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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. 7, Pages 141-162: A Review on Key Innovation Challenges
           for Smart City Initiatives

    • Authors: Rui José, Helena Rodrigues
      First page: 141
      Abstract: Smart city initiatives are being promoted across the world to address major urban challenges, and they all share a common belief in the transformative power of digital technologies. However, the pace of innovation in smart cities seems to be much slower than the rapid and profoundly disruptive transformations brought about by digital innovation in many other domains. To develop new insights about the main causes behind this relatively modest success, this study provides a Systematic Literature Review (SLR) on the connection between major smart city challenges and the essential properties of digital innovation. The review involved the qualitative analysis of 44 research papers reporting on smart city innovation practices and outcomes. The results characterize five major challenge categories for smart city innovation: Strategic vision; Organizational Capabilities and Agility; Technology Domestication; Ecosystem Development; and Transboundary Innovation. This study also explores the connections between these challenges and concrete digital innovation practices in smart city initiatives. The main conclusion is that current innovation practices in smart cities are not properly aligned with what the research literature commonly describes as core properties of digital innovation and that this might be a major cause behind the limited progress in smart city initiatives.
      Citation: Smart Cities
      PubDate: 2024-01-02
      DOI: 10.3390/smartcities7010006
      Issue No: Vol. 7, No. 1 (2024)
       
  • Smart Cities, Vol. 7, Pages 163-178: Using Explainable Artificial
           Intelligence (XAI) to Predict the Influence of Weather on the Thermal
           Soaring Capabilities of Sailplanes for Smart City Applications

    • Authors: Maren Schnieder
      First page: 163
      Abstract: Background: Drones, also known as unmanned aerial vehicles, could potentially be a key part of future smart cities by aiding traffic management, infrastructure inspection and maybe even last mile delivery. This paper contributes to the research on managing a fleet of soaring aircraft by gaining an understanding of the influence of the weather on soaring capabilities. To do so, machine learning algorithms were trained on flight data, which was recorded in the UK over the past ten years at selected gliding clubs (i.e., sailplanes). Methods: A random forest regressor was trained to predict the flight duration and a random forest (RF) classifier was used to predict whether at least one flight on a given day managed to soar in thermals. SHAP (SHapley Additive exPlanations), a form of explainable artificial intelligence (AI), was used to understand the predictions given by the models. Results: The best RF have a mean absolute error of 5.7 min (flight duration) and an accuracy of 81.2% (probability of soaring in a thermal on a given day). The explanations derived from SHAP are in line with the common knowledge about the effect of weather systems to predict soaring potential. However, the key conclusion of this study is the importance of combining human knowledge with machine learning to devise a holistic explanation of a machine learning model and to avoid misinterpretations.
      Citation: Smart Cities
      PubDate: 2024-01-15
      DOI: 10.3390/smartcities7010007
      Issue No: Vol. 7, No. 1 (2024)
       
  • Smart Cities, Vol. 7, Pages 179-207: Delay and Energy Efficient Offloading
           Strategies for an IoT Integrated Water Distribution System in Smart Cities
           

    • Authors: Nibi Kulangara Velayudhan, Aiswarya S, Aryadevi Remanidevi Devidas, Maneesha Vinodini Ramesh
      First page: 179
      Abstract: In the fast-moving world of information and communications technologies, one significant issue in metropolitan cities is water scarcity and the need for an intelligent water distribution system for sustainable water management. An IoT-based monitoring system can improve water distribution system management and mitigate challenges in the distribution network networks such as leakage, breakage, theft, overflow, dry running of pumps and so on. However, the increase in the number of communication and sensing devices within smart cities has evoked challenges to existing communication networks due to the increase in delay and energy consumption within the network. The work presents different strategies for efficient delay and energy offloading in IoT-integrated water distribution systems in smart cities. Different IoT-enabled communication network topology diagrams are proposed, considering the different water network design parameters, land cover patterns and wireless channels for communication. From these topologies and by considering all the relevant communication parameters, the optimum communication network architecture to continuously monitor a water distribution network in a metropolitan city in India is identified. As a case study, an IoT design and analysis model is studied for a secondary metropolitan city in India. The selected study area is in Kochi, India. Based on the site-specific model and land use and land cover pattern, delay and energy modeling of the IoT-based water distribution system is discussed. Algorithms for node categorisation and edge-to-fog allocation are discussed, and numerical analyses of delay and energy models are included. An approximation of the delay and energy of the network is calculated using these models. On the basis of these study results, and state transition diagrams, the optimum placement of fog nodes linked with edge nodes and a cloud server could be carried out. Also, by considering different scenarios, up to a 40% improvement in energy efficiency can be achieved by incorporating a greater number of states in the state transition diagram. These strategies could be utilized in implementing delay and energy-efficient IoT-enabled communication networks for site-specific applications.
      Citation: Smart Cities
      PubDate: 2024-01-16
      DOI: 10.3390/smartcities7010008
      Issue No: Vol. 7, No. 1 (2024)
       
