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2016 IEEE Eighth International Conference on Technology for Education (2016)
Mumbai, Maharashtra, India
Dec. 2, 2016 to Dec. 4, 2016
ISBN: 978-1-5090-6115-0
pp: 62-67
Academic performance is directly affected by student attendance during the lecture hours. There are existing manual and automated attendance tracking systems that work to ensure that students attend the lectures without fail. However, the practical implementation of most automated systems have drawbacks such as high monetary cost, the need to install specialized hardware, and proneness to fake or proxy attendance. To address this, we propose a novel attendance marking system with which students may mark attendance using their smartphones. While applying facial recognition via the smartphone's front camera to determine the student's identity, the system also makes use of the campus Wi-Fi network to determine the student’s location. The proposed system does not require high monetary cost or specialized hardware and yet incorporates adequate foolproof measures to counter fake or proxy attendance. Experimental studies with our system show that fingerprinting, which is the technique used here to determine indoor location, can achieve very good positioning accuracy even in classroom environments, where signal interference is usually very high.
IEEE 802.11 Standard, Fingerprint recognition, Hardware, Face recognition, Radiofrequency identification, Bluetooth, Indoor environments

A. S, K. Bijlani, S. Suresh and P. P, "Attendance Monitoring in Classroom Using Smartphone & Wi-Fi Fingerprinting," 2016 IEEE Eighth International Conference on Technology for Education(T4E), Mumbai, Maharashtra, India, 2016, pp. 62-67.
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