Analysis of Practical Implementations of Automated Student Identification Systems in Electronic Learning Systems
DOI:
https://doi.org/10.31649/1997-9266-2024-173-2-61-70Keywords:
automated attendance systems, e-learning systems, identification, Wi-Fi, Bluetooth, QR code, face recognition, fingerprint scanning, RFIDAbstract
The article reviews existing systems of automated student identification based on various technologies. The systems are implemented on the basis of such technologies as: Wi-Fi, Bluetooth, face recognition, QR code, fingerprint scanning, and RFID. The features and algorithms of each system are analyzed. The algorithms of the systems are presented in the form of UML diagrams.
As a result of the analysis, the advantages and disadvantages of each technology were identified. To compare the analyzed identification methods, the advantages and disadvantages of the systems, technical characteristics of the equipment and other aspects in the context of an automated attendance system were considered.
Wi-Fi-based systems allow for full automation of the identification process and have low hardware costs, but require students to have their own smartphone. Bluetooth-based systems are similar to Wi-Fi-based systems, but instead of a smartphone, they require any Bluetooth-enabled device and do not require a special application to be installed on the device. Systems based on face recognition do not require additional devices and are fully automated, but have lower reliability of student identification and high complexity of database maintenance. QR code-based systems have high identification reliability and low database maintenance complexity, but cannot be automated. Fingerprint-based systems do not require additional devices and have high identification reliability, but they cannot be automated and require direct contact between students and the scanner, which makes the technology impractical for classes with a large number of students. RFID-based systems are fully automated and autonomous, but students need to carry RFID tags with them, and UHF RFID readers are expensive compared to other technologies.
Therefore, it has been demonstrated that the selection of technology for an automated student identification system relies on the set objectives. In specific circumstances, each of the technologies under consideration might represent the optimal choice for implementation in electronic learning systems.
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