Context Of Smart Cities Research Articles

Gulf Cooperation Council Countries and Urbanisation: Are Open Government Data Portals Helping?

Today, the concepts of the smart city and smart government are well established, and have become key in dealing with the challenges faced by rapidly increasing urbanisation across the world. One of the many ways in which smart cities and government can help meet these challenges is by empowering citizens to take more and better control of their own decisions, by giving them access to open (i.e., public and unrestricted) data via online portals. These portals can enable citizens and professionals to make more informed decisions across a wide variety of areas, from health and traffic issues to developing new businesses. They can also encourage citizens to become more involved in the making of more effective social policy. Open data is increasingly seen as a key enabler in designing and implementing knowledge-based solutions for more sustainable urban development. For these reasons, as well as others, OGD (Open Government Data) portals are already being implemented in many countries. However, if smart cities are to maximise their potential, OGD portals must be understood, accepted and—crucially—used by the public. The extent to which this is the case is not clear, as there have been few studies that have specifically examined the impact of open data in a smart city context. This is particularly true in the GCC (Gulf Cooperation Council) countries. This research uses a mixed methods (questionnaires and interviews) approach to examine this issue by carrying out a comparative study of the use of portals across the region and, therefore, whether these countries are making optimum use of open data. An existing evaluation framework was used with a group of evaluators representing professional users who are not experienced in using data portals. The findings of the research suggest that these countries are not yet realising the full potential of their portals, and more effective support for the transition to smart cities could be achieved with fuller and better cross-national cooperation.

Hacking Corporate Smart Cities Under COVID-19: Towards a Smart Governance Approach

ABSTRACT The COVID-19 pandemic has imposed huge challenges on smart cities, requiring a reimagining and transformation of their governance structures. This viewpoint argues that a smart governance approach should be applied to remodel the uniform, often technocratic and corporate-led way of coping with COVID-19 in the smart city context. There is a need to develop more technology-enabled collaborative actions across sectors and among various actors to recover better from the pandemic. A far-sighted view is also needed to build citizen-centric open governance capacities—the emergent character of mass participation in cities—for readiness, responsiveness, and long-term resilience. The need for a robust communication policy is highlighted to transmit well-timed and critical information to a range of actors interested in smart city transformation.

Multiple pathways to solve urban challenges: A shared portfolio approach towards smart city development

Municipalities often collaborate with other stakeholders in smart city projects to develop and implement technological innovations to address complex urban issues. We propose the shared portfolio approach as an alternative way of collaborating , because we have identified possible limitations when the commonly used single-project approach is adopted in complex contexts, such as the smart city context. The portfolio approach enhances flexibility, an embedded focus and cross-project learning, because partners work on multiple projects – either in parallel or in succession – to develop multiple solutions to a specific problem. An in-depth case study is used to illustrate how the shared portfolio approach works. In practice, these insights can be used by public bodies who aim to collaborate in smart city development or by partners who work on smart city projects and wish to continue their collaboration in a portfolio setting. Conceptually, our paper develops a connection between cross-sector partnership literature and smart city literature by revealing how the shared portfolio approach could be an effective way to deal with the complexities of innovation in the smart city context.

Built Environment Cybersecurity: Development and Validation of a Semantically Defined Access Management Framework on a University Case Study

To achieve the potential of smart cities, there is a strong requirement to use a set of useful, but still accessible services within smart city systems. Interoperability challenges and roadblocks for software developers and integrators are well-known consequences of fragmented semantics across different contexts. Furthermore, in the smart city context, there is a need to ensure the security and identity of real-world services operating on this data through the adoption of access control principles (authorization and authentication). The use of ontologies to unify the diverse semantics of multiple domains is one strategy that has had considerable success in the past. This paper describes an access management ontology in smart cities developed to enable the interoperability of physical built environment assets, sensing and actuation devices and current built environment services with existing security standards, digital twin and Building Information Model (BIM) datasets. It also provides interoperability between user interfaces and the actors who use them in the context of establishing an access management in smart cities framework for the built environment. This has been validated through its implementation in the Cardiff Urban Sustainability Platform (CUSP), deployed to manage a variety of smart services on a university campus. This validation has successfully shown the ability of the ontology to function as intended in the context of a digital twin, thereby offering single sign-on and suitable access control.

