Abstract

Keywords

Introduction

Smart electric pole

Sustainable power unit

Conclusion

Data Availability Statement

Declaration of Competing Interest

References

Abstract

With the effective result of IoT architecture in all research areas, we propose IoT framework based energy efficient smart and intelligent street road lighting system that consist of IoT sensor bases smart electric pole with controller for tuning LED lamps. In our work we replace traditional metal halide lamps with mesophic design LED lamps based on human eye sensitivity and it provides significant saving of energy too. Based on the sensor unit information about traffic flow and presence and absence of occupant smart and intelligent decision making module compute intensity level that generate different width pulse using PWM dimming system which triggers LED power switch via DALI controller mounted inside LED Light Controller. For efficient use of sustainable energy resources we use sustainable power systems that consist of PV solar panel units, Battery storage systems and smart electric power grids. For the charging battery system we use MPPT based dynamic battery charging algorithm. From experiment and simulated result, we observe that proposed energy efficient Smart Street lighting saves considerable amount of energy during peak and off peak hours not only at highway roads but at residential and sub-urban pedestrian areas also.

Introduction

Sustainable energy is the method of utilizing energy in an efficient way and at the same time satisfying the needs of the modern world. Sustainable energy can be used in economic, social and environmental issues. An efficient sustainable energy management system can be achieved by using renewable resources in all the possible ways, using sustainable energy resources, using alternative energy resources, making use of smart systems, implementing IoT systems, implementing green technologies. The smart system is the technique, which is used to embed the modern technology into functions already used by the world. In terms of smart system, the information about utility system and traffic flow of the large cities is extracted with the help of sensor also it analysis the pattern of information for prediction. Then, the ability to transfer data over a network without the help of human-to-computer or human-to-human interaction is called IoT or internet of things system and the green technology is used to explain the functions of science and technology to develop products as environmental friendly. Some of the examples of green technology is water purification, conserve natural resources, clan energy creation and waste recycle management. It is also used in digital and mechanical machines, objects and in correlated computing devices.

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Abstract

In recent years, the world’s population living in cities has been rapidly increasing. Cities are transforming their infrastructure in a smarter and more efficient way so that sustainable development forms part of their long-term strategy. However, this transformation does not always result in expected benefits due to a variety of factors such as an absence of social acceptance, a lack of holistic design and the development of unilateral interventions. An analysis of the scientific literature related to the evaluation of the impact of smart city actions revealed a gap in the holistic methods for their assessment. To this end, an accurate evaluation of implemented smart solutions focusing on the energy domain is necessary in order to assess the expected and realized impact of each solution. This paper proposes a seven-step methodology for assessing the impact of smart city interventions and presents a use case for the city of Espoo. A number of major findings were the outcome of our research and development work, such as the need for a thorough analysis of the long-term vision of the city, a combined top-down and bottom-up approach and the ongoing cooperation between all stakeholders involved in urban planning and transformation, in which necessary Key Performance Indicators (KPIs) are defined.

1. Introduction

1.1. The Necessity of Impact Assessment
According to the United Nations [1] 68% of the world’s population is projected to live in urban areas by the year 2050; cities, therefore, are anticipated to face new challenges in sustainably integrating further populace, such as a lack of appropriate infrastructure for sustainable energy and automated systems, applications and commercial arrangements, digital security, network connectivity and data capacity [2]. Cities will be required to transform their infrastructures in a smarter, more efficient and resilient way so that sustainable development forms part of their long-term strategy and a better quality of life is assured to their citizens. The concept of the smart city is multidimensional [3], with the aim of increasing urban sustainability and quality of life while pursuing economic development among its citizens [4]. Additionally, sustainability has gained popularity among scholars, environmental policy makers and government agencies [5]. However, a smart city is not just about creating technically viable urban areas and stimulating economic growth; it requires a multifaceted and multidimensional approach that promotes a structural transformation in the urban ecosystem, directing the development of cities towards their “smartness” in areas such as economy, governance, social, environment, mobility and ICT [6].

