Semantic Location Based Services for

Smart Spaces

Kostas Kolomvatsos, Vassilis Papataxiarhis, Vassileios Tsetsos

Pervasive Computing Research GroupCommunication Networks Laboratory

Department of Informatics and TelecommunicationsUniversity of Athens – Greece

MTSR ‘07 @ Corfu, GreeceMTSR ‘07 @ Corfu, Greece

Outline

Introduction

Spatial Ontology

GIS metadata and ontology

population

Hybrid Navigation Algorithm

Conclusions

Location Based Services LBS: The core of “smart environments”

Are the most popular context-aware services

Navigation service: One of the biggest challenges due to its complexity

Current Objective Universal and optimized access to LBSs

Advanced user experience

Current Limitation Existing representation techniques lead to incapability

of “smart” management and exploitation of spatial data

Motivation Navigation

Typical representation formalism: spatial graphs Problems

• Multi-criteria search NP-hard• Redesign needed to extend an existing algorithm with

more criteria Conclusion: Traditional algorithmic approaches seem

to fail Proposed solution: Semantic enrichment of LBSLocation Based Services

(LBSs)

+

Semantic Web technologies

Semantic LBS

Spatial Model Indoor Navigation Ontology It describes the basic elements of indoor environment

and the basic relationships between them It facilitates path searching

owl:Thing

Space Point_of_InterestPathObstacle

Exit Entrance

Transition_PointNavigational_Point

Vertical_Passage

Path_PointPassage

Path_Element

Horizontal_Passage Motor_Passage

Description

Junction

Turn_Point

End_Point

Image_Description

Video_Description

Audio_Description

Corridor

Floor

Room

Building Corridor_Segment

Door

Elevator

Escalator

Stairway

Ramp Building_Entrance

Open_Area_Entrance

Closed_Area_Entrance

Room_Entrance

Building_Exit

Open_Area_Exit

Closed_Area_Exit

Room_Exit

DangerousSpaceElements PositioningPoint

http://p-comp.di.uoa.gr/projects/ontonav/INOdoc/index.html

GIS Annotation Layered architecture Each layer corresponds to a

basic concept (or set of concepts) in INO Lower layer : Building blueprints Second layer : Corridors (lines) Points are defined upon corridors

Flo o r M a p

C o rrid o rs

Na vig a tio n Po ints

Ro om Entra nc es

Sta irwa ys

...

Basic point metadata x,y coordinates Floor Id Label, etc.

Ontology Population Spatial Database creation

Transform GIS Layers to Spatial Database Tables Automatic instantiation of INO through GIS metadata

SpatialDatabase

Instances Creation

Algorithm

Flo or M a p

C o rrido rs

Na viga tio n Po ints

Ro om Entra nc e s

Sta irwa ys

...

Ontology Instances

Instances Creation Algorithm

Based on GIS data

The algorithm involves the following steps for all floors in the building:

• Find which points belong to each corridor

• Find the ends of each corridor

• Find the neighbors of each point

• Create the instances in INO classes indicated by the GIS layers and the information extracted in the previous steps

Navigation Algorithm Hybrid rule-based algorithm. Takes into account :

Route complexity Euclidean route distance User profile (capabilities and preferences)

Steps: Create “user compatible” building graph based on user

profile and application of access rules• E.g. WheelChaired_User(?x) ^ Stairway(?y)

isObstacleFor(?y,?x) Find the k-simplest paths Assign the total cost of each path as a function of bonuses

and penalties of the total path distance, preferences and perceptual rules

System Functionality (I)

SpatialDB

Building blueprints (GIS)

Building graph

IndoorNavigation

Ontology (INO)

DataMigration

INOinstances

User profile(capabilities)

User-compatible INO

instances

User-compatible graph

System Functionality (II)

COM SEM

User profile

User location and destination

Best TraversablePath

K-simplestpaths

User-compatible graph

Perceptual Rules

SEM : Semantic Path Selection

PRS

User

PRS : Path Presentation

COM : Complexity Path Computation

Navigation Example

A H: 4 possible paths

1) ACFGH shortest path

2) ABDIH simplest path

3) ABDEFGH, node E: stairs

4) ACFEDIH , node E: stairs

Selected Path: ABDIHA little longer than ACFGH, but

much easier to describe !

Implementation Details ESRI ArcGIS software

PostGIS spatial DB

Protégé Ontology Editor

Knowledge Representation Languages Ontology models in OWL-DL

SWRL rules

Bossam for OWL and SWRL reasoning

Mascopt Library for graph creation and path search

Semantics is not everything

Example: Orientation Issues Two extra properties storing

the real GIS coordinates of each door and not only its projection to the corridor Compute the angle between the

line vertical to user’s direction and the line specified by the user’s position to the door.

If angle θ > 90, the door is on the left side

Else, the door is on the right Similar process for the turns.

Contributions and Open Issues Main Contributions

Semantic representation of GIS metadata with the aid of a spatial ontology

A rule-based hybrid combination of k-simplest paths search algorithm with Euclidean distance and other application parameters like user profile and abilities/preferences.

Support for flexible navigation schemes • Content-based navigation• Presentation-based navigation

Open Issues Immature reasoning engines in terms of performance

and interoperability with rule engines Development/Improvement of tools for spatial ontology

population

QUESTIONS?

Thank you!

http://p-comp.di.uoa.gr