2,498 research outputs found

    Delivering real-world ubiquitous location systems

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    Location-enhanced applications are poised to become the first real-world example of ubiquitous computing. In this paper, we emphasize the practical aspects of getting location-enhanced applications deployed on existing devices, such as laptops, tablets, PDAs, and cell phones, without the need to purchase additional sensors or install special infrastructure. Our goal is to provide readers with an overview of the practical considerations that are currently being faced, and the research challenges that lie ahead. We ground the article with a summary of initial work on two deployments of location- enhanced computing: multi-player location-based games and a guide for the Edinburgh Festival

    Mobile crowd sensing: enabling technologies and applications

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    Mobility and Travel Behaviour Data Collection

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    Context Aware Computing for The Internet of Things: A Survey

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    As we are moving towards the Internet of Things (IoT), the number of sensors deployed around the world is growing at a rapid pace. Market research has shown a significant growth of sensor deployments over the past decade and has predicted a significant increment of the growth rate in the future. These sensors continuously generate enormous amounts of data. However, in order to add value to raw sensor data we need to understand it. Collection, modelling, reasoning, and distribution of context in relation to sensor data plays critical role in this challenge. Context-aware computing has proven to be successful in understanding sensor data. In this paper, we survey context awareness from an IoT perspective. We present the necessary background by introducing the IoT paradigm and context-aware fundamentals at the beginning. Then we provide an in-depth analysis of context life cycle. We evaluate a subset of projects (50) which represent the majority of research and commercial solutions proposed in the field of context-aware computing conducted over the last decade (2001-2011) based on our own taxonomy. Finally, based on our evaluation, we highlight the lessons to be learnt from the past and some possible directions for future research. The survey addresses a broad range of techniques, methods, models, functionalities, systems, applications, and middleware solutions related to context awareness and IoT. Our goal is not only to analyse, compare and consolidate past research work but also to appreciate their findings and discuss their applicability towards the IoT.Comment: IEEE Communications Surveys & Tutorials Journal, 201
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