Jiayi Yan, Dr. Xu Shen, Kai Yin
Poli is one of the most prosperous port cities that locates in the southwest of the West Coast New District of Qingdao, Shandong Province in China. It has a total area of 156 square kilometers and a coastline of 40 kilometers. The population of the city is around 114 thousand. As many other cities in China or Worldwide, Poli confronts pressures and challenges brought by exponential growth of urbanisation and population. For example, the war with Covid-19 is an inevitable challenge to be tackled in 2020. Therefore, Poli has been assigned as one of experimental cities by the nation that aims to explore the new paths and models for a sustainable, inclusive smart city development. During the exploration, a city-level Digital Twin solution was adopted and adapted for Poli in order to integrate cutting-edge technologies and thus create a digital replica of Poli’s physical city for better governance and service. Especially, an innovative combination of CIM graphic engine and integrated data resources centre (IDRC) was proposed and applied, as a technical CIM route that guarantee the implementation of the DT solution. As a result, Poli was the winner of 2020 World Smart City Award (Greater China Area) – Governance and Service Award.
This chapter is going to discuss the application of Smart Poli development in four sections, namely: (1) a state of the art of smart city and digital twin development in China and the project background of Poli, (2) the multi-layered CIM-enhanced DT architecture overview, including the CIM graphic engine and IDRC, (3) pilot modules application in Poli’s governance and service including Integration of planning, construction and management, smart governance and digitalised public services, (4) and lessons learned from Smart Poli mission to asset stakeholders, policy and decision makers, practitioners and researchers.
Digital Twin, Smart City, City Information Modeling (CIM), Integrated Data Resource Centre (IDRC)
1 Background: Smart city development in China
Since the concept of smart city was introduced by IBM in 2008 (Palmisano S.J. 2008), the light has never been stopped shining on it. Especially as the Covid-19 pandemic stroke the world abruptly in early 2020, the urgency of smart city development has been increased greatly to tackle a variety of city diseases like medical issues, transportation, and urban sprawling, as well as to improve the capability of city governance and service.
1.1 The evolution and state of the art of smart city development in China
With an overwhelming number of populations around 1.4 billion, China has adopted and adapted the promotion of smart city as a national strategic choice for a decade. Generally, there have been four stages the concluded the development of previous actions (see Figure 1) (National Development and Reform Commission, 2020).
The first stage is relatively explorational and experimental. Departments and organisations from different cities were advocating a unique smart city focus based their understanding independently. For example, Nanjing focused on developing the ‘smart’ level of infrastructure and industry; Wuhan cooperated with IBM mainly concentrating on promoting the perceiving capability like equipping IoT sensers and cloud computing centres and Shenzhen contributed to support the systematic development of e-commerce. Although positive feedbacks were collected from the actions to some extent, the construction of smart city in this stage was comparatively scattered and disorderly without certain targets and proper coordination (Hao et al., 2012).
Figure 1 The development of smart city in China
In the second stage, the national-level organisation was founded to guide and instruct the healthy expansion of smart city projects. Besides, three batches of pilot cities (the ‘city’ indicates the city-scale district) in total of 340 were set to encourage the intelligent development in China from the end of 2013 to 2015 (Ministry of Housing and Urban-Rural Development, 2013; Zhu, Li and Feng, 2019). These two stages embraced the smart city mainly by evolving large-scale information and communication technology (ICT), such as Internet of things (IoT), cloud computing, information system, which partially reflected the advocation of smart planet and smart city from IBM that highly emphasising the importance of embedding ICTs like sensors and equipment to infrastructures (Su, Li and Fu, 2011), thus, to achieve thorough perception and ubiquitous interconnection for public-oriented sustainable innovation. A primary issue is that certain application scenarios or contexts are ambiguous, which is hard for the investors (usually the governmental departments) to leverage the actual values.
In the third stage, smart city strategy was considered a national-level solution from a couple of perspectives. On one hand, as the cities were equipping themselves with ICT infrastructures continuously following the steps of the metropolitan cities like Beijing, Shanghai and Shenzhen, the city governors realised that specific scenarios are required based on the built ICT environment. Therefore, the nationwide smart city emphasis was heavily laid on the governance information systems (e-governance) construction and integration in order to eliminate governance data isolation and improve the efficiency of daily tasks for the public’s welfare. On the other hand, given the speed of urbanisation in China increases rapidly in decades, the construction size was enormous due to the rapid urbanization (see Figure 2). Smart city strategy has been proved to be one of the effective efforts to deal with a variety urban issues (Lu et al., 2020). Guided by this direction, the emphasis of smart city values was moderately turned to architecture, engineering, construction and facility management (AEC/FM) sectors in this stage.
