1. Collaborative Context Recognition for Mobile Devices Software for Context-Aware Multi-User Systems Professor Joao Sousa David Gonzalez

2. Overview Summary of Huuskonen CCR Theory Abstract. Model Interpretation. Implementation Close look. Long-term context Related works. Recommendations.

3. Theory Abstract Once upon a time.... Mobile Devices(MD) were too limited(e.g. Power computing, Energy dependent, not common). Well, still is like that but they are “ubiquitous”. PCs are not “wearable”, but MDs are. MD User Interface are limited, but they are Communication Hubs.

4. Theory Abstract Human Computer Interaction(HCI) must integrate Sensors to engage a real Context experience. Sense of:  Location  Social Situation  Tasks  Activities Must be easy to the user, but the implementation is not trivial.

5. Theory Abstract Context Awareness (CA): Humans are a “Rank-A” CA animals, because:  We use CA for primitive functions like Survival, Reproduction and Subsistence.  Imitate and Learn is a common behavior, so We are Context-driven individuals. The issue is how transfer this to Machines.

6. Simple Model for Human Behavior CA Lost Doubt Do Ask Imitate

7. Mobile Context Awareness This is the first step to allow CCR. It merges IA and HCI. Examples:  Location  Environmental Sensors  Biometrics  Acceleration sensors  Multimedia

8. Application Area Geomarketing Jaiku Clarity Brickstream Nintendo 3DS Latitude by Google

9. Long-term goal State CCR as part of global Initiative. This is not isolated research, but a common effect of Computing Paradigm Shift. Establish improvements to the current architecture. Till now the architectures work, but lack of new frameworks to ease the inherent flexibility of this kind of systems.

10. Model Interpretation A CCR Looks like: Context Awareness Context Recognition Context Reasoning Sensors signals ProcessMethod Signal Processin g Weighted Voting Protocol CCR Server

11. Model Interpretation A CCR System Looks like: Context Awareness Context Recognition Context Reasoning Sensors signals ProcessActor Mobile Device Mobile Device Group CCR Server

12. Implementation Close look Symbian S60, IOS Apache Tomcat Windows, Linux Actor Mobile Devices CCR Server

13. Development up to present State CCR as part of global Initiative: 2008, Bannach – Context Recognition Network 2005, Sung & Blum – Wearable computing 2003, Huuskonen – CCR for MD

14. Recommendations New SW Platforms are requires, in this particular case: Android. Stronger Architecture are required in the Business layer, specifically Web Services. Ontologies are proposed, not yet implemented.

15. Architecture ideas Data Access Business Presentation Data Mining for new Contexts rules More Flexibility and spreadable with Web Services Rich User Interfaces, Context Aware like DK