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Smart Cities
Number of Followers: 3  

  This is an Open Access Journal Open Access journal
ISSN (Online) 2624-6511
Published by MDPI Homepage  [258 journals]
  • Smart Cities, Vol. 6, Pages 3032-3059: An Assessment Model for Sustainable
           Cities Using Crowdsourced Data Based on General System Theory: A Design
           Science Methodology Approach

    • Authors: Usman Ependi, Adian Fatchur Rochim, Adi Wibowo
      First page: 3032
      Abstract: In the quest to understand urban ecosystems, traditional evaluation techniques often fall short due to incompatible data sources and the absence of comprehensive, real-time data. However, with the recent surge in the availability of crowdsourced data, a dynamic view of urban systems has emerged. Recognizing the value of these data, this study illustrates how these data can bridge gaps in understanding urban interactions. Furthermore, the role of urban planners is crucial in harnessing these data effectively, ensuring that derived insights align with the practical needs of urban development. Employing the Design Science Methodology, the research study presents an assessment model grounded in the principles of the city ecosystem, drawing from the General System Theory for Smart Cities. The model is structured across three dimensions and incorporates twelve indicators. By leveraging crowdsourced data, the study offers invaluable insights for urban planners, researchers, and other professionals. This comprehensive approach holds the potential to revolutionize city sustainability assessments, deepening the grasp of intricate urban ecosystems and paving the way for more resilient future cities.
      Citation: Smart Cities
      PubDate: 2023-10-26
      DOI: 10.3390/smartcities6060136
      Issue No: Vol. 6, No. 6 (2023)
       
  • Smart Cities, Vol. 6, Pages 3060-3092: PC-ILP: A Fast and Intuitive Method
           to Place Electric Vehicle Charging Stations in Smart Cities

    • Authors: Mehul Bose, Bivas Ranjan Dutta, Nivedita Shrivastava, Smruti R. Sarangi
      First page: 3060
      Abstract: The widespread use of electric vehicles necessitates meticulous planning for the placement of charging stations (CSs) in already crowded cities so that they can efficiently meet the charging demand while adhering to various real-world constraints such as the total budget, queuing time, electrical regulations, etc. Many classical and metaheuristic-based approaches provide good solutions, but they are not intuitive, and they do not scale well for large cities and complex constraints. Many classical solution techniques often require prohibitive amounts of memory and their solutions are not easily explainable. We analyzed the layouts of the 50 most populous cities of the world and observed that any city can be represented as a composition of five basic primitive shapes (stretched to different extents). Based on this insight, we use results from classical topology to design a new charging station placement algorithm. The first step is a topological clustering algorithm to partition a large city into small clusters and then use precomputed solutions for each basic shape to arrive at a solution for each cluster. These cluster-level solutions are very intuitive and explainable. Then, the next step is to combine the small solutions to arrive at a full solution to the problem. Here, we use a surrogate function and repair-based technique to fix any resultant constraint violations (after all the solutions are combined). The third step is optional, where we show that the second step can be extended to incorporate complex constraints and secondary objective functions. Along with creating a full software suite, we perform an extensive evaluation of the top 50 cities and demonstrate that our method is not only 30 times faster but its solution quality is also 36.62% better than the gold standard in this area—an integer linear programming (ILP) approach with a practical timeout limit.
      Citation: Smart Cities
      PubDate: 2023-11-15
      DOI: 10.3390/smartcities6060137
      Issue No: Vol. 6, No. 6 (2023)
       
  • Smart Cities, Vol. 6, Pages 3093-3111: Assessing Factors Influencing
           Citizens’ Behavioral Intention towards Smart City Living

    • Authors: Aik Wirsbinna, Libor Grega, Michael Juenger
      First page: 3093
      Abstract: The adoption and results achieved by “smart city” projects heavily rely on citizens’ acceptance and behavioral intention to embrace smart city living. Understanding the factors influencing citizens’ behavioral intention towards smart city living is crucial for the effective development and rollout of smart city initiatives. This research paper aims to assess the factors influencing citizens’ behavioral intention towards smart city living using quantitative research methods. Through a comprehensive literature review, an ideation structure was developed, integrating theoretical perspectives from the Technology Acceptance Model (TAM). The structure encompasses key variables such as perceived utility, convenience of use, engagement, trialability, observability, interoperability, willingness, and propensity to embrace smart city lifestyles. A quantitative methodological stance was employed to gather information from a statistically significant subset of citizens residing in urban areas in developed countries. A structured questionnaire, based on the theoretical framework, was formulated and distributed to the participants. Statistical analysis techniques, including structural equation modeling, were used for investigating connections between identified factors and citizens’ behavioral intention towards smart city living. Preliminary findings indicate that behavioral intention towards smart city living strongly depends on attitude and perceived usefulness. By addressing these factors, smart cities can foster greater citizen engagement, participation, and ultimately, the successful realization of smart city living.
      Citation: Smart Cities
      PubDate: 2023-11-16
      DOI: 10.3390/smartcities6060138
      Issue No: Vol. 6, No. 6 (2023)
       
  • Smart Cities, Vol. 6, Pages 3112-3137: An Urban Acoustic Rainfall
           Estimation Technique Using a CNN Inversion Approach for Potential Smart
           City Applications

    • Authors: Mohammed I. I. Alkhatib, Amin Talei, Tak Kwin Chang, Valentijn R. N. Pauwels, Ming Fai Chow
      First page: 3112
      Abstract: The need for robust rainfall estimation has increased with more frequent and intense floods due to human-induced land use and climate change, especially in urban areas. Besides the existing rainfall measurement systems, citizen science can offer unconventional methods to provide complementary rainfall data for enhancing spatial and temporal data coverage. This demand for accurate rainfall data is particularly crucial in the context of smart city innovations, where real-time weather information is essential for effective urban planning, flood management, and environmental sustainability. Therefore, this study provides proof-of-concept for a novel method of estimating rainfall intensity using its recorded audio in an urban area, which can be incorporated into a smart city as part of its real-time weather forecasting system. This study proposes a convolutional neural network (CNN) inversion model for acoustic rainfall intensity estimation. The developed CNN rainfall sensing model showed a significant improvement in performance over the traditional approach, which relies on the loudness feature as an input, especially for simulating rainfall intensities above 60 mm/h. Also, a CNN-based denoising framework was developed to attenuate unwanted noises in rainfall recordings, which achieved up to 98% accuracy on the validation and testing datasets. This study and its promising results are a step towards developing an acoustic rainfall sensing tool for citizen-science applications in smart cities. However, further investigation is necessary to upgrade this proof-of-concept for practical applications.
      Citation: Smart Cities
      PubDate: 2023-11-16
      DOI: 10.3390/smartcities6060139
      Issue No: Vol. 6, No. 6 (2023)
       
  • Smart Cities, Vol. 6, Pages 3138-3160: Unveiling the Socio-Economic
           Fragility of a Major Urban Touristic Destination through Open Data and
           Airbnb Data: The Case Study of Bologna, Italy

    • Authors: Alessandro Nalin, Leonardo Cameli, Margherita Pazzini, Andrea Simone, Valeria Vignali, Claudio Lantieri
      First page: 3138
      Abstract: In the last decades, tourism in urban areas has been constantly increasing. The need for short-term accommodations has been coupled with the emergence of internet-based services, which makes it easier to match demand (i.e., tourists) and supply (i.e., housing). As a new mass tourist destination, Bologna, Italy, has been experiencing tensions between tourists and long-, mid-, or short-term renters. The possibility of easy profits for lessees has led to an increase in such housing, which can be rented out either for touristic reasons or not. This paper aims to unveil the contribution of short-term rental accommodations in distorting the real estate market and conditioning social and economic inequalities. To do this, multiple linear regression analyses (MLR) were performed between accommodation density, real estate market information, and indicators about social, economic, and demographic vulnerability and fragility. Analyses were based on official open data and datasets from a major web-based hospitality exchange platform, i.e., Airbnb, able to provide information on registered accommodations, e.g., type, characteristics (e.g., number of bedrooms and average rating), and location. Outputs of the analyses reveal the role of Airbnb in both rental market and social, economic, and demographic vulnerability and fragility and, hence, can be a solid tool for public policies, both housing- and tourism-related.
      Citation: Smart Cities
      PubDate: 2023-11-20
      DOI: 10.3390/smartcities6060140
      Issue No: Vol. 6, No. 6 (2023)
       
  • Smart Cities, Vol. 6, Pages 3161-3191: Optimal Dispatch Strategy for
           Electric Vehicles in V2G Applications

    • Authors: Ali M. Eltamaly
      First page: 3161
      Abstract: The overutilization of electric vehicles (EVs) has the potential to result in significant challenges regarding the reliability, contingency, and standby capabilities of traditional power systems. The utilization of renewable energy distributed generator (REDG) presents a potential solution to address these issues. By incorporating REDG, the reliance of EV charging power on conventional energy sources can be diminished, resulting in significant reductions in transmission losses and enhanced capacity within the traditional power system. The effective management of the REDG necessitates intelligent coordination between the available generation capacity of the REDG and the charging and discharging power of EVs. Furthermore, the utilization of EVs as a means of energy storage is facilitated through the integration of vehicle-to-grid (V2G) technology. Despite the importance of the V2G technology for EV owners and electric utility, it still has a slow progress due to the distrust of the revenue model that can encourage the EV owners and the electric utility as well to participate in V2G programs. This study presents a new wear model that aims to precisely assess the wear cost of EV batteries, resulting from their involvement in V2G activities. The proposed model seeks to provide EV owners with a precise understanding of the potential revenue they might obtain from participating in V2G programs, hence encouraging their active engagement in such initiatives. Various EV battery wear models are employed and compared. Additionally, this study introduces a novel method for optimal charging scheduling, which aims to effectively manage the charging and discharging patterns of EVs by utilizing a day-ahead pricing technique. This study presents a novel approach, namely, the gradual reduction of swarm size with the grey wolf optimization (GRSS-GWO) algorithm, for determining the optimal hourly charging/discharging power with short convergence time and the highest accuracy based on maximizing the profit of EV owners.
      Citation: Smart Cities
      PubDate: 2023-11-20
      DOI: 10.3390/smartcities6060141
      Issue No: Vol. 6, No. 6 (2023)
       
  • Smart Cities, Vol. 6, Pages 3192-3224: Secure Hydrogen Production Analysis
           and Prediction Based on Blockchain Service Framework for Intelligent Power
           Management System

    • Authors: Harun Jamil, Faiza Qayyum, Naeem Iqbal, Murad Ali Khan, Syed Shehryar Ali Naqvi, Salabat Khan, Do Hyeun Kim
      First page: 3192
      Abstract: The rapid adoption of hydrogen as an eco-friendly energy source has necessitated the development of intelligent power management systems capable of efficiently utilizing hydrogen resources. However, guaranteeing the security and integrity of hydrogen-related data has become a significant challenge. This paper proposes a pioneering approach to ensure secure hydrogen data analysis by integrating blockchain technology, enhancing trust, transparency, and privacy in handling hydrogen-related information. Combining blockchain with intelligent power management systems makes the efficient utilization of hydrogen resources feasible. Using smart contracts and distributed ledger technology facilitates secure data analysis (SDA), real-time monitoring, prediction, and optimization of hydrogen-based power systems. The effectiveness and performance of the proposed approach are demonstrated through comprehensive case studies and simulations. Notably, our prediction models, including ABiLSTM, ALSTM, and ARNN, consistently delivered high accuracy with MAE values of approximately 0.154, 0.151, and 0.151, respectively, enhancing the security and efficiency of hydrogen consumption forecasts. The blockchain-based solution offers enhanced security, integrity, and privacy for hydrogen data analysis, thus advancing clean and sustainable energy systems. Additionally, the research identifies existing challenges and outlines future directions for further enhancing the proposed system. This study adds to the growing body of research on blockchain applications in the energy sector, specifically on secure hydrogen data analysis and intelligent power management systems.
      Citation: Smart Cities
      PubDate: 2023-11-22
      DOI: 10.3390/smartcities6060142
      Issue No: Vol. 6, No. 6 (2023)
       
  • Smart Cities, Vol. 6, Pages 3225-3250: Enhancing Urban Sustainability:
           Unravelling Carbon Footprint Reduction in Smart Cities through Modern
           Supply-Chain Measures

    • Authors: Seyed Behbood Issa Zadeh, Claudia Lizette Garay-Rondero
      First page: 3225
      Abstract: The worldwide Sustainable Development Goals (SDGs) for smart cities and communities focus significant attention on air quality and climate change. Technology and management can reduce fossil fuel dependence in smart cities’ energy supply chains (SC). A sustainable smart city and reduced carbon emissions require coordinated technology and management with appropriate infrastructure. A systematic review of smart city SC management literature that reduces the carbon footprint (C.F) inspired this study. The study shows how each attribute reduces greenhouse gas (GHG) emissions. The Introduction highlights the subject matter and principal goal, which is to investigate how SC management strategies could assist smart cities in lowering their C.F. The Methods and Materials section provides a succinct description of the refining process in Systematic Reviews and Meta-Analyses in Scoping Reviews (PRISMA-ScR) relevant to C.F mitigation in smart city (SC) management. Significant works are described in the Results and Findings section, which exposes how smart cities and SC measurements reduce C.F. The Discussion section examines and scientifically debates the research findings. The Conclusion provides a scientific analysis based on the presented insights and features to enhance how policies must be coordinated to achieve the goal of this research study in a comprehensive way. Furthermore, it provides suggestions for practitioners and governments, and proposals for future research. The main contribution of this paper is conducting and proposing a framework for a better understanding of how the novel digital SCs, their components, and their management practices can help smart cities reduce their C.F.
      Citation: Smart Cities
      PubDate: 2023-11-23
      DOI: 10.3390/smartcities6060143
      Issue No: Vol. 6, No. 6 (2023)
       
  • Smart Cities, Vol. 6, Pages 3251-3265: Usefulness of a Civic Engagement
           Scale for Research on Smart Cities: Measuring Attitudes and Behavior

    • Authors: Jiri Remr
      First page: 3251
      Abstract: Civic engagement plays a critical role in smart city innovation and urban development by encouraging active participation in civic activities such as volunteering, voting, community organizing, or advocacy, all of which contribute to the development of local communities. This study highlights the need to assess civic engagement in smart cities in order to improve the interactions between technology and society. The study assessed the reliability and validity of the Civic Engagement Scale (CES) in the Czech context. The results presented are based on a representative sample of 1366 respondents from the general population aged 15–74. The study included univariate statistics, tests of internal consistency, and principal component analysis. In addition, the study presents the results of confirmatory factor analysis (CFA) that was conducted to examine the fit of the proposed model to empirical data. The results indicate that the CES has excellent psychometric properties, including high internal consistency and favorable absolute and incremental indices. The Czech version of the CES can be considered a valid and reliable instrument. The findings suggest using CES to research and evaluate policy interventions aimed at developing digital platforms that enable citizens to easily participate in urban planning and smart city projects, community-driven smart city projects that ensure local needs and preferences are addressed, or implementing incentive programs for citizens.
      Citation: Smart Cities
      PubDate: 2023-11-23
      DOI: 10.3390/smartcities6060144
      Issue No: Vol. 6, No. 6 (2023)
       
  • Smart Cities, Vol. 6, Pages 3266-3296: Modelling Factors Influencing IoT
           Adoption: With a Focus on Agricultural Logistics Operations

    • Authors: Mohsen Rajabzadeh, Hajar Fatorachian
      First page: 3266
      Abstract: Purpose- In recent years, there has been a notable surge in the utilization of emerging technologies, notably the Internet of Things (IoT), within the realm of business operations. However, empirical evidence has underscored a disconcerting trend whereby a substantial majority, surpassing 70%, of IoT adoption initiatives falter when confronted with the rigors of real-world implementation. Given the profound implications of IoT in augmenting product quality, this study endeavors to scrutinize the extant body of knowledge concerning IoT integration within the domain of agricultural logistics operations. Furthermore, it aims to discern the pivotal determinants that exert influence over the successful assimilation of IoT within business operations, with particular emphasis on logistics. Design/Methodology/Approach- The research utilizes a thorough systematic review methodology coupled with a meta-synthesis approach. In order to identify and clarify the key factors that influence IoT implementation in logistics operations, the study is grounded in the Resource-Based View theory. It employs rigorous grounded theory coding procedures, supported by the analytical capabilities of MAXQDA software. Findings- The culmination of the meta-synthesis endeavor culminates in the conceptual representation of IoT adoption within the agricultural logistics domain. This representation is underpinned by the identification of three overarching macro categories/constructs, namely: (1) IoT Technology Adoption, encompassing facets such as IoT implementation requisites, ancillary technologies essential for IoT integration, impediments encountered in IoT implementation, and the multifaceted factors that influence IoT adoption; (2) IoT-Driven Logistics Management, encompassing IoT-based warehousing practices, governance-related considerations, and the environmental parameters entailed in IoT-enabled logistics; and (3) the Prospective Gains Encompassing IoT Deployment, incorporating the financial, economic, operational, and sociocultural ramifications ensuing from IoT integration. The findings underscore the imperative of comprehensively addressing these factors for the successful assimilation of IoT within agricultural logistics processes. Originality- The originality of this research study lies in its pioneering effort to proffer a conceptual framework that furnishes a comprehensive panorama of the determinants that underpin IoT adoption, thereby ensuring its efficacious implementation within the ambit of agricultural logistics operations. Practical Implications- The developed framework, by bestowing upon stakeholders an incisive comprehension of the multifaceted factors that steer IoT adoption, holds the potential to streamline the IoT integration process. Moreover, it affords an avenue for harnessing the full spectrum of IoT-derived benefits within the intricate milieu of agricultural logistics operations.
      Citation: Smart Cities
      PubDate: 2023-11-24
      DOI: 10.3390/smartcities6060145
      Issue No: Vol. 6, No. 6 (2023)
       
  • Smart Cities, Vol. 6, Pages 3297-3318: The Technology Adoption Model
           Canvas (TAMC): A Smart Framework to Guide the Advancement of
           Microbusinesses in Emerging Economies

    • Authors: Trevor Shenal Anton, Alexander Trupp, Marcus Lee Stephenson, Ka Leong Chong
      First page: 3297
      Abstract: The socioeconomic contribution of microbusinesses towards emerging economies is undeniable. However, numerous factors have broadened the gap between microbusinesses and their smartification. This conceptual study proposes the Technology Adoption Model Canvas (TAMC) based on theories such as the Unified Theory of Acceptance and Use of Technology (UTAUT2), Diffusion of Innovation (
      DOI ), and the Business Model Canvas (BMC) alongside four new/emerging variables, making it possible to understand technology adoption through both individual/cognitive and organizational/physical perspectives. The framework is developed for food service (FS) microbusinesses to facilitate their adaptability in current and future market conditions. Subsequently, we explain the development of the TAMC, including its significance, limitations, and avenues for future research. The proposed framework can provide a solution for FS microbusinesses towards a ‘smarter’ and more sustainable future. It further guides the evaluation of both microbusinesses’ readiness and the factors driving/impeding them towards/from adopting smart technology.
      Citation: Smart Cities
      PubDate: 2023-11-27
      Issue No: Vol. 6, No. 6 (2023)
       
  • Smart Cities, Vol. 6, Pages 3319-3336: Environmental Impact Analysis of
           Residential Energy Solutions in Latvian Single-Family Houses: A Lifecycle
           Perspective

    • Authors: Janis Kramens, Maksims Feofilovs, Edgars Vigants
      First page: 3319
      Abstract: This study aims to compare the technological solutions that can contribute to more sustainable energy use in the residential sector. Specifically, the goal of the study is to evaluate the environmental impact of different energy (heat and electricity) supply technologies applicable for an average size single-family building in Latvia, a country known for climatic condition characterized by cold winters with frequent snowfall. The study applies the lifecycle assessment methodology of ISO 14040 and the impact assessment method known as ReCiPe 2016 v1.1, which has not been used before for the scope addressed in the study in the context of single-family building energy supply technologies for climatic conditions in Latvia. Thus, the results of the study will provide new information for more sustainable energy solutions in this area of study. The technologies included in the defined scenarios are conventional boiler, electricity from the grid, Stirling engine, and solar photovoltaics (PV). The results of the lifecycle impact assessment for damage categories revealed that all scenarios have a high impact on human health due to fine particulate matter formation followed by global warming. Regarding the damage to the ecosystem, the terrestrial ecotoxicity category has highest impact, followed by global warming. Sensitivity analyses affirmed the model’s validity and also showed that the impacts of conventional systems were most sensitive to changes in electricity consumption, and therefore, the scenarios with electricity supply from a Stirling engine or PV can be considered a more robust solution under changing electricity demands from an environmental perspective.
      Citation: Smart Cities
      PubDate: 2023-11-27
      DOI: 10.3390/smartcities6060147
      Issue No: Vol. 6, No. 6 (2023)
       
