USING A VIRTUAL TWIN OF A BUILDING TO ENSURE SECURITY IN EDUCATIONAL INSTITUTIONS

Authors

DOI:

https://doi.org/10.37943/14LUQF6985

Keywords:

computer vision, digital twins, security, education institutions, machine learning, modeling

Abstract

This research paper delves into the exploration of computer vision technology and digital twins as a means to enhance security measures in educational institutions. The study primarily focuses on the creation of a virtual replica of the first floor of a school and the integration of a person detection algorithm with the existing surveillance cameras. By leverag- ing the capabilities of the digital twin and real-time monitoring, comprehensive surveillance of the premises becomes feasible, resulting in simplified security operations. The paper sheds light on the significant potential of training neural networks for specific security tasks, such as the identification of weapons or the detection of anomalies in human behavior. These trained neural networks can be seamlessly integrated into the digital twin, thus ensuring public safety within the educational environment. The findings of this study provide substantial evidence for the effectiveness of computer vision technology and digital twins in bolstering security measures. The ability to create a virtual representation of the school’s first floor enables com- prehensive monitoring and surveillance, aiding in the prevention and prompt response to se- curity incidents. The integration of person detection algorithms further enhances the system’s capabilities by automatically identifying and tracking individuals within the premises. Addi- tionally, the deployment of neural networks for specialized security tasks adds an extra layer of protection, enabling the identification of potential threats and the detection of abnormal behavior patterns. By employing computer vision technology and digital twins, educational institutions can establish an advanced security infrastructure that optimizes monitoring, en- hances situational awareness, and ensures a safer environment for students, staff, and visitors. The research presented in this paper highlights the tremendous potential and practical impli- cations of these technologies in the realm of educational security.

Author Biographies

Azat Absadyk, Astana IT University

Master of Technical Sciences, Postdoctoral researcher, Department of Science and Innovation

Yerdaulet Absattar, Astana IT University

Master of Engineering in Engineering Management, CEO & Founder of Alpha Design LLC, Co-founder of Oraclus, Co-founder of GBEX

References

Wang, H.E., Scholly, J., Triebkorn, P., Sip, V., Medina Villalon, S., Woodman, M.M., Le Troter, A., Guye, M., Bartolomei, F., & Jirsa, V. (2021). VEP atlas: An anatomic and functional human brain atlas dedicated to epilepsy patients. Journal of Neuroscience Methods, 348, 108983. https://doi.org/10.1016/j.jneumeth.2020.108983

Liu, M., Fang, S., Dong, H., & Xu, C. (2021). Review of digital twin about concepts, technologies, and industrial applications. Journal of Manufacturing Systems, 58, 346–361. https://doi.org/10.1016/j. jmsy.2020.06.017

Allam, Z., Sharifi, A., Bibri, S.E., Jones, D.S., & Krogstie, J. (2022). The Metaverse as a virtual form of smart cities: Opportunities and challenges for environmental, economic, and social sustainability in urban futures. Smart Cities, 5(3), 771–801. https://doi.org/10.3390/smartcities5030040

Park, J.-S., Lee, D.-G., Jimenez, J.A., Lee, S.-J., & Kim, J.-W. (2023). Human-focused digital twin applications for occupational safety and health in workplaces: A brief survey and research directions. Applied Sciences, 13(7), 4598. https://doi.org/10.3390/app13074598

Wanasinghe, T.R., Wroblewski, L., Petersen, B.K., Gosine, R.G., James, L.A., De Silva, O., Mann, G.K.I., & Warrian, P.J. (2020). Digital twin for the oil and gas industry: Overview, research trends, opportunities, and challenges. IEEE Access, 8, 104175–104197. https://doi.org/10.1109/access.2020.2998723

Wang, J. , Huang, Y. , Zhai, W. , Li, J. , Ouyang, S. , Gao, H. , Liu, Y. , & Wang, G. (2023). Research on coal mine safety management based on digital twin. Heliyon, 9(3), e13608. https://doi.org/10.1016/j. heliyon.2023.e13608

Kaewunruen, S., AbdelHadi, M., Kongpuang, M., Pansuk, W., & Remennikov, A.M. (2022). Digital twins for managing railway bridge maintenance, resilience, and climate change adaptation. Sensors, 23(1), 252. https://doi.org/10.3390/s23010252