  • Smart Cities, Vol. 7, Pages 208-232: Fit Islands: Designing a
           Multifunctional Virtual Urban Community to Promote Healthy Aging for
           Chinese Older Adults

    • Authors: Zixin Shen, Rongbo Hu, Dong Wan, Thomas Bock
      First page: 208
      Abstract: Within the context of an aging global population, the demographic structure of emerging economies is undergoing a dramatic transformation. Emerging economies have a large population base and rapid economic development, but they are ill-prepared to deal with population aging. Limited resources force many older adults to face health issues such as chronic diseases and loss of physical independence, exacerbating the burden of traditional family and societal elderly care. Uncontrollable events such as the COVID-19 pandemic and regional conflicts have exacerbated the plight of older adults. Improving the quality of life and health of older adults has become a development priority in emerging economies in the face of a rapidly aging population. The development of smart cities has brought with it many available digital technologies, and the consequent development of smart aging offers endless possibilities for improving the quality of life and health of older people, making cities more inclusive of older people. Researchers from developed economies have attempted to address the health issues of older adults through a technology that combines physical exercise and digital technology called Exergame. However, existing projects are not suitable for older adults in emerging economies due to differences in national conditions. The aim of this project is therefore to propose a universal approach to designing a health-promoting Exergame system in the format of a virtual urban community to help emerging economies cope with aging populations, making cities more inclusive. To verify the feasibility of this approach, the authors designed an expandable Exergame called “Fit Islands”, using China as a case study. Based on the initial demonstration, the authors conducted functional tests. The result is that Fit Islands can meet the development objective of motivating Chinese older people to increase their physical activity, providing initial evidence of the feasibility of an Exergame system to promote healthy aging in emerging economies. The application of Fit Islands demonstrates the feasibility of the universal Exergame development method, which can, in principle, provide comprehensive and practical guidance for other countries.
      Citation: Smart Cities
      PubDate: 2024-01-18
      DOI: 10.3390/smartcities7010009
      Issue No: Vol. 7, No. 1 (2024)
       
  • Smart Cities, Vol. 7, Pages 233-253: Urban Traffic Congestion Prediction:
           A Multi-Step Approach Utilizing Sensor Data and Weather Information

    • Authors: Nikolaos Tsalikidis, Aristeidis Mystakidis, Paraskevas Koukaras, Marius Ivaškevičius, Lina Morkūnaitė, Dimosthenis Ioannidis, Paris A. Fokaides, Christos Tjortjis, Dimitrios Tzovaras
      First page: 233
      Abstract: The continuous growth of urban populations has led to the persistent problem of traffic congestion, which imposes adverse effects on quality of life, such as commute times, road safety, and the local air quality. Advancements in Internet of Things (IoT) sensor technology have contributed to a plethora of new data streams regarding traffic conditions. Therefore, the recognition and prediction of traffic congestion patterns utilizing such data have become crucial. To that end, the integration of Machine Learning (ML) algorithms can further enhance Intelligent Transportation Systems (ITS), contributing to the smart management of transportation systems and effectively tackling traffic congestion in cities. This study seeks to assess a wide range of models as potential solutions for an ML-based multi-step forecasting approach intended to improve traffic congestion prediction, particularly in areas with limited historical data. Various interpretable predictive algorithms, suitable for handling the complexity and spatiotemporal characteristics of urban traffic flow, were tested and eventually shortlisted based on their predictive performance. The forecasting approach selects the optimal model in each step to maximize the accuracy. The findings demonstrate that, in a 24 h step prediction, variating Ensemble Tree-Based (ETB) regressors like the Light Gradient Boosting Machine (LGBM) exhibit superior performances compared to traditional Deep Learning (DL) methods. Our work provides a valuable contribution to short-term traffic congestion predictions and can enable more efficient scheduling of daily urban transportation.
      Citation: Smart Cities
      PubDate: 2024-01-19
      DOI: 10.3390/smartcities7010010
      Issue No: Vol. 7, No. 1 (2024)
       
