Public Information Dissemination Using Data Mining-Enabled Image Enhancement and Internet of Things

With the development of the Internet of Things, the requirement of a wide range of human-centered services may now make use of as many computing resources for media technologies and holographic images. The IoT system can monitor the status of equipment in real-time with a robust infrared image recog...

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Main Authors: Kaige Zhuang, Zhijun Xue
Format: Article
Language:English
Published: Hindawi Limited 2021-01-01
Series:Mobile Information Systems
Online Access:http://dx.doi.org/10.1155/2021/2489313
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spelling doaj-5066311170d04ed096bcdf4bca59017e2021-08-16T00:01:19ZengHindawi LimitedMobile Information Systems1875-905X2021-01-01202110.1155/2021/2489313Public Information Dissemination Using Data Mining-Enabled Image Enhancement and Internet of ThingsKaige Zhuang0Zhijun Xue1Art CollegePhotography DepartmentWith the development of the Internet of Things, the requirement of a wide range of human-centered services may now make use of as many computing resources for media technologies and holographic images. The IoT system can monitor the status of equipment in real-time with a robust infrared image recognition algorithm. However, few researchers discuss data mining on images with valuable information. In this study, we present a generic approach that is based on the mining decision tree and holographic image improvement data analysis. We employed advanced data mining techniques to achieve image stability and use light to form a three-dimensional image with real space. The suggested model improves digital image signal transmission and noise through the grey neural network technique and, furthermore, utilization decision tree induction to create attributes-to-target label relations from image pixels. The experimental results show that the suggested approach may be highly efficient and effective for interactive image systems and image mining. Our approach may also be widely utilized and includes extremely efficient convergence systems for essential framework elements.http://dx.doi.org/10.1155/2021/2489313
collection DOAJ
language English
format Article
sources DOAJ
author Kaige Zhuang
Zhijun Xue
spellingShingle Kaige Zhuang
Zhijun Xue
Public Information Dissemination Using Data Mining-Enabled Image Enhancement and Internet of Things
Mobile Information Systems
author_facet Kaige Zhuang
Zhijun Xue
author_sort Kaige Zhuang
title Public Information Dissemination Using Data Mining-Enabled Image Enhancement and Internet of Things
title_short Public Information Dissemination Using Data Mining-Enabled Image Enhancement and Internet of Things
title_full Public Information Dissemination Using Data Mining-Enabled Image Enhancement and Internet of Things
title_fullStr Public Information Dissemination Using Data Mining-Enabled Image Enhancement and Internet of Things
title_full_unstemmed Public Information Dissemination Using Data Mining-Enabled Image Enhancement and Internet of Things
title_sort public information dissemination using data mining-enabled image enhancement and internet of things
publisher Hindawi Limited
series Mobile Information Systems
issn 1875-905X
publishDate 2021-01-01
description With the development of the Internet of Things, the requirement of a wide range of human-centered services may now make use of as many computing resources for media technologies and holographic images. The IoT system can monitor the status of equipment in real-time with a robust infrared image recognition algorithm. However, few researchers discuss data mining on images with valuable information. In this study, we present a generic approach that is based on the mining decision tree and holographic image improvement data analysis. We employed advanced data mining techniques to achieve image stability and use light to form a three-dimensional image with real space. The suggested model improves digital image signal transmission and noise through the grey neural network technique and, furthermore, utilization decision tree induction to create attributes-to-target label relations from image pixels. The experimental results show that the suggested approach may be highly efficient and effective for interactive image systems and image mining. Our approach may also be widely utilized and includes extremely efficient convergence systems for essential framework elements.
url http://dx.doi.org/10.1155/2021/2489313
work_keys_str_mv AT kaigezhuang publicinformationdisseminationusingdataminingenabledimageenhancementandinternetofthings
AT zhijunxue publicinformationdisseminationusingdataminingenabledimageenhancementandinternetofthings
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