Salem, T., & Dragomir, M. (2023). Digital twins for construction projects—Developing a risk systematization approach to facilitate anomaly detection in smart buildings. Telecom, 4(1), 135–145. https://doi.org/10.3390/telecom4010009

Shan, Z. , Zhang, Y. , Zhang, Y. , Tang, S. , & Wang, W. (2021). A review of recent progress and developments in China smart cities. IET Smart Cities, 3(4), 189–200. https://doi.org/10.1049/smc2.12020 10. Jason Shueh. (2017). Smart city surveillance: Singapore’s camera system stands as a potent deterrent. Statescoop. https://statescoop.com/smart-city-surveillance-singapores-camera-system-stands-as-a-potent-deterrent/

Gentile, G. (2023). Does Big Brother exist? Face recognition technology in the United Kingdom. SSRN Electronic Journal. https://doi.org/10.2139/ssrn.4331633

Liang, K.J., Sigman, J.B., Spell, G.P., Strellis, D., Chang, W., Liu, F., Mehta, T., & Carin, L. (2019). Toward automatic threat recognition for airport X-ray baggage screening with deep convolutional object detection (Version 1). arXiv. https://doi.org/10.48550/ARXIV.1912.06329

Lee, C., Kim, Y., Jin, S., Kim, D., Maciejewski, R., Ebert, D., & Ko, S. (2020). A visual analytics system for exploring, monitoring, and forecasting road traffic congestion. IEEE Transactions on Visualization and Computer Graphics, 26(11), 3133–3146. https://doi.org/10.1109/tvcg.2019.2922597

Enelane, N. (2018). Kak rabotaet proekt «Sergek». Reportazh Informburo.kz. Retrieved from In- formburo website: https://informburo.kz/stati/kak-rabotaet-proekt-sergek-reportazh-informburokz.html.

Wong, K.L.X., & Dobson, A.S. (2019). We’re just data: Exploring China’s social credit system in relation to digital platform ratings cultures in Westernised democracies. Global Media and China, 4(2), 220–232. https://doi.org/10.1177/2059436419856090.

Ren, S., He, K., Girshick, R., & Sun, J. (2015). Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks (Version 3). arXiv. https://doi.org/10.48550/ARXIV.1506.01497.

Redmon, J., Divvala, S., Girshick, R., & Farhadi, A. (2015). You Only Look Once: Unified, Real-Time Object Detection (Version 5). arXiv. https://doi.org/10.48550/ARXIV.1506.02640.

Liu, W., Anguelov, D., Erhan, D., Szegedy, C., Reed, S., Fu, C.-Y., & Berg, A. C. (2016). SSD: Single Shot MultiBox Detector. In Computer Vision – ECCV 2016 (pp. 21–37). Springer International Publishing. https://doi.org/10.1007/978-3-319-46448-0_2.

He, K., Gkioxari, G., Dollár, P., & Girshick, R. (2017). Mask R-CNN (Version 3). arXiv. https://doi.org/10.48550/ARXIV.1703.06870.

Dalal, N., & Triggs, B. (n.d.). Histograms of Oriented Gradients for Human Detection. In 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR’05). IEEE. https://doi.org/10.1109/cvpr.2005.177.

Uijlings, J.R.R., van de Sande, K.E.A., Gevers, T., & Smeulders, A.W.M. (2013). Selective Search for Object Recognition. International Journal of Computer Vision, 104(2), 154–171. Springer Science and Business Media LLC. https://doi.org/10.1007/s11263-013-0620-5.

Chan, S., Zhou, X., Huang, C., Chen, S., & Li, Y.F. (2016). An improved method for fisheye camera calibration and distortion correction. In 2016 International Conference on Advanced Robotics and Mechatronics (ICARM). IEEE. https://doi.org/10.1109/icarm.2016.7606985.

Sung, Thaileang & Lee, Hyo Jong. (2018). Images Alignment Using Homography Transformation Matrix.

A-square. (2022, December 4). Using a virtual twin of a building in educational institutions [Video]. YouTube. https://youtu.be/ORjfedZs88A.

Downloads

Published

2023-06-30

How to Cite

Absadyk, A., & Absattar, Y. (2023). USING A VIRTUAL TWIN OF A BUILDING TO ENSURE SECURITY IN EDUCATIONAL INSTITUTIONS. Scientific Journal of Astana IT University, 14(14), 127–140. https://doi.org/10.37943/14LUQF6985

Issue

Section

Articles
betpas