  • Smart Cities, Vol. 6, Pages 3337-3358: A Quantitative Model of Innovation
           Readiness in Urban Mobility: A Comparative Study of Smart Cities in the
           EU, Eastern Asia, and USA Regions

    • Authors: Georgia Ayfantopoulou, Dimos Touloumidis, Ioannis Mallidis, Elpida Xenou
      First page: 3337
      Abstract: 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.
      Citation: Smart Cities
      PubDate: 2023-11-29
      DOI: 10.3390/smartcities6060148
      Issue No: Vol. 6, No. 6 (2023)
       
  • Smart Cities, Vol. 6, Pages 3359-3392: A Smart City Is a Safe City:
           

    • Authors: Magdalena Tutak, Jarosław Brodny
      First page: 3359
      Abstract: The concept of a smart city is based on the extensive multidimensional use of information and communication technologies to create the most favorable living conditions for residents and visitors. It is also important to create favorable conditions for economic activity while respecting the environment. One of the most important dimensions of this concept is security in the broadest sense, particularly that which concerns urban residents. This article addresses this subject by analyzing crime and determining the state of safety in 16 Polish provincial cities between 2013–2022. The measure of this state was chosen to be a set of indicators characterizing a number of registered criminal and economic offenses in the studied cities. On this basis, values of the indices of the dynamics of change for these offenses in individual cities in the analyzed period were determined. In the next stage, the number of offenses was compared to the number of residents of the cities under study and the indices of concentration for total offenses (LQT) and for individual types of offenses (LQn) were determined. Based on these results, the studied cities were divided into four concentration levels. Afterward, these results were used for a multi-criteria analysis of the safety of studied cities, which was carried out using the TOPSIS method. The calculated values of the safety index (Pi) formed the basis for creating a ranking and specifying security levels of studied cities. The results indicate a wide variation among the cities in terms of safety levels. Gdańsk, Bydgoszcz, Olsztyn and Zielona Góra were found to be the safest cities, while Szczecin was found to be the least safe. The methodology developed and the results obtained show the validity of conducting comparative research in areas relevant to the implementation of the smart cities concept. The knowledge gained can be used to build strategies and conduct policies with regard to improving safety in cities, especially those aspiring to be smart cities.
      Citation: Smart Cities
      PubDate: 2023-11-29
      DOI: 10.3390/smartcities6060149
      Issue No: Vol. 6, No. 6 (2023)
       
  • Smart Cities, Vol. 6, Pages 2176-2195: Availability and Adequacy of
           Facilities in 15 Minute Community Life Circle Located in Old and New
           Communities

    • Authors: Wei Wu, Prasanna Divigalpitiya
      First page: 2176
      Abstract: The 15 minute Community Life Circle (15 min-CLC) concept is an urban planning approach that aims to provide various daily services for citizens within a short distance. It has been widely adopted in China, especially in large cities. However, there is a lack of research on how to apply the 15 min-CLC concept in second-tier cities, which have high population densities and lower quality of life. This study chose Jinan City as a case study to explore the underdeveloped areas and facilities of 15 min-CLCs in rapidly developing and medium-size cities, called second-tier cities. First, it analyzed the distribution of facilities and residential POIs in old communities, new communities, and the whole city, to find out which types of facilities are missing at the community level. Second, it examined the relationship between facilities and population in each 15 min-CLC by using the Facility to Population Ratio (FPR), to evaluate the sufficiency of facilities to meet the daily needs of residents. Through the analysis of facility distribution and Facility to Population Ratio, our study found that old communities have all the required facility types within each 15 min-CLC, but they do not have enough number of facilities to support the population. At the same time, identified the underdeveloped regions and provided specific development directions for each 15 min-CLC. The FPR methodology developed in this study can be used to evaluate whether the existing facilities can meet the daily needs of residents in a certain region.
      Citation: Smart Cities
      PubDate: 2023-08-22
      DOI: 10.3390/smartcities6050100
      Issue No: Vol. 6, No. 5 (2023)
       
  • Smart Cities, Vol. 6, Pages 2196-2220: IoT Orchestration-Based Optimal
           Energy Cost Decision Mechanism with ESS Power Optimization for
           Peer-to-Peer Energy Trading in Nanogrid

    • Authors: Faiza Qayyum, Harun Jamil, Naeem Iqbal, Do-Hyeun Kim
      First page: 2196
      Abstract: The Internet of things has revolutionized various domains, such as healthcare and navigation systems, by introducing mission-critical capabilities. However, the untapped potential of IoT in the energy sector is a topic of contention. Shifting from traditional mission-critical electric smart grid systems to IoT-based orchestrated frameworks has become crucial to improve performance by leveraging IoT task orchestration technology. Energy trading cost and ESS power optimization have long been concerns in the scientific community. To address these issues, our proposed architecture consists of two primary modules: (1) a nanogrid energy trading cost and ESS power optimization strategy that utilizes particle swarm optimization (PSO), with two objective functions, and (2) an IoT-enabled task orchestration system designed for improved peer-to-peer nanogrid energy trading, incorporating virtual control through orchestration technology. We employ IoT sensors and Raspberry Pi-based Edge technology to virtually operate the entire nanogrid energy trading architecture, encompassing the aforementioned modules. IoT task orchestration automates the interaction between components for service execution, involving five main steps: task generation, device virtualization, task mapping, task scheduling, and task allocation and deployment. Evaluating the proposed model using a real dataset from nanogrid houses demonstrates the significant role of optimization in minimizing energy trading cost and optimizing ESS power utilization. Furthermore, the IoT orchestration results highlight the potential for virtual operation in significantly enhancing system performance.
      Citation: Smart Cities
      PubDate: 2023-08-22
      DOI: 10.3390/smartcities6050101
      Issue No: Vol. 6, No. 5 (2023)
       
  • Smart Cities, Vol. 6, Pages 2221-2244: Converged Security and Information
           Management System as a Tool for Smart City Infrastructure Resilience
           Assessment

    • Authors: Martin Hromada, David Rehak, Bartosz Skobiej, Martin Bajer
      First page: 2221
      Abstract: Current research on smart cities is primarily focused on the area of applicability of information and communication technologies. However, in the context of a multidisciplinary approach, it is also necessary to pay attention to the resilience and converged security of individual infrastructures. Converged security represents a particular security type based on a selected spectrum of certain convergent security types of, assuming the creation of a complementary whole. Considering the outputs of the analysis of security breaches manifestations, this kind of security makes it possible to detect emerging security breaches earlier (still in the symptom stage), thus providing a more efficient and targeted solution suitable for building smart city infrastructure. In its essence, the article refers to the practical application of the converged security theoretical principles presented in the publication to a functional sample, deployed and tested in practical conditions in context of selected smart city infrastructure protection and resilience. Considering the nature of the practical application, the convergence of a wider spectrum of smart security alarm systems in the resilience assessment context is defined. In the beginning, the general principles of security/safety and the need for their convergence are presented. In this context, the mathematical model called Converged Resilience Assessment (CRA) method is presented for better understanding. Subsequently, Physical Security Information Management (PSIM) and Security Information and Event Management (SIEM) systems are described as a technological concept that can be used for resilience assessment. The most beneficial part is the structural, process, and functional description of the Converged Security and Information Management System (CSIM) using the concept of smart security alarm systems converged security.
      Citation: Smart Cities
      PubDate: 2023-08-25
      DOI: 10.3390/smartcities6050102
      Issue No: Vol. 6, No. 5 (2023)
       
  • Smart Cities, Vol. 6, Pages 2245-2259: Visual Intelligence in Smart
           Cities: A Lightweight Deep Learning Model for Fire Detection in an IoT
           Environment

    • Authors: Muhammad Nadeem, Naqqash Dilshad, Norah Saleh Alghamdi, L. Minh Dang, Hyoung-Kyu Song, Junyoung Nam, Hyeonjoon Moon
      First page: 2245
      Abstract: The recognition of fire at its early stages and stopping it from causing socioeconomic and environmental disasters remains a demanding task. Despite the availability of convincing networks, there is a need to develop a lightweight network for resource-constraint devices rather than real-time fire detection in smart city contexts. To overcome this shortcoming, we presented a novel efficient lightweight network called FlameNet for fire detection in a smart city environment. Our proposed network works via two main steps: first, it detects the fire using the FlameNet; then, an alert is initiated and directed to the fire, medical, and rescue departments. Furthermore, we incorporate the MSA module to efficiently prioritize and enhance relevant fire-related prominent features for effective fire detection. The newly developed Ignited-Flames dataset is utilized to undertake a thorough analysis of several convolutional neural network (CNN) models. Additionally, the proposed FlameNet achieves 99.40% accuracy for fire detection. The empirical findings and analysis of multiple factors such as model accuracy, size, and processing time prove that the suggested model is suitable for fire detection.
      Citation: Smart Cities
      PubDate: 2023-08-28
      DOI: 10.3390/smartcities6050103
      Issue No: Vol. 6, No. 5 (2023)
       
  • Smart Cities, Vol. 6, Pages 2260-2281: Cumulatively Anticipative
           Car-Following Model with Enhanced Safety for Autonomous Vehicles in Mixed
           Driver Environments

    • Authors: Xinyi Yang, Hafiz Usman Ahemd, Ying Huang, Pan Lu
      First page: 2260
      Abstract: The contribution of autonomous vehicles to traffic is one of the key aspects of future ground transportation in smart cities. Autonomous vehicles are able to provide many benefits, but some benefits can only provide advantages if these vehicles comprise a large percent of on the road/driven vehicles, which may take decades. Until then, the robotic drivers in autonomous vehicles will share the same road system with human divers in a mixed-driver environment where the majority of road accidents for autonomous vehicles are associated with the operational inconsistency of human drivers. In this paper, a cumulatively anticipative car-following model (which considers cumulative influences from multiple preceding vehicles) is developed to potentially improve the safety of autonomous vehicles in mixed-driver environments that benefit from enhanced communication between the autonomous vehicles and other components in the transportation system. Through intensive simulations (200 simulations), this study comprehensively evaluates four models including the cumulative anticipative car-following model, the Wiedemann 99 model, adaptive cruise control, and the cooperative adaptive cruise control model. Across 10 scenarios and five speed limits (24.59–33.53 m/s), the cumulative anticipative car-following model consistently demonstrates superior conflict reduction, with average, maximum, and minimum conflict percentages ranging from 77.69% to 91.97% against the Wiedemann 99 model, 67.00% to 93.94% against the adaptive cruise control model, and 69.17% to 93.25% against the cooperative adaptive cruise control model. Notably, the cooperative adaptive cruise control model exhibits suboptimal performance, especially in mixed-driver settings. The cumulative anticipative car-following model also enhances vehicle mobility, reducing average stops by up to 93.54%, 91.74%, 92.04%, 88.60%, and 91.35% in comparison to the other three models at speeds of 24.59 m/s, 26.82 m/s, 29.06 m/s, 31.29 m/s, and 33.53 m/s. Overall, the cumulative anticipative car-following model holds significant potential for conflict reduction and traffic enhancement.
      Citation: Smart Cities
      PubDate: 2023-08-29
      DOI: 10.3390/smartcities6050104
      Issue No: Vol. 6, No. 5 (2023)
       
  • Smart Cities, Vol. 6, Pages 2282-2307: Understanding the Spatiotemporal
           Impacts of the Built Environment on Different Types of Metro Ridership: A
           Case Study in Wuhan, China

    • Authors: Hong Yang, Jiandong Peng, Yuanhang Zhang, Xue Luo, Xuexin Yan
      First page: 2282
      Abstract: As the backbone of passenger transportation in many large cities around the world, it is particularly important to explore the association between the built environment and metro ridership to promote the construction of smart cities. Although a large number of studies have explored the association between the built environment and metro ridership, they have rarely considered the spatial and temporal heterogeneity between metro ridership and the built environment. Based on metro smartcard data, this study used EM clustering to classify metro stations into five clusters based on the spatiotemporal travel characteristics of the ridership at metro stations. And the GBDT model in machine learning was used to explore the nonlinear association between the built environment and the ridership of different types of stations during four periods in a day (morning peak, noon, evening peak, and night). The results confirm the obvious spatial heterogeneity of the built environment’s impact on the ridership of different types of stations, as well as the obvious temporal heterogeneity of the impact on stations of the same type. In addition, almost all built environment factors have complex nonlinear effects on metro ridership and exhibit obvious threshold effects. It is worth noting that these findings will help the correct decisions be made in constructing land use measures that are compatible with metro functions in smart cities.
      Citation: Smart Cities
      PubDate: 2023-08-29
      DOI: 10.3390/smartcities6050105
      Issue No: Vol. 6, No. 5 (2023)
       
  • Smart Cities, Vol. 6, Pages 2308-2346: Optimizing Smart Campus Solutions:
           An Evidential Reasoning Decision Support Tool

    • Authors: Vian Ahmed, Mohamed Faisal Khatri, Zied Bahroun, Najihath Basheer
      First page: 2308
      Abstract: Smart technologies have become increasingly prevalent in various industries due to their potential for energy cost reduction, productivity gains, and sustainability. Smart campuses, which are educational institutions that implement smart technologies, have emerged as a specific application of these technologies. However, implementing available smart technologies is often not feasible due to various limitations, such as funding and cultural restrictions. In response, this study develops a mathematical decision-making tool based on the evidential reasoning (ER) approach and implemented in Python. The tool aims to assist universities in prioritizing smart campus solutions tailored to their specific needs. The research combines a comprehensive literature review with insights from stakeholder surveys to identify six principal objectives and four foundational technologies underpinning smart campus solutions. Additionally, six critical success factors and nine functional clusters of smart campus solutions are pinpointed, and evaluated through the ER approach. The developed decision-support tool underwent validation through various statistical tests and was found to be highly reliable, making it a generalized tool for worldwide use with different alternatives and attributes. The proposed tool provides universities with rankings and utilities to determine necessary smart applications based on inputs such as implementation cost, operation cost, maintenance cost, implementation duration, resource availability, and stakeholders’ perceived benefit.
      Citation: Smart Cities
      PubDate: 2023-09-01
      DOI: 10.3390/smartcities6050106
      Issue No: Vol. 6, No. 5 (2023)
       
  • Smart Cities, Vol. 6, Pages 2347-2366: Optimising Urban Freight Logistics
           Using Discrete-Event Simulation and Cluster Analysis: A Stochastic
           Two-Tier Hub-and-Spoke Architecture Approach

    • Authors: Zichong Lyu, Dirk Pons, Gilbert Palliparampil, Yilei Zhang
      First page: 2347
      Abstract: The transport of freight involves numerous intermediate steps, such as freight consolidation, truck allocation, and routing, all of which exhibit high day-to-day variability. On the delivery side, drivers usually cover specific geographic regions, also known as clusters, to optimise operational efficiency. A crucial aspect of this process is the effective allocation of resources to match business requirements. The discrete-event simulation (DES) technique excels in replicating intricate real-world operations and can integrate a multitude of stochastic variables, thereby enhancing its utility for decision making. The objective of this study is to formulate a routing architecture that integrates with a DES model to capture the variability in freight operations. This integration is intended to provide robust support for informed decision-making processes. A two-tier hub-and-spoke (H&S) architecture was proposed to simulate stochastic routing for the truck fleet, which provided insights into travel distance and time for cluster-based delivery. Real industry data were employed in geographic information systems (GISs) to apply the density-based spatial clustering of applications with noise (DBSCAN) clustering method to identify customer clusters and establish a truck plan based on freight demand and truck capacity. This clustering analysis and simulation approach can serve as a planning tool for freight logistics companies and distributors to optimise their resource utilisation and operational efficiency, and the findings may be applied to develop plans for new regions with customer locations and freight demands. The original contribution of this study is the integration of variable last-mile routing and an operations model for freight decision making.
      Citation: Smart Cities
      PubDate: 2023-09-04
      DOI: 10.3390/smartcities6050107
      Issue No: Vol. 6, No. 5 (2023)
       
  • Smart Cities, Vol. 6, Pages 2367-2396: Energy Saving Optimization of
           Commercial Complex Atrium Roof with Resilient Ventilation Using Machine
           Learning

    • Authors: Ao Xu, Ruinan Zhang, Jiahui Yu, Yu Dong
      First page: 2367
      Abstract: Carbon-neutral architectural design focuses on rationally utilizing the building’s surroundings to reduce its environmental impact. Resilient ventilation systems, developed according to the thermal comfort requirements of building energy-saving research, have few applications. We studied the Jin-an Shopping Mall in Harbin and established the middle point height (h), middle point horizontal location (d), roof angle (α), and exposure to floor ratio (k) as the morphological parameters of the atrium. Using computational fluid dynamics (CFD), the mean radiant temperature (MRT), and the universal thermal climate index calculations (UTCI), this program was set to switch off air conditioning when the resilient ventilation met the thermal comfort requirement to achieve energy savings. The energy-saving efficiency (U) was calculated based on the energy consumption of the original model, and U could reach 7.34–9.64% according to the simulation and prediction. This study provides methods and a theoretical basis for renovating other commercial complexes to improve comfort and control energy consumption.
      Citation: Smart Cities
      PubDate: 2023-09-11
      DOI: 10.3390/smartcities6050108
      Issue No: Vol. 6, No. 5 (2023)
       
  • Smart Cities, Vol. 6, Pages 2397-2429: Harnessing the Potential of the
           Metaverse and Artificial Intelligence for the Internet of City Things:
           Cost-Effective XReality and Synergistic AIoT Technologies

    • Authors: Simon Elias Bibri, Senthil Kumar Jagatheesaperumal
      First page: 2397
      Abstract: The Metaverse represents an always-on 3D network of virtual spaces, designed to facilitate social interaction, learning, collaboration, and a wide range of activities. This emerging computing platform originates from the dynamic convergence of Extended Reality (XR), Artificial Intelligence of Things (AIoT), and platform-mediated everyday life experiences in smart cities. However, the research community faces a pressing challenge in addressing the limitations posed by the resource constraints associated with XR-enabled IoT applications within the Internet of City Things (IoCT). Additionally, there is a limited understanding of the synergies of XR and AIoT technologies in the Metaverse and their implications for IoT applications within this framework. Therefore, this study provides a detailed overview of the literature on the potential applications, opportunities, and challenges pertaining to the deployment of XR technologies in IoT applications within the broader framework of IoCT. The primary focus is on navigating the challenges pertaining to the IoT applications powered by VR and AR as key components of MR in the Metaverse. This study also explores the emerging computing paradigm of AIoT and its synergistic interplay with XR technologies in the Metaverse and in relation to future IoT applications in the realm of IoCT. This study’s contributions encompass a comprehensive literature overview of XR technologies in IoT and IoCT, providing a valuable resource for researchers and practitioners. It identifies challenges and resource constraints, identifying areas that require further investigation. It fosters interdisciplinary insights into XR, IoT, AIoT, smart cities, and IoCT, bridging the gap between them. It offers innovation pathways for effective XR deployment in future IoT/AIoT applications within IoCT. Lastly, policymakers can strategize smart city development within IoCT. These contributions collectively advance our understanding of synergistic opportunities and complementary strengths of cutting-edge technologies for advancing the emerging paradigms of urban development.
      Citation: Smart Cities
      PubDate: 2023-09-13
      DOI: 10.3390/smartcities6050109
      Issue No: Vol. 6, No. 5 (2023)
       
  • Smart Cities, Vol. 6, Pages 2430-2446: Performance Evaluation of Emerging
           Perovskite Photovoltaic Energy-Harvesting System for BIPV Applications

