智能城市系统物联网传感

2019 10th IEEE International Conference on Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications (IDAACS) Pub Date : 2019-09-01 DOI:10.1109/IDAACS.2019.8924423

V. Kochan, Oleksandr Matsiuk, N. Kunanets, V. Pasichnyk, Oleksiy Roshchupkin, A. Sachenko, I. Turchenko, O. Duda, V. Semaniuk, Svitlana Romaniv

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摘要

物联网(IoT)包括大量具有各种物理量、工作原理和参数的传感器。在这种情况下，传感器误差传统上在测量通道中占主导地位。本文讨论了利用神经网络提高传感器精度的一般方法。由于属性的泛化，神经网络可以显著提高传感器的精度，同时降低了转换到单个变换函数的复杂性。

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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Sensing in IoT for Smart City Systems

The Internet of Things (IoT) includes a large set of sensors of various physical quantities, operating principles and parameters. In this case, sensor errors are traditionally dominant in measuring channels. In this paper general methods of increasing the accuracy of sensors using neural networks are considered. Due to the generalization of properties, neural networks can significantly improve the accuracy of sensors with reduced complexity of the transition to their individual transformation functions.

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2019 10th IEEE International Conference on Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications (IDAACS)

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