Exploring the Synergistic Effects of Smart School Platforms and Cloud CCTV on Safety and Pedagogical Effectiveness in Vocational Education: A Systematic Review

Norma; Chen Fang

doi:10.56741/IISTR.jpes.001631

Authors

Norma
normaashari.37@gmail.com
Universitas Negeri Makassar
Chen Fang Qingdao Hengxing University of Science and Technology

Keywords:

Cloud CCTV, Digital Ethics, Pedagogical Effectiveness, Smart School Platforms, Vocational Education

Abstract

This systematic review aims to synthesize the most recent evidence (2023-2025) on the integration of Smart School Platforms and Cloud CCTV systems in vocational education and training (VET), mapping their synergistic effects on pedagogical effectiveness and safety. Following the PRISMA 2020 protocol, a systematic search of the Google Scholar database identified 24 relevant peer-reviewed journal articles published between 2023 and 2025. These studies were analyzed to extract data on technological integration, outcomes, and challenges. The analysis of literature reveals a clear synergy. Smart School Platforms (e.g., AI-LMS, IoT classrooms) demonstrably enhance learning personalization, engagement, and cognitive outcomes. Cloud CCTV enables proactive safety monitoring and provides behavioral data. Critically, their integration creates a tension: the technologies that make environments safer and more data-informed also introduce ethical concerns regarding student privacy, autonomy, and the potential for a surveillance-based pedagogy. This review is the first to systematically synthesize the latest research (2023-2025) on the confluence of pedagogical and security technologies within VET. For VET institutions, the findings underscore the necessity of developing ethical frameworks and transparent policies to harness the benefits of this technological synergy while safeguarding student privacy and trust. This study provides evidence-based foundation for the responsible digital transformation of vocational education, directing future empirical research to explore this interplay in hands-on learning environments like workshops and labs.

Downloads

Download data is not yet available.

Author Biographies

Norma, Universitas Negeri Makassar

is a teacher at SMK Negeri 2 Barru, a master's student in Educational Administration at Makassar State University, an LPDP scholarship awardee, a children's story book writer, a member of the learning media community, and one of the members of FLP (Forum Lingkar Pena). (email: normaashari.37@gmail.com).

Chen Fang, Qingdao Hengxing University of Science and Technology

is a lecturer at Qingdao Hengxing University of Science and Technology (Qingdao, China). Her work focuses on higher education with interests in teaching–learning innovation, curriculum and instruction reform, design-based learning, student engagement, learning assessment, and industry–education integration. She has led and participated in multiple teaching-research and teaching-reform projects at the institutional and provincial levels, developed bilingual teaching materials and course resources, and actively supports outcomes-based course improvement and faculty collaboration. (email: chen.fang@student.undiksha.ac.id).

References

S. McGrath and S. Yamada, “Skills for development and vocational education and training: Current and emergent trends,” Int. J. Educ. Dev., vol. 102, 2023, doi: 10.1016/j.ijedudev.2023.102853. DOI: https://doi.org/10.1016/j.ijedudev.2023.102853

W. Strielkowski, V. Grebennikova, A. Lisovskiy, G. Rakhimova, and T. Vasileva, “AI-driven adaptive learning for sustainable educational transformation,” Sustain. Dev., vol. 33, no. 2, pp. 1921–1947, 2025, doi: 10.1002/sd.3221. DOI: https://doi.org/10.1002/sd.3221

S. Mhlongo, K. Mbatha, B. Ramatsetse, and R. Dlamini, “Challenges, opportunities, and prospects of adopting and using smart digital technologies in learning environments: An iterative review,” Heliyon, vol. 9, no. 6, 2023, doi: 10.1016/j.heliyon.2023.e16348. DOI: https://doi.org/10.1016/j.heliyon.2023.e16348

