A Context Framework for Ambient Intelligence

1. A Context Framework for Ambient Intelligence A. Dogac, G. B. Laleci, Y. Kabak Middle East Technical University

2. Context servers AmI Web Services Motivation interoperable User Context Machine processable Security & privacy

3. Ambient Intelligence • Ubiquitous computing • Ubiquitous communication • Intelligent User Friendly Interfaces • Better integration of technology into our environment, so that people can freely and interactively use it • Seamless (and secure) delivery of services and applications

4. Characteristics of AmI • Awareness • ability of the system to locate and recognize objects and people, their locations, and their needs • Intelligence • allows the system to analyze the context, adapt to people that live in it, learn from their behavior, and eventually to recognize as well as show emotion • Adaptable • learn about the environment and the people within it in order to optimize their own behavior User Context

5. User Context • Any information that can be used to characterize the user and her situation • Coming from sensors • Temporal and spatial location • Environmental attributes • Resources nearby • Physiological measurements • User preferences and profile • Schedule, agenda • Social context

6. An Example Scenario (from ISTAG) • Maria lands to an airport in a Far Eastern Country • The immigration officer replaced by a device • Through its sensors, detects identities, performs visa and passport control (using Maria’s P-Com) • A rented car waiting for her at the exit • Her Hotel has been reserved by her personal software agent

7. Context servers P-Com queries Issues to be considered • Identity information should be understandable by any authorized device • Identity information • Passport and visa information • Machine proccesable • Interoperable • Context Ontologies should be developed

8. Issues to be considered • Privacy • Access should be limited to authorized entities • The user should be able to state how much information to disclose and to whom • Immigration device • Location, visa, passport information • Role or personal identity based privacy mechanisms

9. Issues to be considered • The context servers needs to recognize the device type • It should be possible to exploit context to discover and compose Web Services

10. Proposed System Architecture

11. Context Ontology • Have formal specification • Machine processable • Can be queried through query languages • Define shared conceptualizations • Captures consensual knowledge • Enable knowledge sharing in an open and dynamic distributed system

12. Class Subclass Subclass properties properties Context Ontology • Define all of the concepts in a taxonomic hierarchy • Define the properties and allowed values (facets) • Define the relationships among the classes • Provides a means for intelligent agents to reason about the contextual information

13. Web Ontology Language OWL • OWL is a semantic markup language being developed by the World Wide Web Consortium • for publishing and sharing ontologies • derived from DAML+OIL

14. Security and Privacy Issues • Ontologies are stored in knowledge-bases • Data coming from sensor devices • Solar System (Minami & Kotz) • Data coming from the context server • Limited to authorized entities • Should be possible to state how much information will be disclosed to whom

15. Security and Privacy Issues • View mechanism • Define views on the user context and grant access rights to different users • CREATE CLASS VIEW ScheduleOfMaria SUBCLASSOF Schedule SELECT X FROM ContextServer WHERE X.Name= “Maria” GRANT SELECT ON ScheduleOfMaria TO PersonalAgentOfMaria • KAON server (http://kaon.semanticweb.org)

16. Exploiting User Context for Web Service Discovery • For selecting services in a context-sensitive manner • Services should be discovered based on their semantic descriptions • Agents should • Query the context of the user • Maps the preferences of the user with the properties of the services advertised

17. Web Service Discovery • ebXML registry allows metadata to be stored in the registry through Classification mechanisms

18. An Example Travel Ontology TravelService Transportation Service Accommodation Service Entertainment Service AirTransportation ReserveAFlight BuyATicket Properties of the Generic Service Class originatingFrom destinationTo paymentMethod

19. ReserveAFlight originatingFrom destinationTo paymentMethod Relating Services with Ontologies MyService

20. ebXML Registry Service Ontology defined in class hierarchies through OWL An example scenario Understands she doesn’t have a valid visa Checks her Calendar Checks her Profile Finds the service and its WSDL link Queries for the visa service of the Country Starts arranging her trip invokes Retrieves WSDL desc.

21. Travel Service Passport Service Visa Service Transportation Service Accommodation Service Entertainment Service Air Transfer Land Transfer Sea Transfer ebXML Registry Service Ontology defined in class hierarchies through OWL Domain expert An example scenario Prefers air transfer, collects mileage from THY Queries for the THY reservation service Finds the service and its WSDL link Checks her Preferences Checks her Profile consults invokes Retrieves WSDL desc.

22. Conclusions • AmI combine • Ubiquity, context-awareness, intelligence and natural interaction • There is a need for strong mechanisms for storing and processing context • Context Ontologies

23. Conclusions • To be acceptable AmI should provide • Security • Privacy • Role-based access to context servers • AmI should exploit user Context for reacting user needs automatically • Web Service discovery and composition based on semantics

24. Thank you for your Attention Any Questions?