  • Smart Cities, Vol. 7, Pages 254-276: Efficient Decoder and Intermediate
           Domain for Semantic Segmentation in Adverse Conditions

    • Authors: Xiaodong Chen, Nan Jiang, Yifeng Li, Guangliang Cheng, Zheng Liang, Zuobin Ying, Qi Zhang, Runsheng Zhao
      First page: 254
      Abstract: In smart city contexts, traditional methods for semantic segmentation are affected by adverse conditions, such as rain, fog, or darkness. One challenge is the limited availability of semantic segmentation datasets, specifically for autonomous driving in adverse conditions, and the high cost of labeling such datasets. To address this problem, unsupervised domain adaptation (UDA) is commonly employed. In UDA, the source domain contains data from good weather conditions, while the target domain contains data from adverse weather conditions. The Adverse Conditions Dataset with Correspondences (ACDC) provides reference images taken at different times but in the same location, which can serve as an intermediate domain, offering additional semantic information. In this study, we introduce a method that leverages both the intermediate domain and frequency information to improve semantic segmentation in smart city environments. Specifically, we extract the region with the largest difference in standard deviation and entropy values from the reference image as the intermediate domain. Secondly, we introduce the Fourier Exponential Decreasing Sampling (FEDS) algorithm to facilitate more reasonable learning of frequency domain information. Finally, we design an efficient decoder network that outperforms the DAFormer network by reducing network parameters by 28.00%. When compared to the DAFormer work, our proposed approach demonstrates significant performance improvements, increasing by 6.77%, 5.34%, 6.36%, and 5.93% in mean Intersection over Union (mIoU) for Cityscapes to ACDC night, foggy, rainy, and snowy, respectively.
      Citation: Smart Cities
      PubDate: 2024-01-19
      DOI: 10.3390/smartcities7010011
      Issue No: Vol. 7, No. 1 (2024)
       
  • Smart Cities, Vol. 7, Pages 277-301: Sensors in Civil Engineering: From
           Existing Gaps to Quantum Opportunities

    • Authors: Boris Kantsepolsky, Itzhak Aviv
      First page: 277
      Abstract: The vital role of civil engineering is to enable the development of modern cities and establish foundations for smart and sustainable urban environments of the future. Advanced sensing technologies are among the instrumental methods used to enhance the performance of civil engineering infrastructures and address the multifaceted challenges of future cities. Through this study, we discussed the shortcomings of traditional sensors in four primary civil engineering domains: construction, energy, water, and transportation. Then, we investigated and summarized the potential of quantum sensors to contribute to and revolutionize the management of civil engineering infrastructures. For the water sector, advancements are expected in monitoring water quality and pressure in water and sewage infrastructures. In the energy sector, quantum sensors may facilitate renewables integration and improve grid stability and buildings’ energy efficiency. The most promising progress in the construction field is the ability to identify subsurface density and underground structures. In transportation, these sensors create many fresh avenues for real-time traffic management and smart mobility solutions. As one of the first-in-the-field studies offering the adoption of quantum sensors across four primary domains of civil engineering, this research establishes the basis for the discourse about the scope and timeline for deploying quantum sensors to real-world applications towards the quantum transformation of civil engineering.
      Citation: Smart Cities
      PubDate: 2024-01-22
      DOI: 10.3390/smartcities7010012
      Issue No: Vol. 7, No. 1 (2024)
       
  • Smart Cities, Vol. 7, Pages 302-324: Benchmarking the Functional,
           Technical, and Business Characteristics of Automated Passenger Counting
           Products

