| Title |
Low-Cost Digital Twin Framework for 3D Modeling of Homogenous Urban Zones |
| ID_Doc |
44515 |
| Authors |
Felemban, E; Majid, ARMA; Rehman, FU; Lbath, A |
| Title |
Low-Cost Digital Twin Framework for 3D Modeling of Homogenous Urban Zones |
| Year |
2021 |
| Published |
|
| DOI |
10.1007/978-3-030-80126-7_77 |
| 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. |
| Author Keywords |
Digital twin; Low-cost; 3D Modeling; Data collection; Smart city |
| Index Keywords |
Index Keywords |
| Document Type |
Other |
| Open Access |
Open Access |
| Source |
Conference Proceedings Citation Index - Science (CPCI-S) |
| EID |
WOS:000839363100077 |
| WoS Category |
Computer Science, Artificial Intelligence; Computer Science, Information Systems; Computer Science, Theory & Methods |
| Research Area |
Computer Science |
| PDF |
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