The fourth stage is from the end of 2017 till nowadays, which is an expansion stage of smart city development. Not only the necessity of ICT infrastructures and more updated generation of technology like artificial intelligence (AI), 5G and block chain etc. bolster the smart city solution, but the city-level digital twin is addressed because of the new urbanisation in China, which states the “smart genes” ought to be embedded in the beginning of urbanisation of a certain area or city. The smart city from this stage would be rather be recognised as innovative smarter city (National Development and Reform Commission, 2020) .
Figure 2 Urbanisation rate in China
Considering the development of smart city in China over the decade, it experienced the dilemma period while gained valuable lessons. An appropriate route could be specified corresponding to Chinese characteristics. Suggestions might be taken from the multiple aspects. First of all, an in-depth blueprint or master plan that considering the long-term urban planning and urbanisation of a city, instead of constructing the smart city as a disposable standalone project based on vague experiences; then, it should be avoided to invest the heavy-loaded ICT infrastructures at once, which may result in waste of resources and longer investment cycle; besides, traditional software and hardware technology has obvious technical bottleneck in the face of large-scale intelligent system intended for smart city, which mainly lacks the support of distributed computing, big data, AI and high-efficiency data transmission; Furthermore, it should be realised that the smart city cannot be accomplished at one stroke and, a systematic and strategic schedule would be necessary to keep the smart city ecology sustainable for constant data resources and technology evolution.
1.2 City-level digital twin development in China
In AEC/FM sectors, the concept of digital twins (DTs) has been coined as an integrated approach to plan, predict, present building and infrastructure or city assets that can be implemented with many advanced technologies that could be categorised into three perspectives (i.e., data related technologies, high-fidelity modeling technologies, model-based simulation technologies) (Lu et al., 2020; Liu et al., 2020). Different from the smart city development from the first two (even three) stages concluded previously in China, the proposed DT is more explicit with application scenarios rather than hardware infrastructure and static data accumulation without values created for decision making. For instance, Su, Li and Fu(2011) proposed a technical architecture of smart city in China with three layers of perception, network and application, whereas the specific elements and information composing the smart cities were overlooked. It is stiff to build a smart city with applications without specifying the type of elements or data and scaling down the size of data collection.
In China, the city-level DT is mainly dominated by the city information modeling (CIM) methodology. Literally, CIM seems to be the extension of building information modeling (BIM) from building to city scale. However, it is not a simple model integration of BIM, GIS or all other city elements graphically (Xu et al., 2014), nor a simple carrier that links physical city and a digital city (Wang et al., 2020). The authors of this work indicate CIM from temporal and spatial perspectives:
To be concise, CIM is a more specified representation of the city-level DT, a specialised adoption based on DT technology in AEC/FM sector to create an innovative smarter city. By constructing an intricate system with characteristics of one-to-one correspondence, mutual mapping and collaborative interaction between the physical world and virtual space, it realises the digitisation and virtualisation of all elements of the city, the real-timeness and visualisation of the city status, the coordination and intelligence of city management for decision-making. Besides, CIM can also be regarded as the complex and comprehensive technical system supporting the construction of a smart city, which underpins and promotes the urban planning, construction, and services that ensure the operation of the city. Especially as the urbanisation is in progress, a tremendous volume of constructions is developed, which is an optimal chance to inject “smart gene” at the very beginning. As a result, it is reasonable to explore the CIM-enhanced DT in order to achieve the goal of an intelligent and smarter city.
1.3 Background of Poli Town
Poli locates in the southwest of the West Coast New Area of Qingdao City, Shandong Province, which has a total area of 156 square kilometers and a total population of 162,000. The town is famous and prospective because it enjoys coastline that has the length of 40 kilometers and the total area of 170.12 square kilometers. Poli ranks at 145th of the top 1000 towns of comprehensive strength list in nationwide. And Poli was entitled with the name of “Pilot Town of Innovative Urbanisation” (see Figure 4).