    • Authors: Yerassyl Olzhabay, Muhammad N. Hamidi, Dahaman Ishak, Arjuna Marzuki, Annie Ng, Ikechi A. Ukaegbu
      First page: 2430
      Abstract: Perovskite solar cells (PSCs) are emerging photovoltaics (PVs) with promising optoelectronic characteristics. PSCs can be semitransparent (ST), which is beneficial in many innovative applications, including building-integrated photovoltaics (BIPVs). While PSCs exhibit excellent performance potential, enhancements in their stability and scalable manufacturing are required before they can be widely deployed. This work evaluates the real-world effectiveness of using PSCs in BIPVs to accelerate the development progress toward practical implementation. Given the present constraints on PSC module size and efficiency, bus stop shelters are selected for investigation in this work, as they provide a suitably scaled application representing a realistic near-term test case for early-stage research and engineering. An energy-harvesting system for a bus stop shelter in Astana, Kazakhstan, demonstrates the potential performance evaluation platform that can be used for perovskite solar cell modules (PSCMs) in BIPVs. The system includes maximum power point tracking (MPPT) and charge controllers, which can supply PSCM energy to the electronic load. Based on our design, the bus stop shelter has non-transparent and ST PSCMs on the roof and sides, respectively. May (best-case) and December (worst-case) scenarios are considered. According to the results, the PSCMs-equipped bus stop shelter can generate sufficient daily energy for load even in a worst-case scenario.
      Citation: Smart Cities
      PubDate: 2023-09-13
      DOI: 10.3390/smartcities6050110
      Issue No: Vol. 6, No. 5 (2023)
       
  • Smart Cities, Vol. 6, Pages 2447-2483: Should Autonomous Vehicles
           Collaborate in a Complex Urban Environment or Not'

    • Authors: Sumbal Malik, Manzoor Ahmed Khan, Hesham El-Sayed, M. Jalal Khan
      First page: 2447
      Abstract: A specialized version of collaborative driving is convoy driving. It is referred to as the practice of driving more than one vehicle consecutively in the same lane with a small inter-vehicle distance, maintaining the same speed. Extensive research has been conducted on convoys of heavy-duty trucks on the highway; however, limited research has studied convoy driving in an urban environment. The complex dynamics of an urban environment require short-lived collaboration with varying numbers of vehicles rather than collaborating over hours. The motivation of this research is to investigate how convoy driving can be realized to address the challenges of an urban environment and achieve the benefits of autonomous driving such as reduced fuel consumption, travel time, improved safety, and ride comfort. In this work, the best-fitted coalitional game framework is utilized to formulate the convoy driving problem as a coalition formation game in an urban environment. A hypothesis is formulated that traveling in a coalition is more beneficial for a vehicle than traveling alone. In connection with this, a coalitional game and an all-comprehensive utility function are designed, modeled, and implemented to facilitate the formation of autonomous vehicle coalitions for convoy driving. Multiple solution concepts, such as the Shapley allocation, the Nucleolus, and the Core, are implemented to solve and analyze the proposed convoy driving game. Furthermore, several coalition formation strategies such as traveling mode selection, selecting optimal coalitions, and making decisions about coalition merging are developed to analyze the behavior of the vehicles. In addition to this, extensive numerical experiments with different settings are conducted to evaluate and validate the performance of the proposed study. The experimental results proved the hypothesis that traveling in a convoy is significantly more beneficial than traveling alone. We conclude that traveling in a convoy is beneficial for coalition sizes of two to four vehicles with an inter-vehicle spacing of less than 4 m considering the limitations of an urban environment. Traveling in a coalition allows vehicles to save on fuel, minimize travel time and enhance safety and comfort. Furthermore, the findings of this research state that achieving the enormous benefits of traveling in a coalition requires finding the right balance between inter-vehicle distance and coalition size. In the future, we plan to extend this work by studying the evolving dynamics of the coalitions and the environment.
      Citation: Smart Cities
      PubDate: 2023-09-20
      DOI: 10.3390/smartcities6050111
      Issue No: Vol. 6, No. 5 (2023)
       
  • Smart Cities, Vol. 6, Pages 2484-2498: The Use of the Smart Technology for
           Creating an Inclusive Urban Public Space

    • Authors: Mohammed Itair, Isam Shahrour, Ihab Hijazi
      First page: 2484
      Abstract: This paper strives to enhance the inclusivity of urban public spaces, which play a crucial role in providing essential services for all citizens, including community building, physical and mental well-being, social interaction, civic engagement, citizen participation, and economic vitality. Despite the importance of these spaces, as recognized by the UN’s 2030 sustainability goals, the 2023 UN sustainable development report and scholars have drawn attention to their low availability, particularly for low-income individuals, women, children, and people with disabilities. To improve the inclusivity of public spaces, this paper offers the following contributions. (i) The establishment of a comprehensive framework for assessing public space inclusivity. This framework incorporates eight indicators: spatial distribution, typology, facilities and services, green and humid areas, governance and management, safety, user categories, and user satisfaction. (ii) The utilization of the framework to assess the inclusivity of public spaces in Nablus, a major Palestinian city. This assessment confirms the observations made by the UN and scholars regarding the low inclusivity of public spaces; in particular, a lack of public space, poor spatial distribution, and user dissatisfaction with safety conditions and services. (iii) The introduction of the concept of smart public space, which involves citizens in the governance of this space and leverages smart technology for monitoring, providing real-time information and services to citizens, improving facility efficiency, and creating an eco-friendly environment that preserves resources and biodiversity. By addressing these aspects, this paper enhances inclusivity. It promotes the development of an urban public space that caters to the diverse needs of the community, fostering a sense of belonging and well-being for all.
      Citation: Smart Cities
      PubDate: 2023-09-20
      DOI: 10.3390/smartcities6050112
      Issue No: Vol. 6, No. 5 (2023)
       
  • Smart Cities, Vol. 6, Pages 2499-2518: Strengthening Urban Resilience:
           Understanding the Interdependencies of Outer Space and Strategic Planning
           for Sustainable Smart Environments

    • Authors: Ulpia-Elena Botezatu, Olga Bucovetchi, Adrian V. Gheorghe, Radu D. Stanciu
      First page: 2499
      Abstract: The conventional approach to urban planning has predominantly focused on horizontal dimensions, disregarding the potential risks originating from outer space. This paper aims to initiate a discourse on the vertical dimension of cities, which is influenced by outer space, as an essential element of strategic urban planning. Through an examination of a highly disruptive incident in outer space involving a collision between the Iridium 33 and Cosmos 2251 satellites, this article elucidates the intricate interdependencies between urban areas and outer space infrastructure and services. Leveraging the principles of critical infrastructure protection, which bridge the urban and outer space domains, and employing simulation methods and software, this study articulates the intricate governance complexities of urban security and presents viable solutions for its enhancement. Consequently, the study contributes to the ongoing deliberations regarding the spatial integration of security practices by providing scholarly discourse on urban governance with potential strategies for cultivating sustainable smart cities. In essence, the intrinsic resilience of urban areas heavily relies on the interconnections between cities and outer space, necessitating urban strategists to acknowledge and comprehend these intricate interdependencies. To ensure sustainable urban development, it is imperative to fortify smart cities’ resilience against space debris through the implementation of more stringent regulations.
      Citation: Smart Cities
      PubDate: 2023-09-22
      DOI: 10.3390/smartcities6050113
      Issue No: Vol. 6, No. 5 (2023)
       
  • Smart Cities, Vol. 6, Pages 2519-2552: Multivariate Time-Series
           Forecasting: A Review of Deep Learning Methods in Internet of Things
           Applications to Smart Cities

    • Authors: Vasilis Papastefanopoulos, Pantelis Linardatos, Theodor Panagiotakopoulos, Sotiris Kotsiantis
      First page: 2519
      Abstract: Smart cities are urban areas that utilize digital solutions to enhance the efficiency of conventional networks and services for sustainable growth, optimized resource management, and the well-being of its residents. Today, with the increase in urban populations worldwide, their importance is greater than ever before and, as a result, they are being rapidly developed to meet the varying needs of their inhabitants. The Internet of Things (IoT) lies at the heart of such efforts, as it allows for large amounts of data to be collected and subsequently used in intelligent ways that contribute to smart city goals. Time-series forecasting using deep learning has been a major research focus due to its significance in many real-world applications in key sectors, such as medicine, climate, retail, finance, and more. This review focuses on describing the most prominent deep learning time-series forecasting methods and their application to six smart city domains, and more specifically, on problems of a multivariate nature, where more than one IoT time series is involved.
      Citation: Smart Cities
      PubDate: 2023-09-23
      DOI: 10.3390/smartcities6050114
      Issue No: Vol. 6, No. 5 (2023)
       
  • Smart Cities, Vol. 6, Pages 2553-2574: System Dynamics Model of
           Decentralized Household Electricity Storage Implementation: Case Study of
           Latvia

    • Authors: Armands Gravelsins, Erlanda Atvare, Edgars Kudurs, Anna Kubule, Dagnija Blumberga
      First page: 2553
      Abstract: Increasing renewable energy share in total energy production is a direction that leads toward the European Union’s aims of carbon neutrality by 2050, as well as increasing energy self-sufficiency and independence. Some of the main challenges to increasing renewable energy share while providing an efficient and secure energy supply are related to the optimization and profitability of de-centralized energy production systems. Integration of energy storage systems in addition to decentralized renewable energy production, for example, by solar panels, leads to more effective electricity supply and smart energy solutions. The modeling of such a complex dynamic system can be performed using the system dynamics method. The main aim of this research is to build and validate the basic structure of the system dynamics model for PV and battery diffusion in the household sector. A system dynamics model predicting the implementation of battery storage in private households was created for the case study of Latvia. Modeling results reveal that under the right conditions for electricity price and investment costs and with the right policy interventions, battery storage technologies combined with PV panels have a high potential for utilization in the household sector. Model results show that in a baseline scenario with no additional policies, up to 21,422 households or 10.8% of Latvian households could have combined PV and battery systems installed in 2050. Moderate subsidy policy can help to increase this number up to 25,118.
      Citation: Smart Cities
      PubDate: 2023-09-25
      DOI: 10.3390/smartcities6050115
      Issue No: Vol. 6, No. 5 (2023)
       
  • Smart Cities, Vol. 6, Pages 2574-2592: Enhancing Energy Efficiency in
           Connected Vehicles for Traffic Flow Optimization

    • Authors: Zeinab Shahbazi, Slawomir Nowaczyk
      First page: 2574
      Abstract: In urban settings, the prevalence of traffic lights often leads to fluctuations in traffic patterns and increased energy utilization among vehicles. Recognizing this challenge, this research addresses the adverse effects of traffic lights on the energy efficiency of electric vehicles (EVs) through the introduction of a Multi-Intersections-Based Eco-Approach and Departure strategy (M-EAD). This innovative strategy is designed to enhance various aspects of urban mobility, including vehicle energy efficiency, traffic flow optimization, and battery longevity, all while ensuring a satisfactory driving experience. The M-EAD strategy unfolds in two distinct stages: First, it optimizes eco-friendly green signal windows at traffic lights, with a primary focus on minimizing travel delays by solving the shortest path problem. Subsequently, it employs a receding horizon framework and leverages an iterative dynamic programming algorithm to refine speed trajectories. The overarching objective is to curtail energy consumption and reduce battery wear by identifying the optimal speed trajectory for EVs in urban environments. Furthermore, the research substantiates the real-world efficacy of this approach through on-road vehicle tests, attesting to its viability and practicality in actual road scenarios. In the proposed case, the simulation results showcase notable achievements, with energy consumption reduced by 0.92% and battery wear minimized to a mere 0.0017%. This research, driven by the pressing issue of urban traffic energy efficiency, not only presents a solution in the form of the M-EAD strategy but also contributes to the fields of sustainable urban mobility and EV performance optimization. By tackling the challenges posed by traffic lights, this work offers valuable insights and practical implications for improving the sustainability and efficiency of urban transportation systems.
      Citation: Smart Cities
      PubDate: 2023-09-27
      DOI: 10.3390/smartcities6050116
      Issue No: Vol. 6, No. 5 (2023)
       
  • Smart Cities, Vol. 6, Pages 2593-2618: Comparative Analysis of Smart Grid
           Solar Integration in Urban and Rural Networks

    • Authors: Mohammad Reza Maghami, Jagadeesh Pasupuleti, Chee Mei Ling
      First page: 2593
      Abstract: Solar photovoltaic (PV) power, a highly promising renewable energy source, encounters challenges when integrated into smart grids. These challenges encompass voltage fluctuations, issues with voltage balance, and concerns related to power quality. This study aims to comprehensively analyze the implications of solar PV penetration in Malaysian power distribution networks predominantly found in urban and rural areas. To achieve this, we employed the OpenDSS 2022 and MATLAB 2022b software tools to conduct static power flow analyses, enabling us to assess the effects of solar PV integration over a wide area under two worst-case scenarios: peak-load and no-load periods. Our investigation considered voltage violations, power losses, and fault analysis relative to the power demand of each scenario, facilitating a comprehensive evaluation of the impacts. The findings of our study revealed crucial insights. We determined that the maximum allowable power for both urban and rural networks during no-load and peak-load situations is approximately 0.5 MW and 0.125 MW, respectively. Moreover, as the percentage of PV penetration increases, notable reductions in power losses are observed, indicating the potential benefits of higher smart grid PV integration.
      Citation: Smart Cities
      PubDate: 2023-09-30
      DOI: 10.3390/smartcities6050117
      Issue No: Vol. 6, No. 5 (2023)
       
  • Smart Cities, Vol. 6, Pages 2619-2638: Impact of Large-Scale Electric
           Vehicles’ Promotion in Thailand Considering Energy Mix, Peak Load,
           and Greenhouse Gas Emissions

    • Authors: Ashok Paudel, Watcharakorn Pinthurat, Boonruang Marungsri
      First page: 2619
      Abstract: Thailand’s policies are in accord with the global drive to electrify transportation vehicle fleets due to climate concerns. This dedication is evident through its adoption of the 30@30 initiative and the planned ban on new internal combustion (IC) engine vehicles by 2035, showcasing a strong commitment. The objective of this study was to utilize the Low Emission Analysis Platform (LEAP) software to model the transition possibilities for electric vehicle (EV). Emphasis was placed on the future of the light-duty vehicle (LDV) sector, encompassing the energy sources, electric power demands, and greenhouse gas (GHG) emissions. Two scenarios were evaluated: one involving rapid economic growth and the other characterized by a more-gradual expansion. The former projection foresees 382 vehicles per thousand people by 2040, while the latter estimate envisions 338 vehicles. In the scenario of high growth, the vehicle stock could surge by 70% (27-million), whereas in the case of low growth, it might experience a 47% rise (23.3-million) compared to the base year (15.8 million). The increased adoption of EVs will lead to a decrease in energy demand owing to improved fuel efficiency. Nonetheless, even in the most-extreme EV scenarios, the proportion of electricity in the energy mix will remain below one-third. While GHG emissions will decrease, there is potential for even greater emission control through the enforcement of stricter emission standards. Significant EV adoption could potentially stress power grids, and the demand for charging might give rise to related challenges. The deployment of public fast charging infrastructure could provide a solution by evenly distributing the load across the day. In the most-rapid EV penetration scenario, a public charging program could cap the demand at 9300 MW, contrasting with the 21,000 MW demand for home charging. Therefore, a recommended approach involves devising an optimal strategy that considers EV adoption, a tariff structure with incentives, and the preparedness of the infrastructure.
      Citation: Smart Cities
      PubDate: 2023-10-02
      DOI: 10.3390/smartcities6050118
      Issue No: Vol. 6, No. 5 (2023)
       
  • Smart Cities, Vol. 6, Pages 2639-2660: A Review of Parking Slot Types and
           their Detection Techniques for Smart Cities

    • Authors: Kamlesh Kumar, Vijander Singh, Linesh Raja, Swami Nisha Bhagirath
      First page: 2639
      Abstract: Smart parking system plays a critical role in the overall development of the cities. The capability to precisely detect an open parking space nearby is necessary for autonomous vehicle parking for smart cities. Finding parking spaces is a big issue in big cities. Many of the existing parking guidance systems use fixed IoT sensors or cameras that are unable to offer information from the perspective of the driver. Accurately locating parking spaces can be difficult since they come in a range of sizes and colors that are blocked by objects that seem different depending on the environmental lighting. There are numerous auto industry players engaged in the advanced testing of driverless cars. A vacant parking space must be found, and the car must be directed to park there in order for the operation to succeed. The machine learning-based algorithms created to locate parking spaces and techniques and methods utilizing dashcams and fish-eye cameras are reviewed in this study. In response to the increase in dashcams, neural network-based techniques are created for identifying open parking spaces in dashcam videos. The paper proposed the review of the existing parking slot types and their detection techniques. The review will highlight the importance and scope of a smart parking system for smart cities.
      Citation: Smart Cities
      PubDate: 2023-10-02
      DOI: 10.3390/smartcities6050119
      Issue No: Vol. 6, No. 5 (2023)
       
  • Smart Cities, Vol. 6, Pages 2661-2679: Perceived Importance and Quality
           Attributes of Automated Parcel Locker Services in Urban Areas

    • Authors: Maria Cieśla
      First page: 2661
      Abstract: Recent global trends related to the increasing use of e-commerce are becoming a challenge for courier transport, especially in the last-mile process of delivering products to the final retail recipient. One delivery method is the personal collection of the parcel in an automated post box, available 24/7 for the customer. Our research method was based on a preliminary selection of the most important features of parcel lockers’ service quality, which were extracted based on the analysis of the scientific literature and previous research. This analysis was carried out by conducting a survey of Polish parcel locker users that provided data coded according to the dimensions of the Kano model. Based on the total satisfaction index, the results allowed us to conclude that a dedicated application (−0.96), proper placement of the parcel in the box (−0.82), adjusting the size of the parcel to the size of the box (−0.79), the location of parcel stations (−0.74), and ensuring improvements for the disabled (−0.62) are the most important features in the process of the automatic delivery of parcels to recipients in urban areas. This paper enriches the literature on the customer service quality of self-service technologies for last-mile delivery with the use of automated parcel lockers.
      Citation: Smart Cities
      PubDate: 2023-10-06
      DOI: 10.3390/smartcities6050120
      Issue No: Vol. 6, No. 5 (2023)
       
  • Smart Cities, Vol. 6, Pages 2680-2705: Investigation of Data Quality
           Assurance across IoT Protocol Stack for V2I Interactions

    • Authors: Danladi Suleman, Rania Shibl, Keyvan Ansari
      First page: 2680
      Abstract: Networking protocols have undergone significant developments and adaptations to cater for unique communication needs within the IoT paradigm. However, meeting these requirements in the context of vehicle-to-infrastructure (V2I) communications becomes a multidimensional problem due to factors like high mobility, intermittent connectivity, rapidly changing topologies, and an increased number of nodes. Thus, examining these protocols based on their characteristics and comparative analyses from the literature has shown that there is still room for improvement, particularly in ensuring efficiency in V2I interactions. This study aims to investigate the most viable network protocols for V2I communications, focusing on ensuring data quality (DQ) across the first three layers of the IoT protocol stack. This presents an improved understanding of the performance of network protocols in V2I communication. The findings of this paper showed that although each protocol offers unique strengths when evaluated against the identified dimensions of DQ, a cross-layer protocol fusion may be necessary to meet specific DQ dimensions. With the complexities and specific demands of V2I communications, it’s clear that no single protocol from our tri-layered perspective can solely fulfil all IP-based communication requirements given that the V2I communication landscape is teeming with heterogeneity, where a mixture of protocols is required to address unique communication demands.
      Citation: Smart Cities
      PubDate: 2023-10-06
      DOI: 10.3390/smartcities6050121
      Issue No: Vol. 6, No. 5 (2023)
       
  • Smart Cities, Vol. 6, Pages 2706-2721: The Implications of a Co-Created
           Software Solution for Mobility in Rural Areas

