Random Interval Attendance Management System (RIAMS): A Novel Multimodal Approach for Post-COVID Virtual Learning

Anzar, S. M.; Subheesh, N. P.; Panthakkan, Alavikunhu; Shanid, Malayil; Al-Ahmad, Hussain

doi:10.1109/access.2021.3092260

Cited by 13 publications

(5 citation statements)

References 60 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…This code was stored as a unique identifier in a database and used to identify users. Face recognition technology is one of the most widely used in biometricbased attendance management systems due to its advantages of greater security, improved accuracy, and capability to easily integrate with other systems [22]. The underlying technologies in face recognition system are based on artificial intelligence and machine learning [23].…”

Section: Biometric Based Solutionsmentioning

confidence: 99%

Fraud Mitigation in Attendance Monitoring Systems using Dynamic QR Code, Geofencing and IMEI Technologies

Nwabuwe¹,

Sanghera²,

Alade³

et al. 2023

IJACSA

View full text Add to dashboard Cite

Attendance monitoring is a vital activity in several organizations. Due to its importance, many attendance monitoring systems have been developed to automate this process. Despite several advancements in automated attendance management solutions, attendance fraud remains an issue as some end users can manipulate known vulnerabilities, such as proxy attendance, buddy-punching, early departure, and so on. In this paper, a fraud-resistant attendance management solution is developed by harnessing technologies such as geofencing, dynamic QR code and IMEI Checking. The proposed solution is comprised of a single-page web application where QR code can be enabled for attendance registration, and a mobile application, where endusers can scan generated QR code to register their attendance. Attendance cheating via QR code sharing is prevented by encoding the polygonal coordinates of the event venue in the QR code to determine if the user is within the venue. The proposed system solves the problem of proxy attendance by registering and verifying the end user's device IMEI number. Results obtained from testing indicate that attempts at committing a variety of attendance frauds are effectively mitigated.

show abstract

Section: Biometric Based Solutionsmentioning

confidence: 99%

Fraud Mitigation in Attendance Monitoring Systems using Dynamic QR Code, Geofencing and IMEI Technologies

Nwabuwe¹,

Sanghera²,

Alade³

et al. 2023

IJACSA

View full text Add to dashboard Cite

show abstract

“…Task complexity is increased by the complexity of varied learning settings. Instead than emphasizing course success or teaching impact, the evaluative content of the teaching process is used to gauge the teacher's involvement [17,18]. Comparing educational processes is still difficult because of the wide range of disciplines, course kinds, connections, and instructional materials.…”

Section: Introductionmentioning

confidence: 99%

“…ROC ROC stated as ratio among changes in one variable comparative to equivalent change in another, graphically that rate of change represents slope of line. It is given in equation(18) …”

mentioning

confidence: 99%

Teaching Management System for Higher Vocational and Technical Education Using Wasserstein Generative Adversarial Network Optimized by Fire Hawk Optimization

Jinxiu Wu

2024

jes

View full text Add to dashboard Cite

The vocational education system is currently undergoing purposeful reform and innovation, recognizing the importance of vocational training in the entire educational framework. Assessing and improving teaching quality in vocational education is critical, and addressing this challenge necessitates. The utilize of AI technology, primarily deep learning, is particularly effective in addressing the diverse and sophisticated aspects of evaluating and improving teaching quality. In this research work, Teaching Management System for Higher Vocational and Technical Education Using Wasserstein Generative Adversarial Network Optimized by Fire Hawk Optimization (TMS-WGAN-FHO) is proposed. The input data are gathered from School database (Educational data),then, input data are pre-processed using Square Root Cubature Kalman Filter for cleaning data. Then, pre-processed data are given to Wasserstein Generative Adversarial Network (WGAN) for evaluating and improving the teaching quality for Higher Vocational and Technical Education. In general, WGAN does not express some adoption of optimization strategies for determining optimal parameters to evaluating, improving quality of teaching management system. Hence Fire Hawk Optimization Algorithm (FHOA) is proposed to optimize WGAN classifier which precisely evaluates the teaching quality Higher Vocational and Technical Education. The proposed TMS-WGAN-FHO method is implemented in MATLAB, and it assessed with several performance metrics likes accuracy, cross validation scores, recall, F1-score, ROC. The results show TMS-WGAN-FHO attains 25.8%, 28.5%, and 21.6% higher Accuracy, 15.1%, 17.2%, and 32.8%higher Precision, 27.5%, 24.6% and 22.3% higher Recall are analysed with existing methods such as, evaluation of the vocational education teaching reform's quality using deep learning (EVE-TRQ-DL), art higher vocational education curriculum design incorporating AI-aided virtual reality technology (AHVE-DIAI-VRT), integrating big data analysis with higher vocational education approaches to educate entrepreneurship and innovation (IBDA-HVE-EEV) methods respectively.

show abstract

“…This attendance system solved issues from paper attendance for reporting process [8]. The Electronic student attendance system is currently used in many schools to record student activities [9].…”

Section: Introductionmentioning

confidence: 99%

Improvement of Student Attendance System for Recording Student Surface Body Temperature Based on Internet of Things

Afandi¹,

Enriko²,

Baihaqy³

2023

ELINVO

View full text Add to dashboard Cite

Student attendance is a system used for tracking student activity in school. Many methods are used to develop student attendance systems, such as Quick Response (QR) Code systems, Radio Frequency Identification (RFID) systems, fingerprint systems, and so on. The COVID-19 pandemic has driven technological development, especially in the student attendance system. Measuring human surface body temperature has become a protocol that must be done before entering school. Student attendance systems need to expand the function not only for attendance but also for monitoring student surface body temperature. This research aims to improve student attendance systems by adding surface body temperature measurements and recording during student presence. Recording data can be done by using the internet of things. Student presence data will be sent to school databases throughout the internet. This system uses RFID technology for student presence and a non-contact thermal sensor for temperature measurement. According to data research, non-contact thermal sensors provide a temperature reading with an average error of 1.69%, a minimum error value of 0.96%, and a maximum error value of 2.57% with a range error value of 0.35°C – 0.95°C. RFID test shows that the optimum distance for the system to read an RFID card is 0 – 2cm. The System also successfully sent presence data to the student school database through the internet. This study concludes that developed systems can track student attendance by recording the student’s surface body temperature while in presence. Further work will be focused on managing data networks if this system is used with many users in the school.

show abstract

Random Interval Attendance Management System (RIAMS): A Novel Multimodal Approach for Post-COVID Virtual Learning

Cited by 13 publications

References 60 publications

Fraud Mitigation in Attendance Monitoring Systems using Dynamic QR Code, Geofencing and IMEI Technologies

Fraud Mitigation in Attendance Monitoring Systems using Dynamic QR Code, Geofencing and IMEI Technologies

Teaching Management System for Higher Vocational and Technical Education Using Wasserstein Generative Adversarial Network Optimized by Fire Hawk Optimization

Improvement of Student Attendance System for Recording Student Surface Body Temperature Based on Internet of Things

Contact Info

Product

Resources

About