Context Aware Computing for The Internet of Things: A Survey
Context Aware Computing for The Internet of Things: A Survey
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DOI：
10.1109/surv.2013.042313.00197
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发表时间：
2014-01-01
影响因子：
35.6
通讯作者：
Georgakopoulos, Dimitrios
中科院分区：
文献类型：
--
作者：
Perera, Charith;Zaslavsky, Arkady;Georgakopoulos, Dimitrios
随着我们向物联网（IoT）迈进，世界各地部署的传感器数量正在快速增长。市场研究表明，传感器部署在过去十年中显着增长，并预测未来的增长率将显著增加。这些传感器不断产生大量的数据。然而，为了增加原始传感器数据的价值，我们需要了解它。与传感器数据相关的上下文的收集、建模、推理和分布在这一挑战中起着关键作用。上下文感知计算已被证明在理解传感器数据方面是成功的。在本文中，我们从物联网的角度调查上下文感知。我们在开始时通过介绍物联网范式和上下文感知基础来介绍必要的背景。然后对上下文生命周期进行了深入分析。我们评估了一个项目子集（50个），这些项目代表了过去十年（2001-2011）在上下文感知计算领域提出的大多数研究和商业解决方案。最后，根据我们的评估，我们强调了过去的经验教训和未来可能的研究方向。该调查涉及与上下文感知和物联网相关的广泛技术、方法、模型、功能、系统、应用程序和中间件解决方案。我们的目标不仅是分析、比较和巩固过去的研究工作，而且还要欣赏他们的发现并讨论他们对物联网的适用性。
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.