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Survey of Context Information Fusion for Sensor Networks Based Ubiquitous Systems

机译:基于传感器网络的泛在系统上下文信息融合研究

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Sensor Networks produce a large amount of data. According to the needs this data requires to be processed, delivered and accessed. This processed data when made available with the physical device location, user preferences, time constraints; generically called as context-awareness; is widely referred to as the core function for ubiquitous systems. To our best knowledge there is lack of analysis of context information fusion for ubiquitous sensor networks. Adopting appropriate information fusion techniques can help in screening noisy measurements, control data in the network and take necessary inferences that can help in contextual computing. In this paper we try and explore different context information fusion techniques by comparing a large number of solutions, their methods, architectures and models.
机译:传感器网络产生大量数据。根据需要,需要对这些数据进行处理,传递和访问。该处理后的数据在物理设备位置,用户首选项,时间限制下可用;通常称为上下文意识;被广泛称为泛在系统的核心功能。据我们所知,缺乏对普遍存在的传感器网络的上下文信息融合的分析。采用适当的信息融合技术可以帮助筛选嘈杂的测量值,控制网络中的数据,并采取必要的推断来帮助进行上下文计算。在本文中,我们通过比较大量解决方案,其方法,体系结构和模型来尝试探索不同的上下文信息融合技术。

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