Research trends in the application of big data in smart cities—A literature review

AbstractIn this study, we review articles published in academic journals. in the last 5 years at the intersection of big data and the smart city context. Based on a dataset of 192 articles, we use content analysis to identify recent trends and future research directions. The most influential research areas identified include using big data analytics, electric vehicle integration, and citizen‐centric big data, while the most recent research area that emerged is green space. Our results highlight how big data can influence eight different dimensions of smart cities, with smart mobility attracting the most attention from researchers in the application of big data in smart cities. In contrast, smart people and smart economy are the least explored dimensions from this perspective.

Evaluating Collaborative Public–Private Partnerships

Problem, research strategy, and findings Public–private partnership models designed to facilitate greater collaboration have become increasingly popular. Scholarship on these partnerships has shown that they rely less on contracts and more on trust between partners, engage private partners early to allow for participation in project visioning, and prioritize shared decision making. However, there is a need to further define collaborative partnerships and distinguish them from more conventional models. In addition, research into the impacts of collaborative partnerships within planning processes is limited, and additional insights into their administrative structures, management, and internal dynamics is needed. I respond to these gaps by analyzing the collaborative co-creation public–private partnership formed to plan a smart city in the Quayside district of Toronto (Canada). Drawing on interviews (N = 35), participant observation, and document analysis, I found that those qualities of the Quayside partnership typical of collaborative partnership models reduced governmental oversight, facilitated conflicts of interest, and afforded the private partner substantial power. The challenges precipitated by the partnership structure were amplified through its application in a smart city context, where the private partner was a technology corporation with expansive resources and ambitions. Based on these findings, I argue that collaborative partnerships pose significant risks of privatizing planning processes and that these risks are heightened when asymmetries between partners are particularly stark. Takeaway for practice Planners should not allow a desire for greater collaboration to overshadow the necessity of divisions between public and private roles, because tension between the two is vital to partnership success. If seeking deeper collaboration, planners should ensure that responsibilities are clearly detailed in contracts to avoid ambiguities or conflicts of interest. This is especially important in projects where power differentials between partners are too significant to rely solely on trust instead of contracts.

Emerging technological innovation in Gaza Strip municipalities: an entrepreneurial approach

To boost corporate efficiency in both the public and private sectors, innovation is fundamental. Efficient technological transfer and the role of public–private sector collaboration play a major role in the modern growth of knowledge-based economies. As a public service organization, municipalities normally coordinate with all partners to draw up strategies and use them in communities. A new vision is needed for the Gaza Strip municipalities, where all public and private stakeholders work together to co-design and co-develop new cutting-edge products and services aimed at generating shared value through entrepreneurial behavior. However, concrete examples of smart city projects revealed that municipalities often do not have the necessary capabilities as well as innovative approaches to collaborate with start-ups and other stakeholders’ ecosystems. So, this paper aims to analyze innovation in the municipal sector shedding light on the barriers and challenges that municipalities in the Gaza Strip face in smart city development. This study uses primary data gathered from various stakeholders through focus groups, semi-structured interviews, and webinars to conclude how the Gaza Strip municipalities can work to address challenges in the smart city context; and to explore how to promote an ecosystem of entrepreneurship and innovation to support the adoption of new hi-tech technologies in the municipal sector. The Gaza Strip municipalities need to offer the necessary conditions for entrepreneurial talents who can bring their creative mindset, and technological experiences to the table, making it possible to build the best teams to solve any challenge. The research also concluded that Open Innovation Platforms can be seen as an important tool for enabling start-ups and researchers to develop innovative Hi-Tech solutions.

Engaging citizens in land use policy in the smart city context

In the otherwise rich debate on smart cities, the intersection of land use and spatial planning, on the one hand, their social and societal implications, on the other hand, and finally, the potential inherent in ICT-enhanced tools underlying the functioning, operation, management, and administration of smart city, remain overlooked. Considering that, due to multiple environmental and societal pressures, land use, has become more political than ever, whereby pleas for open and transparent methods of coordination, deliberation, and participation proliferate, it is imperative that citizens are involved in the land use policymaking at the level of the city and the neighborhoods. Even if substantial literature addressing each of these issues exists, approaches that would fit these multiple pieces of the puzzle together in one equation are still missing. By elaborating on the findings of an online survey (N = 5752) involving the citizens of a smart city (Lublin, Poland), this paper responds to this imperative. The findings suggest that utilizing insights from e-participation tools and surveys, in combination with more traditional instruments, such as meetings, debates, and workshops, may significantly improve land use policies in (smart) cities.

