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Natural disasters such as floods and heat waves demonstrate a real lack of control over the environment – although some of these disasters may actually be the result of human decision-making and carelessness.
The increasing frequency and severity of natural disasters has heightened attention to the urgent need for urban sustainability, with digital twin technology playing a leading role in addressing this challenge.
The definition of digital twins is a computer model of a physical process or a copy of a physical entity. They are essentially real and accurate virtual models.
Digital twins are expected to become important tools for urban sustainability because they allow researchers to recreate a specific urban environment and replicate the factors or processes that influence it, such as smart transportation .
Digital twins can also be coupled with sensors in the environment to provide real-time data for close monitoring.
Researchers can then use artificial intelligence to understand these processes and how they affect the environment, predict future conditions and impacts, and make sustainable decisions.
Our critical study of digital twins and their potential in the field of urban sustainability shows that these recent technological developments have proven their impact on the finances and sustainability of public and private organizations. benefit.
We demonstrated that digital twins can monitor real-time data of physical assets and view their performance in different virtual environment scenarios, making resource allocation more efficient.
For example, by measuring and simulating the stormwater capacity of new road networks, a combination of historical and real-time sensor data can be used to design water-sensitive cities to reduce waste and loss.
Although urban digital twins (UDTs) are leading the way in solving technical, ethical and socio-technical issues, there are still some barriers to their application. So how can this technology be used to support sustainable urban development?
The success of UDT technology depends on timely two-way communication between the physical and digital environments – this cannot be discounted.
The first factor we found is that many decision-makers lack digital literacy, which leaves them with little interest in digital technologies, which contributes little to their research and financial resources.
Therefore, the better prepared we are technologically, the more likely we are to adopt digital technologies in our organizations or daily activities.
Finally, there needs to be standards and shared data models so that important data does not remain in silos.
Professional associations such as the Australian Surveying and Spatial Science Institute (SSSI) Standards Australia, Engineers Australia and the Planning Institute of Australia (PIA) believe that standardization is important in developing a common language across stakeholders and jurisdictions, Process and data models play a vital role.
The Spatial Principles to Support Digital Twins of Built and Natural Environments developed by the Australia New Zealand Spatial Information Council emphasizes the role of standardization in information and data management, UDT interoperability, privacy and security.
One problem faced by many industries is that algorithmic decisions can be questioned and doubted due to issues of accountability and transparency.
A recent study we conducted shows that explainable artificial intelligence (XAI), or AI that can explain its results, has an important role in increasing the transparency of AI decision-making and people's trust. The results of this research were published in the journal Nature Sustainability.
XAI solves the problem posed by the “black box” concept—even AI developers cannot clearly explain why it reached a specific result or made a specific decision.
Current digital technologies only measure objective aspects of urban entities, focusing on physical characteristics of the city such as building height, tree canopy, land use type and density, 3D architecture, urban redevelopment visualization, and building energy assessment .
However, a digital twin should be a city that is a combination of objective characteristics (physical and functional) and subjective characteristics (social construction and place experience).
Although some studies have demonstrated new capabilities in measuring place quality, equitable access to facilities, and sociability of urban spaces, system-wide simulations and practical applications are still insufficient and should be the focus of future research to prevent use Inaccurate models lead to poor decisions and strategies.
Because the applications of digital cities are so widespread, so is the professional knowledge behind them.
By engaging IT and engineering professionals with policymakers, end users, and planning and construction experts, we can better harness the value of digital technologies to address future challenges and return current investments to communities .
Australian state governments have begun leveraging digital twin capabilities to better serve their communities. The NSW Spatial Digital Twin provides collaborative digital workflows across organizations across the state. It aggregates and visualizes location information in dynamic and multidimensional models of the real world.
The Victorian Government has been awarded $37.4 million to develop the Victoria Digital Twin platform, integrating large volumes of 2D, 3D and real-time data through a single online platform.
The project is driven by the government’s digital twin pilot project at Fisherman’s Bay in partnership with the University of Melbourne and other stakeholders.
We know that a digital twin should be more than just a replica, it should be coupled with a physical process or entity into a cyber-physical-social system.
Such a system might be more like a brain than a twin - it has nerves that sense, mechanisms that can change physical or digital systems, and regulatory mechanisms that keep physical and digital systems in balance.
We have begun to upskill, raise awareness among professionals, managers and executives, and educate the future workforce about digital twin technology. Our new education programs, such as the Master of Engineering in Digital Infrastructure and the Graduate Certificate in Digital Engineering (Infrastructure), address technical, ethical and socio-technical challenges.
We are also working with industry to identify the future digital engineering needs of the Australian and global infrastructure industry, which is booming and adopting Building Information Modeling (BIM), the Internet of Things (IoT) and virtual reality and other digital tools.
Leveraging research and development into emerging technologies and these educational programs, we create a new capability for the skill set of the future, combining numerical data with statistics, machine learning and data simulation.
The goal is simple – to better engage with communities and communicate physical and social processes, patterns and predictions in the design of sustainable future cities.
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