Smart City Gnosys
Smart city article details
| Title | Digital Twin And Cybergis For Improving Connectivity And Measuring The Impact Of Infrastructure Construction Planning In Smart Cities |
|---|---|
| ID_Doc | 20164 |
| Authors | Shirowzhan S.; Tan W.; Sepasgozar S.M.E. |
| Year | 2020 |
| Published | ISPRS International Journal of Geo-Information, 9, 4 |
| DOI | http://dx.doi.org/10.3390/ijgi9040240 |
| Abstract | Smart technologies are advancing, and smart cities can be made smarter by increasing the connectivity and interactions of humans, the environment, and smart devices. This paper discusses selective technologies that can potentially contribute to developing an intelligent environment and smarter cities. While the connectivity and efficiency of smart cities is important, the analysis of the impact of construction development and large projects in the city is crucial to decision and policy makers, before the project is approved. This raises the question of assessing the impact of a new infrastructure project on the community prior to its commencement-what type of technologies can potentially be used for creating a virtual representation of the city? How can a smart city be improved by utilizing these technologies? There are a wide range of technologies and applications available but understanding their function, interoperability, and compatibility with the community requires more discussion around system designs and architecture. These questions can be the basis of developing an agenda for further investigations. In particular, the need for advanced tools such as mobile scanners, Geospatial Artificial Intelligence, Unmanned Aerial Vehicles, Geospatial Augmented Reality apps, Light Detection, and Ranging in smart cities is discussed. In line with smart city technology development, this Special Issue includes eight accepted articles covering trending topics, which are briefly reviewed. © 2020 by the authors. |
| Author Keywords | Artificial intelligence; Big data; CyberGIS; Digital twin; GIS; Infrastructure construction; Lidar; Machine learning; Mobile laser scanner; Point cloud; Point-based algorithms; Smart city; Smart parking; Urban computing |
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