C. Wang, X. Chen, T. Yu, Y. Liu, and Y. Jing, “Education reform and change driven by digital technology: a bibliometric study from a global perspective,” Humanit. Soc. Sci. Commun., vol. 11, no. 1, 2024, doi: 10.1057/s41599-024-02717-y. DOI: https://doi.org/10.1057/s41599-024-02717-y

C. M. S. Ma, D. T. L. Shek, I. Y. H. Fan, X. Zhu, and X. Hu, “The Impact of digital safety competence on cognitive competence, AI self-efficacy, and character,” Appl. Sci. Switz., vol. 15, no. 10, 2025, doi: 10.3390/app15105440. DOI: https://doi.org/10.3390/app15105440

Y. Sun, W. Huang, Z. Wang, X. Xu, M. Wen, and P. Wu, “Smart Teaching Systems: A Hybrid framework of reinforced learning and deep learning,” Int. J. Emerg. Technol. Learn. IJET, vol. 18, no. 20, pp. 37–50, 2023, doi: 10.3991/ijet.v18i20.44217.

A. Adel, “The Convergence of intelligent tutoring, robotics, and IoT in smart education for the transition from industry 4.0 to 5.0,” Smart Cities, vol. 7, no. 1, pp. 325–369, 2024, doi: 10.3390/smartcities7010014. DOI: https://doi.org/10.3390/smartcities7010014

M. Zhang, “Integrating deep learning into educational big data analytics for enhanced intelligent learning platforms,” Inf. Technol. Control, vol. 53, no. 4, pp. 1060–1073, 2024, doi: 10.5755/j01.itc.53.4.36968. DOI: https://doi.org/10.5755/j01.itc.53.4.36968

A. Badshah, A. Ghani, A. Daud, A. Jalal, M. Bilal, and J. Crowcroft, “Towards smart education through internet of things: a survey,” ACM Comput. Surv., vol. 56, no. 2, 2024, doi: 10.1145/3610401. DOI: https://doi.org/10.1145/3610401

E. Dimitriadou and A. Lanitis, “A critical evaluation, challenges, and future perspectives of using artificial intelligence and emerging technologies in Smart classrooms,” Smart Learn. Environ., vol. 10, no. 1, 2023, doi: 10.1186/s40561-023-00231-3. DOI: https://doi.org/10.1186/s40561-023-00231-3

Z. Dai, Q. Zhang, L. Zhao, X. Zhu, and D. Zhou, “Cloud-Edge computing technology-based internet of things system for smart classroom environment,” Int. J. Emerg. Technol. Learn., vol. 18, no. 8, pp. 79–96, 2023, doi: 10.3991/ijet.v18i08.28299. DOI: https://doi.org/10.3991/ijet.v18i08.28299

Y. Nan, S. Jiang, and M. Li, “Large-scale video analytics with cloud–edge collaborative continuous learning,” ACM Trans. Sens. Netw., vol. 20, no. 1, 2023, doi: 10.1145/3624478. DOI: https://doi.org/10.1145/3624478

A. A. Ravindran, “Internet-of-Things edge computing systems for streaming video analytics: trails behind and the paths ahead,” Internet Things, vol. 4, no. 4, pp. 486–513, 2023, doi: 10.3390/iot4040021. DOI: https://doi.org/10.3390/iot4040021

N. Dhanshika, D. Lahamage, T. Anupam, and R. Sawant, “CCTV Integrated attendance monitoring system using face recognition,” 2024 3rd Int. Conf. Innov. Technol. INOCON 2024, 2024, doi: 10.1109/INOCON60754.2024.10512131. DOI: https://doi.org/10.1109/INOCON60754.2024.10512131

P. L. Jancy, D. M. R. Devi, G. Kavya, S. Aneesh Aashifa, and G. Kirthika, “AI-assisted smart classroom,” 2025 Int. Conf. Comput. Commun. Technol. ICCCT 2025, 2025, doi: 10.1109/ICCCT63501.2025.11019300. DOI: https://doi.org/10.1109/ICCCT63501.2025.11019300

