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Digital Twin (Built environment)

A digital twin presents a digital replica of a real object or process or a system and uses data from the real environment to represent, analyse, validate and simulate present and future behaviour [11]. Typically, connecting real objects with its digital twin enables testing new scenarios or models in real time without interfering with the real objects. Using digital twins, various forms of data analysis can be performed in the digital realm and results can be visualised, e.g., predictive analysis, cause-effect analysis, or analysis of what-if scenarios, and that makes local digital twins (LDTs) of cities, regions or communities an ideal tool for awareness raising, planning and decision-making. Such a solution can play a critical role for climate neutrality initiatives where monitoring, analysis and predictions or forecasting can provide citizens, planners, policy and decision makers, necessary data-driven intelligence on which appropriate actions or interventions can be introduced.  

 

There are common misconceptions about [19] digital twins, such as that it has to be an exact 3D model of a physical thing or confusing the different levels of integration between physical and real systems. The latter is clarified by the following three different definitions [11] [19]: i) a digital model requires manual exchange of data between real objects and digital objects and a change in physical object has no impact on its digital replica; ii) a digital shadow is at next level where there is one-way data exchange and change in physical system is reflected in its digital object; and, iii) a digital twin is expected to have bidirectional exchange of data which means change in one should result in a change in its corresponding model.  

 

There are several digital twin solutions and most of them fall within the digital model or digital shadow category. Most solutions focus on a specific problem domain such as industry [33], manufacturing [23][32], health [12] or medicine [24]. Digital twins have also gained attention in the smart city domain [29][27][15] with numerous examples of LDTs either developed or in development at local, city, regional or national level in the EU and in other parts of the world. In terms of EU-funded research projects several domain-specific digital twin solutions are in development in the urban context such as construction [22][BIMPROVE][COGITO][SPHERE], water [DWC][SCOREWATER], green infrastructure including agriculture & farming [RESET][FinEst GreenTwin][21][13] mobility [DUET][LEAD][MOVE21][AI4CITIES], energy [TwinERGY][SPHERE][AI4CITIES], planning, policy-making and decision support [CUTLER][RESET][Smarticipate][DUET][URBANAGE].  

Source: RUGGEDISED project, Deliverable 6.6 

 

These solutions rely on various technologies including IoTs, AI and other but all are grounded on data from many sources: local platforms, big data, (non-)spatial and temporal data streaming, and require  interoperability, harmonisation and access through web services (e.g., RESTful service interface), federated data spaces and others complying to service interoperability, data privacy and security, data processing based on trusted machine learning and AI models, and 2D/3D and immersive visualisation and simulations.  

Ecosystem of Digital Twins: The key for climate neutrality challenge is to perform data analysis at a city or city-regional scale and it requires cross-disciplinary data fusion and knowledge generation that is often needed across multiple levels of governance. Hence, there are already ongoing efforts on defining principles for an ecosystem of digital twins where results and data sharing across digital twin nodes will be key enabler for deriving much needed intelligence [25]. 

 

For assistance in the implementation of LDTs, cities can benefit from programmes and initiatives under the DIGITAL Europe Programme [35]. 

DUET Technology architecture  

MATURITY:  

 

A few digital twin technologies and their TRL are covered in [11, Table 2]. 

 

Commercial platforms available on the market: Microsoft’s Azure Digital Twin [8], IBM’s Digital Twin Exchange [7], Siemens’ Digital Enterprise Suite [9], GE’s Digital Twin (Assets and Process) [5] are a few examples of commercial digital twin platform. These platforms provide necessary storage, computer and communication tools to design and implement custom or tailor-made solutions.  

 

In the deployment of an LTD, a city or community can take a modular approach, with the first step being the deployment of open-standards based Local Data Platforms, of which there are many available on the market. Components, including those developed by other cities, can be reused, provided shared standards and technical specifications are used, such as the Minimum Interoperability Mechanism (MIMs Plus) of the Living-in.EU movement. This approach provides greater market choice for cities and communities, allowing them to avoid vendor lock in. It also grants greater opportunities to innovative SMEs to scale up. 

 

Validation and demonstration: Some of the above example solutions fall under validation and demonstration category such as DUET, RESET, LEAD, AI4CITIES, CUTLER, Smarticipate, BIMPROVE, DWC, SCOREWATER, FinEst GreenTwin.  

CO-BENEFITS
PRE-CONDITIONS & ENABLING CONDITIONS
CONSTRAINTS/BARRIERS FOR IMPLEMENTATION
DRAWBACKS/ADVERSE IMPACTS OF THE SOLUTIONS after implementation
EXTERNAL LINKS
IMPACTS (Indicators + DNSH)
INSTRUMENTS/Processes for implementation
EXAMPLES

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VTT
JRC
TNO

Last update: June 16, 2023

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Climate resilienceAnalytics and modellingBuildingEnergyTechnology
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