Abstract

     Many standards, projects, and platforms are being developed as the Internet of Things (IoT) is adopted in a wide range of fields. However, because each IoT platform is based on a different resource identifier (ID), it is difficult to identify each device and use the service among heterogeneous IoT platforms. To solve this problem, we propose an interoperability framework that includes an IoT resource name system (RNS) based on analysis of the resource IDs (i.e., device ID and resource request formats) of five selected IoT platforms: oneM2M, Oliot, Watson IoT, IoTivity, and FIWARE. The IoT RNS converts a specific resource path into a resource request format for each platform. The converted resource path is shared among IoT RNSs for each platform, and users can request services from other platforms using converted resource paths. We also present an example of interoperability scenario among heterogeneous IoT platforms using the proposed IoT RNS in a smart city. The scenario includes each stage, such as resource registration and deletion, sharing mapping tables, converting resource addresses, and service requests. Furthermore, to prove the aims of the proposed approach, we implemented the resource interoperability scenario between oneM2M and FIWARE. In the experiments, resources can interwork in the two platforms through resource path conversion. Based on the results, we performed a qualitative evaluation of the IoT RNS with the current studies. In conclusion, our proposal overcomes the issues of building an existing integrated platform or specific central ontology and duplicating resources inside the platform. In addition, we separate the functions of the root and local IoT RNSs to solve communication traffic and memory capability issues.

Introduction

     Internet of Things (IoT) technology is developing and expanding in various fields such as smart homes, healthcare, smart cities, logistics, and smart car. The international standard, “ISO/IEC 20924:2018 Information technology—Internet of Things (IoT)—Vocabulary” (ISO/IEC, 2021), defines the IoT as the “infrastructure of interconnected entities, people systems, and information resources together with services that process and react to information from the physical and virtual world.” In other words, the IoT is hyper-connectivity among smart things, services, and humans to provide useful and seamless services regardless of the types of networks, devices, and platforms and with minimum human involvement. These technologies, related standards, projects, and platforms are continuously being developed (Lee et al., 2021). In particular, IoT platforms are an essential factor in providing interoperability because they support the network connection to various devices (e.g., sensors and access points) and provide services to users. According to the IoT Platform Companies Landscape & Database 2020, the official number of IoT platform companies in the open market is more than 620, up from 450 in 2017. For example, many platforms (e.g., AllSeen Alliance AllJoyn, Apple HomeKit, oneM2M, FIWARE, Google Cloud IoT, GS1 Oliot, IBM Watson IoT, Microsoft Azure, and OCF IoTivity) are being developed to provide various services. Therefore, interoperability, such as requesting services and sharing resources among diverse IoT platforms, is important, and it is an essential factor for building a real IoT environment that provides seamless services regardless of the type of IoT platform.

Conclusion

     IoT technology is rapidly expanding in many fields, including smart homes, logistics, automobiles, healthcare, and smart cities, and related standards, projects, and IoT platforms are constantly being developed and improved. However, the numerous platforms and related standards make it difficult to achieve interoperability and collaboration among platforms. In particular, identifying each resource among heterogeneous IoT platforms is challenging due to various ID formats.

     In order to solve this problem, we firstly classified interoperability taxonomy in IoT environments into middleware, network, syntactic, and semantic interoperability, with common security factors for each case. In addition, we proposed an IoT RNS architecture and scenario in a smart city to convert IDs between heterogeneous IoT platforms. Finally, we compared the proposed IoT RNS with existing projects under development and showed it satisfies the interoperability in the heterogeneous IoT platforms.

     Future studies will expand interoperability by considering security and implementation-related issues in a real environment. Device authentication and authorization will be added to resource sharing among heterogeneous platforms to address particular security issues. Defining these security policies and applying them to IoT RNS will allow restrictions to be applied for unauthorized access to heterogeneous platform resources.

Abstract

Introduction

Nancy Fraser’s conceptualization of justice

Affirmative versus transformative remedies for injustices

Justice in critical literature on smart cities

Redistribution

Recognition

Representation

From the smart to the just city in the digital age

From affirmative to transformative strategies

Retaining and regaining technological sovereignty

Conclusions

Acknowledgements

References

Abstract

     The smart city is the most emblematic contemporary expression of the fusion of urbanism and digital technologies. Critical urban scholars are now increasingly likely to highlight the injustices that are created and exacerbated by emerging smart city initiatives and to diagnose the way that these projects remake urban space and urban policy in unjust ways. Despite this, there has not yet been a comprehensive and systematic analysis of the concept of justice in the smart city literature. To fill this gap and strengthen the smart city critique, we draw on the tripartite approach to justice developed by philosopher Nancy Fraser, which is focused on redistribution, recognition, and representation. We use this framework to outline key themes and identify gaps in existing critiques of the smart city, and to emphasize the importance of transformational approaches to justice that take shifts in governance seriously. In reformulating and expanding the existing critiques of the smart city, we argue for shifting the discussion away from the smart city as such. Rather than searching for an alternative smart city, we argue that critical scholars should focus on broader questions of urban justice in a digital age.