J. Wang, J. Zhang, J. Fan, S. Zhang, J. Wang, and Y. Geng, “Design and application of smart vocational education platform based on new generation information technology,” Proc. - 2020 Int. Conf. Comput. Vis. Image Deep Learn. CVIDL 2020, pp. 505–509, 2020, doi: 10.1109/CVIDL51233.2020.00-40. DOI: https://doi.org/10.1109/CVIDL51233.2020.00-40

D. Li, R. Hu, and Z. Lin, “Vocational education platform based on blockchain and IoT technology,” Comput. Intell. Neurosci., vol. 2022, 2022, doi: 10.1155/2022/5856229. DOI: https://doi.org/10.1155/2022/5856229

H. Lin, “Intelligent teaching system of vocational education based on a new generation of information technology,” Lect. Notes Inst. Comput. Sci. Soc.-Inform. Telecommun. Eng. LNICST, vol. 439 LNICST, pp. 606–616, 2022, doi: 10.1007/978-3-031-04245-4_53. DOI: https://doi.org/10.1007/978-3-031-04245-4_53

M. Zhang, “Optimization strategy of college students’ education management based on smart cloud platform teaching,” Comput. Intell. Neurosci., vol. 2023, no. 1, 2023, doi: 10.1155/2023/5642142. DOI: https://doi.org/10.1155/2023/5642142

J. Faritha Banu, R. Revathi, M. Suganya, and N. R. Gladiss Merlin, “IoT based Cloud integrated smart classroom for a smart and sustainable campus,” Procedia Comput. Sci., vol. 172, pp. 77–81, 2020, doi: 10.1016/j.procs.2020.05.012. DOI: https://doi.org/10.1016/j.procs.2020.05.012

Q. Li, “The Use of artificial intelligence combined with cloud computing in the design of education information management platform,” Int. J. Emerg. Technol. Learn., vol. 16, no. 5, pp. 32–44, 2021, doi: 10.3991/ijet.v16i05.20309. DOI: https://doi.org/10.3991/ijet.v16i05.20309

M. J. Page, J E McKenzie, P M Bossuyt, I Boutron, T C Hoffmann, C D Mulrow, L Shamseer, J M Tetzlaff, E A Akl, S E Brennan, R Chou, J Glanville, J M Grimshaw, A Hróbjartsson, M Lalu, T Li, E Loder, E Mayo- Wilson, S Mc Donald, L A Mc Guinness, L A Stewart, J Thomas, Andrea C Tricco, V A Welch, P Whiting, “The PRISMA 2020 statement: An updated guideline for reporting systematic reviews,” Bmj, vol. 372, 2021, doi: 10.1136/bmj.n71. DOI: https://doi.org/10.1136/bmj.n71

A. F. M. Fahimey, M. Masrom, N. A. Suwastika, A. Azizan, S. A. Othman, and H. H. Nuha, “Enhancing learning management systems with artificial intelligence in vocational education in Malaysia,” 2024 IEEE Int. Conf. Comput. ICOCO 2024, pp. 474–478, 2024, doi: 10.1109/ICOCO62848.2024.10928192. DOI: https://doi.org/10.1109/ICOCO62848.2024.10928192

N. A. Ahmad, N. F. Elias, N. Sahari, and H. Mohamed, “Learning management system acceptance factors for technical and vocational education training (TVET) institutions,” TEM J., vol. 12, no. 2, pp. 1156–1165, 2023, doi: 10.18421/TEM122-61.

