Abstract
Smart cities have been on the rise since the last decade. These cities can only be effective and sustainable when acquiring error-free information from multiple aspects and sources. Prone to errors and mistakes, traditional tools and observation methods require new assessment strategies to provide a clear perspective in simulation and a systematic evaluation for decision-making to be aligned with Industry 4.0. Digital Twin can offer an efficient solution to this problem under the cyber-physical system entity by creating a virtual space identical to the physical region and providing predictive information on the city’s current state. Such systems offer accurate representation in a virtual environment while taking input from the real world and simulating them for future predictions. These near-identical systems are constructed at a very high cost, and the cost increases as more intricate details are added to the environment. This paper presents selective technologies that can potentially contribute to developing a low-cost intelligent environment and smarter urban management framework. It looks into the analysis of the impact of different scenarios on a public event in three dimensions that will be crucial to the decision and policymaker before a plan is approved. The proposed framework will be able to guide present and upcoming potential solutions against the administrative challenges.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
Frost, L.A., Sullivan, D.L.: Smart cities. Frost Sullivan Value Propos. 1(1), 42–49 (2019)
Wang, Y., Chen, Q., Zhu, Q., Liu, L., Li, C., Zheng, D.: A survey of mobile laser scanning applications and key techniques over urban areas. Remote Sens. 11(13), 1540 (2019). https://doi.org/10.3390/rs11131540
Lee, K.W., Son, H.W., Kim, D.I.: Drone remote sensing photogrammetry. Seoul Goomib (2016)
No, H.-S., Baek, T.-K.: Real-time underground facility map production using Drones. J. Korean Assoc. Geogr. Inf. Stud. 20(4), 2016–2017 (2017). https://doi.org/10.11108/kagis.2017.20.4.039
Guisado-Pintado, E., Jackson, D.W.T., Rogers, D.: 3D mapping efficacy of a drone and terrestrial laser scanner over a temperate beach-dune zone. Geomorphology 328, 157–172 (2019). https://doi.org/10.1016/j.geomorph.2018.12.013
Krasikov, I., Kulemin, A.N.: Analysis of digital twin definition and its difference from simulation modelling in practical application. KnE Eng. 105–109 (2020). https://doi.org/10.18502/keg.v5i3.6766
Tao, F., et al.: Digital twin-driven product design framework. Int. J. Prod. Res. 57(12), 3935–3953 (2019). https://doi.org/10.1080/00207543.2018.1443229
Sofia, H., Anas, E., Faiz, O.: Mobile mapping, machine learning and digital twin for road infrastructure monitoring and maintenance: Case study of mohammed VI bridge in Morocco. In: Proceedings - 2020 IEEE International Conference of Moroccan Geomatics, MORGEO 2020 (2020). https://doi.org/10.1109/Morgeo49228.2020.9121882
Tao, F., Cheng, J., Qi, Q., Zhang, M., Zhang, H., Sui, F.: Digital twin-driven product design, manufacturing and service with big data. Int. J. Adv. Manufact. Technol. 94(9–12), 3563–3576 (2017). https://doi.org/10.1007/s00170-017-0233-1
Mina. – SoFlo Muslims. https://soflomuslims.com/mina/. Accessed 01 Oct 2020
Stark, R., Israel, J.H., Wöhler, T.: Towards hybrid modelling environments—Merging desktop-CAD and virtual reality-technologies. CIRP Ann. 59(1), 179–182 (2010). https://doi.org/10.1016/j.cirp.2010.03.102
Majid, A.R.M.A., Hamid, N.A.W.A., Rahiman, A.R., Zafar, B.: GPU-based optimization of pilgrim simulation for Hajj and Umrah rituals. Pertanika J. Sci. Technol. 26(3), 1019–1038 (2018)
Nee, A.Y.C., Ong, S.K.: Virtual and augmented reality applications in manufacturing. IFAC Proc. 46(9), 15–26 (2013). https://doi.org/10.3182/20130619-3-RU-3018.00637
Shirowzhan, S., Tan, W., Sepasgozar, S.M.E.: Digital twin and CyberGIS for improving connectivity and measuring the impact of infrastructure construction planning in smart cities. ISPRS Int. J. Geo-Inf. 9(4), 240 (2020). https://doi.org/10.3390/ijgi9040240
Acknowledgment
The authors extend their appreciation to the Deputyship for Research & Innovation, Ministry of Education in Saudi Arabia, for funding this research work through project number 0909.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2021 The Author(s), under exclusive license to Springer Nature Switzerland AG
About this paper
Cite this paper
Felemban, E., Majid, A.R.M.A., Rehman, F.U., Lbath, A. (2021). Low-Cost Digital Twin Framework for 3D Modeling of Homogenous Urban Zones. In: Arai, K. (eds) Intelligent Computing. Lecture Notes in Networks and Systems, vol 284. Springer, Cham. https://doi.org/10.1007/978-3-030-80126-7_77
Download citation
DOI: https://doi.org/10.1007/978-3-030-80126-7_77
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-80125-0
Online ISBN: 978-3-030-80126-7
eBook Packages: Intelligent Technologies and RoboticsIntelligent Technologies and Robotics (R0)