Application of Computer Vision and Mobile Systems in Education: A Systematic Review

International Journal of Interactive Mobile Technologies (iJIM) Pub Date : 2024-01-12 DOI:10.3991/ijim.v18i01.46483

Rubaiya Tasnim Sholi, Md. Fouad Hossain Sarker, Md. Salman Sohel, Md Kabirul Islam, Maruf Ahmed Tamal, Touhid Bhuiyan, S.M. Khasrul Alam Shakil, Md. Foysal Ahmed

{"title":"Application of Computer Vision and Mobile Systems in Education: A Systematic Review","authors":"Rubaiya Tasnim Sholi, Md. Fouad Hossain Sarker, Md. Salman Sohel, Md Kabirul Islam, Maruf Ahmed Tamal, Touhid Bhuiyan, S.M. Khasrul Alam Shakil, Md. Foysal Ahmed","doi":"10.3991/ijim.v18i01.46483","DOIUrl":null,"url":null,"abstract":"The computer vision industry has experienced a significant surge in growth, resulting in numerous promising breakthroughs in computer intelligence. The present review paper outlines the advantages and potential future implications of utilizing this technology in education. A total of 84 research publications have been thoroughly scrutinized and analyzed. The study revealed that computer vision technology integrated with a mobile application is exceptionally useful in monitoring students’ perceptions and mitigating academic dishonesty. Additionally, it facilitates the digitization of handwritten scripts for plagiarism detection and automates attendance tracking to optimize valuable classroom time. Furthermore, several potential applications of computer vision technology for educational institutions have been proposed to enhance students’ learning processes in various faculties, such as engineering, medical science, and others. Moreover, the technology can also aid in creating a safer campus environment by automatically detecting abnormal activities such as ragging, bullying, and harassment.","PeriodicalId":507995,"journal":{"name":"International Journal of Interactive Mobile Technologies (iJIM)","volume":"44 7","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-01-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Interactive Mobile Technologies (iJIM)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.3991/ijim.v18i01.46483","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}

引用次数: 0

Abstract

The computer vision industry has experienced a significant surge in growth, resulting in numerous promising breakthroughs in computer intelligence. The present review paper outlines the advantages and potential future implications of utilizing this technology in education. A total of 84 research publications have been thoroughly scrutinized and analyzed. The study revealed that computer vision technology integrated with a mobile application is exceptionally useful in monitoring students’ perceptions and mitigating academic dishonesty. Additionally, it facilitates the digitization of handwritten scripts for plagiarism detection and automates attendance tracking to optimize valuable classroom time. Furthermore, several potential applications of computer vision technology for educational institutions have been proposed to enhance students’ learning processes in various faculties, such as engineering, medical science, and others. Moreover, the technology can also aid in creating a safer campus environment by automatically detecting abnormal activities such as ragging, bullying, and harassment.

查看原文本刊更多论文

计算机视觉和移动系统在教育中的应用：系统回顾

计算机视觉产业经历了大幅增长，在计算机智能方面取得了许多有希望的突破。本综述文件概述了在教育领域利用这一技术的优势和潜在的未来影响。本文对总共 84 篇研究出版物进行了深入的研究和分析。研究显示，计算机视觉技术与移动应用程序相结合，在监测学生的看法和减少学术不诚实方面非常有用。此外，它还有助于将手写稿件数字化，以检测抄袭行为，并自动跟踪出勤情况，优化宝贵的课堂时间。此外，人们还提出了计算机视觉技术在教育机构中的几种潜在应用，以加强学生在工程、医学等不同院系的学习过程。此外，该技术还可以通过自动检测异常活动（如拉帮结派、欺凌和骚扰），帮助营造更安全的校园环境。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

求助全文

约1分钟内获得全文求助全文

来源期刊

International Journal of Interactive Mobile Technologies (iJIM)

自引率

0.00%

发文量