    • Authors: Pronello Cristina, Baratti Luca, Anbarasan Deepan
      First page: 302
      Abstract: Urban transport planning and the integration of various mobility options have become increasingly complex, necessitating a thorough understanding of user mobility patterns and their diverse needs. This paper focuses on benchmarking different Automatic Passenger Counting (APC) technologies, which play a key role in Mobility as a Service (MaaS) systems. APC systems provide valuable data for analysing mobility patterns and informing decisions about resource allocation. Our study presents a comprehensive data collection and benchmark analysis of APC solutions. The literature review emphasises the significance of passenger counting for transport companies and discusses various existing APC technologies, such as pressure sensors, wireless sensors, optical infrared sensors (IR), and video image technology. Real-world applications of APC systems are examined, highlighting experimental results and their potential for improving accuracy. The methodology outlines the data collection process, which involved identifying APC companies, conducting interviews with companies and customers, and administering an ad hoc survey to gather specific information about APC systems. The collected data were used to establish criteria and key performance indicators (KPIs) for the benchmarking analysis. The benchmarking analysis compares APC devices and companies based on ten criteria: technology, accuracy, environment, coverage, interface, interference, robustness (for devices), price, pricing model, and system integration (for companies). KPIs were developed to measure performance and make comparison easier. The results of the benchmarking analysis offer insights into the costs and accuracy of different APC systems, enabling informed decision making regarding system selection and implementation. The findings fill a research gap and provide valuable information for transport companies and policy makers, and we offer a comprehensive analysis of APC systems, highlighting their strengths, weaknesses, and business strategies. The paper concludes by discussing limitations and suggesting future research directions for APC technologies.
      Citation: Smart Cities
      PubDate: 2024-01-22
      DOI: 10.3390/smartcities7010013
      Issue No: Vol. 7, No. 1 (2024)
       
  • Smart Cities, Vol. 7, Pages 325-369: The Convergence of Intelligent
           Tutoring, Robotics, and IoT in Smart Education for the Transition from
           Industry 4.0 to 5.0

    • Authors: Amr Adel
      First page: 325
      Abstract: This review paper provides a comprehensive analysis of the automation of smart education in the context of Industry 5.0 from 78 papers, focusing on the integration of advanced technologies and the development of innovative, effective, and ethical educational solutions for the future workforce. As the world transitions into an era characterized by human–machine collaboration and rapidly evolving technologies, there is an urgent need to recognize the pivotal role of smart education in preparing individuals for the opportunities and challenges presented by the new industrial landscape. The paper examines key components of smart education, including intelligent tutoring systems, adaptive learning environments, learning analytics, and the application of the Internet of Things (IoT) in education. It also discusses the role of advanced technologies such as artificial intelligence (AI), machine learning (ML), robotics, and augmented and virtual reality (AR/VR) in shaping personalized and immersive learning experiences. The review highlights the importance of smart education in addressing the growing demand for upskilling and reskilling, fostering a culture of lifelong learning, and promoting adaptability, resilience, and self-improvement among learners. Furthermore, the paper delves into the challenges and ethical considerations associated with the implementation of smart education, addressing issues such as data privacy, the digital divide, teacher and student readiness, and the potential biases in AI-driven systems. Through a presentation of case studies and examples of successful smart education initiatives, the review aims to inspire educators, policymakers, and industry stakeholders to collaborate and innovate in the design and implementation of effective smart education solutions. Conclusively, the paper outlines emerging trends, future directions, and potential research opportunities in the field of smart education, emphasizing the importance of continuous improvement and the integration of new technologies to ensure that education remains relevant and effective in the context of Industry 5.0. By providing a holistic understanding of the key components, challenges, and potential solutions associated with smart education, this review paper seeks to contribute to the ongoing discourse surrounding the automation of smart education and its role in preparing the workforce for the future of work.
      Citation: Smart Cities
      PubDate: 2024-01-30
      DOI: 10.3390/smartcities7010014
      Issue No: Vol. 7, No. 1 (2024)
       
  • Smart Cities, Vol. 7, Pages 370-413: On the Adoption of Smart Home
           Technology in Switzerland: Results from a Survey Study Focusing on
           Prevention and Active Healthy Aging Aspects