The Impact of a Special Economic Zone Management on the Development of Modern Sectors and Technologies in a Polish Metropolis: The Smart City Context

The development of the high-tech sector has so far been studied within the cities, leaving their functioning within the special economic zones in the context of metropolitan belonging unexplored. The main purpose of the article is to determine whether the economic zone has a positive impact on the economic development of cities, which in the context of this research, has been operationalized with the use of computer-aided systems. The authors purposefully choose a Metropolis GZM, Poland (GZM), and Katowice Special Economic Zone (KSEZ). The importance of the high-tech sector in the GZM depends on the development of business in the region. Innovative specializations of cities located in the KSEZ were examined from the point of view of their perception by users of these new technologies, i.e., city residents. The research was conducted among over 1000 inhabitants of 16 cities in the GZM Metropolis. The results show correlations between the existence of modern businesses in metropolitan cities and their development of useful technologies, perceived from the perspective of residents.

Pedestrian Detection with LiDAR Technology in Smart-City Deployments–Challenges and Recommendations

This paper describes a real case implementation of an automatic pedestrian-detection solution, implemented in the city of Aveiro, Portugal, using affordable LiDAR technology and open, publicly available, pedestrian-detection frameworks based on machine-learning algorithms. The presented solution makes it possible to anonymously identify pedestrians, and extract associated information such as position, walking velocity and direction in certain areas of interest such as pedestrian crossings or other points of interest in a smart-city context. All data computation (3D point-cloud processing) is performed at edge nodes, consisting of NVIDIA Jetson Nano and Xavier platforms, which ingest 3D point clouds from Velodyne VLP-16 LiDARs. High-performance real-time computation is possible at these edge nodes through CUDA-enabled GPU-accelerated computations. The MQTT protocol is used to interconnect publishers (edge nodes) with consumers (the smart-city platform). The results show that using currently affordable LiDAR sensors in a smart-city context, despite the advertising characteristics referring to having a range of up to 100 m, presents great challenges for the automatic detection of objects at these distances. The authors were able to efficiently detect pedestrians up to 15 m away, depending on the sensor height and tilt. Based on the implementation challenges, the authors present usage recommendations to get the most out of the used technologies.

An Empirical Study of the Factors Influencing Users’ Intention to Use Automotive AR-HUD

An automotive augmented reality head-up display (AR-HUD) can provide an immersive experience for users and is anticipated to become one of the ultimate terminals for human–machine interaction in future intelligent vehicles within the context of smart cities. However, the majority of the current research on AR-HUD is focused on technological implementation and interaction interface design, and there are relatively few studies that examine the psychological factors that may influence the public’s willingness to utilize this technology. Based on the theory of reasoned action (TRA) and the unified theory of acceptance and use of technology (UTAUT), this study constructs a model of users’ willingness to use automotive AR-HUD involving both cognitive and social factors. The study recruited 377 participants and collected data on users’ effort expectation, performance expectation, social influence, perceived trust, personal innovation, and AR-HUD usage intention through a questionnaire. It was found that users’ effort expectation influenced their intention to use AR-HUD through the mediating role of performance expectation. Social influence had an impact on users’ AR-HUD usage intention through the mediating role of perceived trust, and personal innovation moderated the strength of the role of social influence on perceived trust as a moderating variable.

Enhanced incentive schemes for volunteers to distribute surplus food in smart cities

Food wastage is a major problem in today’s world and the distribution of food surplus is undoubtedly one of the leading solutions to the problem. Surplus distribution is widely practised across the globe and there are several communities for the same as well. However, the success of these movements are determined by the active participation of volunteers. In addition, volunteer availability is an issue that is dependent on several different factors. An incentive module for the volunteers can normalize the availability of the volunteers. Such incentive modules are prone to identity duplication attacks and the implemented solutions do not really encourage volunteer hierarchical structures. In this paper, an incentive module that resists identity duplication and promotes the hierarchical structure between volunteers is presented. In addition, an improved matching module to match the food donors to the receivers utilizing the available volunteers optimally is also proposed. For the simulation, we have used real data taken from a real life smart city context, namely, we have used the OPEN DATA BARCELONA at https://opendata-ajuntament.barcelona.cat/data/en/dataset/est-cadastre-carrecs-us and cast it to our simulation settings using Python libraries.