Figure 4 Poli city view (left), Dongjiakou Port of Poli (middle), future urban plan (right)
The advantages of Poli are prominent from three aspects:
Given the background of Poli, it reached a state where the advantages of the town can be applied to amend the drawbacks and improve the current situation by combining digital and intelligent solutions, therefore, to create an innovative smarter city that empowers sustainable development of Poli.
2 The multi-layered CIM-enhanced DT architecture overview
2.1 Actions before implementation
Based on the thorough understanding of the pros and cons for smart city development and the condition of Poli Town, the concept of CIM-enhanced DT solution is widely accepted from the technological aspect. Nevertheless, a couple of actions are executed before the technical implementation from a research and management aspect.
First of all, a professional team from The State Information Centre (Administration Centre of China E-government Network) affiliated to the National Development and Reform Commission (NDRC) was introduced to cooperate with the leading implementation team (Zhiutech, the authors’ affiliation) to customise the master development plan for Poli of two parts. On one hand, the jointed team completed the Master plan of Smart Poli Development (2020-2025), which has described the current conditions and future direction of the town in order to keep the Town’s prosperity. In the master plan, the importance of the innovative smarter city exploration has been addressed, and the CIM-enhanced DT solution (see details in the following sections) has been verified theoretically through five aspects i.e., infrastructure, decision-making support, urban spatial management, smart governance and public services. On the other hand, the jointed team accomplished Project Implementation Schedule of Smart Poli Development (2020-2025). In the proposed schedule, the entire smart city development is broken down into multiple tangible projects based on the DT solution in the following five years.
According to the master plan and the project implementation schedule, Poli’s smart city construction is designed into three phases (see Figure 5). The goal of the initial phase is to realise the basis of that includes but not limited to city-scale static data like urban planning, building information, infrastructure information, and establish the data standard and unified containers to collect the dynamic data in the long-term run. The second phase is the so-called evolutive phase, which emphasises the interconnection and intelligence. The data collected from phaseⅠcan be utilised in different fields to some extent and big data methods might be applied to generate insights for decision-making. The last but the longest phase is defined to literally make the city “smart”. To be specific, almost all the industries in the city are equipped with corresponding DT systems that can manage and exploited data from different disciplines and providing real-time artificial intelligent decision supports during the life-cycle. Overall, the timeline layout of Poli Town depicts the smart city blueprint and avoids the drawbacks creating a smart city as a one-off project.
Figure 5 Phases for a city to be "smart"
In addition to the master development plan, the governmental administration of Poli Town invited a number of 17 academicians and professors from academic organisations including Chinese Academy of Engineering, Tsinghua University etc., and organised an advisory committee exclusively for Poli’s development. The experts are specialised mainly in computer science, information and industry research areas, which can provide professional and the most updated suggestions on the topic with the governors. The establishment of the committee guarantees the smart city development in Poli Town is appropriate and advanced at the moment from both technical and sociological perspectives. Moreover, the committee plays the role of supervisor during the long-term construction of Smart Poli.
2.2 Multi-layered CIM-enhanced DT architecture
For the Poli smart city construction, a multilayer DT architecture fostered by the concept of CIM was designed carefully at the very beginning. There are three main layers from bottom up. The first layer is the ICT foundation of the whole smart city. In the early years of the smart city development in China, the content of this layer might be enough to represent the city is “smart”. Although these infrastructures are indispensable, the methods to exploit them are lacked. The second layer is the core of Smart Poli, consisting of two counterparts: CIM Graphic Engine (CGE) and Integrated Data Resources Centre (IDRC). Their operations depend on the ICT foundation, while providing exchangeable information for different sub-systems to create services and values. Lastly, the top level of the hierarchy is the application and intelligent services layer for diverse end-users (e.g., governors, enterprises owners, citizens). The specific contents in these three layers planned for Poli Town are illustrated as follows (see Figure 6) :
Figure 6 Multi-layered CIM-enhanced DT architecture
2.2.1 ICT foundation layer
This layer consists of three modules including cloud-based equipment, basic network upgrade and perception capability of facilities. The cloud-based resources are in need because of the high-demand for computing and storage resources and bandwidth. At the same time, disaster recovery is inevitable to improve the resilience of the city. And the capability of cloud-based resources should be planned in advance to satisfy the periodical needs of a smart city. Secondly, although Poli has the ICT foundation to some extent like the high coverage of fixed broadband, it cannot stop to keep the pace with smart city development. The goal of the network upgrade module focuses on 100% coverage of MONET (Multiwavelength optical networking) over the town, 100% coverage of Wi-Fi in the central public area, and the implementation of 5G network ought to be promoted extensively by 2025.
