Simulating and Emulating Smart City Transformation With Digital Twins

As urbanization continues, local governments and urban planners actively seek ways to improve city environments. This involves actions ranging from building/revamping existing infrastructure to implementing sustainability strategies.

These initiatives are usually supported by a wide range of technologies that jointly create “smarter” cities.

Among these approaches are digital twins, virtual replicas of cities that are simulated through technologies such as the Internet of Things (IoT) and Artificial Intelligence (AI) to mirror real-life environments. This enables cities to incorporate and improve resource management, predictive analytics and environmental sustainability through rounds of simulated possibilities.

Despite its advantages, there are challenges in implementing digital twins, including ensuring infrastructure interoperability and performing ongoing maintenance. Also, local governments, urban planners and technology providers should continuously engage with residents to ensure their overall quality of life is considered.

Planning Actions Through Simulated Scenarios

The digital twin is a well-known digitalization process, and this strategy has been widely applied in various domains and verticals, such as manufacturing, logistics and energy. Generally, digital twins are used to simulate and replicate real-world environments by collecting various real-time data from sources, including sensors and cameras, to create digital representations of their physical counterparts. These digital models can then be used for comprehensive monitoring and analysis, which will help improve decision-making processes, optimize performance and predict possibilities.

Using sensors and technologies like IoT and AI are common in enabling smart cities. However, such incorporations are often tailored to address specific challenges (e.g., traffic congestion and energy efficiencies). Omdia believes the ideal approach to creating better smart cities is to integrate these disparate systems into a unified platform, leveraging all the up-to-date data to form a more complete picture. Digital twins serve as a bridge that connects these individual applications to provide more holistic views of the city’s operations, addressing scenarios that may occur before taking further actions.

The implementation of digital twins enables the combination of multiple variables into a single component. For example, in bad weather like thunderstorms, digital twins could capture and simulate scenarios that predict potential flooding areas, the impact on drainage systems and the change in traffic flows. Simultaneously, it captures additional occurrences such as the increased energy consumption in houses and buildings as residents opt for heating or cooling systems in response to not going out due to the bad weather conditions. Rather than looking at the use cases separately (i.e., traffic flow and a building’s energy management), digital twins take these different pieces to form more accurate representations of the entire environment.

Omdia views digital twins as the next level of simulation compared to the “traditional” computer-aided design (CAD) or computer-aided engineering (CAE) based simulations. While both approaches replicate digital models based on actual products and processes, “traditional” simulations typically use historical data and pre-determined parameters and elements inserted by their designers. These designers must continuously feed new rules into the digital models to keep simulations up-to-date and relevant. This may be a challenging task, especially in the context of smart cities where the landscapes and variables are constantly evolving, and there is a high expectation that the simulations accurately reflect the complexities and conditions of smart city environments.

Omdia has noticed the increasing adoption of digital twins in cities across the globe and has observed domain experts and technology providers collaborating on digital twin initiatives. Below are some examples:

More Pieces Are Joining Digital Twin Models

A digital twin is not a standalone technology, nor does it rely solely on a single technology; rather, it converges and leverages diverse technologies to provide more accurate real-world projections. Below are some of the key technologies that enable digital twins:

As more technologies are integrated to enable smart cities, smart cities have also grown to incorporate more of these elements. For instance, Augmented Reality (AR), Virtual Reality (VR), and Mixed Reality (MR), collectively known as Extended Reality (XR), have introduced a whole new concept of concurrent interactions between digital models and real-world environments. Through XR technologies, digital twins can provide interactive experiences to their stakeholders and users to obtain in-depth visualizations and details of the modeled environments. For instance, augmented analytics through devices such as AR glasses and headsets offer features like real-time data overlay that allow users to integrate live data into actual physical environments seamlessly. This applies to various use cases, from performing live infrastructure repair and maintenance to obtaining real-time information during emergency responses such as evacuation routes and resource allocations.

A broader concept encompassing XR is the metaverse, which generally provides a digital space known as the “virtual world” that allows businesses and residents to interact. Omdia believes that digital twins and metaverse can work synergistically in smart cities. Real-time information and insights are injected into the digital space to replicate virtual environments where users can experience immersive interactions and navigations. In addition, using metaverse could contribute to environmental sustainability as physical activities such as meetings, traveling, and event organizing can be performed virtually, ultimately reducing carbon footprints.

As mentioned earlier, AI/ML is one of the core technologies that empower digital twins. Omdia expects the explosive interest and adoption of generative AI to amplify its capabilities and preference further. Generative AI could utilize the data capture to perform self-training and subsequently generate more possible simulations to be analyzed. The inclusion of generative AI could shift the roles of smart city planners to mainly focus on quality control/governance and decision-making rather than hands-on implementations, as the machines will analyze the data by themselves and identify patterns that require attention. This information can be optimized to enable smart cities, with examples including performing predictive maintenance on city infrastructures, improving transportation systems and measuring energy consumption.

Is Digital Twin the Way Forward for Smart Cities?