How smart is mobility in smart cities? An analysis of citizens' value perceptions through ICT applications

Urban mobility plays a key role in any modern society. The advent of digital platforms and dedicated mobile apps, as well as new business models based on the concept of access over ownership and sharing economy (sharing mobility and Mobility as a Service), promises to reshape this sector. It will facilitate and speed up the diffusion of more sustainable and efficient means of transportation based on an intermodal mobility management perspective. The main goal of this paper is to examine the current state of smart mobility together with those factors that may influence the extent of modern sharing mobility proliferation and penetration through ICT applications and social media. The authors applied the content analysis using a sample of more than 1000 citizens' and visitors' reviews published on the official digital platforms of the smart city of Milan. The paper includes a comparison with data drawn from the public urban mobility services users. Based on the nodes resulting from the content analysis, the STEEP method was adopted in order to apply a more complex perspective concerning social, technological, environmental, economic and political issues. This strategic analytical tool was combined with the SWOT analysis dimensions to provide a comprehensive practical contribution to modern municipal smart mobility management systems. The results highlight the need for both smart mobility solutions suppliers and institutions to properly understand and communicate how digital services can be implemented across different users' touchpoints and communication channels to increase the value-added provided to citizens and visitors alike. • Urban mobility services assessment in a smart city context • Analyses of digital platforms and mobile apps for sharing mobility services • Content analysis and Network analysis of the reviews of mobility services' users • Multilevel approach based on the integration of STEEP and SWOT analyses • Theoretical contribution and strategic insights for policy-makers

Innovative platforms for more compliant Smart Cities: A case study

The quality of public services provided to citizens through information and communication technologies has emerged as one of the key points of public administration reform. In Italy, many legislative measures have triggered a virtuous circle of eGovernment that has achieved limited results in adopting new technologies by citizens and businesses [1]. This paper sets out to explore whether the design of an IT platform operating in a smart city context may increase the quality of services provided to citizens. Based on a case study methodology, the research examines the process of revitalization and smartification of a city, seen from the stakeholders’ perspective such as Government, Citizens and Tourists [2]. The paper is original in its examination of the Tely platform enabled by data obtained from the technology developer. It turned out that the platform has the potential to increase the quality of services provided to citizens and promote social integration in an area with a significant migratory population. However, the limitations of a single case study in a specific research context, such as a small town, are acknowledged and further research is needed to fully understand the implications of smart city initiatives and their effective implementation in different contexts.

Crop Type Prediction: A Statistical and Machine Learning Approach

Farmers’ ability to accurately anticipate crop type is critical to global food production and sustainable smart cities since timely decisions on imports and exports, based on precise forecasts, are crucial to the country’s food security. In India, agriculture and allied sectors constitute the country’s primary source of revenue. Seventy percent of the country’s rural residents are small or marginal agriculture producers. Cereal crops such as rice, wheat, and other pulses make up the bulk of India’s food supply. Regarding cultivation, climate and soil conditions play a vital role. Information is of utmost need in predicting which crop is best suited given the soil and climate. This paper provides a statistical look at the features and indicates the best crop type on the given features in an Indian smart city context. Machine learning algorithms like k-NN, SVM, RF, and GB trees are examined for crop-type prediction. Building an accurate crop forecast system required high accuracy, and the GB tree technique provided that. It outperforms all the classification algorithms with an accuracy of 99.11% and an F1-score of 99.20%.

BIG TRAJECTORY DATA: A DISTRIBUTED COMPUTING PERSPECTIVE

Abstract. Trajectory data constitute location of objects at specified time intervals. The continuous availability of GNSS signals, or discrete availability of sensor systems such as license plate recognition cameras are used to generate trajectory data. Consequently, in a smart city context, big trajectory data are being generated on a daily basis. The analysis of big trajectory data entails the use of a distributed environment to conduct analysis, and at least two data sources. The literature review conducted in this paper shows that the two Vs of big data, Volume and Variety, may not be satisfied since researchers usually rely on a centralised computing environment, and analyse data coming from a single data source. Out of the 17 papers published from 2020 in Scopus, only five of them relied on a distributed computing environment, and two of them utilised more than one data source.

