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Ubiquitous environments generate large quantities of data, originating from backend servers, portable devices and wireless mobile sensors. Pervasive sensing devices that monitor properties of the environment (including human beings) can produce a large data source. The unprocessed datasets may include data that is faulty and irrelevant, and data that is important and useful. If not managed correctly the large amount of data from a data-rich pervasive environment may result in information overload or delivery of incorrect information. Context-sensitive quality data management aims to gather, verify, process, and manage the multiple data sources in a pervasive environment in order to deliver high quality, relevant information to the end user. Managing the quality of data from different sources, correlating related data and making use of context are all essential in providing end users with accurate and meaningful data in real-time. This requirement is especially true for critical applications such as in a medical environment. This thesis presents the Data Management System (DMS) architecture. It is designed to deliver a quality of data service to its users. The DMS architecture employs an agent based middleware to intelligently and effectively manage all pervasive data sources, and to make use of context to deliver relevant information to the end-user. DMS components have been designed to manage: data validation; data consistency; context-based data delivery; knowledge management and distributed processing. The DMS components have been rigorously evaluated using various medical-based test cases. This thesis demonstrates a careful, precise approach to data based on the quality of the data and the context of its use. It emphasises the DMS architecture and the role of software agents in providing quality data management.
This book contributes to illustrating the methodological and technological issues of data management in Pervasive Systems by using the DataBenc project as the running case study for a variety of research contributions: sensor data management, user-originated data operation and reasoning, multimedia data management, data analytics and reasoning for event detection and decision making, context modelling and control, automatic data and service tailoring for personalization and recommendation. The book is organized into the following main parts: i) multimedia information management; ii) sensor data streams and storage; iii) social networks as information sources; iv) context awareness and personalization. The case study is used throughout the book as a reference example.
Pervasive Computing: Next Generation Platforms for Intelligent Data Collection presents current advances and state-of-the-art work on methods, techniques, and algorithms designed to support pervasive collection of data under ubiquitous networks of devices able to intelligently collaborate towards common goals. Using numerous illustrative examples and following both theoretical and practical results the authors discuss: a coherent and realistic image of today’s architectures, techniques, protocols, components, orchestration, choreography, and developments related to pervasive computing components for intelligently collecting data, resource, and data management issues; the importance of data security and privacy in the era of big data; the benefits of pervasive computing and the development process for scientific and commercial applications and platforms to support them in this field. Pervasive computing has developed technology that allows sensing, computing, and wireless communication to be embedded in everyday objects, from cell phones to running shoes, enabling a range of context-aware applications. Pervasive computing is supported by technology able to acquire and make use of the ubiquitous data sensed or produced by many sensors blended into our environment, designed to make available a wide range of new context-aware applications and systems. While such applications and systems are useful, the time has come to develop the next generation of pervasive computing systems. Future systems will be data oriented and need to support quality data, in terms of accuracy, latency and availability. Pervasive Computing is intended as a platform for the dissemination of research efforts and presentation of advances in the pervasive computing area, and constitutes a flagship driver towards presenting and supporting advanced research in this area. Indexing: The books of this series are submitted to EI-Compendex and SCOPUS Offers a coherent and realistic image of today’s architectures, techniques, protocols, components, orchestration, choreography, and development related to pervasive computing Explains the state-of-the-art technological solutions necessary for the development of next-generation pervasive data systems, including: components for intelligently collecting data, resource and data management issues, fault tolerance, data security, monitoring and controlling big data, and applications for pervasive context-aware processing Presents the benefits of pervasive computing, and the development process of scientific and commercial applications and platforms to support them in this field Provides numerous illustrative examples and follows both theoretical and practical results to serve as a platform for the dissemination of research advances in the pervasive computing area
This book constitutes the thoroughly refereed post-conference proceedings of the first International Workshop on Quality of Context, QuaCon 2009, held in Stuttgart, Germany, in June 2009. The 11 revised papers presented were carefully reviewed and selected from 19 submissions and included in the volume together with 5 invited papers. Discussed are interdisciplinary approaches to context quality, such as models for degradation and consistency of context data, spatial ontologies and spatial data mining, trust in context data, methods and calculi for context quality assessment, frameworks and metrics for context quality, uncertainty in sensor data processing, quality-aware algorithms for context management, quality-aware event and stream processing, uncertainty in reasoning on context data, application-specific context quality and case studies, and visualization of context quality.