    • Authors: Lutz Eichholz
      First page: 2706
      Abstract: This paper explores the challenges in providing digital services of general interest in rural areas and proposes co-created ride-sharing software solutions to address the specific needs of these regions. This applied research is part of the Smarte.Land.Regionen project, which aims to improve digital public services at the district level. Focusing on rural mobility, the paper introduces ride-sharing benches enhanced with software as a possible low-threshold solution. Via workshops, surveys, and market research, the study identifies barriers to the adoption of ride-sharing benches and investigates factors contributing to their success. The software will be developed in an agile process together with partner counties and applied in a real-world case study. The proposed software solution emphasizes user-centered development, the geographical location of benches, and the prioritization of ride requests over ride offers. The findings highlight safety concerns, a lack of reliability, and the importance of obtaining people who are theoretically interested in solutions to actively participate in them. The paper emphasizes the importance of collaborative development with county stakeholders while also acknowledging the inherent limitations as the overall process becomes more complex and organizational obstacles arise. In addition, the findings suggest that the current state of rural mobility cannot be fundamentally changed by the implementation of ride-sharing software alone. Future research should focus on sustaining and scaling digital solutions, measuring their impact on rural mobility, and ensuring their transferability to other regions. The goal is to contribute to inclusive and sustainable rural development by improving access to digital public services and promoting the adoption of tailored mobility solutions.
      Citation: Smart Cities
      PubDate: 2023-10-09
      DOI: 10.3390/smartcities6050122
      Issue No: Vol. 6, No. 5 (2023)
       
  • Smart Cities, Vol. 6, Pages 2722-2741: The Exclusiveness of Smart
           Cities—Myth or Reality' Comparative Analysis of Selected Economic
           and Demographic Conditions of Polish Cities

    • Authors: Izabela Jonek-Kowalska
      First page: 2722
      Abstract: The Smart City concept is perceived as a method of dynamic development of cities and an opportunity to improve the quality of life of the urban community. Nevertheless, it is not without its disadvantages, among which the possibility of exclusion (economic, social or digital) is most often mentioned. However, the literature on the subject lacks empirical research verifying this allegation. For this reason, the purpose of this article is to conduct a comparative analysis of economic and social conditions in 17 Polish cities, 3 of which are recognized as Smart Cities in international rankings. By analyzing the economic and demographic conditions in the long term, an attempt is made to answer the question of whether Smart Cities offer better living conditions, and if so, how big is the imbalance and the risk of excluding other cities' In the course of the research, the following are taken into account: tax revenue per capita, unemployment rate, population density and level, as well as the share of working and post-working age population. These parameters are analyzed using descriptive statistics and systematized using multi-criteria analysis. The collective comparison of all the surveyed provincial cities shows that the best economic and demographic conditions apply to cities recognized as smart. The average annual rate of changes in tax revenues in the surveyed cities ranges from 5% to almost 8% and is the highest in Warsaw, Kraków and Wrocław. These cities are also characterized by the lowest unemployment rate, ranging from 3% to 4% (in other cities, from 4% to almost 7%). The mentioned cities and Gdańsk are the only ones with a positive rate of population change (from 0.62% to 1.08%). Other studied cities are systematically depopulating (annual rate of change from −0.37% to −7.09%). In Warsaw, Wrocław and Kraków, the share of the working-age population is also decreasing the slowest (the annual rate of change below −1.0%). The cities recognized as smart (Warsaw, Kraków and Wrocław) are matched by Gdańsk and Poznań, which can be considered strong contenders for being smart. Unfortunately, the remaining cities are far from the leaders of the ranking, which may expose them to economic and social exclusion, all the more so that the parameters examined in them are characterized by negative tendencies. It can, therefore, be concluded that striving to be smart can be a cause of increasing the economic and demographic distance. Therefore, it may increase unbalance and generate exclusion in the analyzed areas.
      Citation: Smart Cities
      PubDate: 2023-10-10
      DOI: 10.3390/smartcities6050123
      Issue No: Vol. 6, No. 5 (2023)
       
  • Smart Cities, Vol. 6, Pages 2742-2782: Unlocking the Future: Fostering
           Human–Machine Collaboration and Driving Intelligent Automation
           through Industry 5.0 in Smart Cities

    • Authors: Amr Adel
      First page: 2742
      Abstract: In the quest to meet the escalating demands of citizens, future smart cities emerge as crucial entities. Their role becomes even more vital given the current challenges posed by rapid urbanization and the need for sustainable and inclusive living spaces. At the heart of these future smart cities are advancements in information and communication technologies, with Industry 5.0 playing an increasingly significant role. This paper endeavors to conduct an exhaustive survey to analyze future technologies, including the potential of Industry 5.0 and their implications for smart cities. The crux of the paper is an exploration of technological advancements across various domains that are set to shape the future of urban environments. The discussion spans diverse areas including but not limited to cyber–physical systems, fog computing, unmanned aerial vehicles, renewable energy, machine learning, deep learning, cybersecurity, and digital forensics. Additionally, the paper sheds light on the specific role of Industry 5.0 in the smart city context, illuminating its impact on enabling advanced cybersecurity measures, fostering human–machine collaboration, driving intelligent automation in urban services, and refining data management and decision making. The paper also offers an in-depth review of the existing frameworks that are shaping smart city applications, evaluating how Industry 5.0 technologies could augment these frameworks. In particular, the paper delves into the various technological challenges that smart cities face, bringing potential Industry 5.0-enabled solutions to the fore.
      Citation: Smart Cities
      PubDate: 2023-10-10
      DOI: 10.3390/smartcities6050124
      Issue No: Vol. 6, No. 5 (2023)
       
  • Smart Cities, Vol. 6, Pages 2783-2806: Energy Harvesting on Airport
           Pavements Traffic Dependent: A321 (Narrow-Body) Aircraft Case Study

    • Authors: Diogo Correia, Phillip Richards, Adelino Ferreira
      First page: 2783
      Abstract: Research into novel methods for reducing greenhouse gas emissions is being carried out with the use of energy-harvesting systems. On road pavements, energy-harvesting technology has been successful in finding solutions and applications. This study discusses a solution for airport pavements that aims to produce electric energy from aircraft traffic. The new system is simulated in Simulink/MATLAB with all the components for producing technical data being provided by the manufacturers. The system is internally subdivided by simulating the aircraft in 3DOF and the energy harvesting in 1DOF. The energy-harvesting simulations achieved an energy density of up to 6.80 Wh/(m.vehicle) and a 24% conversion rate. This paper contributes to the exploration of solutions to enable energy-harvesting systems to be placed in airport pavements. These solutions are traffic dependent and require an innovative system to control the operation due to the specifications of airport pavements.
      Citation: Smart Cities
      PubDate: 2023-10-11
      DOI: 10.3390/smartcities6050125
      Issue No: Vol. 6, No. 5 (2023)
       
  • Smart Cities, Vol. 6, Pages 2807-2827: Multiple Linear Regression and
           Machine Learning for Predicting the Drinking Water Quality Index in
           Al-Seine Lake

    • Authors: Raed Jafar, Adel Awad, Iyad Hatem, Kamel Jafar, Edmond Awad, Isam Shahrour
      First page: 2807
      Abstract: Ensuring safe and clean drinking water for communities is crucial, and necessitates effective tools to monitor and predict water quality due to challenges from population growth, industrial activities, and environmental pollution. This paper evaluates the performance of multiple linear regression (MLR) and nineteen machine learning (ML) models, including algorithms based on regression, decision tree, and boosting. Models include linear regression (LR), least angle regression (LAR), Bayesian ridge chain (BR), ridge regression (Ridge), k-nearest neighbor regression (K-NN), extra tree regression (ET), and extreme gradient boosting (XGBoost). The research’s objective is to estimate the surface water quality of Al-Seine Lake in Lattakia governorate using the MLR and ML models. We used water quality data from the drinking water lake of Lattakia City, Syria, during years 2021–2022 to determine the water quality index (WQI). The predictive performance of both the MLR and ML models was evaluated using statistical methods such as the coefficient of determination (R2) and the root mean square error (RMSE) to estimate their efficiency. The results indicated that the MLR model and three of the ML models, namely linear regression (LR), least angle regression (LAR), and Bayesian ridge chain (BR), performed well in predicting the WQI. The MLR model had an R2 of 0.999 and an RMSE of 0.149, while the three ML models had an R2 of 1.0 and an RMSE of approximately 0.0. These results support using both MLR and ML models for predicting the WQI with very high accuracy, which will contribute to improving water quality management.
      Citation: Smart Cities
      PubDate: 2023-10-12
      DOI: 10.3390/smartcities6050126
      Issue No: Vol. 6, No. 5 (2023)
       
  • Smart Cities, Vol. 6, Pages 2828-2848: Train to Vehicle: Toward
           Sustainable Transportation in Dense Urban Regions

    • Authors: Ahmed Ali A. Mohamed, Rohama Ahmad, Jaskaran Singh, Ahmed S. Rahman
      First page: 2828
      Abstract: This article investigates the feasibility of using regenerative energy from braking trains to charge electric buses in the context of New York City’s (NYC) subway and electric bus networks. A case study centered around NYC’s system has been performed to evaluate the benefits and challenges pertaining to the use of the preexisting subway network as a power supply for its new all-electric buses. The analysis shows that charging electric buses via the subway system during subway off-peak periods does not hinder regular train operation. In addition, having the charging electric buses connected to the third rail allows for more regenerative braking energy (RBE) to be recuperated, decreasing the energy wasted throughout the system. It was also found that including a wayside energy storage system (WESS) reduces the overall substation peak power consumption.
      Citation: Smart Cities
      PubDate: 2023-10-16
      DOI: 10.3390/smartcities6050127
      Issue No: Vol. 6, No. 5 (2023)
       
  • Smart Cities, Vol. 6, Pages 2849-2882: Optimal Water Management
           Strategies: Paving the Way for Sustainability in Smart Cities

    • Authors: Ayat-Allah Bouramdane
      First page: 2849
      Abstract: Global urbanization and increasing water demand make efficient water resource management crucial. This study employs Multi-Criteria Decision Making (MCDM) to evaluate smart city water management strategies. We use representative criteria, employ objective judgment, assign weights through the Analytic Hierarchy Process (AHP), and score strategies based on meeting these criteria. We find that the “Effectiveness and Risk Management” criterion carries the highest weight (15.28%), underscoring its pivotal role in strategy evaluation and robustness. Medium-weight criteria include “Resource Efficiency, Equity, and Social Considerations” (10.44%), “Integration with Existing Systems, Technological Feasibility, and Ease of Implementation” (10.10%), and “Environmental Impact” (9.84%) for ecological mitigation. “Community Engagement and Public Acceptance” (9.79%) recognizes involvement, while “Scalability and Adaptability” (9.35%) addresses changing conditions. “Return on Investment” (9.07%) and “Regulatory and Policy Alignment” (8.8%) balance financial and governance concerns. Two low-weight criteria, “Data Reliability” (8.78%) and “Long-Term Sustainability” (8.55%), stress data accuracy and sustainability. Highly weighted strategies like “Smart Metering and Monitoring, Demand Management, Behavior Change” and “Smart Irrigation Systems” are particularly effective in improving water management in smart cities. However, medium-weighted (e.g., “Educational Campaigns and Public Awareness”, “Policy and Regulation”, “Rainwater Harvesting”, “Offshore Floating Photovoltaic Systems”, “Collaboration and Partnerships”, “Graywater Recycling and Reuse”, and “Distributed Water Infrastructure”) and low-weighted (e.g., “Water Desalination”) strategies also contribute and can be combined with higher-ranked ones to create customized water management approaches for each smart city’s unique context. This research is significant because it addresses urban water resource management complexity, offers a multi-criteria approach to enhance traditional single-focused methods, evaluates water strategies in smart cities comprehensively, and provides a criteria-weight-based resource allocation framework for sustainable decisions, boosting smart city resilience. Note that results may vary based on specific smart city needs and constraints. Future studies could explore factors like climate change on water management in smart cities and consider alternative MCDM methods like TOPSIS or ELECTRE for strategy evaluation.
      Citation: Smart Cities
      PubDate: 2023-10-18
      DOI: 10.3390/smartcities6050128
      Issue No: Vol. 6, No. 5 (2023)
       
  • Smart Cities, Vol. 6, Pages 2883-2909: Ranking Sustainable Smart City
           Indicators Using Combined Content Analysis and Analytical Hierarchy
           Process Techniques

    • Authors: Karim Gazzeh
      First page: 2883
      Abstract: Sustainable Smart Cities have a significant potential to ensure equal access to public services, achieve sustainability and governance transparency, improve livability, and anticipate and mitigate increasingly changing threats. This study aims at prioritizing a core set of Sustainable Smart City (SSC) indicators using a combined methodology: (a) Content Analysis and (b) Analytical Hierarchy Process. The study’s contribution is that it successfully developed a more robust ranking of the above-mentioned set of indicators by combining AHP and co-occurrence analyses. The final combined ranking is intended to serve as a Decision Support Tool to streamline the decision-making process and help decision-makers prioritize dimensions to measure, achieve, or monitor actions when they cannot be undertaken simultaneously in contexts of economic recessions, financial constraints, and resource mobilization challenges. The findings draw attention to the need for considering the concept of SSCs through the prism of interconnecting the various current technology-driven “smart silos” under an inclusive umbrella that focuses on the combinations and connectedness to achieve a systemic approach to sustainability and smartness that none of those single areas can achieve in isolation. The results also revealed an interesting paradox, which relegated the Technology and ICT dimension to the bottom of the ranking, contrary to the widespread consensus and opinion, opening an opportunity for discussion among peers.
      Citation: Smart Cities
      PubDate: 2023-10-19
      DOI: 10.3390/smartcities6050129
      Issue No: Vol. 6, No. 5 (2023)
       
  • Smart Cities, Vol. 6, Pages 2910-2931: Adaptive Smart eHealth Framework
           for Personalized Asthma Attack Prediction and Safe Route Recommendation

    • Authors: Eman Alharbi, Asma Cherif, Farrukh Nadeem
      First page: 2910
      Abstract: Recently, there has been growing interest in using smart eHealth systems to manage asthma. However, limitations still exist in providing smart services and accurate predictions tailored to individual patients’ needs. This study aims to develop an adaptive ubiquitous computing framework that leverages different bio-signals and spatial data to provide personalized asthma attack prediction and safe route recommendations. We proposed a smart eHealth framework consisting of multiple layers that employ telemonitoring application, environmental sensors, and advanced machine-learning algorithms to deliver smart services to the user. The proposed smart eHealth system predicts asthma attacks and uses spatial data to provide a safe route that drives the patient away from any asthma trigger. Additionally, the framework incorporates an adaptation layer that continuously updates the system based on real-time environmental data and daily bio-signals reported by the user. The developed telemonitoring application collected a dataset containing 665 records used to train the prediction models. The testing result demonstrates a remarkable 98% accuracy in predicting asthma attacks with a recall of 96%. The eHealth system was tested online by ten asthma patients, and its accuracy achieved 94% of accuracy and a recall of 95.2% in generating safe routes for asthma patients, ensuring a safer and asthma-trigger-free experience. The test shows that 89% of patients were satisfied with the safer recommended route than their usual one. This research contributes to enhancing the capabilities of smart healthcare systems in managing asthma and improving patient outcomes. The adaptive feature of the proposed eHealth system ensures that the predictions and recommendations remain relevant and personalized to the current conditions and needs of the individual.
      Citation: Smart Cities
      PubDate: 2023-10-20
      DOI: 10.3390/smartcities6050130
      Issue No: Vol. 6, No. 5 (2023)
       
  • Smart Cities, Vol. 6, Pages 2932-2943: Should Smart Cities Introduce a New
           Form of Public Transport Vehicles'

    • Authors: Maciej Kruszyna
      First page: 2932
      Abstract: This study shows the concept of an innovative road and rail vehicle as a new form of public transport. Our literature review shows that the idea of a “smart city” contains not only new tools but also vehicles or infrastructure. The new vehicle is proposed based on the observed development of urban public transport means and other novel solutions. A slight innovation proposed here could allow the use of typical and operated tram routes for modified buses. A new type of vehicle could use both the existing tram routes and newly constructed sections with no tracks. It is assumed that new vehicles would drive with trams on the same, shared tracks. All of the conditions should reduce the costs of developing public transport networks in many cities where tram networks already exist. This paper contains a description of the idea and a potential case study location. The implementation conditions are outlined in the Discussion section. The title’s question is also considered there: “Should smart cities introduce a new form of public transport vehicles'” In addition, the potential benefits as well as threats are presented. Conclusions define the next steps for the research. So, this paper is an introduction to the wider research. It will popularize the idea of a new vehicle and could motivate the industry to construct a prototype. At this stage, no models or detailed calculations were conducted.
      Citation: Smart Cities
      PubDate: 2023-10-20
      DOI: 10.3390/smartcities6050131
      Issue No: Vol. 6, No. 5 (2023)
       
  • Smart Cities, Vol. 6, Pages 2944-2959: Robust-Adaptive Controllers
           Designed for Grid-Forming Converters Ensuring Various Low-Inertia
           Microgrid Conditions

    • Authors: Watcharakorn Pinthurat, Prayad Kongsuk, Boonruang Marungsri
      First page: 2944
      Abstract: As the integration of renewable energy sources (RESs) and distributed generations (DGs) increases, the need for stable and reliable operation of microgrids (MGs) becomes crucial. However, the inherent low inertia of such systems poses intricate control challenges that necessitate innovative solutions. To tackle these issues, this paper presents the development of robust-adaptive controllers tailored specifically for grid-forming (GFM) converters. The proposed adaptive-robust controllers are designed to accommodate the diverse range of scenarios encountered in low-inertia MGs. The proposed approach applies both the robust control techniques and adaptive control strategies, thereby offering an effective means to ensure stable and seamless converter performance under varying operating conditions. The efficacy of the introduced adaptive-robust controllers for GFM converters is validated within a low-inertia MG, which is characterized by substantial penetration of converter-interfaced resources. The validation also encompasses diverse MG operational scenarios and conditions.
      Citation: Smart Cities
      PubDate: 2023-10-23
      DOI: 10.3390/smartcities6050132
      Issue No: Vol. 6, No. 5 (2023)
       
  • Smart Cities, Vol. 6, Pages 2960-2981: Smart City Information Systems:
           Research on Information Published for Citizens and Design of Effective
           Content in the Czech Republic

    • Authors: Hana Důbravová, Vladimír Bureš
      First page: 2960
      Abstract: The concept of Smart Cities integrates innovative technologies to improve citizens’ quality of life in towns and cities worldwide. Crisis management is a separate section directly managed by the leadership of municipalities, cities and counties in cooperation between police, fire and municipal police to ensure the safety of residents and safety in public spaces. The purpose of this study is to investigate to which extent publicly available information related to the field of crisis management is unavailable to residents in municipalities, towns and cities through online information systems. The primary aim is to provide suggestions for a general information system structure and content that would highlight and satisfy the need to address the crisis management issue, especially in providing immediate information to the population through an innovative online form. The achievement of this goal is methodologically based on qualitative research analysing and comparing the information published for residents through Smart City information systems in selected towns and municipalities. Document analysis or conceptual design was applied, and evaluation criteria for objective assessment of Smart City information systems were appropriately determined. The comparative analysis based on this set of criteria enabled the development of the proposals of information systems’ content that can be used to keep the information systems for Smart Cities in cities, municipalities and regions, actual and beneficial. From the available resources, two main modules that focused either on citizens or cities were synthesised. Moreover, SWOT analysis or the Smart Regions Rapid Response structure was derived. Acquired results outline generic structures and contents that support the development of the concept of Smart Cities and can be suitably implemented for the development of the modification of information systems containing relevant information for residents, cities and municipalities, focusing on citizen safety.
      Citation: Smart Cities
      PubDate: 2023-10-23
      DOI: 10.3390/smartcities6050133
      Issue No: Vol. 6, No. 5 (2023)
       
  • Smart Cities, Vol. 6, Pages 2982-3004: A Comparative Analysis of
           Multi-Label Deep Learning Classifiers for Real-Time Vehicle Detection to
           Support Intelligent Transportation Systems

    • Authors: Danesh Shokri, Christian Larouche, Saeid Homayouni
      First page: 2982
      Abstract: An Intelligent Transportation System (ITS) is a vital component of smart cities due to the growing number of vehicles year after year. In the last decade, vehicle detection, as a primary component of ITS, has attracted scientific attention because by knowing vehicle information (i.e., type, size, numbers, location speed, etc.), the ITS parameters can be acquired. This has led to developing and deploying numerous deep learning algorithms for vehicle detection. Single Shot Detector (SSD), Region Convolutional Neural Network (RCNN), and You Only Look Once (YOLO) are three popular deep structures for object detection, including vehicles. This study evaluated these methodologies on nine fully challenging datasets to see their performance in diverse environments. Generally, YOLO versions had the best performance in detecting and localizing vehicles compared to SSD and RCNN. Between YOLO versions (YOLOv8, v7, v6, and v5), YOLOv7 has shown better detection and classification (car, truck, bus) procedures, while slower response in computation time. The YOLO versions have achieved more than 95% accuracy in detection and 90% in Overall Accuracy (OA) for the classification of vehicles, including cars, trucks and buses. The computation time on the CPU processor was between 150 milliseconds (YOLOv8, v6, and v5) and around 800 milliseconds (YOLOv7).
      Citation: Smart Cities
      PubDate: 2023-10-23
      DOI: 10.3390/smartcities6050134
      Issue No: Vol. 6, No. 5 (2023)
       
