JomFacial Recognition Attendance Systems

Tee, F. K.; Loh, G. X.; Sumaiya, K.; Y., Z.; JosephNg, P. S.; Phan, K. Y.; Lim, J. T.

doi:10.1007/978-3-030-82616-1_55

Cited by 4 publications

(2 citation statements)

References 21 publications

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“…In this paper, the authors tackle the theoretical aspects of this problem, exploring the implications of the implementation of such systems both managerially and logistically [3]. In essence, it provides an analysis of data collected from the implementation of a facial recognition system in classrooms within a university setting, and the advantages of automatic attendance systems replacing traditional manual attendance systems.…”

Section: Related Workmentioning

confidence: 99%

“…While it may seem like a minor inconvenience, teachers may lose up to 18 hours of instructional value per school year performing this meaninglessly routine task (provided that they are using a minute a day to record attendance, in 6 separate classes for 180 days). Taking this into account, a method of relegating this menial task to an automated software would provide a marked boost in the efficiency over the course of a single school year [3]. Additionally, this particular solution is not only limited to the bounds of a classroom environment, although that was its original purpose.…”

Section: Introductionmentioning

confidence: 99%

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A Mobile Application to Mark Attendance using a Combined Backend of the Firestore Database and Amazon AWS Services

Jiang¹,

Sun²

2023

Computer Science and Machine Learning Trends 2023

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Since the beginning of the COVID-19 pandemic, education largely shifted away from the physical classroom and towards more digitally oriented platforms. This simplified classroom attendance problems greatly, as newly created programming scripts could easily track the students in a meeting room via their names. However, with the recent growing return to in person education, it has become apparent that the problem of attendance within the context of a non-virtual classroom environment has yet to be solved in an efficacious automated fashion. In larger classrooms, the severity of this problem becomes exacerbated even further, as teachers are forced to allocate valuable time for the purpose of marking attendance. The flourishing world of machine-learning based algorithms were the first solutions that we considered, and within the context of the premise, we concluded that facial recognition would likely be the most feasible and effective approach that we could use. This paper develops a mobile application to apply real time face recognition for the purpose of the above stated problem, using a combined backend of the Firestore database and Amazon AWS services. Applying our application to in person classrooms, the results show that our solutions are immensely effective in both saving time and reducing error.

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Section: Related Workmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%