The book addresses the impact of ambient intelligence, particularly its user-centric context-awareness requirement on data management strategies and solutions. Techniques of conceptualizing, capturing, protecting, modelling, and querying context information, as well as context-aware data management application are discussed, making the book is an essential reference for computer scientists, information scientists and industrial engineers.
This volume contains the proceedings of Pervasive 2002, the ?rst in a series of international conferences on Pervasive Computing. The conference took place at ETH Zurich from August 26to 28, 2002. Its objective was to present, discuss, and explore the latest technical developments in the emerging ?eld of pervasive computing, as well as potential future directions. Pervasive Computing is a cross-disciplinary area that extends the appli- tion of computing to diverse usage models. It covers a broad set of research topics such as low power, integrated technologies, embedded systems, mobile - vices, wireless and mobile networking, middleware, applications, user interfaces, security, and privacy. The great amount of interest we are witnessing in Per- sive Computing is driven by relentless progress in basic information technologies such as microprocessors, memory chips, integrated sensors, storage devices, and wireless communication systems that continue to enable ever smaller, lighter, and faster systems. Such systems are also becoming a?ordable due to their high integration and mass production, paving the way for their adoption.
Provides research developments on mobile technologies and services. Explains how users of such applications access intelligent and adaptable information services, maximizing convenience and minimizing intrusion.
This paper presents a framework to address new data management challenges introduced by data-intensive pervasive computing environments. These challenges include a spatio-temporal variation of data and data source availability lack of a global catalog and schema and no guarantee of reconnection among peers due to the serendipitous nature of the environment. An important aspect of our solution is to treat devices as semi-autonomous peers guided in their interactions by profiles and context. The profiles are grounded in a semantically rich language and represent information about users. devices and data described in terms of "beliefs", "desires", and "intentions". We present a prototype implementation of this framework over combined Bluetooth and Ad-Hoc 802.11 networks. and present experimental and simulation results that validate our approach and measure system performance.
This year marks the third edition of EuroSSC. It builds on the success of the past editions, held in Enschede, The Netherlands in 2006, and in Kendal, UK in 2007. On behalf of the Organizing Committee, we would like to welcome you to EuroSSC 2008, in Zurich, Switerland. This volume contains the invited papers and technical peer-reviewed papers selected for presentation at the conference. At EuroSSC we aim to explore technologies, algorithms, architectures, p- tocols, and user aspects underlying context-aware smart surroundings, coop- ating intelligent objects, and their applications. Since its inception, EuroSSC has taken a complementary technology-driven and user-driven view to discuss these aspects. It is one of the particularities of EuroSSC, and the 2008 edition made no exception. In addition we emphasized aspects related to quality of c- text and context-aware feedback by actuator systems. This re?ects the growing importance that context processing in uncertain environments and sensor and actuator networks take in ambient intelligence environments. We received 70 paper submissions. They originate from 30 countries of - rope, the Middle East and Africa (66%), Asia (22%), North America (9%), and South America (3%). These numbers re?ect the European origins of EuroSSC, but also show that EuroSSC is a recognized and attractive platform for parti- pants from all regions of the world.
This book constitutes the thoroughly refereed proceedings of the Second International Conference on Context-Aware Systems and Applications, ICCASA 2013, held in Phu Quoc Island, Vietnam in November 2013. The 36 revised full papers presented were carefully selected and reviewed from over 100 submissions and cover a wide spectrum of issues in the area of context-aware systems (CAS) and context-based recommendation systems.