    • Authors: Raphael Iten, Joël Wagner, Angela Zeier Röschmann
      First page: 370
      Abstract: Smart home (SH) technologies offer advancements in comfort, energy management, health, and safety. There is increasing interest in technology-enabled home services from scholars and professionals, particularly to meet the needs of a growing aging population. Yet, current research focuses on assisted living scenarios developed for elderly individuals with health impairments, and neglects to explore the potential of SHs in prevention. We aim to improve comprehension and guide future research on the value of SH technology for risk prevention with a survey assessing the adoption of SHs by older adults based on novel ad hoc collected data. Our survey is based on the theoretical background derived from the extant body of literature. In addition to established adoption factors and user characteristics, it includes previously unexamined elements such as active and healthy aging parameters, risk and insurance considerations, and social and hedonic dimensions. Descriptive results and regression analyses indicate that a vast majority of individuals acknowledge the preventive benefits of SHs. Additionally, we observe that individuals with higher levels of social activity, technology affinity, and knowledge of SHs tend to report greater interest. Moreover, perceived enjoyment and perceived risk emerge as central elements for SH adoption. Our research indicates that considering lifestyle factors when examining technology adoption and emphasizing the preventive benefits present possibilities for both future studies and practical implementations.
      Citation: Smart Cities
      PubDate: 2024-01-30
      DOI: 10.3390/smartcities7010015
      Issue No: Vol. 7, No. 1 (2024)
       
  • Smart Cities, Vol. 7, Pages 414-444: Smart Cities and Urban Energy
           Planning: An Advanced Review of Promises and Challenges

    • Authors: Saeed Esfandi, Safiyeh Tayebi, John Byrne, Job Taminiau, Golkou Giyahchi, Seyed Ali Alavi
      First page: 414
      Abstract: This review explores the relationship between urban energy planning and smart city evolution, addressing three primary questions: How has research on smart cities and urban energy planning evolved in the past thirty years' What promises and hurdles do smart city initiatives introduce to urban energy planning' And why do some smart city projects surpass energy efficiency and emission reduction targets while others fall short' Based on a bibliometric analysis of 9320 papers published between January 1992 and May 2023, five dimensions were identified by researchers trying to address these three questions: (1) energy use at the building scale, (2) urban design and planning integration, (3) transportation and mobility, (4) grid modernization and smart grids, and (5) policy and regulatory frameworks. A comprehensive review of 193 papers discovered that previous research prioritized technological advancements in the first four dimensions. However, there was a notable gap in adequately addressing the inherent policy and regulatory challenges. This gap often led to smart city endeavors underperforming relative to their intended objectives. Overcoming the gap requires a better understanding of broader issues such as environmental impacts, social justice, resilience, safety and security, and the affordability of such initiatives.
      Citation: Smart Cities
      PubDate: 2024-01-31
      DOI: 10.3390/smartcities7010016
      Issue No: Vol. 7, No. 1 (2024)
       
  • Smart Cities, Vol. 7, Pages 445-459: Engaging Young People in the
           Development of Innovative Nature-Inspired Technologies for Carbon
           Sequestration in Cities: Case Studies from Portugal

    • Authors: Manuela Moreira da Silva, Lurdes Ferreira, Teresa Sarmento, Catarina Selada
      First page: 445
      Abstract: Currently, cities are the most vulnerable places on the planet to the effects of global change, both anthropogenic and climate-related, and this is not compatible with harmony and well-being regarding the economy, nature, and future generations. Young people have a unique potential to catalyze the transformative sustainable change that the planet needs now, as they are the first generation to grow up with tangible impacts of climate change. We tested a new strategy to empower young people to foster carbon neutrality in cities by engaging them in ecosystem services quantification and technological innovation to increase CO2 sequestration in two Portuguese cities. The species with best performance for carbon sequestration were M. exelsa in Porto and O. europea in Loulé, and for air pollutant removal and hydrological regulation were P. hispanica in Porto and P. pinea in Loulé. Through the innovative advanced summer program SLI, a nature-based learning experience, young people developed two new concepts of technological solutions to accelerate city decarbonization by designing a hedge for air pollution hotspots and a biodevice to be placed at bus stops using autochthonous shrubs and mosses. Initiatives like SLI contribute to a greater awareness among young people about the drivers that brought us to the current climate emergency, motivating them towards more balanced lifestyles and creating innovative nature-based solutions towards a smart and sustainable city.
      Citation: Smart Cities
      PubDate: 2024-01-31
      DOI: 10.3390/smartcities7010017
      Issue No: Vol. 7, No. 1 (2024)
       
