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The Development of a State-Aware Equipment Maintenance Application Using Sensor Data Ranking Techniques

机译:使用传感器数据分级技术开发状态感知设备维护应用程序

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摘要

Billions of electric equipment are connected to Internet of Things (IoT)-based sensor networks, where they continuously generate a large volume of status information of assets. So, there is a need for state-aware information retrieval technology that can automatically recognize the status of each electric asset and provide the user with timely information suitable for the asset management of electric equipment. In this paper, we investigate state-aware information modeling that specializes in the asset management of electric equipment. With this state-aware information model, we invent a new asset state-aware ranking technique for effective information retrieval for electric power and energy systems. We also derive an information retrieval scenario for IoT in power and energy systems and develop a mobile application prototype. A comparative performance evaluation proves that the proposed technique outperforms the existing information retrieval technique.
机译:成千上万的电气设备连接到基于物联网(IoT)的传感器网络,在该网络中,它们不断生成大量资产状态信息。因此,需要一种状态感知信息检索技术,该技术可以自动识别每种电气资产的状态,并为用户提供适合电气设备资产管理的及时信息。在本文中,我们研究专门用于电气设备资产管理的状态感知信息模型。利用这种状态感知信息模型,我们发明了一种新的资产状态感知排序技术,可用于电力和能源系统的有效信息检索。我们还推导了电力和能源系统中IoT的信息检索方案,并开发了移动应用程序原型。通过比较性能评估证明,所提出的技术优于现有的信息检索技术。

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