Abstract
With the rapid development of intelligent surveying and mapping industry, the application of Internet of Things and GNSS in deformation monitoring is becoming more and more extensive. Surveying and mapping engineering has high requirements for practical ability training, but traditional offline teaching methods cannot meet the needs of students, and the cost of offline education is relatively high. Therefore, based on WebGL technology and B/S architecture, with the background of high-rise deformation monitoring, this paper carries out a comprehensive chain integration of software and hardware operation functions in the production process such as the basic principle, data acquisition and data analysis of GNSS-based deformation monitoring technology, and builds a virtual simulation experiment system for high-rise deformation monitoring based on the Internet of Things and GNSS. The system simulates the basic system theory cognition in the process of collecting the Internet of Things and deformation data, the layout of the deformation monitoring network of the Internet of Things and the deformation data analysis and other functions, innovates the teaching method of modern surveying and mapping information technology practice courses, and uses virtual simulation technology to train innovative applied talents with professional competence and social adaptability. More accurately judge the possible disaster of the building, and take corresponding measures to avoid the occurrence of major accidents.
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References
He, Y., Lu, H., Song, Y., Liu, L.: Design and implementation of virtual simulation experiment system for acquisition and production of UAV real-scene 3D data. In: 2021 4th IEEE International Conference on Automation, Electronics and Electrical Engineering, AUTEEE 2021, pp. 249–254 (2021)
Li, L., Liang, Z., Ding, R.: Application research of virtual simulation technology in UAV surveying and mapping practice teaching. Fujian Build. Mater. (05), 92–96 (2022)
Yue, X., He, X., Ma, F.: Application of virtual simulation technology in surveying and mapping engineering practice teaching. Surveying Mapping Eng. 30(01), 76–80 (2021)
Zhang, D., Gu, Y., Liu, M.: Development and design of virtual simulation experimental teaching system for Internet of Things. Digit. Commun. World (01), 271–272 (2021)
Ling, X.: Design of graphical virtual simulation experimental platform based on Internet of Things. Mod. Electron. Technol. 40(01), 32–35+40 (2017)
Li, L., Zhang, L., Wang, S.-Y.: Research on virtual simulation system of IoT training based on multi-software. Comput. Program. Skills Maintenance (06), 56–58 (2022)
Shen, J.: Implementation of virtual simulation based on NB-IoT application system. J. Nanjing Open Univ. (02), 72–76 (2022)
Qi, H., Xiong, H., Chen, J.: Design and development of virtual simulation experiment for excavation deformation monitoring with multi-scenario dynamic change. J. Southeast Univ. (Philos. Soc. Sci. Ed.) 21(S1), 146–148 (2019)
Jin, Q., Feng, G., Li, G.: Integrated practical training design of virtual simulation teaching of “Internet of Things Smart Agriculture”. Computer Age (04), 21–23+28 (2022)
Long, J., Tang, W., Yang, C.: Research on virtual simulation platform for Dam state safety monitoring. In: National Dam Safety Monitoring Technical Information Network 2006 Monitoring Technical Information Exchange Meeting (2006)
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Yang, W., He, Y., Xie, Z., He, T. (2024). Design and Implementation of Virtual Simulation Experimental System for Deformation Monitoring of Tall Buildings Based on Internet of Things and GNSS. In: Dong, J., Zhang, L., Cheng, D. (eds) Proceedings of the 2nd International Conference on Internet of Things, Communication and Intelligent Technology. IoTCIT 2023. Lecture Notes in Electrical Engineering, vol 1197. Springer, Singapore. https://doi.org/10.1007/978-981-97-2757-5_17
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DOI: https://doi.org/10.1007/978-981-97-2757-5_17
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