N. N. Bizhanov, G. M. Manarbek, and A. A. Shaikh, “Exploring the use of learning management system as an effective tool for quality management of vocational education,” J. Econ. Res. Bus. Adm., vol. 150, no. 4, pp. 91–108, 2024, doi: 10.26577/be.2024.150.i4.a7. DOI: https://doi.org/10.26577/be.2024.150.i4.a7

L. Ye and Z. Lu, “An Empirical study on the learning outcomes of vocational students in a smart classroom,” Int. J. Sociol. Anthropol. Sci. Rev., vol. 4, no. 6, pp. 605–620, 2024, doi: 10.60027/ijsasr.2024.5143. DOI: https://doi.org/10.60027/ijsasr.2024.5143

L. Wang and Y. Wang, “Design and implementation of STEAM programs in vocational schools in a smart education environment,” Contemp. Educ. Teach. Res., vol. 4, no. 12, pp. 677–684, 2023, doi: 10.61360/bonicetr232015491212. DOI: https://doi.org/10.61360/BoniCETR232015491212

N. A. Ahmad, N. F. Elias, N. Sahari, and H. Mohamed, “Learning management system acceptance factors for technical and vocational education training (TVET) Institutions,” TEM J., vol. 12, no. 2, pp. 1156–1165, 2023, doi: 10.18421/TEM122-61. DOI: https://doi.org/10.18421/TEM122-61

P. Kumar, P. Negi, P. Sharma, and P. Mittal, “IoT-Enabled smart classrooms for enhanced learning environments,” 2025 2nd Int. Conf. Comput. Intell. Commun. Technol. Netw. CICTN 2025, pp. 944–949, 2025, doi: 10.1109/CICTN64563.2025.10932356. DOI: https://doi.org/10.1109/CICTN64563.2025.10932356

J. Huang and D. Zhou, “A scalable real-time computer vision system for student posture detection in smart classrooms,” Educ. Inf. Technol., vol. 29, no. 1, pp. 917–937, 2024, doi: 10.1007/s10639-023-12365-5. DOI: https://doi.org/10.1007/s10639-023-12365-5

S. A. Suryantoro, M. Muchlas, and B. Santosa, “Use of digital learning management systems for enhancing cognitive achievement in vocational productive course,” J. Vocat. Educ. Stud., vol. 7, no. 1, pp. 126–136, 2024, doi: 10.12928/joves.v7i1.10360. DOI: https://doi.org/10.12928/joves.v7i1.10360

L. Li, Y. Lu, L. Liu, and Y. Gao, “Design and implementation of collaborative learning algorithm for vocational education based on multi-agent system,” Proc. - 2024 3rd Int. Conf. Artif. Intell. Auton. Robot Syst. AIARS 2024, pp. 398–403, 2024, doi: 10.1109/AIARS63200.2024.00080. DOI: https://doi.org/10.1109/AIARS63200.2024.00080

H. U. Khan, M. Abbas, O. Alruwaili, S. Nazir, M. H. Siddiqi, and S. Alanazi, “Selection of a smart and secure education school system based on the internet of things using entropy and TOPSIS approaches,” Comput. Hum. Behav., vol. 159, 2024, doi: 10.1016/j.chb.2024.108346. DOI: https://doi.org/10.1016/j.chb.2024.108346

J. Gu, “Application of intellectual educational technologies in vocational education,” Int. Cult. Technology Stud., vol. 9, no. 4, pp. 199–212, 2025, doi: 10.17586/2587-800x-2024-9-4-199-212. DOI: https://doi.org/10.17586/2587-800X-2024-9-4-199-212

M. Liu, P. Liu, R. Lu, and X. Jiang, “Intelligent and personalized vocational education: applications and strategies,” Proc. - 2024 14th Int. Conf. Inf. Technol. Med. Educ. ITME 2024, pp. 503–507, 2024, doi: 10.1109/ITME63426.2024.00106. DOI: https://doi.org/10.1109/ITME63426.2024.00106

N. El Brouzi, L. Belhaj, and A. Bouaaich, “Elevating vocational training: the power of learning management systems in shaping digital skills,” Int. J. Multidiscip. Res., vol. 6, no. 6, 2024, doi: 10.36948/ijfmr.2024.v06i06.30509. DOI: https://doi.org/10.36948/ijfmr.2024.v06i06.30509

