This book explores the application of machine learning techiques to problems of classification, showing how they can be decomposed into much simpler sub-problems, and demonstrating how this approach often leads to improved classification performance.

Mobile context-awareness is a popular research trend in the field of ubiquitous computing. Advances in mobile device sensory hardware and the rise of 'virtual' sensors such as web application programming interfaces (APIs) mean that the mobile user is exposed to a vast range of data that can be used for new advanced applications. Mobile Context Awareness presents work from industrial and academic researchers, focusing on novel methods of context acquisition in the mobile environment particularly through the use of physical and virtual sensors along with research into new applications utilising this context. In addition, the book provides insights into the technical and usability challenges involved in mobile context-awareness, as well as observations on current and future trends in the field.

With contributions by international experts from both academia and industry Contains methods and algorithms to solve unique problems in mobile context-awareness A focus on empiricism: many chapters contain results of evaluations in the field Includes supplementary material: sn.pub/extras

Klappentext

The importance of context in computer science has increased in recent decades as computers have become ever more pervasive in everyday life. Context awareness the idea that computers can sense and react to a user's situation has been a popular research topic for a number of years. Its appeal lies in a variety of areas, notably through making users' lives easier by relieving task burden, such as when searching for nearby shops, restaurants or transportation links.

One of the most ubiquitous tools in the progress of context awareness has been the mobile device; its enormous popularity and permeation into daily life coupled with increasingly sophisticated hardware has greatly improved the potential for context awareness in the world. The very mobility of these devices is key to the idea of mobile context awareness, where the sensing and reacting is enabled by, and even conducted upon, the device itself.

The motivation behind this book is threefold: to explore the capabilities, challenges, and applications of mobile context awareness. In addition to the mobility that smartphones and similar devices bring to context awareness, we explore the capabilities that these mobile devices offer, the problems or challenges that they might introduce, and the applications and use cases for which mobile devices play a key part.

With contributions from both academia and industry experts, Mobile Context Awareness serves as a collection of research around these important topics, providing an interesting, informative and comprehensive overview of the subject at present, as well as insights into the future developments of the field.

Inhalt

Foreword.- Introduction.- Modeling Success, Failure, and Intent of Multi-Agent Activities Under Severe Noise.- Energy Accuracy Trade-offs of Sensor Sampling in Smart Phone based Sensing Systems.- Acceleration Noise Correction for Transfer Inference Using Accelerometers on Mobile Devices.- Mobile Sensing of User's Motion and Position Context for Automatic Check-in Suggestion and Validation.- The Case for Context-Aware Resources Management in Mobile Operating Systems.- A Scalable Sensor Middleware for Social End-User Programming.- Mobile Context-Aware Support for Public Transportation Systems.- Quality Sensitive Web Service Profiling and Discovery: In support of Mobile and Pervasive Applications.- A Middleware Supporting Adaptive and Context-Aware Mobile Applications.