  • Smart Cities, Vol. 6, Pages 3005-3031: Blockchain-Based Malicious
           Behaviour Management Scheme for Smart Grids

    • Authors: Ziqiang Xu, Ahmad Salehi Shahraki, Carsten Rudolph
      First page: 3005
      Abstract: The smart grid optimises energy transmission efficiency and provides practical solutions for energy saving and life convenience. Along with a decentralised, transparent and fair trading model, the smart grid attracts many users to participate. In recent years, many researchers have contributed to the development of smart grids in terms of network and information security so that the security, reliability and stability of smart grid systems can be guaranteed. However, our investigation reveals various malicious behaviours during smart grid transactions and operations, such as electricity theft, erroneous data injection, and distributed denial of service (DDoS). These malicious behaviours threaten the interests of honest suppliers and consumers. While the existing literature has employed machine learning and other methods to detect and defend against malicious behaviour, these defence mechanisms do not impose any penalties on the attackers. This paper proposes a management scheme that can handle different types of malicious behaviour in the smart grid. The scheme uses a consortium blockchain combined with the best–worst multi-criteria decision method (BWM) to accurately quantify and manage malicious behaviour. Smart contracts are used to implement a penalty mechanism that applies appropriate penalties to different malicious users. Through a detailed description of the proposed algorithm, logic model and data structure, we show the principles and workflow of this scheme for dealing with malicious behaviour. We analysed the system’s security attributes and tested the system’s performance. The results indicate that the system meets the security attributes of confidentiality and integrity. The performance results are similar to the benchmark results, demonstrating the feasibility and stability of the system.
      Citation: Smart Cities
      PubDate: 2023-10-23
      DOI: 10.3390/smartcities6050135
      Issue No: Vol. 6, No. 5 (2023)
       
  • Smart Cities, Vol. 6, Pages 1630-1662: Optimization Approaches for
           Demand-Side Management in the Smart Grid: A Systematic Mapping Study

    • Authors: Safaa Mimi, Yann Ben Maissa, Ahmed Tamtaoui
      First page: 1630
      Abstract: Demand-side management in the smart grid often consists of optimizing energy-related objective functions, with respect to variables, in the presence of constraints expressing electrical consumption habits. These functions are often related to the user’s electricity invoice (cost) or to the peak energy consumption (peak-to-average energy ratio), which can cause electrical network failure on a large scale. However, the growth in energy demand, especially in emerging countries, is causing a serious energy crisis. This is why several studies focus on these optimization approaches. To our knowledge, no article aims to collect and analyze the results of research on peak-to-average energy consumption ratio and cost optimization using a systematic reproducible method. Our goal is to fill this gap by presenting a systematic mapping study on the subject, spanning the last decade (2013–2022). The methodology used first consisted of searching digital libraries according to a specific search string (104 relevant studies out of 684). The next step relied on an analysis of the works (classified using 13 criteria) according to 5 research questions linked to algorithmic trends, energy source, building type, optimization objectives and pricing schemes. Some main results are the predominance of the genetic algorithms heuristics, an insufficient focus on renewable energy and storage systems, a bias in favor of residential buildings and a preference for real-time pricing schemes. The main conclusions are related to the promising hybridization between the genetic algorithms and swarm optimization approaches, as well as a greater integration of user preferences in the optimization. Moreover, there is a need for accurate renewable and storage models, as well as for broadening the optimization scope to other objectives such as CO2 emissions or communications load.
      Citation: Smart Cities
      PubDate: 2023-06-30
      DOI: 10.3390/smartcities6040077
      Issue No: Vol. 6, No. 4 (2023)
       
  • Smart Cities, Vol. 6, Pages 1663-1689: E-Governance in Smart Cities:
           Global Trends and Key Enablers

    • Authors: Aleksandra Kuzior, Olena Pakhnenko, Inna Tiutiunyk, Serhiy Lyeonov
      First page: 1663
      Abstract: A smart city is a complex concept that can be analyzed from different aspects and points of view. E-governance plays a key role in facilitating the integration of all elements of a smart city. The purpose of the article is to investigate key enablers of e-governance in terms of economic, social, political, information and technological indicators. The research base includes 68 smart cities selected on the basis of different regional affiliations and different economic, social and political developments. The authors apply the methods of cluster analysis (to divide smart cities into clusters according to e-governance indicators); construction of an integral indicator using the linear mathematical model and the Fishburn formula; VAR/VEC modeling (to stud the key factors influencing the development of e-government in smart cities). It was found that the Human Development Index has the greatest impact on e-governance, while the GNI per capita indicator demonstrated the absence of influence for all clusters. The factor of information technologies was defined as the main factor of direct influence on the Smart City Governance Index for smart cities of the first cluster with the highest indicators of e-governance.
      Citation: Smart Cities
      PubDate: 2023-06-30
      DOI: 10.3390/smartcities6040078
      Issue No: Vol. 6, No. 4 (2023)
       
  • Smart Cities, Vol. 6, Pages 1690-1718: DC Microgrids: A Propitious Smart
           Grid Paradigm for Smart Cities

    • Authors: Shriram S. Rangarajan, Rahul Raman, Amritpal Singh, Chandan Kumar Shiva, Ritesh Kumar, Pradip Kumar Sadhu, E. Randolph Collins, Tomonobu Senjyu
      First page: 1690
      Abstract: Recent years have seen a surge in interest in DC microgrids as DC loads and DC sources like solar photovoltaic systems, fuel cells, batteries, and other options have become more mainstream. As more distributed energy resources (DERs) are integrated into an existing smart grid, DC networks have come to the forefront of the industry. DC systems completely sidestep the need for synchronization, reactive power control, and frequency control. DC systems are more dependable and productive than ever before because AC systems are prone to all of these issues. There is a lot of unrealized potential in DC power, but it also faces some significant challenges. Protecting a DC system is difficult because there is no discrete location of where the current disappears. DC microgrid stability that is dependent on inertia must also be considered during the planning stage. The problems that DC microgrids have include insufficient power quality and poor communication. The power quality, inertia, communication, and economic operations of these value streams, as well as their underlying architectures and protection schemes, are all extensively discussed in this paper. This review paper examines the pros and cons of both grid-connected and isolated DC microgrids. In addition, the paper compares the different kinds of microgrids in terms of power distribution and energy management agency, such as the prerequisites for a DC microgrid’s planning, operation, and control that must be met before state-of-the-art systems can be implemented.
      Citation: Smart Cities
      PubDate: 2023-07-03
      DOI: 10.3390/smartcities6040079
      Issue No: Vol. 6, No. 4 (2023)
       
  • Smart Cities, Vol. 6, Pages 1719-1743: Smart Cities—A Structured
           Literature Review

    • Authors: Jose Sanchez Gracias, Gregory S. Parnell, Eric Specking, Edward A. Pohl, Randy Buchanan
      First page: 1719
      Abstract: Smart cities are rapidly evolving concept-transforming urban developments in the 21st century. Smart cities use advanced technologies and data analytics to improve the quality of life for their citizens, increase the efficiency of infrastructure and services, and promote sustainable economic growth. Smart cities integrate multiple domains, including transportation, energy, health, education, and governance, to create an interconnected and intelligent urban environment. Our research study methodology was a structured literature review using Web of Science and Google Scholar and ten smart city research questions. The research questions included smart city definitions, advantages, disadvantages, implementation challenges, funding, types of applications, quantitative techniques for analysis, and prioritization metrics. In addition, our study analyzes the implementation of smart city solutions in international contexts and proposes strategies to overcome implementation challenges. The integration of technology and data-driven solutions in smart cities has the potential to revolutionize urban living by providing citizens with personalized and accessible services. However, the implementation also presents challenges, including data privacy concerns, unequal access to technology, and the need for collaboration across private, public, and government sectors. This study provides insights into the current state and future prospects of smart cities and presents an analysis of the challenges and opportunities they present. In addition, we propose a concise definition for smart cities: “Smart cities use digital technologies, communication technologies, and data analytics to create an efficient and effective service environment that improves urban quality of life and promotes sustainability”. Smart cities represent a promising avenue for urban development. As cities continue to grow and face increasingly complex challenges, the integration of advanced technologies and data-driven solutions can help to create more sustainable communities.
      Citation: Smart Cities
      PubDate: 2023-07-11
      DOI: 10.3390/smartcities6040080
      Issue No: Vol. 6, No. 4 (2023)
       
  • Smart Cities, Vol. 6, Pages 1744-1764: Smart City Assessment in Developing
           Economies: A Scoping Review

    • Authors: Julius Jay Lacson, Hussein Sinsuat Lidasan, Vidya Spay Putri Ayuningtyas, Larmie Feliscuzo, Johann Heinrich Malongo, Nove Joshua Lactuan, Paul Bokingkito, Lemuel Clark Velasco
      First page: 1744
      Abstract: There are limited research articles that focus on smart city assessment (SCA) applications as it is a relatively new field of research and practice. However, numerous studies have been conducted and published to date, particularly in developing countries, with the broad objective of building theoretical frameworks that are centered on smart city assessments. This study aimed to systematically examine the available literature on SCA, particularly in the context of developing economies, and provide valuable insights for the various stakeholders involved in smart city projects. The specific objectives of the study were to synthesize the existing literature on smart city assessment in developing economies, analyze the frameworks employed for smart city assessment, and identify critical gaps in these frameworks while providing recommendations for future research. The methodology employed involved a scoping review procedure, and the data that were collected and analyzed were specific to developing economies. The findings revealed that SCA often incorporates other research methods, such as mixed and quantitative analyses, and embraces a multidisciplinary approach that encompasses various subject areas. While social science emerged as a prominent subject area, sustainability, renewable energy, and industrial development also play crucial roles in smart city assessments. This study highlighted that ISO 37122:2019 is the most widely adopted framework due to its structured methodology, ability to measure progress over time, and potential for benchmarking against other cities. However, it is important to consider that each framework has its own strengths and weaknesses, and cities may opt to utilize multiple frameworks or tailor them to their specific needs. Our paper concludes by emphasizing the significance of this research in providing comprehensive insights into smart city assessment in developing economies and the need for further studies to address the identified gaps and enhance future assessments.
      Citation: Smart Cities
      PubDate: 2023-07-13
      DOI: 10.3390/smartcities6040081
      Issue No: Vol. 6, No. 4 (2023)
       
  • Smart Cities, Vol. 6, Pages 1765-1785: Microgrids Resiliency Enhancement
           against Natural Catastrophes Based Multiple Cooperation of Water and
           Energy Hubs

    • Authors: Sattar Shojaeiyan, Moslem Dehghani, Pierluigi Siano
      First page: 1765
      Abstract: With the ever-growing frequency of natural catastrophe occurrences such as hurricanes, floods, earthquakes, etc., the idea of resilient microgrids (MGs) has attracted more attention than before. Providing the opportunity for a multi-carrier energy supply after a natural catastrophe can lessen power losses and improve power resiliency and reliability. Critical loads within the MG can be prioritized and restored in the shortest possible time based on the condition of the network after the damaging occurrence by considering the energy hub (EH) systems and the optimum design and allocation of these multi-carrier systems. To this end, this paper aims to address the resilience framework in MGs considering sets of water and EHs (WEHs) consisting of CHP (combined heat and power), a boiler, energy storage, and a desalination unit. This study focused on considering an effective resilient scheme to restore critical loads in a short period after a natural catastrophe when the MG experiences an unpredictable event. By applying the idea of WEHs, there would be a chance of restoring the system by using two sets of WEH systems in the appropriate islanded points to restore the system and critical loads of electricity, heat, and water. For this purpose, different scenarios were considered for assessing the resiliency of the system against a natural catastrophic event that causes serious damage to the network by analyzing the energy-not-supplied (ENS) factor. Moreover, the allocated WEHs can adequately supply the electrical, water, and thermal demand loads throughout the day after the natural catastrophe. To mitigate the unforeseen variations in the renewable sources, a battery is located in the WEH, which can attend to the optimal scheduling effectively. A scenario-based method is also introduced to improve the resiliency of MGs in an uncertain environment such as electrical, heat, and water stochastic demands. The appropriate efficiency of the offered model was considered on a modified IEEE test system.
      Citation: Smart Cities
      PubDate: 2023-07-15
      DOI: 10.3390/smartcities6040082
      Issue No: Vol. 6, No. 4 (2023)
       
  • Smart Cities, Vol. 6, Pages 1786-1813: An Incident Detection Model Using
           Random Forest Classifier

    • Authors: Osama ElSahly, Akmal Abdelfatah
      First page: 1786
      Abstract: Traffic incidents have adverse effects on traffic operations, safety, and the economy. Efficient Automatic Incident Detection (AID) systems are crucial for timely and accurate incident detection. This paper develops a realistic AID model using the Random Forest (RF), which is a machine learning technique. The model is trained and tested on simulated data from VISSIM traffic simulation software. The model considers the variations in four critical factors: congestion levels, incident severity, incident location, and detector distance. Comparative evaluation with existing AID models, in the literature, demonstrates the superiority of the developed model, exhibiting higher Detection Rate (DR), lower Mean Time to Detect (MTTD), and lower False Alarm Rate (FAR). During training, the RF model achieved a DR of 96.97%, MTTD of 1.05 min, and FAR of 0.62%. During testing, it achieved a DR of 100%, MTTD of 1.17 min, and FAR of 0.862%. Findings indicate that detecting minor incidents during low traffic volumes is challenging. FAR decreases with the increase in Demand to Capacity ratio (D/C), while MTTD increases with D/C. Higher incident severity leads to lower MTTD values, while greater distance between an incident and upstream detector has the opposite effect. The FAR is inversely proportional to the incident’s location from the upstream detector, while being directly proportional to the distance between detectors. Larger detector spacings result in longer detection times.
      Citation: Smart Cities
      PubDate: 2023-07-17
      DOI: 10.3390/smartcities6040083
      Issue No: Vol. 6, No. 4 (2023)
       
  • Smart Cities, Vol. 6, Pages 1814-1831: Route Planning for Emergency
           Evacuation Using Graph Traversal Algorithms

    • Authors: Alexandros Gaitanis, Athanasios Lentzas, Grigorios Tsoumakas, Dimitris Vrakas
      First page: 1814
      Abstract: The automatic identification of various design elements in a floor-plan image has gained increasing attention in recent research. Emergency-evacuation applications can benefit greatly from automated floor-plan solutions, as they allow for the development of horizontal solutions instead of vertical solutions targeting a specific audience. In addition to that, current evacuation plans rely on static signs without taking into account the dynamic characteristics of each emergency case. This work aims to extract information from a floor-plan image and transform it into a graph that is used for pathfinding in an emergency evacuation. First, the basic elements of the floor-plan image, i.e., walls, rooms and doors, are identified. This is achieved using Panoptic-DeepLab, which is a state-of-the-art deep neural network for the panoptic segmentation of images, and it is available from DeepLab2, an image segmentation library. The neural network was trained using CubiCasa5K, a large-scale floor-plan image dataset containing 5000 samples, annotated into over 80 floor-plan object categories. Then, using the prediction of each pixel, a graph that shows how rooms and doors are connected is created. An application that presents this information in a user-friendly manner and provides graph editing capabilities was developed. Finally, the exits are set, and the optimal path for evacuation is calculated from each node using Dijkstra’s algorithm.
      Citation: Smart Cities
      PubDate: 2023-07-21
      DOI: 10.3390/smartcities6040084
      Issue No: Vol. 6, No. 4 (2023)
       
  • Smart Cities, Vol. 6, Pages 1832-1857: Key Factors Affecting Smart
           Building Integration into Smart City: Technological Aspects

    • Authors: Rasa Apanavičienė, Mustafa Muthnna Najm Shahrabani
      First page: 1832
      Abstract: This research presents key factors influencing smart building integration into smart cities considering the city as a technological system. This paper begins with an overview of the concept of smart buildings, defining their features and discussing the technological advancements driving their development. The frameworks for smart buildings are presented, emphasizing energy efficiency, sustainability, automation, and data analytics. Then, the concept of a smart city and the role of digitalization in its development is explored. The conceptual framework of smart building into a smart city is presented, contributing to understanding the complex process of integrating smart buildings into smart cities. Further research delves into the factors influencing the integration of smart buildings into smart cities, focusing on energy, mobility, water, security systems, and waste management infrastructure domains. Each thematic area is examined, highlighting the importance of integration and the associated challenges and opportunities, based on research in the literature and the analysis of case studies. This enables the identification of 26 factors influencing integration and the synthesis of findings. The findings indicate that the successful integration of smart buildings into smart cities requires attention to multiple factors related to smart energy, smart mobility, smart water, smart security, and smart waste management infrastructures. The results obtained from this research provide valuable insights into the factors influencing smart building integration into a smart city from a technological perspective, enabling stakeholders to make informed decisions and develop strategies paving the way for sustainable, resilient, and efficient urban environments.
      Citation: Smart Cities
      PubDate: 2023-07-31
      DOI: 10.3390/smartcities6040085
      Issue No: Vol. 6, No. 4 (2023)
       
  • Smart Cities, Vol. 6, Pages 1858-1878: The Use of Artificial Intelligence
           in the Assessment of User Routes in Shared Mobility Systems in Smart
           Cities

    • Authors: Andrzej Kubik
      First page: 1858
      Abstract: The use of artificial intelligence in solutions used in smart cities is becoming more and more popular. An example of the use of machine learning is the improvement of the management of shared mobility systems in terms of assessing the accuracy of user journeys. Due to the fact that vehicle-sharing systems are appearing in increasing numbers in city centers and outskirts, and the way vehicles are used is not controlled by operators in real mode, there is a need to fill this research gap. The article presents a built machine learning model, which is a supplement to existing research and is updated with new data from the existing system. The developed model is used to determine and assess the accuracy of trips made by users of shared mobility systems. In addition, an application was also created showing an example of using the model in practice. The aim of the article is therefore to indicate the possibility of correct identification of journeys with vehicles from shared mobility systems. Studies have shown that the prediction efficiency of the data generated by the model reached the level of 95% agreement. In addition, the research results indicate that it is possible to automate the process of evaluating journeys made in shared mobility systems. The application of the model in practice will facilitate management and, above all, it is open to further updates. The use of many machine learning models will allow solving many problems that will occur in an increasing number of smart cities.
      Citation: Smart Cities
      PubDate: 2023-08-01
      DOI: 10.3390/smartcities6040086
      Issue No: Vol. 6, No. 4 (2023)
       
  • Smart Cities, Vol. 6, Pages 1879-1900: Drivers’ Experiences and
           Informed Opinions of Presence Sensitive Lighting Point towards the
           Feasibility of Introducing Adaptive Lighting in Roadway Contexts

    • Authors: Henrika Pihlajaniemi, Aale Luusua, Eveliina Juntunen
      First page: 1879
      Abstract: Applications of adaptive and intelligent lighting technologies such as presence sensitive lighting, potentially offer solutions for reducing the energy consumption of road lighting while maintaining user comfort and safety. However, little is known about road users’ experiences of such lighting. To address this gap, we conducted a real-world case study of a presence sensitive roadway lighting on a collector road in a housing area in southern Finland. New, controllable LED lighting with PIR (passive infrared) presence sensors was implemented along the road, and test scenarios were designed, programmed, and tested. The lighting was adapted both to motor vehicles using the road and to the measured traffic density along it. Drivers’ experiences and attitudes toward the lighting were collected in a three-phase evaluation with questionnaires from the community of about 1000 households using the road as part of their daily mobility. The results indicate that as an experience, presence sensitive lighting in a road environment was at least as positive as traditional, uncontrolled lighting. User experiences of presence sensitive lighting did not differ from the experiences of uncontrolled lighting regarding pleasantness, uniformity, glare, and road visibility. Most of the drivers (86%) did not notice any dynamic change in the lighting. When informed about the tested lighting strategies, most of the participants (72%) would prefer either one of the intelligent lighting modes to be the permanent lighting solution. The results of this exploratory, real-world study point towards the potential feasibility of this technology from a user experience perspective, as the experienced stability of the lighting was unaltered in the tested scenarios; importantly, it also highlights the need to study adaptive roadway lighting further, especially through confirmatory studies in controlled settings.
      Citation: Smart Cities
      PubDate: 2023-08-07
      DOI: 10.3390/smartcities6040087
      Issue No: Vol. 6, No. 4 (2023)
       