Introduction

     We live in an age where digitization, digital networks, big data, and internet-based infrastructures are ‘mediating and augmenting the production of space’ and in so doing, are ‘transforming socio-spatial relations’ (Ash, Kitchin, and Leszczynski 2018, 29). The smart city is an emblematic expression of these transformations where data, sensors, and algorithms are presented as technical solutions for urban problems. After initially being dominated by affirmative perspectives, since about 2014 an increasing number of critical views on the smart city have been published by geographers and urban scholars (amongst by now many others, see Cardullo and Kitchin 2019; Cugurullo 2018; Greenfield 2013; Hollands 2008, 2015; Kitchin 2016; Leszczynski 2016; Rose 2020; Söderström, Paasche, and Klauser 2014; Wiig and Wyly 2016), with some of the earliest and most cited critiques being published precisely in this journal (Hollands 2008; Söderström, Paasche, and Klauser 2014).

     Most of these critiques directly or indirectly invoke questions of justice; however, they rarely define its meaning. Consequently, the meaning of justice in critical smart city debates remains elusive and theoretically underdeveloped. This is despite the fact that critical urban geographers have of course long engaged with concepts of social justice, from Lefebvre’s (2003 [1970]) call for the right to the city, further developed for example by Marcuse et al. (2009) and Brenner, Marcuse, and Mayer (2009), to questions of spatial justice (Soja 2010; Marcuse 2009; Fainstein 2009), to Harvey’s (1973) seminal work on justice and the city, to interventions like Fainstein (2010) which highlight the importance of participatory engagement to expand understandings of urban justice (for on overview on some of them with reference to the smart city see Kitchin, Cardullo, and Di Feliciantonio 2019; for an application of David Harvey’s social justice theory on questions of the smart city see Vanolo 2019).

Conclusions

     We are currently observing the increasing centrality of digital technologies in public discourse, proposed as responses to current social and political problems of the city. In this article, we presented a comprehensive definition and framework of justice to guide progressive efforts in assessing and reimagining smart city initiatives and argued for transformative remedies for injustice. Building on Fraser’s tripartite framework, we examined justice in critical smart city literature along economic, social, and political lines. We observed notable tensions, marked by a recognition on the one hand of the ways in which digital practices mediate and reinforce domination, dispossession, disenfranchisement, and social differentiation, and on the other, a desire to exploit the emancipatory potential of digital practices as sites of generative possibility for thinking, acting, and being otherwise. In assessing visions of alternative smart cities, we highlighted the need for transformational change, for instance, through technology sovereignty movements which provide collective ownership of data-intensive digital and algorithmic platforms and services.

Abstract

Introduction

Review of literature on the current understanding and ongoing debate of smart cities

Method and data

Results and discussion

Conclusion

Declarations

References

Abstract

     Smart city is one of the fastest growing socio-economic and scientific initiative in the world. Still, it is only in principle and a mere blueprint for many developing countries. This study reviews literature on smart city in Nigeria and developing countries. Our aim is to explore ways to improve the quality of Nigeria’s urban areas, based on recent research on the concept of smart city and its implementation. We summarise key research findings, and gather evidence that shows what composition of urban governance, social, economic, and environmental factors, that would influence actualising a smart city in Nigeria. Although knowledge has grown tremendously in the current literature on the definition, significance, governance, policy, and implementation of a smart city, its significance in Nigeria and other developing countries is supplemental. As an environmentally friendly initiative, a smart city will support urban sustainability and livelihood in Nigeria in a myriad of ways—environmental protection, and mainstream urban services, including public security and safety, access to quality health care, efficient power supply, clean water distribution, assets management, smart transportation, etc. However, despite her unique traditional urban agglomeration trends, Nigeria is unambitious and constrained towards actualising a smart city. Actualising a smart city in Nigeria and other developing countries would require radical and ambitious policies on development of human and infrastructural capacity, as well as institutional reinforcement. This highlights the need for more research, of which we are optimistic that the findings of this research will support with its new insight and clear guidelines.

Introduction

     A smart city is modern architectural philosophy, focusing on the use of information and communication technology (ICT) to solve problems endogenous to the city, and to power vital activities. It represents a major transformation from the traditional urban agglomeration to a twenty-frst-century metropolis, which advances city functions, promotes economic growth, and improves the quality of life for citizens (Bakıcı et al., 2013). One obvious beneft of a smart city is the level of government response to the needs and well-being of citizens through positive interaction between the government and citizens, aided by technology-driven policies and services. When we look at some of the smart cities in the world today for example Singapore, San-Diego, Barcelona, and Hong Kong, we could fnd that smartness of cities creates applications and urban services that combine technology and promotes the development of policies and practices to address the social, economic, and environmental challenges facing today’s urban areas (Su et al., 2011).