The third module indicates the requirements for a diversity of IoT sensors being installed in municipal facilities considering the needs from subjects like sewage disposal, rainwater treatment, gas and heating supply etc. For example, the underground pipelines should be equipped with IoT devices and surveillance cameras in order to monitor slight anomalies in real time and locate the element precisely for maintenance efficiency improvement; the application of intelligent street light poles is another mission in this module. The “smart poles” would assist to strengthen the 4G/5G signal and provide Wi-Fi signal, collect city operation data (e.g., transportation, environment and security) and offer dynamic instructions for pedestrians and vehicles. In general, this layer mainly refers to the hardware and infrastructures that underpin and improve the transmission and perception of the entire smart city.
2.2.2 Core layer
The core layer plays the primary role in the proposed architecture, especially with the CGE and IDRC as mentioned previously. Its operation depends on the cloud-based resources and the heterogenous data acquisition from IoT devices, while it provides the pre-processed systematic digital materials for the services and application layer. The core layer is the cardinal bond in between. And because of the emphasis of CIM in this layer, the proposed architecture is able to target issues from the AEC/FM industry, especially to avoid the side-effects from urbanisation to the most extent. Additionally, this layer is fused with cutting-edge technology and methods in the industry as BIM, GIS and AI, which could be the most representative characteristic of a city-level digital twin.
CIM Graphic Engine
Generally speaking, the CGE is literally a synthesised fundamental platform of graphic information. The platform integrates fragmented data of multiple categories from scattered departments of Poli Town. After proper data cleaning, transformation and classification, the fragmented data becomes organised data base. Then combining dynamic information, the static graphic data is transforming to “data assets” that literally represent the physical corresponding which can be used for management (see Figure 7).
Figure 7 CGE architecture
To be specific, BIM as a building-level digital twin providing the detailed information of buildings under construction, is definitely need to be documented at the first place; but considering the facts that the application of BIM is not extensive and BIM files are not constant from the design to operation process in China, many of the as-is data for the current city is collected in other ways. For instance, the 3D Tiles data (Cesium, 2021) from aerial photogrammetry is widely accepted in a recent couple of years, representing the current condition of the built environment in a very realistic and precise way and can be merged with BIM files to some extent. But it needs to be clarified that the 3D tiles data is only the outward skin of the buildings or city views, detailed parameters and information should be embedded via proper developing tools. Other important categories mainly contain DEM (digital elevation model) and DOM (Digital Orthophoto Map) and DLG (Digital Line Graph), urban plan, land resources plan, transportation plan, underground utility plan, landscape plan etc. All these segmented data from different department is aggregated and classified to five specialised databases (see Figure 7, top level). Especially, the “cleaned” graphic data can be utilised by a single unit or layer. For example, a specific building or a residential layer from the urban plan can be tagged and tracked alone. Based on the preparation, all the data can be visualised and presented as a city information model with certain internal services (e.g., city-level clash detections of plans, land resources utilisation ratio), as well as APIs (application programme interface) that supports services proposed in the entire DT architecture (see Figure 8).
Figure 8 CGE supported comparison analysis between photogrammetry and BIM data (web-based)
The CGE is considered to be an effective coordinating platform in the middle in the implementation of Smart Poli. The CGE is centred around the concept of CIM, where the temporal and spatial traits are emphasised. From the temporal perspective, the CGE works as a container that records the past of the city (historical sites, or constructions that have been demolished), holds the present of the city in different ways (BIM, 3D tiles, surveillance videos etc.) as well as deduce the future status of the city graphically. And the CGE is constantly updated as the physical assets are added in the future. From the spatial perspective, the CGE constructs the digital counterparts with the physical Poli Town visually, it forms the 3D master plan of the town that could facilitate management from a more holistic view. In addition, no matter the urban plans, constructions or infrastructures, they will have at least decades of years influences to the city once they are completed. In that case, the CGE might be the optimal digital representation because it coordinates the digital assets visually from the AEC/FM aspect and can be connected to other industries flexibly.
