Learn to Sense vs. Sense to Learn: A System Self-Integration Approach

D. Guastella, Evangelos Pournaras
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Abstract

The diffusion of Internet of Things (IoT) devices has opened up new opportunities for decentralized data analytics. In this context, data transmission can be affected by both network issues and distance between devices and receivers. These factors can affect the ability to aggregate and analyze data from multiple IoT devices, resulting in noisy, partial, or incorrect information. To this end, self-healing techniques pursue corrective actions when information acquired from sensors is not reliable. In this paper, we propose a new self-integration approach to improve the performance of decentralized self-healing techniques.
学会感知vs.感知学习:一种系统自集成方法
物联网(IoT)设备的普及为分散的数据分析提供了新的机会。在这种情况下,数据传输可能受到网络问题和设备与接收器之间距离的影响。这些因素会影响聚合和分析来自多个物联网设备的数据的能力,从而导致嘈杂、部分或不正确的信息。为此,当从传感器获取的信息不可靠时,自我修复技术会采取纠正措施。在本文中,我们提出了一种新的自集成方法来提高分散自修复技术的性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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