  • Smart Cities, Vol. 6, Pages 1901-1921: Towards the Cognitive Factory in
           Industry 5.0: From Concept to Implementation

    • Authors: Wagner Augusto Aranda Cotta, Sérgio Ivan Lopes, Raquel Frizera Vassallo
      First page: 1901
      Abstract: Industry 5.0 (I5.0) represents a shift towards a human-centered industry and emphasizes the integration of human and machine capabilities. A highly compatible concept for enabling the I5.0 implementation is intelligent spaces (ISs), i.e., physical spaces equipped with a network of sensors, which obtains information about the place it observes, and a network of actuators, which enables changes in the environment through computing services. These spaces can sense, interpret, recognize user behavior, adapt to preferences, and provide natural interactions between humans and intelligent systems, using the IoT, AI, computer vision, data analytics, etc., to create dynamic and adaptive environments in real time. The integration of ISs and I5.0 has paved the way for the development of cognitive factories, which transform industrial environments into ISs. In this context, this article explores the convergence of IS and I5.0 concepts and aims to provide insights into the technical implementation challenges of cognitive factories. It discusses the development and implementation of a laboratory replica of a cognitive cell as an example of a segment of a cognitive factory. By analyzing the key points and challenges associated with cognitive cell implementation, this article contributes to the knowledge base surrounding the advanced manufacturing paradigm of I5.0.
      Citation: Smart Cities
      PubDate: 2023-08-09
      DOI: 10.3390/smartcities6040088
      Issue No: Vol. 6, No. 4 (2023)
       
  • Smart Cities, Vol. 6, Pages 1922-1936: Renovation or Redevelopment: The
           Case of Smart Decision-Support in Aging Buildings

    • Authors: Bin Wu, Reza Maalek
      First page: 1922
      Abstract: In Germany, as in many developed countries, over 60% of buildings were constructed before 1978, where most are in critical condition, requiring either demolition with plans for redevelopment or renovation and rehabilitation. Given the urgency of climate action and relevant sustainable development goals set by the United Nations, more attention must be shifted toward the various sustainability aspects when deciding on a strategy for the renovation or redevelopment of existing buildings. To this end, this study focused on developing a smart decision support framework for aging buildings based on lifecycle sustainability considerations. The framework integrated digital technological advancements, such as building information modeling (BIM), point clouds processing with field information modeling (FIM)®, and structural optimization, together with lifecycle assessment to evaluate and rate the environmental impact of different solutions. Three sustainability aspects, namely, cost, energy consumption, and carbon emissions, were quantitatively evaluated and compared in two scenarios, namely, renovation, and demolition or deconstruction combined with redevelopment. A real building constructed in 1961 was the subject of the experiments to validate the framework. The result outlined the limitations and advantages of each method in terms of economics and sustainability. It was further observed that optimizing the building design with the goal of reducing embodied energy and carbon in compliance with modern energy standards was crucial to improving overall energy performance. This work demonstrated that the BIM-based framework developed to assess the environmental impact of rehabilitation work in aging buildings can provide effective ratings to guide decision-making in real-world projects.
      Citation: Smart Cities
      PubDate: 2023-08-10
      DOI: 10.3390/smartcities6040089
      Issue No: Vol. 6, No. 4 (2023)
       
  • Smart Cities, Vol. 6, Pages 1937-1957: A Spatio-Temporal Task Allocation
           Model in Mobile Crowdsensing Based on Knowledge Graph

    • Authors: Bingxu Zhao, Hongbin Dong, Dongmei Yang
      First page: 1937
      Abstract: With the increasing popularity of wireless networks and the development of smart cities, the Mobile Crowdsourcing System (MCS) has emerged as a framework for automatically assigning spatiotemporal tasks to workers. The study of mobile crowdsourcing makes a valuable research contribution to community service and urban route planning. However, previous algorithms have faced challenges in effectively addressing task allocation issues with massive spatial data. In this paper, we propose a novel solution to the spatiotemporal task allocation problem using a knowledge graph. Firstly, we construct a robust spatiotemporal knowledge graph (STKG) and employ a knowledge graph embedding algorithm to learn the representations of nodes and edges. Next, we utilize these representations to build a task transition graph, which is a weighted and learning-based graph that highlights important neighbors for each task. We then apply a simplified Graph Convolutional Network (GCN) and an RNN-based model to enhance task representations and capture sequential transition patterns on the task transition graph. Furthermore, we design a similarity function to facilitate personalized task allocation. Through experimental results, we demonstrate that our solution achieves higher accuracy compared to existing approaches when tested on three real datasets. These research findings are significant as they contribute to an 18.01% improvement in spatiotemporal task allocation accuracy.
      Citation: Smart Cities
      PubDate: 2023-08-10
      DOI: 10.3390/smartcities6040090
      Issue No: Vol. 6, No. 4 (2023)
       
  • Smart Cities, Vol. 6, Pages 1958-1972: Assessing the Progress of Smart
           Cities in Saudi Arabia

    • Authors: Abdulaziz Aldegheishem
      First page: 1958
      Abstract: Information and communication technology is changing the manner in which urban policies are designed. Saudi Arabia bases its smart initiative on the use of information and communication technologies in six dimensions, including economy, people, environment, living, mobility, and governance to improve quality of life and sustainable environment. This study draws on four Saudi Arabian cities including Riyadh, Makkah, Jeddah, and Medina, and aims to analyze their progress in the transformation into smart cities. The six identified areas were assessed using 57 indicators based on national and international information and literature. The results show that the four cities are progressing successfully into smart cities, with the highest progress evident for smart economy and the lowest progress for smart mobility in all investigated cities. Study findings show that Riyadh has made the most progress in the six smart city dimensions, concluding that Riyadh has been efficiently executing the smart city initiative with an aim to be a unique model in the world.
      Citation: Smart Cities
      PubDate: 2023-08-11
      DOI: 10.3390/smartcities6040091
      Issue No: Vol. 6, No. 4 (2023)
       
  • Smart Cities, Vol. 6, Pages 1973-1995: Digitalization and Smartification
           of Urban Services to Enhance Urban Resilience in the Post-Pandemic Era:
           The Case of the Pilgrimage City of Makkah

    • Authors: Yusuf A. Aina, Ismaila Rimi Abubakar, Abdulaziz I. Almulhim, Umar Lawal Dano, Mohammad Javad Maghsoodi Tilaki, Sharifah R. S. Dawood
      First page: 1973
      Abstract: The COVID-19 pandemic has significantly disrupted human socioeconomic activities, leaving an everlasting impact on urban systems. As a result, there is a growing scholarly focus on exploring how urban planning strategies and tools can help create resilient cities. In Saudi Arabia, the pilgrimage city of Makkah, which has always faced the challenge of managing crowds during the annual pilgrimage, was left deserted due to lockdowns and social distancing measures. To quickly revive socioeconomic and pilgrimage activities in the city, a set of digital tools and communication technologies were deployed to manage crowds and enforce social distancing to minimize the spread of the COVID-19 virus. This study examines the role of digitalization and smartification in reviving the city and the importance of context in building urban resilience. This study used desktop research and case study analysis to highlight the transformation to the new normal and the development of future smart technologies for the city. Smart solutions provided valuable support in reducing the impacts of the pandemic and restarting Makkah’s economy. Although most activities have been restored, some facilities and services are still operating below capacity. Digitalization and smartification of urban services could play a major role in improving service delivery and urban resilience.
      Citation: Smart Cities
      PubDate: 2023-08-11
      DOI: 10.3390/smartcities6040092
      Issue No: Vol. 6, No. 4 (2023)
       
  • Smart Cities, Vol. 6, Pages 1996-2034: The Making of Responsible
           Innovation and Technology: An Overview and Framework

    • Authors: Wenda Li, Tan Yigitcanlar, Will Browne, Alireza Nili
      First page: 1996
      Abstract: In an era in which technological advancements have a profound impact on our cities and societies, it is crucial to ensure that digital technology is not only driven by technological progress with economic goals but that it can also fulfill moral and social responsibilities. Hence, it is needed to advocate for ‘Responsible Innovation and Technology’ (RIT) to ensure cities and societies can harness the potential of technological progress and prosperity while safeguarding the well-being of individuals and communities. This study conducts a PRISMA review to explore and understand RIT concepts and its characteristics. In this study, we emphasize that RIT should deliver acceptable, accessible, trustworthy, and well governed technological outcomes, while ensuring these outcomes are aligned with societal desirability and human values, and should also be responsibly integrated into our cities and societies. The main contribution of this study is to identify and clarify the key characteristics of RIT, which has not been performed in such detail so far. The study, reported in this paper, also broadens the understanding of responsible research and innovation in the technosphere, particularly from a bottom-up perspective. Furthermore, the paper develops an RIT conceptual framework outlining its possible design procedures, which could be used by governments, companies, practitioners, researchers, and other stakeholders as a tool to address the grand challenges that accompany technological and scientific progress. The framework also informs science, technology, and innovation policy.
      Citation: Smart Cities
      PubDate: 2023-08-14
      DOI: 10.3390/smartcities6040093
      Issue No: Vol. 6, No. 4 (2023)
       
  • Smart Cities, Vol. 6, Pages 2035-2056: Data-Driven Approach for Urban
           Micromobility Enhancement through Safety Mapping and Intelligent Route
           Planning

    • Authors: Tiago Tamagusko, Matheus Gomes Correia, Luís Rita, Tudor-Codrin Bostan, Miguel Peliteiro, Rodrigo Martins, Luísa Santos, Adelino Ferreira
      First page: 2035
      Abstract: Micromobility responds to urban transport challenges by reducing emissions, mitigating traffic, and improving accessibility. Nevertheless, the safety of micromobility users, particularly cyclists, remains a concern in urban environments. This study aims to construct a safety map and a risk-averse routing system for micromobility users in diverse urban environments, as exemplified by a case study in Lisbon. A data-driven methodology uses object detection algorithms and image segmentation techniques to identify potential risk factors on cycling routes from Google Street View images. The ‘Bikeable’ Multilayer Perceptron neural network measures these risks, assigning safety scores to each image. The method analyzed 5321 points across 24 parishes in Lisbon, with an average safety score of 4.5, indicating a generally safe environment for cyclists. Carnide emerged as the safest area, while Alcântara exhibited a higher level of potential risks. Additionally, an equation is proposed to compute route efficiency, enabling comparisons between different routes for identical origin-destination pairs. Preliminary findings suggest that the presented routing solution exhibits higher efficiency than the commercial routing benchmark. Risk-averse routes did not result in a substantial rise in travel distance or time, with increments of 7% on average. The study also contributed to increasing the existing amount of cycle path data in Lisbon by 12%, correcting inaccuracies, and updating the network in OpenStreetMap, providing access to more precise information and, consequently, more routes. The key contributions of this study, such as the safety map and risk-averse router, underscore the potential of data-driven tools for boosting urban micromobility. The solutions proposed demonstrate modularity and adaptability, making them fit for a range of urban scenarios and highlighting their value for cities prioritizing safe, sustainable urban mobility.
      Citation: Smart Cities
      PubDate: 2023-08-17
      DOI: 10.3390/smartcities6040094
      Issue No: Vol. 6, No. 4 (2023)
       
  • Smart Cities, Vol. 6, Pages 2057-2080: Examining the Adoption of
           Sustainable eMobility-Sharing in Smart Communities: Diffusion of
           Innovation Theory Perspective

    • Authors: Anthony Jnr. Bokolo
      First page: 2057
      Abstract: The transport sector is undergoing disruption due to trends such as tightening environmental targets, digitalization, and servitization, contributing to low-carbon mobility and offering citizen-oriented services. As a response, various initiatives, such as electric mobility (eMobility), have emerged that promote sustainable road transport and active mobility in the last few years. However, irrespective of the potential of eMobility, there are still few studies that examine individuals’ intention and adoption of eMobility-sharing services in smart communities. Accordingly, this study aims to develop a model grounded on the Diffusion of Innovation (DoI) theory to investigate the factors that impact individuals’ adoption of eMobility-sharing service and how to improve the adoption of eMobility-sharing service. A mixed-mode methodology was employed; quantitative data from survey questionnaires were used to gather data, and Statistical Package for Social Science (SPSS) was used to analyze the data. Additionally, qualitative data via interview was collected to demonstrate in ArchiMate modeling language how eMobility-sharing services are practically implemented as a use case study within smart communities. Findings from this study offer a model that focuses on eMobility-sharing adoption from the perspective of smart communities. Additionally, the findings offer a better understanding of how such integrated, multimodal systems fit with the sustainable mobility needs of citizens. More importantly, general recommendations to policymakers and practitioners to increase the uptake of shared eMobility are provided.
      Citation: Smart Cities
      PubDate: 2023-08-17
      DOI: 10.3390/smartcities6040095
      Issue No: Vol. 6, No. 4 (2023)
       
  • Smart Cities, Vol. 6, Pages 2081-2105: Pseudolites to Support Location
           Services in Smart Cities: Review and Prospects

    • Authors: Tong Liu, Jian Liu, Jing Wang, Heng Zhang, Bing Zhang, Yongchao Ma, Mengfei Sun, Zhiping Lv, Guochang Xu
      First page: 2081
      Abstract: The location service is an important part of the smart city. A unified location service for outdoor and indoor/overground and underground activity will assist the construction of smart cities. However, with different coordinate systems and data formats, it is difficult to unify various positioning technologies on the same basis. Global navigation satellite system (GNSS)-based positioning is the only way to provide absolute location under the Earth-centered, Earth-fixed coordinate system (ECEF). Increasing indoor and underground human activity places significant demand on location-based services but no GNSS signals are available there. Fortunately, a type of satellite that is indoors, known as pseudolite, can transmit GNSS-like ranging signals. Users can obtain their position by receiving ranging signals and their resection without adding or switching other sensors when they go from outdoors to indoors. To complete the outreach of the GNSS indoors and underground to support the smart city, how to adapt the pseudolite design and unify coordinate frames for linking to the GNSS remain to be determined. In this regard, we provide an overview of the history of the research and application of pseudolites, the research progress from both the system side and the user side, and the plans for pseudolite-based location services in smart cities.
      Citation: Smart Cities
      PubDate: 2023-08-18
      DOI: 10.3390/smartcities6040096
      Issue No: Vol. 6, No. 4 (2023)
       
  • Smart Cities, Vol. 6, Pages 2106-2124: Knowledge Management for Smart
           Cities—Standardization and Replication as Policy Instruments to
           Foster the Implementation of Smart City Solutions

    • Authors: Patrick Ruess, René Lindner
      First page: 2106
      Abstract: As cities tackle a variety of recent challenges, such as climate change or resilience against natural hazards, the concept of smart cities has increasingly moved into the spotlight to provide technological solutions as appropriate countermeasures. European policymakers chose the systematic funding of smart city initiatives to incentivize and accelerate innovation and sustainability transitions by disseminating knowledge, data, and information. As this undertaking is complex, there is a pressing need to involve and engage capable stakeholders to successfully implement and operate smart city projects. To ensure the diffusion and effectiveness of these initiatives, activities towards replication and standardization as knowledge management instruments have been applied in some of these research projects. However, there is a knowledge gap on how standardization can be combined with replication efforts. As one possible answer, the lighthouse project Smarter Together has actively integrated standardization in its replication activities, resulting in the development of the CEN Workshop Agreement 17381 for describing and assessing smart city solutions. The analysis of these activities resulted in the development of 11 assumptions, which show the role of standardization as a knowledge carrier for replication activities and as a facilitator for stakeholder engagement. These findings reinforce the chosen and future policy decisions.
      Citation: Smart Cities
      PubDate: 2023-08-18
      DOI: 10.3390/smartcities6040097
      Issue No: Vol. 6, No. 4 (2023)
       
  • Smart Cities, Vol. 6, Pages 2125-2149: Profiling Citizens in the Smart
           City: A Quantitative Study in Wallonia

    • Authors: Clémentine Schelings, Aurore Defays, Catherine Elsen
      First page: 2125
      Abstract: Based on the assumption that citizens can participate in smart city development, this paper aims to capture the diversity of their profiles and their positioning towards smart city dynamics. The article starts with a literature review of some models of citizens to better understand how they could be portrayed in the smart city era. Considering that there is no “general citizen” and that usual typologies remain restrictive, we construct tailor-made personas, i.e., fictitious profiles based on real data. To this end, we present the results of a large-scale survey distributed to highly educated Walloon people in the framework of a general public exhibition. The profiling focuses on three aspects: (1) perception of smart city dimensions, (2) intended behavior regarding smart city solutions, and (3) favorite participatory methods. The collected answers were first analyzed with descriptive and nonparametric statistics, then classified with a k-means cluster analysis. The main results are five personas, which highlight the coexistence of different citizen groups that think and behave in a specific way. This process of profiling citizens’ priorities, behaviors, and participatory preferences can help professional designers and local governments to consider various citizens’ perspectives in the design of future smart solutions and participatory processes.
      Citation: Smart Cities
      PubDate: 2023-08-18
      DOI: 10.3390/smartcities6040098
      Issue No: Vol. 6, No. 4 (2023)
       
  • Smart Cities, Vol. 6, Pages 2150-2175: Development of a Maturity Model for
           Assessing Smart Cities: A Focus Area Maturity Model

    • Authors: Thajba Aljowder, Mazen Ali, Sherah Kurnia
      First page: 2150
      Abstract: The concept of smart cities has gained significant attention due to the potential of smart cities to optimize city services and enhance citizens’ quality of life. Cities are investing in digital transformation to become smarter, sustainable, and resilient. Therefore, there is a need to build a comprehensive and holistic model to assess smart city initiatives. This paper aims to develop a model that can capture the maturity of smart city adoption across various functional domains. These domains are divided into focus areas that capture different dimensions of a smart city and grouped into seven groups: ICT, economy, environment, social, resources, services, and governance. Each focus area has a set of maturity levels that describe the capabilities and outcomes of the city at different stages of development. To develop the model, the focus areas were extracted from the literature based on 16 models that have been reviewed. Assessing these models helped in identifying gaps and building the foundation of the model. Using the information extracted from the literature, a focus area model was designed and developed. The model development included seven main phases, which were: scope, design, populate, test, deploy, and maintain. The current paper validates the proposed model using the Delphi method, which involves the participation of a panel of sixty field experts. The experts evaluated the model’s correctness and completeness based on their experience and provided feedback. This feedback was used to revise and finalize the model. The smart city maturity model provides a framework for benchmarking, planning, and improving smart city initiatives. Cities can use the model to measure their performance and evaluate their weaknesses and strengths. The model is also the most comprehensive in terms of the scope of the focus areas included, and the results show that the model has a high level of accuracy and consistency and can effectively assess smart city adoption.
      Citation: Smart Cities
      PubDate: 2023-08-18
      DOI: 10.3390/smartcities6040099
      Issue No: Vol. 6, No. 4 (2023)
       
  • Smart Cities, Vol. 6, Pages 1227-1238: Mechanical, Structural, and
           Environmental Properties of Building Cements from Valorized Sewage Sludges
           

    • Authors: Rkia Zari, Abderrazzak Graich, Karima Abdelouahdi, Mohamed Monkade, Abdelaziz Laghzizil, Jean-Michel Nunzi
      First page: 1227
      Abstract: Building materials can enable the recycling of sewage sludge from tannery wastewater treatment by infiltration/percolation over coal and clay waste. The process avoids energy-intensive operations and yields a stable and environmentally friendly product. The sludge under study is mainly composed of SiO2, CaO, Al2O3, and Fe2O3, which is convenient to replace the mortar in cement. Different mortars were made by substituting a variable amount of sludge, from 0 to 30%, into the standard cement. The microstructure and mechanical properties of the mortar specimens were characterized after curing for 7 days and 28 days. The best properties were obtained with 15% sludge. Above 15%, the strength decreases at an early stage, as confirmed by SEM and XRD analysis, with more voids and ettringites at larger sludge content. The leaching tests of the mortar confirm that the cumulative values of heavy metals are far below the Deutsch regulatory limits (NEN 7043), justifying retention of the metals in the matrix. Radiological assessment of the sludge mortars also confirms their safety with the values of naturally occurring radioactive materials, surface radon exhalation and annual effective dose far below the required limits. The study suggests that 15% sludge can be used to sustainably replace cement and meet building safety requirement standards.
      Citation: Smart Cities
      PubDate: 2023-04-29
      DOI: 10.3390/smartcities6030059
      Issue No: Vol. 6, No. 3 (2023)
       
