Smart Classroom System (SCS) Berbasis Kamera Untuk Memantau Keadaan Peserta Didik
Abstract
Sistem pendidikan di abad 21 harus didukung sepenuhnya oleh penerapan teknologi informasi dan komunikasi (TIK). Hal ini mendorong berbagai pihak untuk berlomba-lomba membangun fasilitas pendidikan berbasis TIK. Pada penelitian ini dikembangkan smart classroom system (SCS), yaitu ruang kelas cerdas yang mampu melihat dan mengamati keadaan peserta didik secara visual layaknya manusia. Melalui SCS ini pendidik dapat meningkatkan pencapaian tujuan pembelajaran melalui umpan balik yang diberikan oleh sistem. SCS dikembangkan berdasarkan pendekatan pendeteksian wajah menggunakan sensor kamera berbantuan model deep super resolution untuk meningkatkan kualitas citra. Melalui sistem ini dapat dilakukan proses pencatatan kehadiaran secara otomatis, pemantauan ekspresi wajah, dan deteksi atensi yang dapat digunakan sebagai umpan balik bagi pendidik selama proses pembelajaran berlangsung. Selain itu SCS juga dapat menyimpan data video pembelajaran dalam jumlah yang besar, sehingga di kemudian hari dapat dilakukan analisis big-data untuk menemukan pola-pola aktifitas yang sebelumnya tidak diketahui dan tidak teramati oleh manusia secara manual.References
[1] D. Franklin, J. Flachsbart, and K. Hammond, “The intelligent classroom,†IEEE Intell. Syst. Their Appl., vol. 14, no. 5, pp. 2–3, Sep. 1999, doi: 10.1109/5254.796079.
[2] H. Ren and G. Xu, “Human action recognition in smart classroom,†Proc. - 5th IEEE Int. Conf. Autom. Face Gesture Recognition, FGR 2002, pp. 417–422, 2002, doi: 10.1109/AFGR.2002.1004189.
[3] Y. Shi, W. Xie, G. Xu, R. Shi, Y. Mao, and F. Liu, “The Smart Classroom :,†pp. 47–55.
[4] C. Burghardt, C. Reisse, T. Heider, M. Giersich, and T. Kirste, “Implementing scenarios in a smart learning environment,†6th Annu. IEEE Int. Conf. Pervasive Comput. Commun. PerCom 2008, pp. 377–382, 2008, doi: 10.1109/PERCOM.2008.96.
[5] C. Di, Z. Gang, and X. Juhong, “An introduction to the technology of blending-reality smart classroom,†Proc. - 2008 Int. Symp. Knowl. Acquis. Model. KAM 2008, pp. 516–519, 2008, doi: 10.1109/KAM.2008.172.
[6] A. Dekdouk, “Integrating mobile and ubiquitous computing in a smart classroom to increase learning effectiveness,†2012 Int. Conf. Educ. e-Learning Innov. ICEELI 2012, 2012, doi: 10.1109/ICEELI.2012.6360684.
[7] M. A. Rahman, V. K. Sarker, and K. A. Sayeed, “IClassroom: Toward a low cost interactive classroom,†Proceeding 15th Int. Conf. Comput. Inf. Technol. ICCIT 2012, pp. 209–214, 2012, doi: 10.1109/ICCITECHN.2012.6509739.
[8] G. Mahesh, K. R. Jayahari, and K. Bijlani, “A smart phone integrated smart classroom,†Int. Conf. Next Gener. Mob. Appl. Serv. Technol., pp. 88–93, Dec. 2016, doi: 10.1109/NGMAST.2016.31.
[9] S. Yang and L. Chen, “A face and eye detection based feedback system for smart classroom,†Proc. 2011 Int. Conf. Electron. Mech. Eng. Inf. Technol. EMEIT 2011, vol. 2, pp. 571–574, 2011, doi: 10.1109/EMEIT.2011.6023166.
[10] S. P. Singh, A. Kumar, A. Singh, and K. Jain, “Smart and intelligent next generation classrooms over cloud,†Proc. 2015 IEEE 3rd Int. Conf. MOOCs, Innov. Technol. Educ. MITE 2015, pp. 273–277, Jan. 2016, doi: 10.1109/MITE.2015.7375329.
[11] Y. Kim, T. Soyata, and R. F. Behnagh, “Towards Emotionally Aware AI Smart Classroom: Current Issues and Directions for Engineering and Education,†IEEE Access, vol. 6, pp. 5308–5331, Jan. 2018, doi: 10.1109/ACCESS.2018.2791861.
