Construction of College Students’ Mental Health Assessment and Art Therapy System Aided by the Internet of Things and Big Data

In order to improve the effect of college students’ mental health assessment, this paper combines the Internet of Things and big data technology to build a college student’s mental health assessment system and analyzes and verifies the clustering effectiveness indicators by using FCM, GK, and GG clu...

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Main Author: Qing Li
Format: Article
Language:English
Published: Wiley 2022-01-01
Series:Advances in Multimedia
Online Access:http://dx.doi.org/10.1155/2022/9233823
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author Qing Li
author_facet Qing Li
author_sort Qing Li
collection DOAJ
description In order to improve the effect of college students’ mental health assessment, this paper combines the Internet of Things and big data technology to build a college student’s mental health assessment system and analyzes and verifies the clustering effectiveness indicators by using FCM, GK, and GG clustering algorithms. Moreover, this paper explores the basic concepts and processes of FCM algorithm, GK algorithm, and GG algorithm and expounds the connection between the three algorithms. In addition, this paper uses four datasets to conduct clustering experiments and compares the CS indicator with several other indicators. The experimental results demonstrate the effectiveness of the CS indicator. The simulation study shows that the student mental health assessment system based on the Internet of Things and big data technology proposed in this paper can play a certain role in student mental health and art therapy, and it also verifies that art therapy plays a certain role in student psychotherapy.
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institution Kabale University
issn 1687-5699
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publishDate 2022-01-01
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series Advances in Multimedia
spelling doaj-art-ebb89cf4f5164b298295aaf5d2e3100f2025-02-03T01:22:51ZengWileyAdvances in Multimedia1687-56992022-01-01202210.1155/2022/9233823Construction of College Students’ Mental Health Assessment and Art Therapy System Aided by the Internet of Things and Big DataQing Li0College of Art and DesignIn order to improve the effect of college students’ mental health assessment, this paper combines the Internet of Things and big data technology to build a college student’s mental health assessment system and analyzes and verifies the clustering effectiveness indicators by using FCM, GK, and GG clustering algorithms. Moreover, this paper explores the basic concepts and processes of FCM algorithm, GK algorithm, and GG algorithm and expounds the connection between the three algorithms. In addition, this paper uses four datasets to conduct clustering experiments and compares the CS indicator with several other indicators. The experimental results demonstrate the effectiveness of the CS indicator. The simulation study shows that the student mental health assessment system based on the Internet of Things and big data technology proposed in this paper can play a certain role in student mental health and art therapy, and it also verifies that art therapy plays a certain role in student psychotherapy.http://dx.doi.org/10.1155/2022/9233823
spellingShingle Qing Li
Construction of College Students’ Mental Health Assessment and Art Therapy System Aided by the Internet of Things and Big Data
Advances in Multimedia
title Construction of College Students’ Mental Health Assessment and Art Therapy System Aided by the Internet of Things and Big Data
title_full Construction of College Students’ Mental Health Assessment and Art Therapy System Aided by the Internet of Things and Big Data
title_fullStr Construction of College Students’ Mental Health Assessment and Art Therapy System Aided by the Internet of Things and Big Data
title_full_unstemmed Construction of College Students’ Mental Health Assessment and Art Therapy System Aided by the Internet of Things and Big Data
title_short Construction of College Students’ Mental Health Assessment and Art Therapy System Aided by the Internet of Things and Big Data
title_sort construction of college students mental health assessment and art therapy system aided by the internet of things and big data
url http://dx.doi.org/10.1155/2022/9233823
work_keys_str_mv AT qingli constructionofcollegestudentsmentalhealthassessmentandarttherapysystemaidedbytheinternetofthingsandbigdata