Computer vision for dynamic student data management in higher education platform
Artificial Intelligence (AI) supported access system is the computer interacted communication system. According to the accessible and dynamic data management schemes have been introduced in education. However, some specific limitations have been noted in existing systems, such as the data collected might not be sufficient for access and retrieval purposes. It remains challenging in organizational and institutional data management. In this research, A Dynamic Student Data Management System using AI Computer Vision Techniques (DSDM-AICV) for the Higher education institution data access and retrieval process is introduced. A process flow regarding data is generated based on the collected information with an AI-enabled archive and dynamic user access. The flow of dynamic data helps to explore the relations between student data and data management improvement. The proposed method showed its effectiveness in the education system and compared it with the available schemes, and the execution result shows extensive efficiency. The numerical results show that the proposed method enhances the data accessibility ratio of 96.8%, decision-making ratio of 97.3%, reliability ratio of 95.6%, the student performance ratio of 98.7%, and operational efficiency ratio of 93.4% compared to other existing methods.
Journal of Multiple-Valued Logic and Soft Computing
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Chen, Weimiao; Jackson Samuel, R. Dinesh; and Krishnamoorthy, Sujatha, "Computer vision for dynamic student data management in higher education platform" (2021). Kean Publications. 1081.