I. Noguera, D. Barrientos, M. Torres-Sánchez, and P. Pineda-Herrero, “Exploring pedagogical and digital practices in vocational education and training: comparing teacher and student perspectives,” Educ. Sci., vol. 14, no. 7, 2024, doi: 10.3390/educsci14070734. DOI: https://doi.org/10.3390/educsci14070734

Y. Sun, W. Huang, Z. Wang, X. Xu, M. Wen, and P. Wu, “Smart Teaching Systems: A Hybrid framework of reinforced learning and deep learning,” Int. J. Emerg. Technol. Learn. IJET, vol. 18, no. 20, pp. 37–50, 2023, doi: 10.3991/ijet.v18i20.44217. DOI: https://doi.org/10.3991/ijet.v18i20.44217

Rejisha and Brintha, “Integrating deep learning and CCTV for real-time health monitoring in Schools,” International J. Sci. Res. Eng. Manag., vol. 08, no. 11, pp. 1–6, 2024, doi: 10.55041/ijsrem39114. DOI: https://doi.org/10.55041/IJSREM39114

C. Viana, “Innovative Protection in Education: Employing IoT, AI, and Cloud Computing for enhanced detection and supportive response systems in Schools,” pp. 73–92, 2024, doi: 10.5121/csit.2024.140105. DOI: https://doi.org/10.5121/csit.2024.140105

D. Das, U. Ghosh, P. Chatterjee, and S. Shetty, “Advanced federated learning-empowered edge-cloud framework for school safety prediction and emergency alert system,” 2023 IEEE 12th Int. Conf. Cloud Netw. CloudNet 2023, pp. 507–512, 2023, doi: 10.1109/CloudNet59005.2023.10490054. DOI: https://doi.org/10.1109/CloudNet59005.2023.10490054

M. Ryoo and S. Yoo, “Usability Evaluation of a Web Apps child behavior analysis data-driven responsive service platform,” TECHART J. Arts Imaging Sci., vol. 10, no. 3, pp. 47–51, 2023, doi: 10.15323/techart.2023.10.10.3.47. DOI: https://doi.org/10.15323/techart.2023.10.10.3.47

N. Kerich, S. O. Omuterema, and M. M. Pepela, “Evaluating the role of electronic security surveillance in enhancing safety in secondary schools: a case study of trans nzoia county, Kenya,” Afr. J. Empir. Res., vol. 5, no. 4, pp. 163–173, 2024, doi: 10.51867/ajernet.5.4.14. DOI: https://doi.org/10.51867/ajernet.5.4.14

D. Pandya, K. Rana, and A. Padhiyar, “Comparative analysis of deep learning approach to identify usage of mobile phone in the classroom environment,” Educ. Inf. Technol., vol. 30, no. 10, pp. 13105–13128, 2025, doi: 10.1007/s10639-025-13351-9. DOI: https://doi.org/10.1007/s10639-025-13351-9

H. Meishar-Tal and A. Forkosh-Baruch, “Panopticon, Synopticon, and Omniopticon: A conceptual framework for understanding the utilization of cameras and video recordings in education,” Educ. Philos. Theory, vol. 56, no. 14, pp. 1391–1402, 2024, doi: 10.1080/00131857.2024.2395338. DOI: https://doi.org/10.1080/00131857.2024.2395338

R. Kunwar, “Perceptions of school administrators, teachers, and students on the use of CCTV cameras and their impact on learning mathematics,” World J. Educ. Technol. Curr. Issues, vol. 16, no. 3, pp. 215–234, 2024, doi: 10.18844/wjet.v16i3.9335. DOI: https://doi.org/10.18844/wjet.v16i3.9335

M. Devkota, “The Privacy Price of School Safety Stakeholders’ Perceptions Towards the Use of Closed-Circuit Television (CCTV) in Schools,” Madhyabindu J., vol. 9, no. 1, pp. 48–72, 2024, doi: 10.3126/madhyabindu.v9i1.65386. DOI: https://doi.org/10.3126/madhyabindu.v9i1.65386