Classroom Attendance Systems Based on Bluetooth Low Energy Indoor Positioning Technology for Smart Campus

Student attendance during classroom hours is important, because it impacts the academic performance of students. Consequently, several universities impose a minimum attendance percentage criterion for students to be allowed to attend examinations; therefore, recording student attendance is a vital task. Conventional methods for recording student attendance in the classroom, such as roll-call and sign-in, are an inefficient use of instruction time and only increase teachers’ workloads. In this study, we propose a Bluetooth Low Energy-based student positioning framework for automatically recording student attendance in classrooms. The proposed architecture consists of two components, an indoor positioning framework within the classroom and student attendance registration. Experimental studies using our method show that the Received Signal Strength Indicator fingerprinting technique that is used in indoor scenarios can achieve satisfactory positioning accuracy, even in a classroom environment with typically high signal interference. We intentionally focused on designing a basic system with simple indoor devices based on ubiquitous Bluetooth technology and integrating an attendance system with computational techniques in order to minimize operational costs and complications. The proposed system is tested and demonstrated to be usable in a real classroom environment at Rangsit University, Thailand.

[1]  Daniel R. Marburger,et al.  Does Mandatory Attendance Improve Student Performance? , 2006 .

[2]  T. Price,et al.  Improving the quantity and quality of attendance data to enhance student retention , 2005 .

[3]  Boxian Dong,et al.  Neural Network Based Radio Fingerprint Similarity Measure , 2018, 2018 International Conference on Indoor Positioning and Indoor Navigation (IPIN).

[4]  Harish Narula,et al.  Bluetooth Smart Based Attendance Management System , 2015 .

[5]  Gabriel de Blasio,et al.  Beacon-Related Parameters of Bluetooth Low Energy: Development of a Semi-Automatic System to Study Their Impact on Indoor Positioning Systems , 2019, Sensors.

[6]  Vicki R Voskuil,et al.  Chronic Student Absenteeism , 2016, NASN school nurse.

[7]  Mohamed A. Mohandes,et al.  Class Attendance Management System Using NFC Mobile Devices , 2017, Intell. Autom. Soft Comput..

[8]  B. Macfarlane The Surveillance of Learning: A Critical Analysis of University Attendance Policies , 2013 .

[9]  Carles Gomez,et al.  Overview and Evaluation of Bluetooth Low Energy: An Emerging Low-Power Wireless Technology , 2012, Sensors.

[10]  Seng Chun Hoo,et al.  Biometric-Based Attendance Tracking System for Education Sectors: A Literature Survey on Hardware Requirements , 2019, J. Sensors.

[11]  Pranab Kumar Pani,et al.  Absenteeism and performance in a quantitative module A quantile regression analysis , 2016 .

[12]  Dimitrios Tzovaras,et al.  A Low-Cost Indoor Activity Monitoring System for Detecting Frailty in Older Adults , 2019, Sensors.

[13]  Faraz Junejo,et al.  Radio Frequency Identification (RFID) Based Attendance & Assessment System with Wireless Database Records , 2015 .