Conclusion

     A smart city represents a shift both in mindset and architectural framework from the traditional agglomeration of roads, public utilities, and amenities to a modern system that uses big data and ICT to enhance the livelihood of the citizens and government policy and program of service delivery within the city. This is a major incentive for research and policy towards the sustainable development of cities. There is also an opportunity to tackle urban scenic distortion and to provide a more dynamic and diversifed science to address common issues – such as climate change, increasing frequency, and severity of crimes, social disorders, and disasters – arising from urban agglomerations and the burgeoning human population in cities.

For the developing countries (DCs) such as Nigeria – the focus of this study – a smart city’s conceptualization is slightly skewed because of the vagaries of challenges to its actualization. Thus, the idea of a smart city is still more utopian than realistic. However, the future of the DCs is arguably a smart city because of the complex urbanizations and predictions that places within the DCs will contribute signifcantly to the global urban populations, which is estimated at 90% of the global population by 2050. Therefore, to address the attendant problems that prevail presently in the DCs’ urban areas – which include environmental, economic, and human development issues – a smart city is a potent option.

Abstract

Introduction

Seeing the smart city

Smart city visibility

Visibility and stratagems

Three strategies of visibility

Visualizing smart cities

A politics of visibility

Declarations

References

Abstract

     Cities across the world are increasingly labelling themselves as smart in one way or another. At the same time, this smartness appears amorphous or invisible in its built urban environment. Critical researchers writing on the smart city regularly express confusion or exasperation about precisely the difficulty to locate the smart in the city. Visibility of the smart city is not a given. This article argues that visibility in the case of the smart city is instead strategically produced, and that the strategy opted for tells us something about the kind of urban imaginary put forward. The article introduces a provisional and non-exhaustive taxonomy of strategies of visibility based on analyses of three different cases of smart city projects (in Brazil, Sweden and Canada) and identifies the ways in which the smart city is made visible (or not)—symbolic presence of smart, modelling smart and ubiquitous invisible smart—and discusses what kind of city is envisioned based on each strategy.

Introduction

     The following article investigates the visibility of the smart city. The main argument is that smart city visibility is strategic rather than given, and the article presents three different strategies of visibility inferred from urban examples: the control room of Rio de Janeiro’s smart city operations (the COR), a proposed smart model city in Sweden (Plusstaden) and visualizations of the proposed and later discontinued project Sidewalk Toronto. These three cases represent three different strategies of making the smart city visible: symbolic presence of smart (manifestation through a representation of a smart object or space), modelling smart (constructing exemplary environments), and ubiquitous invisible smart (a strategic invisibility). The article, furthermore, argues that the way in which the smart city is made visible outlines different future imaginaries that produce different relationships between state, smart system, and inhabitants. Smart city visibility will therefore ultimately constitute a political question, not least with regards to transparency, and deserves more scholarly attention than has been the case up to now.

     The principal contribution of the article is to the under researched field of the smart city’s medial and material manifestations. While smart city visibility is touched on in a range of critical research into the following areas: material manifestations of the smart city (Halpern 2015; Picon 2015; Halegoua 2020), visualizations of smart city (Rose 2017, 2018a, b) and narratives of the smart city (Söderström et al. 2014), there is very little research concerning itself with its visibility as such, and even less on the strategic aspects of this visibility. In this sense, the article contributes to the field of smart city visibility through differentiating between different approaches to visibility of smart cities. The article provides a preliminary framework for further analysis of smart city visibility and offers a set of analytical concepts for future research and policymaking.

A politics of visibility

     Sometimes, the smart city is presented as a uniform corporate vision, at times juxtaposed with ‘civic hackers’ (Townsend 2013) or the ‘social city’ (Halegoua 2020), offering community-based non-corporate alternatives to the corporate smart city vision. The smart visions here discussed through their strategies of visibility cannot be neatly divided in this sense. Instead, the material suggests a bigger variation of smart city dreams—the municipal government (with IBM in Rio de Janeiro) vs the national Swedish platform proposed by Plusstaden and the corporate smart city of Sidewalk Toronto.

     I am not arguing that one smart city strategy of visibility is necessarily preferable to others, it would seem to be too early to decide, nor that all models are good or bad. Rather, they present different problems to its inhabitants, not only through the different subjectivities encouraged but also in terms of experience and transparency. These problems need to be addressed through other measures, through policy and laws. The strategies of visibility themselves require different societal responses and the strategies’ political effects will depend on these responses.

