Smart City Framework Development: Challenges and Solutions

Al-Masri, Ahmed N.; Ijeh, Anthony C.; Nasir, Manal

doi:10.1007/978-3-030-01659-3_38

Cited by 6 publications

(5 citation statements)

References 14 publications

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“…However, it is revealed that the highest number of crucial challenges are related to technology. Therefore, much attention is required towards the availability of right and up‐to‐date technology for a smoother development of smart cities such as IoT (Al‐Masri & Ijeh, 2019), computational intelligence based on enterprise data like healthcare, NADRA, and others. Technological changes are rapid in Pakistan, where e‐government (Stergiou, Psannis, Plageras, Ishibashi, & Kim, 2018), e‐healthcare (Memos, Psannis, Ishibashi, Kim, & Gupta, 2018), and e‐agriculture are some of the initiatives.…”

Section: Resultsmentioning

confidence: 99%

Challenges for sustainable smart city development: A conceptual framework

Khan

Malik

Zafar

et al. 2020

Sustainable Development

120

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Sustainable smart city development experience various challenges, such as legislation and policies, funding, infrastructure, and technological aspects. Numerous studies have highlighted the importance of sustainability concepts in smart cities' development. However, there is scarce research focusing on the challenges faced for the development of sustainable smart cities. This study aimed to develop a conceptual framework that provides critical challenges faced by private and government organisations, and the respective solutions of the challenges for the development of sustainable smart cities. Pakistan has been chosen as a case study that yields a total of 17 respondents from the executive, managerial, and operational levels of private enterprises and government organisations involved in smart city development. This research is a preliminary step towards providing insights and significance of infusing sustainability in the development of smart cities. The proposed conceptual framework can act as a practise guideline for practitioners to prepare themselves for sustainable smart city development.

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Section: Resultsmentioning

confidence: 99%

Challenges for sustainable smart city development: A conceptual framework

Khan

Malik

Zafar

et al. 2020

Sustainable Development

120

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“…Although indicators 9-21 of Table 3 are directly related to mobility, indicators 1-8 provide essential information on the broader innovation context within which mobility solutions are implemented. Governance and policy, for example, play a vital role in creating a conducive environment for innovation in mobility, ensuring that the city has the capability to develop and implement supportive policies [32]. Infrastructure is another critical aspect, as the availability and quality of infrastructure directly impact the feasibility and effectiveness of innovative mobility solutions [33].…”

Section: Methodsmentioning

confidence: 99%

A Quantitative Model of Innovation Readiness in Urban Mobility: A Comparative Study of Smart Cities in the EU, Eastern Asia, and USA Regions

Ayfantopoulou,

Touloumidis,

Mallidis

et al. 2023

Smart Cities

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The smart cities paradigm has gained significant attention as a tool to address the multifaceted challenges posed by contemporary urban mobility systems. While cities are eager to integrate cutting-edge technologies to evolve into digital and intelligent hubs, they often deal with infrastructure and governance bottlenecks that prevent the rapid adoption of industry-driven innovations. This study introduces a three-step methodological approach to forecast a city’s innovation readiness in urban mobility, thus facilitating city-led innovation and identifying key areas within urban mobility systems that require attention. Initially, a comprehensive literature review was undertaken to ascertain the most impactful innovation indicators influencing a city’s ability to embrace new technologies. Subsequently, Principal Component Analysis (PCA) was applied to identify these indicators, highlighting the primary markers of innovation for each city. The final step involved the application of both random and fixed-effects regression models to quantify the influence of distinct unobserved variables—such as economic, cultural, and political factors—on the innovation readiness of various cities. The methodology’s effectiveness was tested using data from cities across diverse regions. The findings underscore that merely 7 out of 21 innovation indicators are critical for assessing a city’s innovation readiness. Moreover, the random-effects model was identified as the most suitable for capturing the nuances of unobserved variables in the studied cities. The innovation readiness scores at the city level revealed a diverse range, with cities like Madrid, Gothenburg, and Mechelen demonstrating high readiness, while others like Kalisz and Datong showed lower scores. This research contributes to the strategic planning for smart cities, offering a robust framework for policymakers to enhance innovation readiness and foster sustainable urban development, with a newfound emphasis on city-specific analysis.

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“…Smart municipality [55], smart city services [56,57], utilities systems control in urban environment [58], energy optimization and next-generation building management systems [59], public safety, transportation, healthcare and education [60] are examples of applications available in a smart cities context, aimed to increase the quality of life of the citizens [61].…”

Section: Arrowhead Framework In the Landscape Of Smart City Frameworkmentioning

confidence: 99%

“…Sensors 2020, 20, x FOR PEER REVIEW 14 of 29 public safety, transportation, healthcare and education [60] are examples of applications available in a smart cities context, aimed to increase the quality of life of the citizens [61]. All these applications are disjointed without a framework that integrates them, providing interoperability for heterogeneous devices and services, being capable to gather and manipulate reliable data sources [62] in a secure way and to transform them into valuable information for citizens and other stakeholders.…”

Section: Smart Municipalitymentioning

confidence: 99%

Arrowhead Technology for Digitalization and Automation Solution: Smart Cities and Smart Agriculture

Marcu

Suciu²,

Balaceanu³

et al. 2020

Sensors

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The Internet of Things (IoT) concept has met requirements for security and reliability in domains like automotive industry, food industry, as well as precision agriculture. Furthermore, System of Systems (SoS) expands the use of local clouds for the evolution of integration and communication technologies. SoS devices need to ensure Quality of Service (QoS) capabilities including service-oriented management and different QoS characteristics monitoring. Smart applications depend on information quality since they are driven by processes which require communication robustness and enough bandwidth. Interconnectivity and interoperability facilities among different smart devices can be achieved using Arrowhead Framework technology via its core systems and services. Arrowhead Framework is targeting smart IoT devices with wide applicability areas including smart building, smart energy, smart cities, smart agriculture, etc. The advantages of Arrowhead Framework can be underlined by parameters such as transmission speed, latency, security, etc. This paper presents a survey of Arrowhead Framework in IoT/SoS dedicated architectures for smart cities and smart agriculture developed around smart cities, aiming to outline its significant impact on the global performances. The advantages of Arrowhead Framework technology are emphasized by analysis of several smart cities use-cases and a novel architecture for a telemetry system that will enable the use of Arrowhead technology in smart agriculture area is introduced and detailed by authors.

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Smart City Framework Development: Challenges and Solutions

Cited by 6 publications

References 14 publications

Challenges for sustainable smart city development: A conceptual framework

Challenges for sustainable smart city development: A conceptual framework

A Quantitative Model of Innovation Readiness in Urban Mobility: A Comparative Study of Smart Cities in the EU, Eastern Asia, and USA Regions

Arrowhead Technology for Digitalization and Automation Solution: Smart Cities and Smart Agriculture

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