How Should the Structure of Smart Cities Change to Predict and Overcome a Pandemic?

Kim, JungHoon; Kim, Joo Young

doi:10.3390/su14052981

Cited by 5 publications

(10 citation statements)

References 26 publications

(27 reference statements)

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“…The study emphasized the critical role of societal factors, such as public trust, citizen compliance, and community engagement, in the successful deployment of these technological solutions. Kim et al [4] explored the necessary adaptations to the structures of smart cities to effectively predict and overcome pandemics. They examined the roles of smart city technologies and infrastructure in enhancing preparedness and response to pandemic outbreaks.…”

Section: Pandemic Management In Smart Citiesmentioning

confidence: 99%

“…Furthermore, the interconnected nature of smart cities enables seamless sharing and collaboration among different entities, fostering an environment conducive to the development of innovative solutions to societal challenges [3]. In this context, the challenge of pandemic disease diagnosis in smart cities encompasses several key aspects that need to be addressed in order to effectively alleviate the outbreak of infectious diseases [2][3][4]. These challenges stem from the unique characteristics of smart cities, such as their high population density, complex mobility patterns, and diverse sources of data.…”

Section: Introductionmentioning

confidence: 99%

“…Precise diagnosis not only supports the operative treatment and management of diseased individuals, but also enables proactive measures to be taken, such as resource allocation, targeted interventions, and public awareness campaigns [5]. Smart cities possess the capacity to transform pandemic disease diagnosis through the utilization of IoT and AI technologies, facilitating timely and evidence-based decision-making that can have life-saving implications and safeguard communities [3][4][5].…”

Section: Introductionmentioning

confidence: 99%

“…First, they rely on centralized data repositories where sensitive health information is collected and saved in a single location, which poses noteworthy concerns concerning data privacy and security. Additionally, the sheer volume and velocity of data generated in smart cities can overwhelm centralized systems, causing delays and inefficiencies in diagnosis and replies to efforts [4,5]. Moreover, centralized approaches may encounter regulatory and governance matters, such as data ownership and access rights, impeding operative collaboration and information exchange among diverse stakeholders.…”

Section: Introductionmentioning

confidence: 99%

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Towards Efficient and Trustworthy Pandemic Diagnosis in Smart Cities: A Blockchain-Based Federated Learning Approach

et al. 2023

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In the aftermath of the COVID-19 pandemic, the need for efficient and reliable disease diagnosis in smart cities has become increasingly serious. In this study, we introduce a novel blockchain-based federated learning framework tailored specifically for the diagnosis of pandemic diseases in smart cities, called BFLPD, with a focus on COVID-19 as a case study. The proposed BFLPD takes advantage of the decentralized nature of blockchain technology to design collaborative intelligence for automated diagnosis without violating trustworthiness metrics, such as privacy, security, and data sharing, which are encountered in healthcare systems of smart cities. Cheon–Kim–Kim–Song (CKKS) encryption is intelligently redesigned in BFLPD to ensure the secure sharing of learning updates during the training process. The proposed BFLPD presents a decentralized secure aggregation method that safeguards the integrity of the global model against adversarial attacks, thereby improving the overall efficiency and trustworthiness of our system. Extensive experiments and evaluations using a case study of COVID-19 ultrasound data demonstrate that BFLPD can reliably improve diagnostic accuracy while preserving data privacy, making it a promising tool with which smart cities can enhance their pandemic disease diagnosis capabilities.

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Section: Pandemic Management In Smart Citiesmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Towards Efficient and Trustworthy Pandemic Diagnosis in Smart Cities: A Blockchain-Based Federated Learning Approach

et al. 2023

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“…e strategic system is located at the strategic layer, which is at the highest level of the smart city system; the social system and economic system are at the activity layer that is at the middle of the smart city system, and the support system and space system are at the physical layer that is at the bottom of the smart city system. At the same time, the strategic system, social system, economic system, support system, and space system are all interrelated, interactive, and interdependent [24]. e formation, operation, and development of the smart city system are revealed through the interconnection and interaction between the five subsystems in the three layers.…”

Section: System Model Design Of Smart Citymentioning

confidence: 99%

Building a Smart City Planning System Integrating Multidimensional Spatiotemporal Features

Lu¹

2022

Scientific Programming

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With the development of mobile communication technology and the popularization of mobile devices, the connection between people has become increasingly close, the data circulating between them have increased rapidly, and the multidimensional space-time characteristics have gradually entered the stage of the times. The proposal of the basic smart city system is a revolution in the concept of urban construction. A smart city is both an opportunity and a challenge for the urbanization process. By analyzing the multidimensional spatiotemporal feature engineering, this paper studies the development trend of smart cities and discusses how multidimensional spatiotemporal features play a fundamental role in the smart city system.

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Adapting Smart Street Strategy for Post-Covid Built Environment

Ahmad,

Abdelkarim,

Mohammed

et al. 2023

The International Conference on Civil Infrastructure and Construction

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The street networks occupy 25% of land use and are the veins of cities. By 2050, more than two-thirds of the world’s population will live in urban areas. The urban street infrastructures and systems are expected to serve the public in performing mandatory and social activities on the streets. In addition, walkability and mobility within urban streets are linked with better public health demands. Therefore, there is a need for the public street to adopt smart features to provide better public health towards limiting the spread of covid.The study aims to develop a framework for smart street strategies to facilitate post covid built environment. The study adopts an integrative approach to deduct the smart street features through a robust literature review and workshops that influence post-Covid built environment within the urban design (Infrastructure) and information management. The study objective includes identifying the processes for adapting smart street strategies and healthcare concerns that can be leveraged to support public health in cities. As a result, the strategy can be adopted and applied by policymakers for implementation worldwide. The contributing features of the effort will focus on tracking, controlling, and preventing analogy. As a result, the framework will provide a baseline for neighborhoods, communities, and cities to develop and integrate novel strategies for managing public health to have an effective and efficient post-Covid pandemic built environment.

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How Should the Structure of Smart Cities Change to Predict and Overcome a Pandemic?

Cited by 5 publications

References 26 publications

Towards Efficient and Trustworthy Pandemic Diagnosis in Smart Cities: A Blockchain-Based Federated Learning Approach

Towards Efficient and Trustworthy Pandemic Diagnosis in Smart Cities: A Blockchain-Based Federated Learning Approach

Building a Smart City Planning System Integrating Multidimensional Spatiotemporal Features

Adapting Smart Street Strategy for Post-Covid Built Environment

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