Abstract

1. Introduction

2. Methodology

3. Characteristics of a Happiness Driven Smart City

4. Key factors contributing to characteristic performance in a Happiness Driven Smart City system

5. Mechanism for developing Happiness Driven Smart City

6. Strategic measures and assessment process for the application of HDSC mechanism

7. A Greater Manchester case study

8. Discussion and conclusion

CRediT authorship contribution statement

Acknowledgment

Appendix

References

Abstract

     Smart City conception has become a global trend with the advancement of Information and Communications Technologies (ICTs). Many cities have proposed Smart City development strategies to capture the opportunities brought by ICTs. However, little attention has been given to investigate whether and how Smart City acts upon human happiness. To fill this gap, this study introduces a Happiness Driven Smart City (HDSC) mechanism to better guide the development of Smart City towards a more human-centered direction. HDSC mechanism includes a three-layer interrelated structure and is underpinned by a set of Strategic Measures. The assessment criteria have also been established for applying HDSC mechanism to investigate the performance of Smart City initiatives. The HDSC mechanism established in this study is a first attempt to assess the performance of Smart City development from the lens of human happiness. By applying HDSC mechanism in investigating Manchester’s Smart City initiatives, the mechanism is proven effective to help decision makers understand the status quo of Smart City development in their urban context, based upon which the strength and weakness in the process of HDSC development can be drawn out. Consequently, Smart City blueprint can be better achieved towards a happiness-driven direction via dynamic assessment and adjustment.

Introduction

     Smart City is expected to provide better solutions for the intensified socioeconomic and environmental challenges associated with the unprecedented urbanization by embracing advanced Information and Communication Technologies (ICTs), where challenge like climate change, energy crisis, or social inequality could all find its way out through the development and application of state-of-the-art technologies (Manville et al., 2014; Michalec et al., 2019; United Nations, D.o.E.a.S.A., 2019; Yigitcanlar et al., 2019). The idealized narrative of Smart City has been widely accepted and turned to global movement at an appreciable speed for economic expansion and societal transformation (Cheng et al., 2020; Deloitte, 2018; Vu et al., 2020). It was reported that more than 1000 cities globally have introduced the Smart City initiatives with Europe, North America, Japan and Korea at the leading position (Deloitte, 2018). By applying Smart City initiatives, some global cities keep their central position in the landscape of innovation and knowledge generation (Yigitcanlar et al., 2016), and others have revitalized their urban economy to foster, attract and retain innovation abilities (Holland, 2015). However, it appears that Smart City’s influence upon human happiness has been paid with only marginal attention amid the practices of Smart City development.

Discussion and conclusion

     This paper argues that human happiness should be embodied as a key element in the process of Smart City development. The study embarks with the research question that whether and how Smart City acts upon human happiness in the trendy development of Smart City globally. By conceptualizing the Happiness Driven Smarty City (HDSC) and capturing the Characteristics and Factors of HDSC, a Happiness Driven Smart City Mechanism has been established, which is underpinned by various applicable and measurable Strategic Measures. To our knowledge, the HDSC Mechanism is a first attempt to assess the performance of Smart City development from the lens of human happiness, which integrates human happiness into the planning, constructing and delivering process of Smart City strategies. The established HDSC Mechanism in this study provide an applicable toolkit to urban governors for better harnessing Smart City blueprint towards a happiness-driven and human-centered direction. The applicability and effectiveness of HDSC mechanism has been validated via the empirical investigation to Greater Manchester’s Smart City initiatives.

Abstract

1. Introduction

2. Integrated Data Exchanges: The Foundation of Smart Cities

3. Applying Governance Approaches to Provisioning IDE Services

4. Discussion: Governance and Sustainability of IDEs

5. Conclusion

References

Abstract

     Collecting, processing, and distributing information has always been a core function of government. This core function has evolved from the earliest ancient governments using clay tablets to today’s smart cities relying on integrated data exchanges (IDE). A smart city “uses information and information technology to make better decisions to improve the quality of life” (Nam and Pardo, 2011). The IDE framework builds upon the data platform literature (O’Reilly, Jan. 2011) by incorporating governance systems to manage a smart city’s activities. This conceptual paper takes existing research, synthesizes it, and creates a new framework to identify how cities can select the appropriate governance rules to facilitate the political, financial, and operational sustainability of their IDEs, and derivatively, their smart city efforts.

