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A Semantic Context Service for Smart Offices

机译:智能办公室的语义上下影服务

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Smart Home environments aim to integrate physical devices, human beings and computing entities in homes and buildings. They have to support characteristics coming from mobile computing, ubiquitous computing and sensor networking in order to provide intelligent, context-aware and pro-active applications. In this vision, "context" plays a central role; but, the raw context data, obtained by various data sources, are represented in heterogeneous formats and thus it's not possible to understand their meanings without a prior knowledge of the particular context information model. Therefore, data sources are not able to produce high-level context information, but provide only raw information. Such low-level information should be combined in order to generate higher-level context information. In this paper we propose a Semantic Context Service, that exploits Semantic Web technologies to support Smart Offices. In particular, this service relies on ontologies and rules to classify several typologies of entities, which can be involved in smart homes and offices, and to infer higher-level context information from low-level information coming from positioning systems and sensors in the physical environments.
机译:智能家庭环境旨在将物理设备,人类和建筑物中的计算实体集成在一起。它们必须支持来自移动计算的特征,普遍存在的计算和传感器网络,以便提供智能,背景感知和积极的应用程序。在这种愿景中,“背景”起着核心作用;但是,由各种数据源获得的原始上下文数据以异构格式表示,因此在没有特定上下文信息模型的先验知识的情况下,不可能理解其含义。因此,数据源无法生成高级上下文信息,但仅提供原始信息。应该组合这样的低级信息以生成更高级别的上下文信息。在本文中,我们提出了一个语义上下影服务,用于利用语义网络技术来支持智能办公室。特别是,此服务依赖于本体和规则来分类各个实体的几个类型,这些类型可以参与智能家庭和办公室,并从来自物理环境中的定位系统和传感器的低级信息推断出更高级别的上下文信息。

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