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A Tool for Checking Attendance of Students in Classroom Automatically

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2016 ASEE Annual Conference & Exposition


New Orleans, Louisiana

Publication Date

June 26, 2016

Start Date

June 26, 2016

End Date

August 28, 2016





Conference Session

Teaching and Advising Tools Using Computers and Smart Devices

Tagged Division

Computers in Education

Tagged Topic


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Paper Authors


Taekyoung Kwon Seoul National University

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Ted "Taekyoung" Kwon is a professor with Department of Computer Science and Engineering, Seoul National University (SNU).
Before joining SNU, he was a Postdoctoral Research Associate at University of California Los Angeles and
City University New York. He obtained BS, MS and PhD at SNU in 1993, 1995, 2000, respectively. During his graduate program,
he was a visiting student at IBM T.J. Watson Research Center and at University of North Texas. He was a visiting professor
at Rutgers University in 2010. His research interest lies in future Internet, indoor localization, network security, and wireless networks.

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Myungchul Kwak Seoul National University

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I'm a Ph.D student at the Dept. of Computer Science and Engineering, Seoul National University, Seoul, Korea. (Mar. 2012 - Current). Before joining SNU, I obtained B.S. in Dept. of Computer Science and Engineering, Hanyang University, Ansan, Korea.

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Junghwan Song Seoul National University Orcid 16x16


Selin Chun Seoul National University

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•M.S. in Dept. of Computer Science and Engineering, Seoul National University, Korea, 2015.3 - current
•B.S. in Dept. of Computer Science and Engineering, Seoul National University, Korea, 2011.3 - 2015.2

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Seokho Chi Seoul National University

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Associate Professor at the Department of Civil and Environmental Engineering at Seoul National University in Seoul, Korea. He has worked on construction management, occupational health and safety in construction, disaster management, and IT applications in construction specifically using advanced technologies including Big Data analysis, PMIS (Project Information Management Systems), video mining, and smart sensing.

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We design and implement a software tool that can check the attendance of enrolled students automatically. The students need to install the application to their android phones. The challenging issue in designing the software tool is that we need to find out whether a student is inside or outside the classroom in an automatic fashion. For this purpose, the application in a student's phone will measure the current signal strengths of WiFi and Bluetooth devices in and around the classroom, which are reported to a server running the software that checks the student attendance. Then, the server decides whether the students are located inside or outside the classroom by analyzing the signal strengths. We already carried out the comprehensive measurements of WiFi and Bluetooth strengths. It turns out that when a student stands right next to the wall outside the classroom, her measured WiFi signal strength is not noticeably different from that of a student inside the classroom. That is, WiFi signal strengths cannot serve as a determining factor to localize the student at the granularity of classrooms. In Bluetooth devices, we can adjust the transmission power levels, which greatly helps to localize the students. By deploying Bluetooth devices with appropriate power levels, we can achieve significantly better localization performance. To further enhance the precision of class attendances, we also use pedestrian dead reckoning (PDR), which estimates the trajectory of a student by measuring the magnetic sensor (azimuth) and the accelerometer.

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