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CONCEPT HIERARCHIES FOR SENSOR DATA FUSION IN THE COGNITIVE IoT

机译:认知物联网中传感器数据融合的概念层次结构

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Sensor data fusion refers to technological solutions aiming at collecting, classifying and complementing data coming from multiple sensors. It has the potential of enabling context awareness which, on the other hand, represents a huge potential to be exploited in the field of IoT applications. Sensor fusion and IoT have to deal with multi-faced issues like heterogeneity, sensor/actuator management, data accuracy and reliability. This paper proposes a multi-tier approach dealing with sensor fusion and IoT aspects in a modular way. The approach relies on the use of the agent metaphor, statecharts and on the Rainbow multi-agent platform. Agents can be dynamically added and removed from an application thus promoting system openness and scalability. Heterogeneity and distribution issues are transparently managed by Rainbow which hides the physical layer on top of which the applications are built. As a significant case study, the approach was exploited for the implementation of a working prototype devoted to improve security of some artworks (statues) of the MAB museum located in the city of Cosenza, Italy.
机译:传感器数据融合是指旨在收集,分类和补充来自多个传感器的数据的技术解决方案。另一方面,它具有启用上下文意识的潜力,它代表了在物联网应用领域中利用的巨大潜力。传感器融合和物联网必须处理异质性,传感器/执行器管理,数据准确性和可靠性等多面问题。本文提出了一种以模块化方式处理传感器融合和物联网方面的多层方法。该方法依赖于代理隐喻,StateCharts和彩虹多代理平台的使用。可以从应用程序动态添加和移除代理,从而促进系统开放性和可扩展性。通过彩虹透明地管理异质性和分布问题,其隐藏在构建应用程序的顶部的物理层。作为一个重要的案例研究,该方法被利用,实施了一个工作原型,以改善位于意大利Cosenza市的MAB博物馆的一些艺术品(雕像)的安全性。

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