Apart from obtaining and analyzing data, Omdia believes that another core component digital twins have is risk assessments, allowing parties that have access to the digital twins to gauge potential variables and possibilities of smart city implementations before proceeding to the deployment stage. For instance, urban developers could test how establishing a new building would impact the traffic flows of the designated area; another example is where city municipalities can identify locations with high population density to place public transport facilities. From a commercial standpoint, retailers could leverage data and simulated scenarios to strategically position stores in locations with high visibility; this approach also enables them to develop innovative business models tailored to specific areas and population bases.

Besides commercial and economic gains, digital twins are a powerful tool to address the rising emphasis on environmental sustainability. From energy efficiency to waste management, IoT-enabled sensors provide comprehensive and granular details of environmental conditions and their corresponding infrastructures. This data is then fed into digital twins where advanced analytics and AL/ML would process and simulate current environmental conditions and predict future outcomes where smart city planners can formulate proactive strategies.

Digital twins also play a vital role in supporting disaster resilience. This is crucial, especially for countries/cities that are prone to natural disasters, such as Japan, Indonesia, and America. The occurrence of disasters could ultimately disrupt the normal functions of a city, impacting factors such as economic stability, environmental sustainability, and even casualties. Besides that, cities affected by disasters will also face recovery challenges ranging from repairing/rebuilding damaged infrastructures to restoring public services such as healthcare and education. Omdia believes that by leveraging digital twins, cities can predict the occurrences of these disasters and perform effective planning and coordination to mitigate potential losses. Also, these digital models can be used to assess and evaluate the damages of disasters to formulate effective and efficient recovery strategies.

While digital twins are a commendable approach, several factors must be considered. One of them is the establishment of relevant infrastructures. Greenfield cities would usually have fewer challenges integrating digital twins as aspects such as infrastructure design, interoperability, and scalability can be discussed and incorporated during the planning phase. Established cities with legacy systems may face more difficulties as enabling digital twins would require harmonious synchronization between software, data, and platforms. Retrofitting new technologies into existing infrastructures may take time as assessments on interoperability and integration are critical to creating coexisting ecosystems. In addition, retrofitting could also potentially disrupt daily operations, and regular maintenance should also take place to ensure that the digital assets accurately reflect their physical counterparts.

Omdia has identified public-private partnerships (PPPs) as a widely preferred practice for smart city projects. This investment model involves local governments and city municipalities reaching out to private entities ranging from technology providers to infrastructure developers to jointly address challenges the city faces. Hence, the implementation of digital twins is expected to be executed via PPPs. As such, public and private entities should align their interests, especially on objectives and expectations, before engaging in joint smart city projects. This is crucial as misaligned views may hinder the progress of the projects or even lead to project abandonment.

Omdia advises caution on the results generated from digital twins, as digital models are heavily built on assumptions and dependent on the data they are fed. During the initial phase of a digital twin implementation, there may be possibilities of overlooking important parameters or feeding the wrong data, which could lead to inaccurate predictions. On top of that, these digital models may not predict unforeseen circumstances, for example, the occurrence of road accidents that might alter the traffic results. In these situations, Omdia expects digital twin stakeholders to continuously validate and update/refine the criteria that build the models and parties that utilize these models to exercise caution before making decisions or taking action.

Outlook

Cities are continuously evolving to incorporate growing trends in urbanization, sustainability approaches, and demands to improve quality of life. Ideally, the efficiency and timely implementation of smart city projects are crucial to address ongoing concerns and realize their intended goals. However, these deployments often carry the concern of “What if it did not turn out the way we expected?” Moreover, some of these smart city projects are standalone initiatives that aim to resolve specific pain points without considering the aftereffects of the deployment. Omdia believes that digital twins could tackle these issues as they provide holistic views of the cities’ current conditions, and their simulated digital models allow the anticipation of possible scenarios.

Omdia has observed a wide adoption of digital twins across the globe and expects this practice to continue to expand due to its nature of identifying limitations of physical environments via virtual approaches and its capabilities to simulate numerous results with diverse variables. Also, rising innovative technologies such as generative AI and XR could further enable digital twins, making it more relevant and enticing for smart city planners to adopt this practice.

Through the implementation of digital twins and the introduction of new technologies, Omdia believes this will gain significant traction. Such technological advances may increase their likelihood of participating and contributing ideas to improve the efficiency of digital twins. Omdia also expects local authorities or technology providers to kickstart education initiatives to improve senior residents’ digital literacy to adapt to the technology shifts, having the notion that cities are only as smart as their people.

Partnerships will remain a core foundation to enable smart cities, especially in technology implementations. Omdia expects PPPs to play a pivotal role with various stakeholders pooling their talents and resources to deploy successful digital twins, given that such an approach brings numerous advantages, including funding, access to technologies, infrastructure building, and creating engaging platforms to interact with communities. However, all parties involved in the PPPs should align their interests and perform proper delegations on the engagements to achieve synergized outcomes.