Ambient Intelligence -

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Résumé :
This volume of the LNCS is the formal proceedings of the 2nd European Symposium on Ambient Intelligence, EUSAI 2004. This event was held on November 8?10, 2004 at the Eindhoven University of Technology, in Eindhoven, the Netherlands. EUSAI 2004 followed a successful first event in 2003, organized by Philips Research. This turned out to be a timely initiative that created a forum for bringing together European researchers, working on different disciplines all contributing towards the human-centric technological vision of ambient intelligence. Compared to conferences working on similar and overlapping fields, the first EUSAI was characterized by a strong industrial focus reflected in the program committee and the content of the program. As program chairs of EUSAI 2004 we tried to preserve the character for this event and its combined focus on the four major thematic areas: ubiquitous computing, context awareness, intelligence, and natural interaction. Further, we tried to make EUSAI 2004 grow into a full-fledged double-track conference, with surrounding events like tutorials and specialized workshops, a poster and demonstration exhibition and a student design competition. The conference program included three invited keynotes, Ted Selker from MIT, Tom Rodden from the University of Nottingham and Tom Erickson from IBM.

Sommaire:
Ubiquitous Computing: Software Architectures, Communication, and Distribution.- Super-distributed RFID Tag Infrastructures.- Using Ontologies to Address Key Issues in Ubiquitous Computing Systems.- Performance Evaluation of Personal Agent Migration Policies in an Ambient Use Case Scenario.- QoS Provision Using Dual RF Modules in Wireless LAN.- Using Cooperative Artefacts as Basis for Activity Recognition.- Privacy Protection in Memory-Based Collaborative Filtering.- Context-Aware, Ontology-Based Service Discovery.- Context-Based Service Access for Train Travelers.- System for Monitoring and Coaching of Sportsmen.- From Imagination to Experience: The Role of Feasibility Studies in Gathering Requirements for Ambient Intelligent Products.- Context Sensing and Machine Perception.- Using Integration Frameworks for Developing Context-Aware Applications.- A Generic Topology for Ambient Intelligence.- A Distributed Location Sensing Platform for Dynamic Building Models.- Distributed Feature Extraction for Event Identification.- Towards an Extensible Context Ontology for Ambient Intelligence.- Integrating Handhelds into Environments of Cooperating Smart Everyday Objects.- Remote Code Execution on Ubiquitous Mobile Applications.- The PLANTS System: Enabling Mixed Societies of Communicating Plants and Artefacts.- Multiple User Profile Merging (MUPE): Key Challenges for Environment Awareness.- Human Computer Interaction in Ambient Intelligence Environments.- Towards a Playful User Interface for Home Entertainment Systems.- Shaping the Ambience of Homes with Domestic Hypermedia.- Tangible Computing in Everyday Life: Extending Current Frameworks for Tangible User Interfaces with Personal Objects.- End-User Configuration of Ambient Intelligence Environments: Feasibility from a User Perspective.- VIEWs: Visual Interaction Enriched Windows.- Information Capture Devices for Social Environments.- Rich Interaction: Issues.- From Metaphors to Simulations to Idioms: Supporting the Conceptualisation Process.- Algorithms, Ontologies, and Architectures for Learning and Adaptation.- CAMELEON-RT: A Software Architecture Reference Model for Distributed, Migratable, and Plastic User Interfaces.- A Fair Energy Conserving Routing Algorithm for Wireless Sensor Networks.- Distance-Based Access Modifiers Applied to Safety in Home Networks.- AmbieSense - A System and Reference Architecture for Personalised Context-Sensitive Information Services for Mobile Users.- Realising the Ambient Intelligence Vision Through the Deployment of Mobile, Intentional Agents.- Ambient Intelligence Using KGP Agents.- Services Platforms for Context-Aware Applications.- Modelling Context: An Activity Theory Approach.- Confidence Estimation of the State Predictor Method.