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9 April 2024 College student activity attendance management system design based on Internet of Things and deep learning technology
Yan Wang, Jinyan Pang
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Proceedings Volume 12989, Third International Conference on Intelligent Traffic Systems and Smart City (ITSSC 2023); 1298914 (2024) https://doi.org/10.1117/12.3023911
Event: Third International Conference on Intelligent Traffic Systems and Smart City (ITSSC 2023), 2023, Xi'an, China
Abstract
The admission qualification and attendance management of campus activities is a difficult problem in college student management. In order to solve this problem, this paper proposes a rapid deployment method of existing equipment and new equipment based on the Internet of Things technology. The collected data is transmitted to the resource server and data server through the Internet of Things and is combined with the "dynamic two-dimensional code" to complete the admission qualification and attendance management. As a result, it solves the problems of difficult deployment and poor scalability of traditional equipment. Therefore, compared with the traditional equipment recording or paper recording method, this method has the advantages of transformation, easy deployment and convenient maintenance. At the same time, real-time logs can be generated in the system after checking in the above way. Using the technology of "deep learning" to analyse these logs, we can accurately analyse and judge the rules of college students' daily activity attendance.
(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.
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Yan Wang and Jinyan Pang "College student activity attendance management system design based on Internet of Things and deep learning technology", Proc. SPIE 12989, Third International Conference on Intelligent Traffic Systems and Smart City (ITSSC 2023), 1298914 (9 April 2024); https://doi.org/10.1117/12.3023911
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KEYWORDS
Data modeling
Internet of things
Education and training
Intelligence systems
Deep learning
Telecommunications
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