2000 · 1.7K citations · 52 references
Context‑aware computing enables mobile apps to use contextual data such as location, time, nearby devices, and user activity, yet despite a decade of research it remains largely unavailable to everyday users. This survey examines the types of context used, models of context information, systems that collect and disseminate context, and applications that adapt to changing context. The authors systematically reviewed literature on context types, context models, supporting systems, and adaptive applications. The survey shows that context‑aware research is a mature yet rich field, identifies key challenges, and offers solutions to guide future work toward practical deployment.
Context-aware computing is a mobile computing paradigm in which applications can discover and take advantage of contextual information (such as user location, time of day, nearby people and devices, and user activity). Since it was proposed about a decade ago, many researchers have studied this topic and built several context-aware applications to demonstrate the usefulness of this new technology. Context-aware applications (or the system infrastructure to support them), however, have never been widely available to everyday users. In this survey of research on context-aware systems and applications, we looked in depth at the types of context used and models of context information, at systems that support collecting and disseminating context, and at applications that adapt to the changing context. Through this survey, it is clear that context-aware research is an old but rich area for research. The difficulties and possible solutions we outline serve as guidance for researchers hoping to make context-aware computing a reality.
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Context-aware Pervasive System, Engineering, Social Computing +15