[12] K. R. Jayahari, B. Beenu, and K. Bijlani, “Delivery monitoring system for teachers’ voice in traditional classrooms and automatic controlling system in smart/remote classrooms,†2017 IEEE Int. Conf. Smart Technol. Manag. Comput. Commun. Control. Energy Mater. ICSTM 2017 - Proc., pp. 115–121, Oct. 2017, doi: 10.1109/ICSTM.2017.8089136.
[13] Z. Liu, P. Luo, X. Wang, and X. Tang, “Deep learning face attributes in the wild,†in Proceedings of the IEEE International Conference on Computer Vision, 2015, vol. 2015 Inter, pp. 3730–3738, doi: 10.1109/ICCV.2015.425.
[14] Martin~Abadi et al., “TensorFlow: Large-Scale Machine Learning on Heterogeneous Systems.†2015, [Online]. Available: https://www.tensorflow.org/.
[15] E. Bisong, “Google Colaboratory,†Build. Mach. Learn. Deep Learn. Model. Google Cloud Platf., pp. 59–64, 2019, doi: 10.1007/978-1-4842-4470-8_7.
[16] C. Ledig et al., “Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network,†Proc. - 30th IEEE Conf. Comput. Vis. Pattern Recognition, CVPR 2017, vol. 2017-January, pp. 105–114, Sep. 2016, doi: 10.48550/arxiv.1609.04802.
[17] F. Schroff, D. Kalenichenko, and J. Philbin, “FaceNet: A unified embedding for face recognition and clustering,†Proc. IEEE Comput. Soc. Conf. Comput. Vis. Pattern Recognit., vol. 07-12-June-2015, pp. 815–823, Oct. 2015, doi: 10.1109/CVPR.2015.7298682.
[18] S. Luan, C. Chen, B. Zhang, J. Han, and J. Liu, “Gabor Convolutional Networks,†IEEE Trans. Image Process., vol. 27, no. 9, pp. 4357–4366, Sep. 2018, doi: 10.1109/TIP.2018.2835143.
[19] N. Dalal and B. Triggs, “Histograms of Oriented Gradients for Human Detection,†in 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR’05), vol. 1, pp. 886–893, doi: 10.1109/CVPR.2005.177.
[20] R. Stiefelhagen, M. Finke, J. Yang, and A. Waibel, “From Gaze to Focus of Attention,†Lect. Notes Comput. Sci. (including Subser. Lect. Notes Artif. Intell. Lect. Notes Bioinformatics), vol. 1614, pp. 765–772, 1999, doi: 10.1007/3-540-48762-X_94.
[21] S. R. H. Langton, H. Honeyman, and E. Tessler, “The influence of head contour and nose angle on the perception of eye-gaze direction,†Percept. Psychophys., vol. 66, no. 5, pp. 752–771, 2004, doi: 10.3758/BF03194970.
[2] H. Ren and G. Xu, “Human action recognition in smart classroom,†Proc. - 5th IEEE Int. Conf. Autom. Face Gesture Recognition, FGR 2002, pp. 417–422, 2002, doi: 10.1109/AFGR.2002.1004189.
[3] Y. Shi, W. Xie, G. Xu, R. Shi, Y. Mao, and F. Liu, “The Smart Classroom :,†pp. 47–55.
[4] C. Burghardt, C. Reisse, T. Heider, M. Giersich, and T. Kirste, “Implementing scenarios in a smart learning environment,†6th Annu. IEEE Int. Conf. Pervasive Comput. Commun. PerCom 2008, pp. 377–382, 2008, doi: 10.1109/PERCOM.2008.96.
[5] C. Di, Z. Gang, and X. Juhong, “An introduction to the technology of blending-reality smart classroom,†Proc. - 2008 Int. Symp. Knowl. Acquis. Model. KAM 2008, pp. 516–519, 2008, doi: 10.1109/KAM.2008.172.
[6] A. Dekdouk, “Integrating mobile and ubiquitous computing in a smart classroom to increase learning effectiveness,†2012 Int. Conf. Educ. e-Learning Innov. ICEELI 2012, 2012, doi: 10.1109/ICEELI.2012.6360684.
[7] M. A. Rahman, V. K. Sarker, and K. A. Sayeed, “IClassroom: Toward a low cost interactive classroom,†Proceeding 15th Int. Conf. Comput. Inf. Technol. ICCIT 2012, pp. 209–214, 2012, doi: 10.1109/ICCITECHN.2012.6509739.
[8] G. Mahesh, K. R. Jayahari, and K. Bijlani, “A smart phone integrated smart classroom,†Int. Conf. Next Gener. Mob. Appl. Serv. Technol., pp. 88–93, Dec. 2016, doi: 10.1109/NGMAST.2016.31.