Introduction

     Managing information has always been a core function of government
Managing information has always been a core function of government. For example, one of the earliest civilizations in the world, the ancient city of Sumer in Mesopotamia (c. 4500 – c. 1900 BCE) (Anon Feb. 01, 2020) used cuneiform tablets (Anon Apr. 01, 2022) to record contracts and property transfers. In fact, most of the clay tablets that were unearthed, were used to support a public function. Some historians also believe that the expansion of these earliest empires critically depended on a code of law that could be communicated to the far-flung parts of the empire (e.g., the famous Hammurabi’s Code, 1758 BCE) (Charpin and Todd, 2010). Since then, new technologies have developed to improve the collection and distribution information, generating new challenges and opportunities for civilization and also how government should provide data and information1: including the printing press (Adelmann, Mar. 19, 2012) (McLuhan, 1962), the telegraph (Howe, 2007), the Internet (Castells, 2001), AI (Yigitcanlar et al., 2022) and block-chain (Tsampoulatidis et al., 2022). “Smart cities” are the latest conceptualization about how technology can improve government (Anthopoulos and Reddick, 2022) 2. Although by some accounts, the term has become a brand that businesses use to sell technologies (Smith and Prieto Martín, 2022), this study defines smart cities as those that “use information and information technology to make better decisions to improve the quality of life” (Nam and Pardo, 2011).

Conclusion

     If good public management is good decision-making (Simon, 1947), then information is the lifeblood of government. Creating, storing, and analyzing information is not only a core government function, but it is also foundational to the rest of society. As for government, evidence-based or data driven decision-making is key to be recognized as a “smart” city. Foundational to smart city efforts is an IDE to manage vast and disparate sources of information. One of the contributions of this study is defining an IDE and its role in curating, managing, and disseminating information.

     In constructing a conceptual framework for an IDE, dimensions of political sustainability, operational sustainability, and financial sustainability emerged. This study makes the argument that IDE sustainability may be dependent on different governance models: municipal, regional cooperative, and PPP. If an important goal is to use up-to-date technology to make sure that the city stays innovative, it makes more sense to have this function governed by public-private governance systems and their accompanying rules than to keep that within a municipal governance system. If, however, the strategic goal is to make sure that the public is actively involved in smart city efforts or to be transparent and accountable, a public governance system is more appropriate for those functions.

Abstract

Introduction

Review of literature

Methodology

Integrated smart city model

Conclusion

Appendix

References

Abstract

     In smart city architecture, information and communication technologies are used to improve living standards and its management by citizens and government. Most researchers have divided this structure into six main components: smart people, the smart government, smart environment, smart transportation, smart economy, and smart life. Due to the connection between smart cities and the challenges resulting from their implementation and especially its integration, there exists no perfect solution for the concept of an integrated smart city so far according to our studies. Some more general concepts such as security, ICT infrastructure, and knowledge are not seen integrative in these structures. Therefore, it seems that new sub-components and general extra-components should be added to the existing models to form an integrated structure in such a way that the executive projects are located in their proper place in this structure and create and guarantee the integration of the smart city. Therefore, the requirements engineering of the smart city can also be explained more precisely. This study presents a model of an integrated graph in such a way that besides maintaining and improving the model of the smart city and existing models, it will fully cover the integration and requirements engineering and methodologies of the smart city in the future.

Introduction

     The process of urbanization is currently taking place at a rapid pace on a global scale. Every year, millions of people migrate from rural to urban areas to gain comfort and economic opportunities. According to the United Nations (UN), 6. 5 billion people will live in cities by 2050, and more than 60% of the world’s population will be concentrated in cities (Schuurman and Baccarne 2012). On the global scale, International Data Corporation (IDC) estimates that the steady increase in smart cities’ expenses will rise to $ 158 billion by 2022 (Twice as much as $ 80 billion in 2018) (Visan and Ciurea 2020). Rapid population growth, besides putting considerable pressure on current cities, will pose serious threats to the future, leading to increased demand for services, housing facilities beyond the capacity of cities, as well as irreparable damage to the environment. As a result, cities face many challenges as their resources and infrastructure increase under increasing pressure (Breetzke 2016). Therefore, they always suffer from adverse consequences. Also, the sudden emergence of problems such as the recent Panorama of Covid-19 as well as advances in telecommunications, especially the Internet, along with the development of electronic devices, have changed people’s everyday life and their minds in all aspects of economic and social fields (Das and Zhang 2020).

Conclusion

     In previous research based on the current situation and thematic literature, the concept of smart city was mostly proposed and implemented as an island with six main components in different societies. Also due to the increase in urbanization and the connection of smart cities with the challenges that arise in implementing and integrating the urban model, a suitable solution for the concept of integrated smart city Was not provided to your best knowledge and some essential concepts such as security, ICT infrastructure and knowledge are not seen integrative in these structures. In order to integrate, prevent data redundancy, ease of access, create security at different levels, the present study Provides a flexible, integrated, localizable dynamic model with a new approach that breaks down six core components into several sub components that creates a graph-like model, in which each sub component represents a set of implementable smart projects in different communities.