At present, the CGE of Poli Town has been constructed and maintained with the achievements in Table 1. Moreover, the residential information including 108 buildings in urban rural residential area and the corresponding 70,000 individual resident records in each building, as we call it “one file per household”. There were also 1116 enterprises records as we call it “one file per building”. All the residential and enterprise data are embedded in the CGE as parameters to match the building visually.
Table 1 CGE data collected
Integrated Data Resources Centre
The exist of IDRC integrates the non-graphical data that is necessary for the smart city development, which is an innovative attempt for a CIM-fostered DT architecture in China. As we mentioned in the previous section, China has elevated the smart city construction as a national-level strategy since 2015, one of the biggest missions was to promote e-governance systems. The executive departments started the informatisation work extensively while lacking unified coordination or techniques or data standards. For example, the residential ID data base of Poli Town from different departments cannot be updated at the same time because the systems are isolated, which results in a very tedious process for the public to deal with a single daily affair. Thus, there indeed were internal improvements through these steps, but the systems cannot be extended as the technology and public requirements evolve (Table 2). Another important reason for the advocation of IDRC is out of the status of current DT implementation. The emerge of CIM and DT are related highly to visualisation of physical assets and it is overemphasised the importance transforming 2D information to 3D. However, a system without actual users would be a waste of time and efforts. As the implementation team analysed the requirement regarding to the smart city mission, it was realised that not all the needs require the cooperation with 3D elements. That is the internal reason for the team to decide to design CGE and IDRC, representing graphic and non-graphic engines respectively. Hence, the establish of IDRC is a technical and sustainable consideration for Smart Poli.
Table 2 Data requirements from governmental departments
Requirements for data integration
Social Governance Centre
Governmental Services Centre
Planning and Construction Office
Comprehensive Law Enforcement Department
the Party office
The cores of IDRC lies in two aspects: data sharing and data assets management. Data sharing indicates the necessity of the comprehensive data standards, which refers to the normative constraints to ensure the consistency and accuracy of internal and external use and exchange of data. The goal of data standard management is to achieve the effectiveness, consistency, openness of the data resources in Poli Town through the unified data standard. It provides the reference for data assets management. Besides, the standardised data could be adopted as semi-open services like APIs for other platforms to use, which encouraged the efficiency and innovative. As for the data assets management, it addresses the point that the digitalised figure or alphabet might be plain and useless, whereas they are valuable when certain scenes (e.g., policy-making, land resources analysis) are given. Accordingly, it is important to maintain the data resources so as to make it the true digital assets of the city that creates values. And as the cutting-edge data analytical technology and algorithms evolve, they can magnify the influences of the accumulated data and trans from the static data to dynamic one.
The data aggregates in IDRC and becomes the data assets through several processes (see Figure 9). The foremost step is to collect and exact useful data including structured data (e.g., MySQL, Oracle, DB2), semi-structured data (e.g., XML, json) and non-structured data (e.g., PDF, PNG, MP3) and to apply proper method for data storage. The next step is eptomised as data governance, which requires data configuration, modeling, analysis, fusion computing etc. After that, the data would be deployed for exchange and packed as component services. In this proposed IDRC for Poli Town exclusively, there are six systems established based on the services and actual requirements from governors in Poli, which are e-document circulation system, social governance system, governmental services system, comprehensive law enforcement system, the Party management system and emergency management system.
Figure 9 Data "evolution" roadmap in IDRC
IDRC is regarded as an important part of the Poli “brain” besides the CGE. Through appropriate adaptation of data analytics and data mining, there are a minimum of three aims targeted with the construction of IDRC, which are 1) being able to provide one-stop service for the public and improve work efficiency; 2) providing integrated analysis reports and knowledge so as to improve the decision-making during governance; 3) improve the ubiquitous perception capability for the public in Poli and underpinning diverse intelligent applications in the Smart Poli architecture sustainably.
The core layer with CGE and IDRC is the backbone of the CIM-enhanced DT architecture. It underpins the smart city development with cutting-edge and unified technical methods. Simultaneously, the design of this layer attempts to overcome major problems with traditional smart city architectures, i.e., lacking of thinking from the urban planning and AEC/FM aspect or insufficient coordination from a short-term to long-term run.
