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Towards a Context-aware Middleware in Smart Car Space

机译:迈向智能汽车空间中的背景知识中间件

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Cars have become an increasingly important and exciting test bed for ubiquitous computing. However, smart car space is still little addressed in the literature to enable high adaptation in a mobile and resource-limited space. This paper focuses on building a context-aware software infrastructure for smart car space in middleware framework. To support context-awareness, we embed capabilities of context modeling and context reasoning. We apply a three-layer manner, including sensor, context atom, and context situation, to efficiently acquire and process contexts. We implement rule-based reasoning in our prototype. We evaluate the performance, and show the proposed middleware is promising.
机译:汽车已成为无处不在的计算越来越重要和令人兴奋的试验台。然而,在文献中仍然很少地解决了智能汽车空间,以实现在移动和资源有限的空间中的高适应性。本文侧重于构建中间件框架中的智能汽车空间的背景感知软件基础架构。为了支持上下文意识,我们嵌入了上下文建模和上下文推理的能力。我们应用了三层方式,包括传感器,上下文原子和情境情况,以有效地获取和处理上下文。我们在原型中实施基于规则的推理。我们评估表现,并显示所提出的中间件是有前途的。

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