processes using
semantic modeling techniques
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Presentation Structure
 Introduction
 System Design
 Conclusions
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OntoNav Architecture
 Navigation Service (NAV)
 Geometric Path Computation Service (GEO)
 Semantic Path Selection Service (SEM)
Indoor
Positioning
System
GEO
NAV
Spatial
DB
Ontology
Repository
SEM
User
Profiles
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System Functionality
Building representation
(graph)
Feature
Extraction
Spatial
DB
Building blueprints
Indoor
Navigation
Ontology (INO)
Graph
creation
algorithm
INO
instances
NAV
SEM
Best traversable
path
Geometric
path computation
(graph traversal)
GEO
User and
destination
locations
User profile
(capabilities and
preferences)
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Indoor Navigation Ontology (INO) I
 Represents complex built environments,
along with user models, from a navigation
perspective
 Imports concepts from indoor location
ontology
 Building, Floor, Room, Corridor, …
 Since no such well-established ontology exists,
aggregation/merging and extensions of existing
indoor location models are pursued
 INO currently undergoes a model-evaluatereengineer process
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Indoor Navigation Ontology (INO) II
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User profiles
 Describe the capabilities and preferences of
users
 A user profile (UP) contains:
 Physical navigation rules (e.g., wheelchair)
 Perceptual navigation rules (e.g., child)
 Routing preferences (e.g., calendar-driven)
 A user typically selects a predefined UP and
further adjusts it
 UPs are implemented as sets of rules that use
the INO vocabulary and are applied to INO
instances
 e.g., if user x cannot walk and path p contains a
vertical passage v of type “stairs” then p is
excluded
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NAV Service
 Provides the interface between end-users
and OntoNav
 Receives user requests
 Retrieves user position and location of
destination
 Handles path presentation issues
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GEO Service
 Inputs: (a) a planar graph that accumulates
the floor sub-graphs, (b) user and destination
locations
 Output: all possible walkable paths
 Edges=corridor segments, vertices=exits and
passages (i.e., each location is reduced to a
set of exits or passages)
 Performs a hierarchical clustering in the graph
for more efficient path discovery
 Walkable paths are computed with a graph
traversal algorithm, since no path can be
excluded a priori
 Computational complexity might be a problem
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SEM Service
 Inputs: (a) user profile, (b) all walkable paths
 Output: “best” traversable path (BTP) and its
anchors
 The physical navigation rules and the routing
preferences of the user profile are used for
exclusion of non-traversable paths
 From the remaining paths, the shortest is the
BTP
 The physical and perceptual navigation rules are
applied to BTP in order to select the most
appropriate anchors (landmarks) for its
presentation
 E.g., for a blind or illiterate user, voice-enabled
anchors should be selected along the BTP
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Example: GEO
Destination
5 walkable paths
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Example: SEM
Destination
2 traversable paths
BTP is not the shortest path
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Implementation Issues
 OntoNav is currently in the development
phase using:
 Web Ontology Language (OWL-DL) navigation ontology
 Semantic Web Rules Language (SWRL) - user
profiles
 SweetRules v2.0 - SWRL rules engine
 Racer – OWL reasoning engine
 PostGIS – spatial database
 OntoNav is an advanced application in the
Semantic Web domain with increased
applicability in everyday life
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Presentation Structure
 Introduction
 System Design
 Conclusions
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Added Value of OntoNav
 A purely user-centric navigation system,
that adheres to the Inclusive Design
paradigm
 Based on a hybrid location model
(geographic and semantic) that:
 Enables more advanced interpretations of
distance than the Euclidean one
 Introduces user-defined quality metrics to
the path selection process
 Suitable for “intelligent context-aware
environments”
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Future Work
 Inference of user status for assistance during
the navigation process

e.g., identification of lost, wandering,
stationary, or deviated users
 Decrease computational complexity
 GEO service integrates a graph traversal
which is a greedy algorithm
 Further work: bypass the GEO service and
prune non-traversable paths using only the
semantic model
 OntoNav URL: http://p-comp.di.uoa.gr/projects/ontonav
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