  • Smart Cities, Vol. 6, Pages 1239-1253: Can Bike-Sharing Reduce Car Use in
           Alexandroupolis' An Exploration through the Comparison of Discrete Choice
           and Machine Learning Models

    • Authors: Santhanakrishnan Narayanan, Nikita Makarov, Evripidis Magkos, Josep Maria Salanova Grau, Georgia Aifadopoulou, Constantinos Antoniou
      First page: 1239
      Abstract: The implementation of bike-sharing systems (BSSs) is expected to lead to modifications in the travel habits of transport users, one of which is the choice of travel mode. Therefore, this research focuses on the identification of factors influencing the shift of private car users to BSSs based on stated preference survey data from the city of Alexandroupolis, Greece. A binary logit model is employed for this purpose. The estimation results indicate the impacts of gender, income, travel time, travel cost and safety-related aspects on the mode shift, through which behavioural insights are derived. For example, car users are found to be twice as sensitive to the cost of BSSs than to that of car. Similarly, they are highly sensitive to BSS travel time. Based on the behavioural findings, policy measures are suggested under the following categories: (i) finance, (ii) regulation, (iii) infrastructure, (iv) campaigns and (v) customer targeting. In addition, a secondary objective of this research is to obtain insights from the comparison of the specified logit model with a machine learning approach, as the latter is slowly gaining prominence in the field of transport. For the comparison, a random forest classifier is also developed. This comparison shows a coherence between the two approaches, although a discrepancy in the feature importance for gender and travel time is observed. A deeper exploration of this discrepancy highlights the hurdles that often occur when using mathematically more powerful models, such as the random forest classifier.
      Citation: Smart Cities
      PubDate: 2023-04-30
      DOI: 10.3390/smartcities6030060
      Issue No: Vol. 6, No. 3 (2023)
       
  • Smart Cities, Vol. 6, Pages 1254-1278: Blockchain-Based Business Process
           Management (BPM) for Finance: The Case of Credit and Claim Requests

    • Authors: Bálint Molnár, Galena Pisoni, Meriem Kherbouche, Yossra Zghal
      First page: 1254
      Abstract: Because of the competitive economy, organizations today seek to rationalize, innovate, and adapt to changing environments and circumstances as part of business process improvement efforts. The strength of blockchain technology lies in its usage as an apt technology to enhance the efficiency and effectiveness of business processes; furthermore, it prevents the use of erroneous or obsolete data and allows sharing of confidential data securely. The use of superior technology in the execution and automation of business processes brings opportunities to rethink the specific process itself as well. Business processes modeling and verification are essential to control and assure organizational evolution, therefore, the aim of this paper is three-fold: firstly, to provide business process management patterns in finance, based on blockchain, specifically for the loan-application process in the banking industry and claim process in the insurance industry that could be used and customized by companies; secondly, to critically analyze challenges and opportunities from the introduction of such approach for companies, and thirdly, to outline how companies can implement the loan business process as a web service. Partner companies (a bank and an insurance company) formulated the potential requirements for M2P along with the application of blockchain technology. An experimental design framework was established that gave the necessary services to model the requirements, check the models, and operationalize the models. The applied research methodologies are as follows: design science research paradigm and software case study, model-to-programming (M2P) of business processes, and utilization of patterns of workflow and blockchain.
      Citation: Smart Cities
      PubDate: 2023-05-03
      DOI: 10.3390/smartcities6030061
      Issue No: Vol. 6, No. 3 (2023)
       
  • Smart Cities, Vol. 6, Pages 1279-1302: Stormwater Sewerage Masterplan for
           Flood Control Applied to a University Campus

    • Authors: Bethy Merchán-Sanmartín, Paúl Carrión-Mero, Sebastián Suárez-Zamora, Maribel Aguilar-Aguilar, Omar Cruz-Cabrera, Katherine Hidalgo-Calva, Fernando Morante-Carballo
      First page: 1279
      Abstract: Floods generated by rain cause significant economic and human losses. The campus of the Escuela Superior Politécnica del Litoral (ESPOL) has a drainage system that conducts stormwater to two discharge points outside the campus. The system works effectively at the macro-drainage level. However, a very crowded area is deficient at the micro-drainage level, which has registered flooding and the proliferation of vectors that affect people’s health. This work aimed to design a masterplan for stormwater sewerage by analyzing the existing situation and applying technical criteria that allow the establishment of solutions and strategies to control floods at the university campus. The methodology consisted of: (i) data collection and processing for the stormwater drainage system diagnosis; (ii) a design proposal for micro-drainage and (iii) a SWOT analysis to propose improvement strategies in water management. The resulting flows for return periods of 5 years, 10 years, and 25 years are 9.67 m3/s, 11.85 m3/s, and 15.85 m3/s, respectively. In the latter, as the most critical area (presence of flooding), the implementation of a trapezoidal channel 80.20 m long, with a capacity of 1.00 m3/s, for a return period of 25 years was proposed. The stormwater masterplan will contribute to the execution of activities within the campus and prevent accidents and the proliferation of diseases, constituting a water-management model that can be replicated locally, regionally, and internationally.
      Citation: Smart Cities
      PubDate: 2023-05-09
      DOI: 10.3390/smartcities6030062
      Issue No: Vol. 6, No. 3 (2023)
       
  • Smart Cities, Vol. 6, Pages 1303-1324: Dynamic Pricing for the Open Online
           Ticket System: A Surrogate Modeling Approach

    • Authors: Elizaveta Stavinova, Ilyas Varshavskiy, Petr Chunaev, Ivan Derevitskii, Alexander Boukhanovsky
      First page: 1303
      Abstract: Dynamic pricing is frequently used in online marketplaces, ticket sales, and booking systems. The commercial principles of dynamic pricing systems are often kept secret; however, their application causes complex changes in human behavior. Thus, a scientific tool is needed to evaluate and predict the impact of dynamic pricing strategies. Publications in the field lack a common quality evaluation methodology, public data, and source code, making them difficult to reproduce. In this paper, a data-driven method, DPRank, for evaluating dynamic pricing systems is proposed. DPRank first builds a surrogate price elasticity of demand model using public data generated by a hidden dynamic pricing model, and then applies the surrogate model to build an exposed dynamic pricing model. The hidden and exposed dynamic pricing models were then systematically compared in terms of quality using a Monte Carlo simulation in terms of a company’s revenue. The effectiveness of the proposed method was tested on the dataset collected from the website of a Russian railway passenger carrier company. Depending on the train type, the quality difference between the hidden and exposed models can vary by several dozen percent on average, indicating the potential for improving the existing (hidden) company’s dynamic pricing model.
      Citation: Smart Cities
      PubDate: 2023-05-09
      DOI: 10.3390/smartcities6030063
      Issue No: Vol. 6, No. 3 (2023)
       
  • Smart Cities, Vol. 6, Pages 1325-1344: Perceptions and Attitudes toward
           Risks of City Administration Employees in the Context of Smart City
           Management

    • Authors: Karolina Wielicka-Gańczarczyk, Izabela Jonek-Kowalska
      First page: 1325
      Abstract: Smart cities are required to be effectively and efficiently managed in order to ensure the desired level of sustainability and quality of life for all inhabitants. This is a particularly difficult challenge in crisis situations of considerable scale and intensity (for example, the COVID-19 pandemic, armed conflicts, social tensions). For this reason, the aim of this article is to identify the attitudes and perceptions of risk by city administration employees combined with an assessment of their impact on the consequences of risk (the implementation of internal and external threats). The analyses used the results of a survey conducted on a representative sample of 399 Polish municipal offices, as well as descriptive statistics and structural equation modeling. The obtained results show that: (1) employees of municipal offices negatively perceive risk and are aware of its destructive impact on the organization, but are reluctant to report the risks; (2) individual and collective measures are taken in offices to protect against risks, but employees are not always encouraged to report potential sources of risk (rarely in the form of an informal conversation and even more rarely in a systemic form); (3) for the most part, employees are aware that internal and external risks have a negative impact on the operation of municipal offices; (4) the consequences of risks are more strongly influenced by employees’ perceptions of risk than by individual, team, and systemic attitudes toward risk. The added value of the research presented in this article comes from diagnosing the behavioral aspects of urban risk management and assessing the impact of attitudes toward risks and risk perceptions (internal and external) in a broad, representative range.
      Citation: Smart Cities
      PubDate: 2023-05-10
      DOI: 10.3390/smartcities6030064
      Issue No: Vol. 6, No. 3 (2023)
       
  • Smart Cities, Vol. 6, Pages 1345-1384: The Metaverse as a Virtual Model of
           Platform Urbanism: Its Converging AIoT, XReality, Neurotech, and
           Nanobiotech and Their Applications, Challenges, and Risks

    • Authors: Simon Elias Bibri
      First page: 1345
      Abstract: With their exponentially rising computational power, digital platforms are heralding a new era of hybrid intelligence. There has recently been much enthusiasm and hype that the Metaverse has the potential to unlock hybrid intelligence. This is premised on the idea that the Metaverse represents an applied convergence of Artificial Intelligence of Things (AIoT) and Extended Reality (XR) that intersects with urbanism in terms of the distinctive features of platform-mediated everyday life experiences in cities. However, social interaction and its resulting social organization in the Metaverse are mediated and governed by algorithms and thus submitted to—a dream of—complete logical ordering. This raises a plethora of concerns related to the systemic collection and algorithmic processing of users’ personal, brain, and biometric data, i.e., profound societal—and the hardest to predict ethical—implications. Therefore, this study analyzes and synthesizes a large body of scientific literature on the unfolding convergence of AIoT and XR technologies, neurotechnology, and nanobiotechnology in the realm of the Metaverse in order to derive a novel conceptual framework for the Metaverse as an envisioned virtual model of platform urbanism. Further, it examines the key challenges and risks of these converging technologies in relation to the Metaverse and beyond. This study employs thematic analysis and synthesis to cope with multidisciplinary literature. The analysis identifies seven themes: (1) Platformization, (2) platform urbanism, (3) virtual urbanism, (4) XR technologies, (5) AIoT technologies, (6) neurotechnology, and (7) nanobiotechnology. The synthesized evidence reveals that, while neurotechnology and nanobiotechnology have numerous benefits and promising prospects, they raise contentions and controversies stemming from their potential use to inflict harm to human users—if left unchecked—through the black box of the algorithmic mediation underpinning the Metaverse. The findings serve to steer the Metaverse to contribute to human flourishing and wellbeing by adhering to and upholding ethical principles as well as leveraging its underlying disruptive technologies in meaningful ways. They also aid scholars, practitioners, and policymakers in assessing the pros and cons of these technologies, especially their inevitable ramifications.
      Citation: Smart Cities
      PubDate: 2023-05-11
      DOI: 10.3390/smartcities6030065
      Issue No: Vol. 6, No. 3 (2023)
       
  • Smart Cities, Vol. 6, Pages 1385-1397: The Concept of Learning Cities:
           Supporting Lifelong Learning through the Use of Smart Tools

    • Authors: Ionelia Hirju, Radu-Ionut Georgescu
      First page: 1385
      Abstract: This paper presents an initiative in which QR codes on public transport are used to provide citizens with books that they can read and that will improve their general knowledge. It builds on the concept of the learning city and combines it with smart city tools. This paper aims to use a descriptive–empirical approach, including an experiment in Bucharest. This research aims to contribute to the academic world, urban sociology, public administration, and lifelong learning education.
      Citation: Smart Cities
      PubDate: 2023-05-14
      DOI: 10.3390/smartcities6030066
      Issue No: Vol. 6, No. 3 (2023)
       
  • Smart Cities, Vol. 6, Pages 1398-1415: From Traffic Congestion to
           Sustainable Mobility: A Case Study of Public Transport in Odesa, Ukraine

    • Authors: Sergii Myronenko, Hennadii Oborskyi, Dmytro Dmytryshyn, Vyacheslav Shobik, Dirk Lauwers, Frank Witlox
      First page: 1398
      Abstract: Consistent and reliable information on passenger traffic is considered crucial for the efficient operation of the public transport (PT) network. The PT network is used to improve public services and thus attract more passengers. This study evaluated the passenger traffic in Odesa, Ukraine, due to the inefficient urban transport system. The main aim of this study was to make PT better by examining passenger distribution on traffic routes and specifying characteristics of PT travel influencing individual satisfaction. The metric-tabular method was used to collect data and examine the number of incoming and outgoing passengers at each bus stop. The results of the passenger and PT analysis provide valuable recommendations for optimizing future routes. It is beneficial for transport companies to implement such recommendations so that inefficient transport on the route can be reduced by either reforming the route network or choosing the optimal number of buses. According to the findings of this study, understanding PT services is the most important determinant of PT adoption. The main implications of the findings are of particular interest to policymakers who develop policies in the field of passenger transport and also to transport scientists and students.
      Citation: Smart Cities
      PubDate: 2023-05-19
      DOI: 10.3390/smartcities6030067
      Issue No: Vol. 6, No. 3 (2023)
       
  • Smart Cities, Vol. 6, Pages 1416-1434: A Cloud-Based Data Storage and
           Visualization Tool for Smart City IoT: Flood Warning as an Example
           Application

    • Authors: Victor Ariel Leal Sobral, Jacob Nelson, Loza Asmare, Abdullah Mahmood, Glen Mitchell, Kwadwo Tenkorang, Conor Todd, Bradford Campbell, Jonathan L. Goodall
      First page: 1416
      Abstract: Collecting, storing, and providing access to Internet of Things (IoT) data are fundamental tasks to many smart city projects. However, developing and integrating IoT systems is still a significant barrier to entry. In this work, we share insights on the development of cloud data storage and visualization tools for IoT smart city applications using flood warning as an example application. The developed system incorporates scalable, autonomous, and inexpensive features that allow users to monitor real-time environmental conditions, and to create threshold-based alert notifications. Built in Amazon Web Services (AWS), the system leverages serverless technology for sensor data backup, a relational database for data management, and a graphical user interface (GUI) for data visualizations and alerts. A RESTful API allows for easy integration with web-based development environments, such as Jupyter notebooks, for advanced data analysis. The system can ingest data from LoRaWAN sensors deployed using The Things Network (TTN). A cost analysis can support users’ planning and decision-making when deploying the system for different use cases. A proof-of-concept demonstration of the system was built with river and weather sensors deployed in a flood prone suburban watershed in the city of Charlottesville, Virginia.
      Citation: Smart Cities
      PubDate: 2023-05-19
      DOI: 10.3390/smartcities6030068
      Issue No: Vol. 6, No. 3 (2023)
       
  • Smart Cities, Vol. 6, Pages 1435-1484: State-of-the-Art Review on
           Shipboard Microgrids: Architecture, Control, Management, Protection, and
           Future Perspectives

    • Authors: Asmaa M. Aboelezz, Bishoy E. Sedhom, Magdi M. El-Saadawi, Abdelfattah A. Eladl, Pierluigi Siano
      First page: 1435
      Abstract: Shipboard microgrids (SBMGs) are becoming increasingly popular in the power industry due to their potential for reducing fossil-fuel usage and increasing power production. However, operating SBMGs poses significant challenges due to operational and environmental constraints. To address these challenges, intelligent control, management, and protection strategies are necessary to ensure safe operation under complex and uncertain conditions. This paper provides a comprehensive review of SBMGs, including their classifications, control, management, and protection, as well as the most recent research statistics in these areas. The state-of-the-art SBMG types, propulsion systems, and power system architectures are discussed, along with a comparison of recent research contributions and issues related to control, uncertainties, management, and protection in SBMGs. In addition, a bibliometric analysis is performed to examine recent trends in SBMG research. This paper concludes with a discussion of research gaps and recommendations for further investigation in the field of SBMGs, highlighting the need for more research on the optimization of SBMGs in terms of efficiency, reliability, and cost-effectiveness, as well as the development of advanced control and protection strategies to ensure safe and stable operation.
      Citation: Smart Cities
      PubDate: 2023-05-22
      DOI: 10.3390/smartcities6030069
      Issue No: Vol. 6, No. 3 (2023)
       
  • Smart Cities, Vol. 6, Pages 1485-1506: Generating Natural Cities Using 3D
           Road Network to Explore Living Structure: A Case Study in Hong Kong

    • Authors: Zhiyang Xiao, Zhenhan Peng, Zidong Yu, Xintao Liu
      First page: 1485
      Abstract: Compared with administrative cities, natural cities can be generally referred to as the areas generated based on the density of different urban facilities (e.g., point of interest, road network, etc.). To some extent, natural cities are outperformed in some related urban studies, such as urban living structure analysis. Nevertheless, traditional ways of generating natural cities are mostly limited to the planar space. Modern cities such as Hong Kong are vertical cities with high buildings, 3D road networks and land uses. Therefore, traditional nature cities could be biased when applied to 3D cities. In this work, a 3D road network in Hong Kong is adopted to extract true road intersections and generate modified natural cities to explore urban living structures. Numerous living structure units are classified into two parts: tiny and serried ones representing natural cities and vast ones representing rural areas. The classification method applies head/tail breaks, and a clustering algorithm was fitted for heavy-tailed distribution. According to the living structure theory, the living structures of the proposed natural cities and traditional natural cities based on the same road network in Hong Kong are compared. The findings show that the distribution of modified natural city regions is more reasonable compared with typical ones. The improved model will more clearly show the inherent living structure of the city and will allow an analysis of the relationship between the part and wholeness of the city.
      Citation: Smart Cities
      PubDate: 2023-05-24
      DOI: 10.3390/smartcities6030070
      Issue No: Vol. 6, No. 3 (2023)
       
  • Smart Cities, Vol. 6, Pages 1507-1522: IoT-Based Segregation with Location
           Tracking and Air Quality Monitoring for Smart Cities

    • Authors: Abhishek Kadalagere Lingaraju, Mudligiriyappa Niranjanamurthy, Priyanka Bose, Biswaranjan Acharya, Vassilis C. Gerogiannis, Andreas Kanavos, Stella Manika
      First page: 1507
      Abstract: Massive human population, coupled with rapid urbanization, results in a substantial amount of garbage that requires daily collection. In urban areas, garbage often accumulates around dustbins without proper disposal at regular intervals, creating an unsanitary environment for humans, plants, and animals. This situation significantly degrades the environment. To address this problem, a Smart Waste Management System is introduced in this paper, employing machine learning techniques for air quality level classification. Furthermore, this system safeguards garbage collectors from severe health issues caused by inhaling harmful gases emitted from the waste. The proposed system not only proves cost-effective but also enhances waste management productivity by categorizing waste into three types: wet, dry, and metallic. Ultimately, by leveraging machine learning techniques, we can classify air quality levels and garbage weight into distinct categories. This system is beneficial for improving the well-being of individuals residing in close proximity to dustbins, as it enables constant monitoring and reporting of air quality to relevant city authorities.
      Citation: Smart Cities
      PubDate: 2023-05-27
      DOI: 10.3390/smartcities6030071
      Issue No: Vol. 6, No. 3 (2023)
       
  • Smart Cities, Vol. 6, Pages 1523-1544: Exploring the Challenges and Issues
           in Adopting Cybersecurity in Saudi Smart Cities: Conceptualization of the
           Cybersecurity-Based UTAUT Model

