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Ontology-based data semantic management and application in IoT- and cloud-enabled smart homes

机译：基于本体的数据语义管理和在支持IoT和云的智能家居中的应用

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摘要

The application of emerging technologies of Internet of Things (IoT) and cloud computing have increasing the popularity of smart homes, along with which, large volumes of heterogeneous data have been generating by home entities. The representation, management and application of the continuously increasing amounts of heterogeneous data in the smart home data space have been critical challenges to the further development of smart home industry. To this end, a scheme for ontology-based data semantic management and application is proposed in this paper. Based on a smart home system model abstracted from the perspective of implementing users' household operations, a general domain ontology model is designed by defining the correlative concepts, and a logical data semantic fusion model is designed accordingly. Subsequently, to achieve high-efficiency ontology data query and update in the implementation of the data semantic fusion model, a relational-database-based ontology data decomposition storage method is developed by thoroughly investigating existing storage modes, and the performance is demonstrated using a group of elaborated ontology data query and update operations. Comprehensively utilizing the stated achievements, ontology-based semantic reasoning with a specially designed semantic matching rule is studied as well in this work in an attempt to provide accurate and personalized home services, and the efficiency is demonstrated through experiments conducted on the developed testing system for user behavior reasoning.
机译：物联网（IoT）和云计算等新兴技术的应用增加了智能家居的普及，与此同时，家庭实体已在生成大量异构数据。智能家居数据空间中不断增加的异构数据数量的表示，管理和应用一直是智能家居行业进一步发展的关键挑战。为此，提出了一种基于本体的数据语义管理和应用方案。基于从实现用户家庭操作的角度抽象的智能家居系统模型，通过定义相关概念设计通用领域本体模型，并据此设计逻辑数据语义融合模型。随后，为了在数据语义融合模型的实现中实现高效的本体数据查询和更新，通过深入研究现有的存储模式，开发了一种基于关系数据库的本体数据分解存储方法，并通过一组实例进行了演示。详细的本体数据查询和更新操作。综合利用所陈述的成就，在这项工作中还研究了具有特殊设计的语义匹配规则的基于本体的语义推理，以期提供准确和个性化的家庭服务，并通过在已开发的测试系统上进行的实验来证明效率。用户行为推理。

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