Understanding citizen perceptions of AI in the smart city

Artificial intelligence (AI) is embedded in a wide variety of Smart City applications and infrastructures, often without the citizens being aware of the nature of their “intelligence”. AI can affect citizens’ lives concretely, and thus, there may be uncertainty, concerns, or even fears related to AI. To build acceptable futures of Smart Cities with AI-enabled functionalities, the Human-Centered AI (HCAI) approach offers a relevant framework for understanding citizen perceptions. However, only a few studies have focused on clarifying the citizen perceptions of AI in the context of smart city research. To address this gap, we conducted a two-phased study. In the pre-study, we explored citizen perceptions and experiences of AI with a short survey (N = 91). Second, scenario-based interviews (N = 7) were utilized to gain in-depth insights of citizen perceptions of AI in the Smart City context. Five central themes were recognized: (1) I don’t like them monitoring me, (2) I want maximum gain for minimum effort, (3) I don’t want AI to mimic people, (4) I’ll avoid using AI if I consider the risk too high, and (5) I don’t need to be concerned about AI. These offer an idea of human-centered requirements worth considering while designing AI applications for future Smart Cities.

An emergent taxonomy of boundary spanning in the smart city context – The case of smart Dublin

Smart cities emphasize the use of advanced technology to deliver better services to and improve the well-being of their residents. Since the administrative authorities that manage cities often lack the knowledge and skills needed to transform their operations in this way, smart city initiatives usually involve a complex set of actors, from local urban authorities and their technical departments to small and large IT firms, academics, and civic organizations, as well as individual citizens. Mediating organizations are often set up to coordinate and manage such interactions. However, little is known about the roles and activities of such bodies. Using data from the Dublin smart city projects, this study draws on the concept of boundary spanning to develop a taxonomy of the work of such intermediaries. Divided into technical, political, social, and cultural domains, the study demonstrates the critical role of the work done by such bodies in enhancing collaboration among and the participation of a diverse group of citizens, IT and digital strategy departments of local authorities, universities and local/international IT companies (e.g., Google, Facebook or Airbnb), leading to a bottom-up governance style of leading smart city initiatives and projects.

Blockchain applications in smart sustainable city context—A systematic mapping study

The advancement in blockchain applications in the smart sustainable city infrastructure is evaluated in this paper through a comprehensive mapping review. The evaluation is carried out by posing four research questions that address current developments in blockchain technology in the context of smart cities and point out areas where additional study is needed. This study also includes a scoping of blockchain applications in a smart city context to highlight the obstacles to incorporating blockchain technology into smart city infrastructure. Finally, some suggestions for overcoming the problems of incorporating blockchain technology with smart city infrastructure are offered. This research will help researchers and policymakers gain a better understanding of blockchain applications in smart cities.

Building Heating and Cooling Load Prediction Using Ensemble Machine Learning Model.

Building energy consumption prediction has become an important research problem within the context of sustainable homes and smart cities. Data-driven approaches have been regarded as the most suitable for integration into smart houses. With the wide deployment of IoT sensors, the data generated from these sensors can be used for modeling and forecasting energy consumption patterns. Existing studies lag in prediction accuracy and various attributes of buildings are not very well studied. This study follows a data-driven approach in this regard. The novelty of the paper lies in the fact that an ensemble model is proposed, which provides higher performance regarding cooling and heating load prediction. Moreover, the influence of different features on heating and cooling load is investigated. Experiments are performed by considering different features such as glazing area, orientation, height, relative compactness, roof area, surface area, and wall area. Results indicate that relative compactness, surface area, and wall area play a significant role in selecting the appropriate cooling and heating load for a building. The proposed model achieves 0.999 for heating load prediction and 0.997 for cooling load prediction, which is superior to existing state-of-the-art models. The precise prediction of heating and cooling load, can help engineers design energy-efficient buildings, especially in the context of future smart homes.