    • Authors: Nawaf Alhalafi, Prakash Veeraraghavan
      First page: 1523
      Abstract: This study aims to explore the challenges and issues in adopting cybersecurity practices in smart Saudi cities and to develop and validate a newly developed cybersecurity-based unified theory of acceptance and use of technology 3 (UTAUT3) model. The study has a twofold purpose. First, it identified the key challenges and issues in adopting smart cities in Saudi smart cities. Second, it developed a technology-based model to adopt cybersecurity practices in Saudi smart cities. Two surveys were conducted to achieve these objectives. The first survey identified challenges and gaps in adopting cybersecurity practices in smart cities, revealing concerns about weak cybersecurity platforms, privacy breaches, and the impact of IT infrastructure advancements on Saudi culture (N = 554: common public). The second survey focused on developing and validating a cybersecurity-based UTAUT3 model (N = 108: IT professionals), emphasizing nine factors: performance expectancy, effort expectancy, social influence, facilitating conditions, safety, resiliency, availability, confidentiality, and integrity of cybersecurity. The model’s validity and reliability were assessed, demonstrating its potential for understanding user behavior and adoption patterns in smart cities. The study findings provide valuable insights into the factors influencing the adoption of cybersecurity measures in smart Saudi cities, highlighting the need for targeted strategies, effective awareness programs, and collaboration between stakeholders to promote a secure and resilient digital environment. Future research may focus on refining the model, extending its applicability to other regions or countries, and investigating the impact of emerging technologies and evolving cyber threats on user behavior and cybersecurity practices.
      Citation: Smart Cities
      PubDate: 2023-05-29
      DOI: 10.3390/smartcities6030072
      Issue No: Vol. 6, No. 3 (2023)
       
  • Smart Cities, Vol. 6, Pages 1545-1559: Innovations in Shared
           Mobility—Review of Scientific Works

    • Authors: Katarzyna Turoń, János Tóth
      First page: 1545
      Abstract: Shared mobility is developing at a very fast pace around the world, becoming an alternative to classic forms of travel and, according to the public, providing innovative services. In recent years, these innovative services have also gained wide interest among scientists from a multicriteria point of view. However, among the topics and reviews in the literature, no review paper considering shared mobility in terms of innovation was identified. This article’s research objective was to indicate the perception of innovation in shared mobility in scientific works. The results indicate that innovations in shared mobility are a niche topic considered in few scientific works. What is more, in most cases, shared mobility services are perceived as innovative in themselves without detailed service analysis. Moreover, the issues of open innovation, which are closely related to the concept of accessible Mobility as a Service system and smart cities, are often overlooked. In addition, there was no work identified that fully referred to all areas of innovative service. The article supports researchers in the determination of further research directions in the field of shared mobility and fills the research gap in the field of knowledge about open innovation, especially in the context of the development of shared mobility services in smart cities.
      Citation: Smart Cities
      PubDate: 2023-05-29
      DOI: 10.3390/smartcities6030073
      Issue No: Vol. 6, No. 3 (2023)
       
  • Smart Cities, Vol. 6, Pages 1560-1588: Blue Seaports: The Smart,
           Sustainable and Electrified Ports of the Future

    • Authors: Daniel Clemente, Tomás Cabral, Paulo Rosa-Santos, Francisco Taveira-Pinto
      First page: 1560
      Abstract: Seaports are at the forefront of global trade networks, serving as hubs for maritime logistics and the transportation of goods and people. To meet the requirements of such networks, seaport authorities are investing in advanced technologies to enhance the efficiency and reliability of port infrastructures. This can be achieved through the digitalization and automation of core systems, aimed at optimizing the management and handling of both goods and people. Furthermore, a significant effort is being made towards a green energy transition at seaports, which can be supported through marine renewable sources. This promotes energy-mix diversification and autonomy, whilst reducing the noteworthy environmental footprint of seaport activities. By analyzing these pertinent topics under the scope of a review of container-terminal case studies, and these ports’ respective contexts, this paper seeks to identify pioneering smart seaports in the fields of automation, real-time management, connectivity and accessibility control. To foster the sustainable development of seaports, from an energy perspective, the potential integration with marine renewable-energy systems is considered, as well as their capabilities for meeting, even if only partially, the energy demands of seaports. By combining these fields, we attempt to construct a holistic proposal for a “model port” representing the expected evolution towards the seaports of the future.
      Citation: Smart Cities
      PubDate: 2023-06-05
      DOI: 10.3390/smartcities6030074
      Issue No: Vol. 6, No. 3 (2023)
       
  • Smart Cities, Vol. 6, Pages 1589-1611: Optimization of Taxi Allocation for
           Minimizing CO2 Emissions Based on Heuristics Algorithms

    • Authors: Manik Mondal, Kazushi Sano, Teppei Kato, Chonnipa Puppateravanit
      First page: 1589
      Abstract: Recently, the rapid climate change caused by increasing CO2 emissions has become a global concern. Efficient transportation systems are necessary to reduce CO2 emissions in cities. Taxi services are an essential part of the transportation system, both in urban areas with high demand and in rural areas with inadequate public transportation. Inefficient taxi services cause problems such as increased idle times, resulting in increased CO2 emissions. This study proposes a taxi allocation model that minimizes taxi idle time costs for efficient taxi service operation. We also propose three heuristic algorithms to solve the proposed model. At last, we conduct a case study by using real taxi data in Nagaoka, Japan. By comparing the three algorithms, the dynamic greedy algorithm produced the best result in terms of idle time cost and CPU time. The findings indicate that by minimizing idle time costs and reducing the number of taxis, it is possible to achieve a significant 81.84% reduction in CO2 emissions within the transportation sector. Further, in order to estimate the idle time costs the sensitivity of demand is considered.
      Citation: Smart Cities
      PubDate: 2023-06-09
      DOI: 10.3390/smartcities6030075
      Issue No: Vol. 6, No. 3 (2023)
       
  • Smart Cities, Vol. 6, Pages 1612-1629: Small-Scale Ship Detection for SAR
           Remote Sensing Images Based on Coordinate-Aware Mixed Attention and
           Spatial Semantic Joint Context

    • Authors: Zhengjie Jiang, Yupei Wang, Xiaoqi Zhou, Liang Chen, Yuan Chang, Dongsheng Song, Hao Shi
      First page: 1612
      Abstract: With the rapid development of deep learning technology in recent years, convolutional neural networks have gained remarkable progress in SAR ship detection tasks. However, noise interference of the background and inadequate appearance features of small-scale objects still pose challenges. To tackle these issues, we propose a small ship detection algorithm for SAR images by means of a coordinate-aware mixed attention mechanism and spatial semantic joint context method. First, the coordinate-aware mixed attention mechanism innovatively combines coordinate-aware channel attention and spatial attention to achieve coordinate alignment of mixed attention features. In this way, attention with finer spatial granularity is conducive to strengthening the focusing ability on small-scale objects, thereby suppressing the background clutters accurately. In addition, the spatial semantic joint context method exploits the local and global environmental information jointly. The detailed spatial cues contained in the multi-scale local context and the generalized semantic information encoded in the global context are used to enhance the feature expression and distinctiveness of small-scale ship objects. Extensive experiments are conducted on the LS-SSDD-v1.0 and the HRSID dataset. The results with an average precision of 77.23% and 90.85% on the two datasets show the effectiveness of the proposed methods.
      Citation: Smart Cities
      PubDate: 2023-06-15
      DOI: 10.3390/smartcities6030076
      Issue No: Vol. 6, No. 3 (2023)
       
  • Smart Cities, Vol. 6, Pages 1043-1058: “15-Minute City” and
           Elderly People: Thinking about Healthy Cities

    • Authors: Felipe Ulloa-Leon, Juan Correa-Parra, Francisco Vergara-Perucich, Francisca Cancino-Contreras, Carlos Aguirre-Nuñez
      First page: 1043
      Abstract: Considering the global scenario of population aging, which countries such as Chile are going through, the social problems that it means in terms of viability and quality of life for the elderly are increasing and are a cause for concern. For this reason, this study summarizes the results of investigating the accessibility of services and recreational spaces under the parameters of a “15-minute city” for the elderly people in the city of Santiago de Chile. The investigation employed a multivariate geostatistical analysis with a quantitative approach and was developed on a census block scale to test some of the principles of the 15-min city along with the principles on active aging of the elderly. The results are surprising, show a good territorial coverage for the study area and open the possibility of Santiago becoming a 15-min city for older adults. However, there are still several challenges in terms of public policies, from mental and physical health to the design of public spaces, which are fundamental to think about for cities of the future.
      Citation: Smart Cities
      PubDate: 2023-03-20
      DOI: 10.3390/smartcities6020050
      Issue No: Vol. 6, No. 2 (2023)
       
  • Smart Cities, Vol. 6, Pages 1059-1086: Impacts of Product Variety and
           Supply Chain Networks on the Influx of Information Exchange in Industry
           Applications

    • Authors: Estu Rizky Huddiniah, Hilmil Pradana
      First page: 1059
      Abstract: Managing product variety is a challenging problem given the increasing complexity of supply chain networks. To overcome this complexity, managing integration in the supply chain is essential for companies to coordinate effectively. By managing the influx of information exchange between the various entities involved in the supply chain network, integration can be achieved successfully. In this paper, we are targeting research questions regarding the impact of the influx of information exchange on product variety and supply chain networks and the key factors influencing its exchange from different industries’ perspectives. To investigate our research questions and to conduct a case study across different industries and companies, this study aims to explore the impact of supply chain network complexity, which causes an influx of information exchange due to increasing product variety through qualitative research. In our results, by categorizing the raw interview data, we visualize correspondent opinions to facilitate deep analysis, including factors such as product variety, supply chain networks, and information exchange. The key factors that can influence the influx of information exchange from different industries’ and companies’ perspectives are presented in our results to provide valuable insights into the significant factors affecting the success of the smart business.
      Citation: Smart Cities
      PubDate: 2023-04-03
      DOI: 10.3390/smartcities6020051
      Issue No: Vol. 6, No. 2 (2023)
       
  • Smart Cities, Vol. 6, Pages 1087-1108: Smart City Transformation: An
           Analysis of Dhaka and Its Challenges and Opportunities

    • Authors: Ashish Kumar Karmaker, S M Rezwanul Islam, Md Kamruzzaman, Md Mamun Ur Rashid, Md Omer Faruque, Md Alamgir Hossain
      First page: 1087
      Abstract: Cities worldwide are experiencing rapid urbanization and an increasing population, creating a pressing need for smart infrastructure to enhance citizen services. Dhaka, the capital of Bangladesh, faces similar technological and socio-economic challenges, making it crucial to transform it into a sustainable smart city. This research analyzes the opportunities and challenges of smart cities and Dhaka through SWOT and PESTEL analyses. The study employs a fuzzy rule-based inference system in a MATLAB simulation to calculate the smart city index based on parameters such as governance, transportation, waste management, utility management, healthcare, and industrial automation. The findings reveal that good governance has the highest impact on the smart city index, followed by transportation. The paper proposes a sustainable smart city transportation framework and management technique, outlining future research directions. The proposed framework is expected to impact socio-economic, technological, and environmental aspects positively.
      Citation: Smart Cities
      PubDate: 2023-04-07
      DOI: 10.3390/smartcities6020052
      Issue No: Vol. 6, No. 2 (2023)
       
  • Smart Cities, Vol. 6, Pages 1109-1131: Effects and Externalities of Smart
           Governance

    • Authors: Yelena Popova, Sergejs Popovs
      First page: 1109
      Abstract: The concept of a smart city is widely implemented all over the world, and this fact creates both possibilities and new challenges for all participants and stakeholders of the process. This study examines the implementation of smart governance in the context of smart cities. The goal of the research is to distinguish between the effects and externalities of the smart governance domain, both positive and negative ones; the effects and externalities are elicited from the outcomes of smart governance implementation revealed from a review of scientific publications devoted to the results, barriers, and facilitators of smart governance functioning. The publications were selected according to a systematic review methodology, then the selected articles were analyzed and the factors that foster the processes of smart governance implementation (facilitators) or vice versa hamper the acquisition of results (barriers), as well as the outcomes of smart governance, were extracted. The extracted factors were attributed to six areas: Information, Efficiency, Citizen-Centricity, Transparency, Digital Divide, and Regulation. Further, the outcomes of smart governance implementation were distinguished as effects and externalities, which were both positive and negative.
      Citation: Smart Cities
      PubDate: 2023-04-12
      DOI: 10.3390/smartcities6020053
      Issue No: Vol. 6, No. 2 (2023)
       
  • Smart Cities, Vol. 6, Pages 1132-1151: AHSS—Construction
           Material Used in Smart Cities

    • Authors: Bożena Szczucka-Lasota, Tomasz Węgrzyn, Abílio Pereira Silva, Adam Jurek
      First page: 1132
      Abstract: With the level of development of the smart city, there are more and more research sub-areas in which the latest material and technological solutions are used, enabling the proper management and functioning of these cities. On the one hand, the introduced materials and technologies are designed to facilitate the functioning of residents both in the urban space and at home; on the other hand, the implemented solutions strive to be consistent with the principles of sustainable development. As shown in this article, reports on new technical and technological solutions and their positive and negative effects are strongly emphasized in publications on the development of smart cities. The most highlighted materials research in the smart city area concerns smart materials and their characteristics and applications. A research gap in this area is in the presentation of material solutions, particularly materials intended for the load-bearing structures of vehicles (electric vehicles, flying vehicles) or infrastructure elements (buildings, shelters, etc.) designed to increase the durability of the structure while reducing its weight. This paper aims to comprehensively present the most important research areas related to the functioning of smart cities in light of previous research, with particular emphasis on new material solutions used for thin-walled load-bearing structures in smart cities made of AHSS (advanced high-strength steel). These solutions are very essential for smart cities because their use allows for the installation of additional devices, sensors, transmitters, antennas, etc., without increasing the total weight of the structure; they reduce the number of raw materials used for production (lighter and durable thin structures), ensure lower energy consumption (e.g., lighter vehicles), and also increase the passive safety of systems or increase their lifting capacity (e.g., the possibility of transporting more people using transports at the same time; the possibility of designing and arranging, e.g., green gardens on buildings; etc.). AHSS-welded joints are usually characterized by too-low strength in the base material or a tendency to crack. Thus, the research problem is producing a light and durable AHSS structure using welding processes. The research presented in this article concerns the possibility of producing welded joints using the Metal Active Gas (MAG) process. The test methods include the assessment of the quality of joints, such as through visual examination (VT); according to the requirements of PN-EN ISO 17638; magnetic particle testing (MT); according to PN-EN ISO 17638; and the assessment of the selected mechanical properties, such as tensile strength tests, bending tests, and fatigue strength checks. These methods enable the selection of the correct joints, without welding defects. The results have a practical implication; advanced production technology for obtaining AHSS joints can be used in the construction of the load-bearing elements of mobile vehicles or parts of point infrastructure (shelters, bus stops). The obtained joint is characterized by adequate strength for the production of the assumed structures. The originality of the manuscript is the presentation of a new, cheaper, and uncomplicated solution for obtaining an AHSS joint with good mechanical properties. The application of the presented solution also contributes to sustainable development (lower fuel and material consumption use by mobile vehicles) and may contribute to increasing the load capacity of mobile vehicles (the possibility of transporting more people).
      Citation: Smart Cities
      PubDate: 2023-04-13
      DOI: 10.3390/smartcities6020054
      Issue No: Vol. 6, No. 2 (2023)
       
  • Smart Cities, Vol. 6, Pages 1152-1166: Understanding the Links between
           Diversity and Creativity as Assessed in the Boroughs of London

    • Authors: David Pac-Salas, Leandro Sepulveda, Juan Miguel Baez Melian, Jaime Minguijon
      First page: 1152
      Abstract: This paper analyses the links between creativity and diversity in the different boroughs of London. Based on rich data from the UK Census of Population of 2011 and other sources, we specifically analysed the correlations between creativity and diversity within the London boroughs. The main results of this study indicate that there is no direct correlation between creativity and diversity. Some significant correlations have been observed, however, between variables that shape such indices. Namely, the “creative class” tend to live in more diverse, more heterogeneous neighbourhoods (alongside people from many different countries) and they are more prepared to tolerate such diverse environments. The study also shows that diversity of geographical origin (measured by country of origin) is a more relevant factor for boosting creativity than variables such as religious diversity. This article contributes to the theoretical field of research exploring the impact of diversity on creative people and cities.
      Citation: Smart Cities
      PubDate: 2023-04-17
      DOI: 10.3390/smartcities6020055
      Issue No: Vol. 6, No. 2 (2023)
       
  • Smart Cities, Vol. 6, Pages 1167-1184: Camera-Based Smart Parking System
           Using Perspective Transformation

    • Authors: Bowie Liu, Hawking Lai, Stanley Kan, Calana Chan
      First page: 1167
      Abstract: The concept of the “smart city” has emerged with the advancement of technology, but some facilities are not sufficiently intelligent, such as parking lots. Hence, this paper proposes an inexpensive and plug-to-play camera-based smart parking system for airports. The system utilizes inverse perspective mapping (IPM) to provide an aerial view image of the parking lot, which is then processed to extract parking space information. The system also includes a guidance system to assist drivers in finding available parking spaces. The system is simulated on a 3D scene based on the parking lot of Macao International Airport. In the experiment, our system achieved an accuracy rate of 97.03% and a mean distance error of 8.59 pixels. This research study shows the potential of enhancing parking lots using only cameras as data collectors, and the results show that the system is capable of providing accurate and useful information. It performs well in parking lots with open space, in particular. Moreover, it is an economical solution for implementing a smart parking lot.
      Citation: Smart Cities
      PubDate: 2023-04-18
      DOI: 10.3390/smartcities6020056
      Issue No: Vol. 6, No. 2 (2023)
       
  • Smart Cities, Vol. 6, Pages 1185-1201: Factors Affecting Car-Sharing
           Services

    • Authors: Katarzyna Turoń
      First page: 1185
      Abstract: Car-sharing systems, i.e., short-term car rental services, are solutions indicated as an alternative to individual motorization; they can be used in an increasing number of cities around the world. These services, along with their intensive development, are becoming more and more complex. Due to their complexity, they involve not only an increasing number of stakeholders or infrastructure elements, but also indicate numerous links with the functioning of cities, especially smart cities. To properly implement or improve the car-sharing system, both in terms of operational issues regarding the system’s functioning or changes in the vehicle fleet, it is important to be familiar with the elements that make up car-sharing, as well as the factors that affect it. This work aims to present the factors affecting car-sharing, as well as the transport model of car-sharing services. This work fills the research gap stemming from the lack of comprehensive studies and knowledge on car-sharing. A detailed analysis of the literature shows that there are six main groups of factors affecting car-sharing: economic and technical, transport, social, environmental, organizational, and other issues; among these factors, more than 150 quantitative and qualitative criteria can be distinguished. Furthermore, the work also showed factors that are a niche in the literature and can be the basis for further research on car-sharing. Detailed familiarity with these factors could translate into increased profitability and, above all, success in the functioning of on-the-market services. This article supports the implementation and improvement of car-sharing services. In addition, it supports scientists in the preparation of scientific papers and mathematical models in the field of car-sharing and the factors that affect it.
      Citation: Smart Cities
      PubDate: 2023-04-20
      DOI: 10.3390/smartcities6020057
      Issue No: Vol. 6, No. 2 (2023)
       
  • Smart Cities, Vol. 6, Pages 1202-1226: Intelligent and Environmentally
           Friendly Solutions in Smart Cities’ Development—Empirical
           Evidence from Poland

    • Authors: Agnieszka Janik, Adam Ryszko, Marek Szafraniec
      First page: 1202
      Abstract: This study presents a comprehensive analysis aiming to identify the implementation level of intelligent and environmentally friendly solutions (IEFS) in cities in Poland, and barriers impeding their development. Based on a representative sample of 280 cities, it was evident that the implementation level of IEFS in Poland is relatively very low. The most common barriers to IEFS implementation as indicated by representatives of city authorities were high costs, lack of adequate funds, and lack of awareness of benefits resulting from applying IEFS. Nevertheless, regression analyses showed that the IEFS implementation level was mostly affected by cities’ population size and perception of individual IEFS as integral elements of the smart city concept. It was also revealed that the high costs of implementing IEFS, the lack of their inclusion in local development strategies, the lack of appropriate legal regulations, the lack of widespread good practices, and the resistance of inhabitants to change and to new technologies perceived as impediments had significant negative effects on the implementation level of specific IEFS. Furthermore, the analyses demonstrated that perceiving certain issues as barriers did not hinder the implementation of such solutions. Based on a discussion of the results, relevant recommendations and directions for future research are proposed.
      Citation: Smart Cities
      PubDate: 2023-04-21
      DOI: 10.3390/smartcities6020058
      Issue No: Vol. 6, No. 2 (2023)
       
 
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