Abstract

1. Introduction

2. Literature review

3. Empirical framework

4. Empirical findings

5. Conclusion and discussion

Disclosure statement

Notes on contributors

References

Abstract

     The aim of the present study is to reveal the causal effects of Smart City policies on urban innovation. Using the panel data harvested from 103 cities in China, the constructed sample was analysed rigorously based on the combination of the strength of Propensity Score Matching (PSM) and Difference-in-Differences (DID). As suggested by the empirical results, Smart City policies indeed positively and significantly impact urban innovation . Besides, whether policy effects vary with the regional location and city scale is explored; the results reveal that the impact is significantly positive only for the megacities as well as cities in central China.

Introduction

     Since the late 1990s, smart city projects have been rolled out globally. According to Deloitte Touche Tohmatsu’s report (Deloitte, 2018), the constructions of over 1,000 smart cities have been launched worldwide with 500 policy pilot areas in China, which noticeably outclasses Europe’s 90 of the second place. The mentioned projects are capable of not only enhancing the intelligence of specific socio-economic aspects of daily life, but also presenting a considerable number of other benefits, which cover fostering a competitive economy (Giffinger & Haindl, 2010), boosting more feasible governance (Nam & Pardo, 2011), expediting the innovation process (Paskaleva, 2011; Schaffers et al., 2012), advancing social capital (Hodgkinson, 2011), protecting diversity and individuality (Lind, 2012), etc. Nevertheless, some have argued that the potentials or benefits of smart cities have been overestimated; they considered that smart cities may not be as ‘smart’ as their name suggests (Hollands, 2008). Though considerable capitals have been invested in the advancement of smart cities, smart cities have not achieved their original goals (Yigitcanlar & Lee, 2014). Numerous risks also exist in the application of smart city strategies, e.g., the digital divide resulting from unequal use of ICT (Coe et al., 2001), the replication of technology solutions (Townsend et al., 2010), the overlook of city’s requirements and priorities (Caragliu & Del Bo, 2019), the slow progression attributed to budgetary issues and inadequate planning (Shwayri, 2013), etc.

Conclusion and discussion

     The present paper aims to evidence whether Smart City policies make cities more innovative – in the case of Chinese cities. To accurately estimate the policy effect, Propensity Score Matching (PSM) and Difference-in-Differences (DID) are integrated to eliminate some biases that might affect the effectiveness of this study. To be specific, PSM technique is adopted to construct the matched control group that possesses similar observable city characteristics with treatment group. Subsequently, DID approach is employed to estimate the differences of those groups’ treatment effects before and after the policy implementation. Besides, our results comply with several existing studies (Caragliu & Del Bo, 2019; Veeckman & Graaf, 2014), revealing that Smart City policies indeed stimulate urban innovation. Though innovative is not a major objective of implementation of Smart City policies, our findings have demonstrated a positive spill-over effect of the policies on urban innovation. Compared with similar non-pilot cities, pilot cities of smart city policy are granted more patents.

Abstract

Introduction

What are smart cities?

Methodology

Analysis of smart city initiatives

Comparing PSI in HK and SG

Discussion

Conclusion

Acknowledgements

References

Abstract

     Since the 2000s, Hong Kong (HK) and Singapore (SG) have been working to reinvent themselves as smart cities. Despite their similarities, SG has consistently ranked ahead of HK on several smart city indices. To explain this gap, the smart city initiatives of both cities were categorized using a six-factor typology of public sector innovation. Further analysis indicated that SG was ahead of HK because its government has been more aggressive in funding and fostering innovation. This paper suggests that a government’s financial support for public sector innovation, as well as its ability to redirect resources within the public sector and get citizens involved, will catalyse transformational efforts into a smart city.

Introduction

     The cities of Hong Kong (HK) and Singapore (SG) are often compared as a result of their similarities—a colonial history (Kratoska, 2006; Onimaru, 2019; Tan, 1997), values and culture (Chia et al., 2007), relatively high levels of human development (Delang & Yu, 2015; Ramesh & Holliday, 2001), strong economic competitiveness (Li et al., 2013; Schwab, 2018), as well as being two of the four ‘Asian tigers’ and important regional transport and financial hubs (Huat et al., 2004; Jarvis, 2011; Woo, 2015). The IMD World Competitiveness Center ranked HK at third place in 2018, second in 2019, and fifth in 2020; SG was ranked second in 2018, and first in both 2019 and 2020. A separate ranking by the Global Competitiveness Report ranked HK at fourth place in 2018, third in 2019; while SG ranked second in 2018 and first in 2019 (at the time of writing, rankings were not available for 2020). Overall, the two cities are very close rivals in global rankings of governance and development, and they are in competition for foreign investment and global talent.