2.2.3 Applications and services layer
This is the layer where specific applications and services are developed for stakeholders and public users based on the abilities from the ICT foundation layer and the core CGE and IDRC layer. As previously mentioned, the master plan of Smart Poli has depicted the developing route from 2020 to 2025, the focal modules have been lied in the five area as follows:
So far, achievements have been made for the spatial application, governance and public services modules gradually.
3 Pilot modules in Smart Poli
After the research and compiling of the master development plan for Poli Town completed in the early 2020, the actual construction of Smart Poli has been undergoing for a year. As for now, the major accomplishments exist in the following aspects.
3.1 Integration of planning, construction and management (urban spatial management)
The starting point of the requirements for this module is from the asset owner’s perspective. The status quo of urban planning, construction and management of Poli Town need to be provided to corresponding policy and decision makers from a more holistic view.
In planning stage, one of the biggest challenges is to manage the land resources and yield economic analysis with reliable data and proper algorithms, rather than the traditional workflow based only on decision-makers’ knowledge and experiences. According to the proposed DT architecture, especially with the supports of CGE and IDRC, the function in this module allows to check the current usage conditions (aerial photogrammetry data) of land resources in Poli and compare with the future plan sets (CAD files and embedded dynamic parameters). The comparison results demonstrate the deficiencies and neglects because of the lack of coordination from different planning department. A manager from the Planning and Construction Office as one of the target users of this module has stated that the deficiencies caused by inconsistence among different plan usually leads to economic loss of hundreds of millions. The original method was going onsite area by area to finalise the validation of the land resources and proposed urban plans, which was overwhelmingly time-consuming and inaccurate. What is even worse, the deficiencies might be overlooked totally. Therefore, this module would be an inevitable saver for the sustainability of Poli Town. In addition, regulations and limitations have been converted and built as algorithms in the module, which allows decision-makers to acquire multi-dimensional data analysis (e.g., detailed cost and profits) by inputting parameters. It realises the simulation of land resources for potential construction projects (see Figure 10).
Figure 10 Urban plan coordination (top left); "one file per household" (top right); land resources analysis (bottom left); land resources economic analysis (bottom right)
As for the ongoing construction projects, a system called Intelligent Construction Supervision System of Poli was built supported by the CGE and IDRC. It intends to form the one-stop management workflow of projects, which is developed from the asset owner and governmental supervisors’ perspective. For example, currently there are 19 projects under construction. The summary is updated dynamically including investment analysis, overall project schedule analysis, environment impacts monitoring, emergency alerts etc. Moreover, the conditions of each construction sites are recorded by application of aerial photogrammetry and IoT sensors. Each of the projects can be visited remotely by a simple click in the system showing construction sites in realistic 3D. The system improves the management intensity and efficiency greatly (see Figure 11).
Figure 11 Intelligent Construction Supervision System of Poli project overview (left); Project details (right)
In the operation and maintenance aspect, the progress has not been made obviously according to the schedule. However, one influential movement, i.e., digital grid management on floating population, for the city-level operation has been made. Based on information gathered in the CGE and IDRC, a three-level grid structure has been designed for Poli Town. There are 96 smallest units that belong to 20 community units, which all belongs to the town-level administration. According to the grid structure, a mobile-end APP and a web-end application were developed for the onsite worker and administrator respectively to keep updating and managing the floating population unit by unit. Besides, the data is consistent with the “one file per household” database in the CGE. The digital grid management contributed greatly during the most severe time of Covid-19 in 2020.
Figure 12 Digital grid management for floating population: mobile-end APP (left) and PC-end platform (right)
3.2 Smart governance in Poli
Depending on establish of IDRC and CGE (partially), they became the technology driver of change in governance. IDRC talks not only to each isolated system in the Poli Town, it also opens up to the e-governance database of the upper level (district-level), which enhances data exchanging (Fig. 13). It fosters the development of city-level data standards with IoT and Internet data and also with district-level database. The highly efficient sharing of data leads to a large time saving of administrative examination and approval both internally within the superior and subordinate departments and externally for the public services. For example, the approval of a proposed construction would be finished by examining all the related documents and the 3D construction site thanks to the help of the CGE and IDRC only through mobile devices.
