## 3 Integrating DT in CPS
### Smart Cities  
The objective of the smart city is to leverage information communication and data-related technologies so that resources can be efficiently used, leading to better quality of life, reduction of resource input, etc. So far, the majority of focus has been on government and energy initiatives, followed by transportation, building, and water, among other goals. A number of research and development efforts on smart cities and DT applications have been generated [92; 93; 94; 95; 96]. Similar to smart manufacturing, smart cities are the combination of a wide range of IoT domains to address the complex challenges in cities and must incorporate cloud/edge computing with big data collection and analysis as essential techniques to drive the realization of efficiency and optimization [11; 97].  
It should be noted that the development of the smart city has involved several opportunities and challenges: (i) people's expectations are constantly changing. How can people's expectations be accounted for when they are frequently and forever changing, even when real-time communication is a reality? How can the change in expectation be evaluated? (ii) How can the latest technologies be utilized to improve the efficiency of our government? How can we forecast outcomes and avoid potential losses or mistakes? How can we mitigate the risks? These questions have become the urgent issues that a government must consider with respect to smart cities. Similar to numerous practices in smart manufacturing, in smart cities, we could leverage DT to detect and address a problem before it arises, reducing cost, rather than attempting to solve a problem after it has occurred. If the results from the DT match the expectation, data can be transferred to real physical objects to implement the changes in a fast and seamless way.  
Some efforts toward integrating DT with smart cities have already been made [98; 99; 100; 101; 102; 103]. For example, [PERSON] et al. [98] reviewed some key technologies in Digital Twin City (DTCs), such as surveying and mapping, building information model, IoT, next-generation wireless networking, and blockchain. [PERSON] et al. [99] reviewed some challenges of DT cities and discussed some research that leveraged DT into smart cities. Note that while the city DT cannot provide solutions for addressing problems in cities, DT can provide benefits in several areas. In order to demonstrate the performance of DT, it is necessary to conduct research on data collection, data management, the utilization of big data, virtual reality (VR), IoT, and 3D Modeling. Likewise, [PERSON] et al. [100] discussed technologies that can be useful for enabling smarter cities. They identified trends in geospatial science, particularly in the application of geographic information system (GIS), and observed the impacts of newly developed online applications such as ArcGIS Urban.  
More and more smart cities around the world are embracing DT to replicate its performance and response to changes. By the year 2020, 118 cities were using DT in Smart City projects and systems. Cities are also using DT to reduce carbon dioxide emissions and manage traffic efficiently. According to ABI Research, DT could assist cities in carrying out cost-effective urban resource planning [104]. We believe that DT has the potential to further improve upon the already significant gains that it has achieved.