     Although SG and HK have been relatively close rivals in various areas, SG has consistently ranked ahead of HK on indices related to smart cities. These include the IMD Smart City Index 2020 which ranked SG first and HK 32nd, the Global Innovation Index 2020 where SG ranked eighth and HK ranked 11th (Cornell University, INSEAD, and WIPO, 2020), and the IESE Cities in Motion Index 2019 which ranked SG ranked seventh and HK 11th (Berrone et al., 2019). The disparity is curious, especially since the governments of both cities had been proactively seeding and steering various initiatives to transform them into smart cities.

Conclusion

     Both HK and SG need to thrive economically, while ensuring sustainable development and building up capital for the future. While the two cities are unique, one would expect more similarities in their global standing as smart cities. The comparison of the two cities in this paper sheds light on how PSI and governance has affected the development of the cities. Smart city initiatives often require support from both the public and private sectors. Both the design and delivery of public services need to change, so innovation needs to come from within the public sector. Using private sector resources and funding, the SG government has been more effective than HK in creating a smart city. However, it has also been more exposed to criticism when initiatives have failed. The paper shows that the development of smart cities is also accompanied by new challenges, such as the risk of cyber-attacks and citizens’ reluctance to use new technologies. Governments need to be prepared to handle these challenges. Future studies should examine how well the governments of smart cities have adapted and innovated in response to the Covid-19 pandemic.

Introduction

One of the most noteworthy arcs of the 21st century has been the explosive growth seen in the usage and deployment of technology. More specifically, the advancement of information and communications technology (ICT) has been the foundation for many of the innovations seen over this century thus far. The wide-spanning adoption of the Internet for social media, e-commerce, news consumption, and more has redefined much of our everyday lives and industries across the world. Due to the advancements of ICT, there are many exciting opportunities for what is yet to come. One longstanding opportunity for the future is the vision of the smart city.

There are countless different ideas and definitions for what exactly qualifies as a smart city. A more general definition, provided by Bakıcı et al. in [1], defines smart cities as being high-tech cities that serve to connect people, information, and city-wide infrastructure and resources using advances in technology to improve sustainability, innovation, and overall quality-of-life. The extent to which how pervasive (or intrusive) technologies are incorporated to accomplish such goals is often a point of contention in the literature [2]. However, the many different visions for what define smart cities all generally involve heavy utilization of technology to improve the maintenance of cities to further improve and/or optimize city-specific operations for different stakeholders (e.g., citizens, the environment).

Realizing the ambitious vision of smart cities requires seamlessly making decisions for a host of different applications and domains with minimal sacrifice with respect to performance and resource costs. Some applications of interest for smart cities include, but are not limited to, smart traffic light control, smart information spread (or advertisement), smart energy distribution, smart waste management, etc. Ideally, data generated in urban environments can be collected in smart cities using CT-powered infrastructure to train and inform models designed for these applications to make realtime decisions. For instance, insistent collection of traffic congestion data from roadside units(RSU) and other sources can be sent to ICT infrastructure to train machine learning models how to make optimal decisions related to traffic lights to reduce congestion. This approach is becoming more within reach given the advances in vehicular ad hoc networks (VANET) [3, 4, 5] and other Internetof-Vehicles (IoV) systems [6, 7, 8].

Making smart decisions in a timely fashion will require a powerful pipeline ready to support intense amounts of data collection, analytics, and adaptive decision-making. For instance, video feeds at road intersections — to empower models for smart traffic light control — are large in size (in terms of bytes) and will require automated processes to make meaningful decisions in real-time. However, video cameras that provide such video feeds will be unable, on their own, to perform such analytics and decision-making. Such tasks would require more computational resources than would be available at video cameras and other similar sensors that can be found in urban environments. Thus, for such applications, smart cities will need to be able to provide heavy computational power on-demand, even for devices that do not have such resources locally. Applications (e.g., big data analytics, video classification) all require large amounts of compute resources in order to adequately process. Because Internet-of-Things (IoT) devices like smartphones are often ill-equipped to meet the needs of such processes [9, 10], a standard approach for providing these services on these devices is to rely on remote resources.