Abstract
To provide reliable, time-saving and automatic class attendance system, the concept of Internet of Things (IoT) based class attendance monitoring system using embedded Linux platform is presented in this paper. The study is focused on the design and implementation of face detection and recognition system using Raspberry Pi. The system takes images of students, and analyzes, detects and recognizes faces using image processing algorithms, where the Haar cascade classifier algorithm is implemented to detect faces and local binary pattern histogram algorithm is used to recognize these faces. After collecting image processing data, the system generates a final attendance record and uploads it in a cloud server. The cloud server has been implemented using python based web framework. The record can be accessed remotely from a user-friendly, web application using the Internet. Finally, the system is also capable of sending an email notification with the final record to the teachers and students in a specific time. Tests and performance analysis were done to verify the efficiency of this system.
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References
Patel, R., Patel, N., Gajjar, M.: Online students attendance monitoring system in classroom using radio frequency identification technology: a proposed system framework. Int. J. Emerg. Technol. Adv. Eng. 2(2), 61–66 (2012)
Gowri, Ch.S.R., Kiran, V., Rama Krishna, G.: Automated intelligence system for attendance monitoring with open CV based on internet of things (IoT). Int. J. Sci. Eng. Technol. Res. (IJSETR) 5(4), 905–913 (2016)
Shoewu, O., Olaniyi, O.M., Lawson, A.: Embedded computer-Based lecture attendance management system. Afr. J. Comput. ICT 4(3), 27–36 (2011)
Mani Kumar, B., Praveen Kumar, M., Rangareddy: RFID based Attendance monitoring system using IOT with TI CC3200 Launchpad. Int. J. Mag. Eng. Technol. Manag. Res. 2(7), 1465–1467 (2015)
Uddin, M.S., Allayear, S.M., Das, N.C., Talukder, F.A.: A location based time and attendance system. Int. J. Comput. Theor. Eng 6(1), 1–2 (2014)
Grimmett, R.; Raspberry Pi Robotic Projects. 3rd Edn. Packt Publishing (2016)
Abaya, W.F., Basa, J., Sy, M., Abad, A.C., Dadios, E.P.: Low cost smart security camera with night vision capability using Raspberry Pi and OpenCV. In: 2014 International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment and Management (HNICEM), Palawan, pp. 1–6 (2014)
Pasumarti, P., Purna Sekhar, P.: Classroom attendance using face detection and Raspberry-Pi. Int. Res. J. Eng. Technol. (IRJET) 05(03), 3–5 (2018)
Rajkumar, S., Prakash, J.: Automated attendance using Raspberry Pi. Int. J. Pharm. Technol. (IJPT) 8(3), 16214–16221 (2016)
T. M. Inc.: Train a Cascade Object Detector. http://www.mathworks.se/help/vision/ug/train-a-cascadeobject-detector.html#btugex8
Ronacher, A.: Quickstart (2010). http://flask.pocoo.org/docs/0.12/quickstart/#quickstart
Acknowledgement
This work is financially supported by the National Natural Science Foundation of P. R. China (No.: 61672296, No.: 61602261), Scientific & Technological Support Project of Jiangsu Province (No.: BE2015702, BE2016185, No.: BE2016777), Postgraduate Research and Practice Innovation Program of Jiangsu Province (No.: KYCX17_0798).
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Salman, H., Uddin, M.N., Acheampong, S., Xu, H. (2019). Design and Implementation of IoT Based Class Attendance Monitoring System Using Computer Vision and Embedded Linux Platform. In: Barolli, L., Takizawa, M., Xhafa, F., Enokido, T. (eds) Web, Artificial Intelligence and Network Applications. WAINA 2019. Advances in Intelligent Systems and Computing, vol 927. Springer, Cham. https://doi.org/10.1007/978-3-030-15035-8_3
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DOI: https://doi.org/10.1007/978-3-030-15035-8_3
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