[9] S. Yang and L. Chen, “A face and eye detection based feedback system for smart classroom,†Proc. 2011 Int. Conf. Electron. Mech. Eng. Inf. Technol. EMEIT 2011, vol. 2, pp. 571–574, 2011, doi: 10.1109/EMEIT.2011.6023166.
[10] S. P. Singh, A. Kumar, A. Singh, and K. Jain, “Smart and intelligent next generation classrooms over cloud,†Proc. 2015 IEEE 3rd Int. Conf. MOOCs, Innov. Technol. Educ. MITE 2015, pp. 273–277, Jan. 2016, doi: 10.1109/MITE.2015.7375329.
[11] Y. Kim, T. Soyata, and R. F. Behnagh, “Towards Emotionally Aware AI Smart Classroom: Current Issues and Directions for Engineering and Education,†IEEE Access, vol. 6, pp. 5308–5331, Jan. 2018, doi: 10.1109/ACCESS.2018.2791861.
[12] K. R. Jayahari, B. Beenu, and K. Bijlani, “Delivery monitoring system for teachers’ voice in traditional classrooms and automatic controlling system in smart/remote classrooms,†2017 IEEE Int. Conf. Smart Technol. Manag. Comput. Commun. Control. Energy Mater. ICSTM 2017 - Proc., pp. 115–121, Oct. 2017, doi: 10.1109/ICSTM.2017.8089136.
[13] Z. Liu, P. Luo, X. Wang, and X. Tang, “Deep learning face attributes in the wild,†in Proceedings of the IEEE International Conference on Computer Vision, 2015, vol. 2015 Inter, pp. 3730–3738, doi: 10.1109/ICCV.2015.425.
[14] Martin~Abadi et al., “TensorFlow: Large-Scale Machine Learning on Heterogeneous Systems.†2015, [Online]. Available: https://www.tensorflow.org/.
[15] E. Bisong, “Google Colaboratory,†Build. Mach. Learn. Deep Learn. Model. Google Cloud Platf., pp. 59–64, 2019, doi: 10.1007/978-1-4842-4470-8_7.
[16] C. Ledig et al., “Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network,†Proc. - 30th IEEE Conf. Comput. Vis. Pattern Recognition, CVPR 2017, vol. 2017-January, pp. 105–114, Sep. 2016, doi: 10.48550/arxiv.1609.04802.
[17] F. Schroff, D. Kalenichenko, and J. Philbin, “FaceNet: A unified embedding for face recognition and clustering,†Proc. IEEE Comput. Soc. Conf. Comput. Vis. Pattern Recognit., vol. 07-12-June-2015, pp. 815–823, Oct. 2015, doi: 10.1109/CVPR.2015.7298682.
[18] S. Luan, C. Chen, B. Zhang, J. Han, and J. Liu, “Gabor Convolutional Networks,†IEEE Trans. Image Process., vol. 27, no. 9, pp. 4357–4366, Sep. 2018, doi: 10.1109/TIP.2018.2835143.
[19] N. Dalal and B. Triggs, “Histograms of Oriented Gradients for Human Detection,†in 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR’05), vol. 1, pp. 886–893, doi: 10.1109/CVPR.2005.177.
[20] R. Stiefelhagen, M. Finke, J. Yang, and A. Waibel, “From Gaze to Focus of Attention,†Lect. Notes Comput. Sci. (including Subser. Lect. Notes Artif. Intell. Lect. Notes Bioinformatics), vol. 1614, pp. 765–772, 1999, doi: 10.1007/3-540-48762-X_94.
[21] S. R. H. Langton, H. Honeyman, and E. Tessler, “The influence of head contour and nose angle on the perception of eye-gaze direction,†Percept. Psychophys., vol. 66, no. 5, pp. 752–771, 2004, doi: 10.3758/BF03194970.
Published
2022-07-13
How to Cite
WIHARDI, Yaya et al.
Smart Classroom System (SCS) Berbasis Kamera Untuk Memantau Keadaan Peserta Didik.
INFORMATION SYSTEM FOR EDUCATORS AND PROFESSIONALS : Journal of Information System, [S.l.], v. 6, n. 1, p. 67-76, july 2022.
ISSN 2548-3587.
Available at: <https://87383.shichuantrade-tw.tech/index.php/ISBI/article/view/1771>. Date accessed: 13 mar. 2025.
doi: https://doi.org/10.51211/isbi.v6i1.1771.
Section
Articles
