Investigation on big data evaluation and visualization of internet of things based on edge computing

Q4 Engineering
Qiwen Long
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引用次数: 0

Abstract

With the rapid development and popularization of Internet of Things (IoT) technology, a large number of IoT devices have generated massive amounts of data. In order to efficiently process and analyze this data and extract valuable information from it, the analysis and visualization of Big Data (BD) of the IoT based on Edge Computing (EC) has become a hot topic in current research. How to efficiently process and analyze these data has become a current research hot topic. Based on EC technology, this paper used a solution for BD analysis and visualization of the IoT. This paper used Sobel operator and edge extraction algorithm to analyze the BD analysis and visualization research of the IoT based on EC. Firstly, useful information in the image is extracted through the Sobel operator to improve image quality, in order to better understand and utilize image data; Then, edge extraction algorithms are used to quickly and accurately extract the edge information of the image for subsequent data processing and analysis. This scheme used EC nodes to preliminary process and analyze the data, reduced the burden of the central server, and improved the response speed and real-time performance. At the same time, this article also designed a visualization platform to display the analysis results in the form of charts, making it easy for users to intuitively understand the data situation. The experimental results showed that the score of data and information visualization results based on EC was between 89 and 95. The research results showed that the IoT BD analysis and visualization research method based on EC could effectively improve the efficiency and accuracy of IoT data processing and achieve more intuitive data display through experiments. BD analysis and visualization technology can rely on IoT devices to extract useful information and knowledge, and help users better achieve monitoring, control, and decision support for IoT devices.

基于边缘计算的物联网大数据评估与可视化研究
随着物联网(IoT)技术的快速发展和普及,大量物联网设备产生了海量数据。为了高效处理和分析这些数据并从中提取有价值的信息,基于边缘计算(EC)的物联网大数据(BD)分析和可视化已成为当前研究的热点。如何高效地处理和分析这些数据已成为当前的研究热点。本文基于边缘计算技术,提出了一种物联网大数据分析与可视化解决方案。本文使用 Sobel 算子和边缘提取算法来分析基于 EC 的物联网 BD 分析和可视化研究。首先,通过Sobel算子提取图像中的有用信息,提高图像质量,以便更好地理解和利用图像数据;然后,利用边缘提取算法快速准确地提取图像的边缘信息,以便后续的数据处理和分析。该方案利用 EC 节点对数据进行初步处理和分析,减轻了中心服务器的负担,提高了响应速度和实时性。同时,本文还设计了一个可视化平台,以图表的形式展示分析结果,方便用户直观地了解数据情况。实验结果表明,基于EC的数据信息可视化结果得分在89分至95分之间。研究结果表明,基于EC的物联网北斗分析与可视化研究方法能有效提高物联网数据处理的效率和准确性,并通过实验实现更直观的数据展示。北斗分析与可视化技术可以依托物联网设备提取有用的信息和知识,帮助用户更好地实现对物联网设备的监测、控制和决策支持。
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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来源期刊
Measurement Sensors
Measurement Sensors Engineering-Industrial and Manufacturing Engineering
CiteScore
3.10
自引率
0.00%
发文量
184
审稿时长
56 days
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