A digital twin smart city for citizen feedback

White, Gary; Zink, Anna; Codecà, Lara; Clarke, Siobhán

doi:10.1016/j.cities.2020.103064

Cited by 268 publications

(156 citation statements)

References 30 publications

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“…The integration of the real-time data flows into the 3D can be used for tracking the widespread of information and determine vulnerable objects during disasters (Ham and Kim, 2020;Fan et al, 2021). This type of information can inform city officials about what areas to evacuate first (White et al, 2021).…”

Section: City Dtsmentioning

confidence: 99%

“…However, some officials consider the system to be too dangerous to allow everyone to experiment with it, because, for example, militants or terrorists can use the information about the height, location, and the view from the buildings to plan their attacks (Geddie and Aravindan, 2018). Due to these reasons, Virtual Singapore will not be connected to the worldwide web, and the model has not yet been made publicly available, so the citizens are unable to interact with it (Geddie and Aravindan, 2018;White et al, 2021).…”

Section: Virtual Singaporementioning

confidence: 99%

“…A common critique for the CDTs like Virtual Singapore and the simulations that can be conducted in these environments is their overreliance on historical data, which limits its predictive capabilities for the extreme situations for which there are no data available (GeoTwin, 2020)-which is the case for the Virtual Singapore project (Holstein, 2015). Other critical takes on the current generation of CDTs include lack of mechanisms for citizen engagement, interaction, and feedback report, as well as underutilization of urban mobility data (White et al, 2021). Concerns related to the privacy protection of the micro-level data about individuals used for agent-based simulations in CDTs are also voiced (Bektas and Schumann, 2019;Bliss, 2019).…”

Section: Virtual Singaporementioning

confidence: 99%

“…With the digitalization of cities, different types of data can be generated within the urban boundaries (White et al, 2021), providing detailed information about transportation (Menouar et al, 2017), water supply (Parra et al, 2015), waste management (Medvedev et al, 2015), and power generation (Oldenbroek et al, 2017). However, meaningful knowledge discovery from such distinctively different data remains problematic due to issues of noise and missing values in the data or linking structured and unstructured data (Mohammadi and Taylor, 2020).…”

Section: Data For Dtsmentioning

confidence: 99%

“…The high demand for city data from CDTs raises concerns about the safety and privacy of the data because certain applications such as real-time traffic flow simulations would require an excessive amount of individualized information (Bliss, 2019). Although not all CDTs of the current generation include urban mobility data (White et al, 2021), the potential issues related to data aggregation infrastructure on the city-level pose significant concerns among various stakeholders, affecting the trust levels in the technology (Ismagilova et al, 2020).…”

Section: Data For Dtsmentioning

confidence: 99%

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Exploring city digital twins as policy tools: A task-based approach to generating synthetic data on urban mobility

Papyshev

Yarime

2021

Data & Policy

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This article discusses the technology of city digital twins (CDTs) and its potential applications in the policymaking context. The article analyzes the history of the development of the concept of digital twins and how it is now being adopted on a city-scale. One of the most advanced projects in the field—Virtual Singapore—is discussed in detail to determine the scope of its potential domains of application and highlight challenges associated with it. Concerns related to data privacy, availability, and its applicability for predictive simulations are analyzed, and potential usage of synthetic data is proposed as a way to address these challenges. The authors argue that despite the abundance of urban data, the historical data are not always applicable for predictions about the events for which there does not exist any data, as well as discuss the potential privacy challenges of the usage of micro-level individual mobility data in CDTs. A task-based approach to urban mobility data generation is proposed in the last section of the article. This approach suggests that city authorities can establish services responsible for asking people to conduct certain activities in an urban environment in order to create data for possible policy interventions for which there does not exist useful historical data. This approach can help in addressing the challenges associated with the availability of data without raising privacy concerns, as the data generated through this approach will not represent any real individual in society.

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Section: City Dtsmentioning

confidence: 99%

Section: Virtual Singaporementioning

confidence: 99%

Section: Virtual Singaporementioning

confidence: 99%

Section: Data For Dtsmentioning

confidence: 99%

Section: Data For Dtsmentioning

confidence: 99%

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Exploring city digital twins as policy tools: A task-based approach to generating synthetic data on urban mobility

Papyshev

Yarime

2021

Data & Policy

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The realm of metaverse: A survey

Venugopal

Subramanian

Peatchimuthu

2023

Computer Animation & Virtual

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The next step of digital development is the metaverse, which has the potential to drastically alter how people use technology and expand the range of services available beyond conventional systems that can be accessed online. As the efficiency, performance, and quality of service access reach their peak levels, the focus has shifted to the user experience. Due to this, there is an increasing demand for more involved and thorough customer service, and service providers are willing to increase their present standards. Consumers are genuinely asking for tactile and immersive elements in their digital interfaces, but these features can only be made possible by the metaverse's potentially futuristic subfields of virtual reality (VR), augmented reality (AR), mixed reality (MR), and extended reality (XR). However, the metaverse may not be widely used due to significant security and privacy issues either from underlying technology or produced by the new digital environment. A variety of fundamental problems, such as scalability and interoperability, can arise in terms of ensuring security for the metaverse because of the metaverse's inherent properties, such as immersive realism, sustainability, and heterogeneity. In this survey, we propose a hypothetical meta‐stack framework to understand the various components in the realm of metaverse and then provide wide‐ranging insights on the most recent development in metaverse realm in the context of cutting‐edge technologies, security vulnerabilities and preventive measures specific to the metaverse and the research challenges pertaining to metaverse.

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5‐2: Unveiling Privacy Challenges: Big Data‐Driven Digital Twins in Smart City Applications

Zheng,

Li,

et al. 2024

Symp Digest of Tech Papers

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Urban centers serve as dynamic hubs of data and information, continually shaping the modern landscape. The fusion of Big Data and Digital Twin (DT) technology plays a pivotal role in advancing smart city initiatives. DT, acting as a comprehensive virtual replica mirroring physical entities' lifecycles, utilizes real‐time data, simulations, and machine learning to enrich decision‐making processes. In urban development, Big Data assumes diverse roles, particularly in urban planning, resource management, and traffic optimization, providing valuable, data‐driven insights to decisionmakers. Simultaneously, DT technology contributes significantly to modeling urban environments, enabling real‐time simulations, and strengthening decision support systems. However, challenges persist, notably in data security and model precision. Addressing these challenges necessitates concerted efforts to enhance data privacy measures and refine the cognitive capabilities of DT models. This paper examines the intricate interplay between Big Data and DT technology in shaping the evolution of smart cities, offering insights into their roles, applications, and implementation challenges. Furthermore, it advocates for future research endeavors aimed at overcoming existing obstacles, thereby fostering secure and effective deployment of Big Data‐driven DT technology and promoting innovative advancements in smart city management and sustainable development.

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A digital twin smart city for citizen feedback

Cited by 268 publications

References 30 publications

Exploring city digital twins as policy tools: A task-based approach to generating synthetic data on urban mobility

Exploring city digital twins as policy tools: A task-based approach to generating synthetic data on urban mobility

The realm of metaverse: A survey

5‐2: Unveiling Privacy Challenges: Big Data‐Driven Digital Twins in Smart City Applications

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