Figure 13 Data sharing and exchanging within different levels of departments
An innovative attempt is to firstly utilise blockchain technology in the Smart Poli construction nation-wide. To specific, the selected data sets (e.g., building, construction site, resident, IoT devices, city elements and governmental department) in the IDRC are coded based on the blockchain technology, and the codes matches their counterparts in the physical world one by one. Then, every code was embedded with an ID that corresponds to the address (public key) on the blockchain service network. We name the ID “digital twin ID (DTID)”. As a result, the authenticity of data with the DTID can be guaranteed and the origin of data can be tracked down. Besides, DTID adopted APIs were developed for utilisation in diverse functions and services, like blockchain e-signature on governmental documents.
Values of smart governance are driven by AI recognition as well. As for now, the applications of AI are more on the analysis of the surveillance video streams. The warnings would be sent to different departments once the deficiency is detected. For instance, issues like garbage pilling, random parking, illegal advertisement in the city would be dealt with by related governmental department once they are recognised. In the near future, AI will be employed in areas including but not limited in urban management, transportation, community security and discipline inspection.
3.3 Smart public services
The satisfactions from the public would be one of the destinations of the entire Smart Poli Mission. The services are targeting two categories of users: individual and enterprise. So far, a one-stop APP has been released for the public. Poli residences can login via personal ID and AI face recognition for individual tasks like material preparation instructions, appointment making to the administrative examination and approval hall, personal information update, documents receiving and delivery etc. There is no need for people to go onsite back and forth for the same task. Besides, necessary information would be record through DTID for the sake of authenticity and security.
As for the enterprises, things are becoming easier as well. For example, company owners do not have to go to the administrative examination and approval hall in the West Coast of Qingdao New District that is far away from Poli for the project commencement permit, instead, the service can be provided in every nearby office in Poli Town. An enterprise-related persona might be depicted as follows in Figure 14.
Figure 14 Lifecycle services for enterprise owner
4 Implementation experiences acquired from Smart Poli
With more than a year’s endeavors on the smart city construction in Poli, there are experiences epitomised by the governmental administration and the implementation team, which might guide the foreseen projects in Poli Town or other smart city projects based on a DT architecture.
This chapter introduces the implementation case of Poli Town in China from four aspects, which are (1) the evolution of smart city development in China through four stages and a specific DT direction that practitioners are exploring, the background of reasons why Poli is ready to embrace the smart city solution; (2) a detailed demonstration of the multi-layer CIM-enhanced DT architecture, especially how the core layer with CGE and IDRC underpins the architecture, even the smart city; (3) current values are illustrated both in general and in details, partially proved the effectiveness of the proposed architecture and technology and (4) certain experiences are summerised for asset owners, practitioners and researchers to be considered and discussed on the topic.
This case study not only contributes to the smart city implementations in China, but also present to the world a pilot innovative smart city model supported by the digital twin. The multilayers of the CIM-enhanced architecture are very alike the composing of an intelligent human-being, who owns the torso (ICT foundation layer), the heart (the core layer with CGE and IDRC) and the brain (services and applications). And the human-being grow-up gradually as he learns, to gain wisdom. The implementation team of Smart Poli took advantages including economy, management, industry etc. and overcome the downsides of traditional smart city solution, in order to create true values and fulfill the requirements from the public. Especially, as the CIM-enhanced DT architecture is established based on the built environment (AEC/FM sector), it has extended the scenarios to governance and services, healthcare and transportation, and more in the near future. The cutting-edge technology (e.g., AI, blockchain and data analytics) were combined but not abused. As a result, the Smart Poli project has been honored the 2020 World Smart City Award (Greater China Area) – Governance and Service Award. The award is an encourage and inspiration for all the smart city participants, i.e., government, technical team, and every individual in Poli Town, rather than the destination of the Smart Poli mission.
In the future, the scheduled projects are commencing gradually as the DT architecture indicates. User feedbacks has been collected consistently to improve the performance of current applications and services. Necessary evaluation and economic analysis are anticipated by all stakeholders. By the time this chapter been completed, Poli Town has attracted attention from nation-owned enterprise for potential investment because of the prototype effects of the smart city development. We are looking forward to the prospects of Poli in the near future.
This chapter is developed based on the outcomes of the “Smart Poli” project at Beijing ZhiuTech Co. Ltd., The authors would like to thank the project’s steering group and officials from Poli Town government for supportive statistics and feedbacks.
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