Semantic Location Based Services for Smart Spaces Kostas Kolomvatsos, Vassilis Papataxiarhis, Vassileios Tsetsos P ervasive C omputing R esearch G roup C ommunication N etworks L aboratory Department of Informatics and Telecommunications University of Athens – Greece MTSR 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 LBS Location 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

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 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 Spatial Database Instances Creation Algorithm 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) Spatial DB Building blueprints (GIS) Building graph Indoor Navigation Ontology (INO) Data Migration INO instances User profile (capabilities) User-compatible INO instances User-compatible graph

System Functionality (II) COM SEM User profile User location and destination Best Traversable Path K-simplest paths 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: ABDIH A 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

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