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https://gnanaganga.inflibnet.ac.in:8443/jspui/handle/123456789/16899
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DC Field | Value | Language |
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dc.contributor.author | Upreti, Kamal | - |
dc.contributor.author | Dadhich, Priyanka | - |
dc.contributor.author | Gautam, Anjali | - |
dc.contributor.author | Singh, Jagendra | - |
dc.contributor.author | Kushwah, Virendra Singh | - |
dc.contributor.author | Parashar, Jyoti | - |
dc.contributor.author | Gangwar, Divya | - |
dc.contributor.author | Ghosh, Soumi | - |
dc.date.accessioned | 2024-12-12T09:38:21Z | - |
dc.date.available | 2024-12-12T09:38:21Z | - |
dc.date.issued | 2024 | - |
dc.identifier.citation | Vol. 27, No. 4; pp. 1445-1454 | en_US |
dc.identifier.issn | 0972-0529 | - |
dc.identifier.issn | 2169-0065 | - |
dc.identifier.uri | http://dx.doi.org/10.47974/JDMSC-1997 | - |
dc.identifier.uri | https://gnanaganga.inflibnet.ac.in:8443/jspui/handle/123456789/16899 | - |
dc.description.abstract | This research examines the integration of emerging technologies in the form of the Internet of Things and Artificial Intelligence in driving forward to the educational application of Education 4.0. The systematic meta-analysis study provides evidence in the transformative capability of these technologies regarding attendance, performance, and learning pathway. The system's implementation was in the form of IoT sensors to capture and record student attendance, while the use of Artificial Intelligence based on machine learning models such as Support Vector Machine, Artificial Neural Network, k-Nearest Neighbors, and Decision Tree generated a personalized recommendation for the academic improvement or sports activity to be participated as an extracurricular activity. The performance evaluation of these models was illustrated for accuracy to correctly predict student responses related to the provided recommendations. The findings of implementation suggest the system's significant impacts given the augmented performance achievement with respect to academics and sports is the result of the implementation. It was measured comparing students' performance before and after system implementation to capture the interpretation of student improvement regarding the use of the implemented system. The findings indicated that the system's implementation contributed to the increase in academic improvement from 65% to 75% and sports performance from 55% to 70% depending on student response to the provided academical or extracurricular recommendations. Such findings confirm an overall improvement in performance based on the use of the presented system. | en_US |
dc.language.iso | en | en_US |
dc.publisher | Journal of Discrete Mathematical Sciences & Cryptography | en_US |
dc.publisher | Taru Publications | en_US |
dc.subject | Mathematical Modeling | en_US |
dc.subject | Ordinary Differential Equations | en_US |
dc.subject | A Duopoly Economy | en_US |
dc.subject | Market Share | en_US |
dc.title | Investigation on The Analysis of Integration of IOT and AI Technologies With Information Security for Advanced Education 4.0 | en_US |
dc.type | Article | en_US |
Appears in Collections: | Journal Articles |
Files in This Item:
File | Size | Format | |
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jdmsc-1997.pdf | 798.28 kB | Adobe PDF | View/Open |
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