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A Pragmatic Approach to Realizing Context-Aware Personal Services Sangkeun Lee, Dongjoo Lee, Seungseok Kang, and Sang-goo Lee School of Computer Science and Engineering Seoul National University, Seoul {liza183, therocks, pyxis81, sglee}@europa.snu.ac.kr ECBS Workshop 2008 Sydney 1 Context-Aware Personal Services Network and computing technologies have improved The number of mobile devices has increased The number of content and service have increased Context Aware-Personal Service • Actively and autonomously adapts and provides the most appropriate service or content to users, accurately interpreting the context without much user supervision. Service Voice recorder Cell phone Content PC Home Network GPS Navigator PDA User Service Content User’s Context Service Digital camera How can we provide the Service most appropriate service or content to users? Content Content Realizing context-aware personal services has become one of the most important issues in pervasive computing Copyright 2008 by CEBT Semantic Tech & Context - 2 Context-Aware Personal Services “In a world of infinite choice, context – not content – is king.” (Listens.com) Context Primary types: identity, location, time, activity Secondary types: all other sources of information, either explicit or implicit, that help us better determine the user’s need Context-aware adaptive, reactive, responsive, situated, context-sensitive, environmentdirected Issues Modeling, Processing, Security & Privacy, Robustness, Scalability & Performance Our Objective To build a practical semantic technology adoption technology for context-aware personal services To present a context-aware personal service framework based on our strategy Copyright 2008 by CEBT Semantic Tech & Context - 3 Survey on Context-Aware Computing Copyright 2008 by CEBT Semantic Tech & Context - 4 Survey on Context-Aware Computing Achieving generality and feasibility at the same time is very difficult Copyright 2008 by CEBT Semantic Tech & Context - 5 Practical Semantic Technology Adoption for Context-Aware Personal Services Some existing approaches represent as much context information as possible in ontology Some previous approaches have attempted to achieve the ideal goal of machines “understanding” user contexts as well as humans do, and have considered the limitations of reasoning systems as problems to be solved in the future. Some existing approaches have relied on complex technologies such as description logics, artificial intelligence, and natural language processing Current existing ontology reasoning systems cannot process the high-level inferences Conventional Approach Practical Approach Focus on what we don’t have upper ontology, powerful inference engines Focus on what we have relational database technology, transactional data, inference engines that have limitations Focus on Inference complex concept hierarchies FOL vs. F-Logic vs. DL Focus on data simple usable concepts low degree of inference Satisfy scientific constraint completeness, decidability Satisfy business value performance, feasibility Copyright 2008 by CEBT Acceptable Performance & Scalability Semantic Tech & Context - 6 A Context-Aware Personal Service Framework – Conceptual Architecture Our framework is designed based on the strategy presented in previous section To enable a flexible and easily extensible context-aware personal service, it is necessary to consider a wide range of issues – Hardware & Network Infrastructure Here, we focus on software technology Copyright 2008 by CEBT Semantic Tech & Context - 7 이상근 Context-Aware Personal Service Process Flow Context Manager controls the abstraction levels of context information based on predefined context rules Request Processor chooses an Dynamic Info. (Activity) Static Info. (Profile) Users Service Providing Define effective algorithm to provide the appropriate content or service, and performs actual services. Contents Recommendation Automatic Device Configuration Seamless Service Home Network PDA PC Digital camera GPS Navigator Device-dependent Context Data (Low-Level) Context Manager Context Rule Integrated Context Data (High-Level) Service Trigger Service Rule Request Request Processor Define Applications Voice recorder Use Service Trigger identifies a match between current context match and a predefined service rule, then triggers a request to the Request Processor Cell phone Select Ranking Algorithm Support Rule Mining Service Providers Data Mining Copyright 2008 by CEBT User DB Music DB Movie DB Log Large amount of video & audio resources in Legacy Database Semantic Tech & Context - 8 A Context-Aware Personal Service Framework – Layer Separation Service Request Layer focuses on context information The system controls the abstraction levels of much low-level information and transforms it into manageable numbers of high-level context information. Our reasoning engine performs inferences with a reasonable amount of context information, thereby increasing performance in this layer. Service Processing Layer manages a number of large-sized content databases such as music and movie databases We assume that the semantics of the content data are relatively less important than the context information and thus use relational database technology. However, simple inferences can still be processed using this method by maintaining well-defined and clean data. Copyright 2008 by CEBT Semantic Tech & Context - 9 Implementation We implemented the prototype of our framework, named CAP(Context-Aware Personalization) in Java XML-RPC protocol Context and Service rule in XML format Simple reasoning engine Simple context data model Several demo scenarios Virtual devices Copyright 2008 by CEBT Semantic Tech & Context - 10 Use Case We were able to construct useful demo scenarios using CAP A is driving his car to the airport. As soon as the fuel-alert indicator lights, the system matches the current context to predefined Gas Station Recommendation Service. Then it triggers Gas Station Recommendation Service, and sends the context information, including location, route, time, and user identification, to the proper service provider. Gas Station Recommendation Service Provider searches the best 10 gas stations, using the user profile data that they have and context that they received from CAP. Then the service provider sends the list of gas stations to the system, which displays the list on the interface in A’s car Acceptable Scalability & Performance because We do not allow complex reasoning or ontology We use simple context-data & rule model We process large number of instances using RDBMS Copyright 2008 by CEBT Semantic Tech & Context - 11 Conclusions & Future Work Conclusions We presented a strategy with respect to conventional technologies, such as relational databases. We emphasized well-defined and clean data, rather than inference itself and mathematical constraints. We presented CAP System that is domain independent, easily extensible, and could be used in various types of context-aware personal services, based on our semantic technology adoption strategy. Finally, we illustrated how CAP was used to support the implementation of a demo context-aware personal service with acceptable performance and scalability. Future Work privacy and security feature rule mining for more intelligent services test and evaluate our system using actual hardware devices. Copyright 2008 by CEBT Semantic Tech & Context - 12 Current CAP System – Server & Client Altitude Sensor Humidity WWW Real World Environment Temperature Pressure Sensor Sensor … Location Device (Client) Device (Client) Device (Client) Device (Client) Virtual Sensor Server Interface GUI Interface Request Processor Context Manager Context Rules Vocabulary Ontology Privacy Manager Privacy Policy Service Trigger Service Repository Legacy System Service Processor Context Data Service Rules Context-aware Service Description Language (CASDL) Log Manager Log Service Description Copyright 2008 by CEBT Semantic Tech & Context - 13 Thank You Thank You 감사합니다 Copyright 2008 by CEBT Semantic Tech & Context - 14