Springer Mobile Context Awareness

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. From the Back Cover 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.