  • Smart Cities, Vol. 7, Pages 460-474: Predicting Autonomous Driving
           Behavior through Human Factor Considerations in Safety-Critical Events

    • Authors: Jamal Raiyn, Galia Weidl
      First page: 460
      Abstract: This paper investigates the ability of autonomous driving systems to predict outcomes by considering human factors like gender, age, and driving experience, particularly in the context of safety-critical events. The primary objective is to equip autonomous vehicles with the capacity to make plausible deductions, handle conflicting data, and adjust their responses in real-time during safety-critical situations. A foundational dataset, which encompasses various driving scenarios such as lane changes, merging, and navigating complex intersections, is employed to enable vehicles to exhibit appropriate behavior and make sound decisions in critical safety events. The deep learning model incorporates personalized cognitive agents for each driver, considering their distinct preferences, characteristics, and requirements. This personalized approach aims to enhance the safety and efficiency of autonomous driving, contributing to the ongoing development of intelligent transportation systems. The efforts made contribute to advancements in safety, efficiency, and overall performance within autonomous driving systems. To describe the causal relationship between external factors like weather conditions and human factors, and safety-critical driver behaviors, various data mining techniques can be applied. One commonly used method is regression analysis. Additionally, correlation analysis is employed to reveal relationships between different factors, helping to identify the strength and direction of their impact on safety-critical driver behavior.
      Citation: Smart Cities
      PubDate: 2024-02-01
      DOI: 10.3390/smartcities7010018
      Issue No: Vol. 7, No. 1 (2024)
       
  • Smart Cities, Vol. 7, Pages 475-495: The Cybersecurity Applied by Online
           Travel Agencies and Hotels to Protect Users’ Private Data in Smart
           Cities

    • Authors: Lázaro Florido-Benítez
      First page: 475
      Abstract: The purpose of this paper is to analyse the cybersecurity in online travel agencies (OTAs) and hotel sectors to protect users’ private data in smart cities. Methodologically, this research uses a sample of information about cyberattacks that occurred during the period of 2000–2023 in companies operating as OTAs and in the travel, tourism, and food sectors, which was obtained from research articles. Then, we had to expand the research to include updated information about cyberattacks from digital newspapers, regulatory sources, and state data breach notification sites like CSIS, KonBriefing, EUROCONTROL, and GlobalData. The findings of the current research prove that hotels and OTAs were constantly exposed to cyberattacks in the period analysed, especially by data breaches and malware attacks; in fact, this is the main novelty of this research. In addition, these incidents were severe for both guests and tourism companies because their vulnerabilities and consequences affect the reputation of companies and smart cities where these firms operate, as well as consumer confidence. The results also showed that most of the cyberattacks examined in this manuscript were aimed at stealing information about the companies’ and users’ private data such as email addresses; credit card numbers, security codes, and expiration dates; and encoded magstripe data; among many other types of data. Cyberattacks and cyberthreats never disappear completely in the travel and tourism sectors because these illegal activities are closely related to the hacker’s thirst for power, fame, and wealth.
      Citation: Smart Cities
      PubDate: 2024-02-04
      DOI: 10.3390/smartcities7010019
      Issue No: Vol. 7, No. 1 (2024)
       
  • Smart Cities, Vol. 7, Pages 496-517: An Artificial Intelligence and
           Industrial Internet of Things-Based Framework for Sustainable Hydropower
           Plant Operations

    • Authors: Fation T. Fera, Christos Spandonidis
      First page: 496
      Abstract: Hydropower plays a crucial role in supplying electricity to developed nations and is projected to expand its capacity in various developing countries such as Sub-Saharan Africa, Argentina, Colombia, and Turkey. With the increasing demand for sustainable energy and the emphasis on reducing carbon emissions, the significance of hydropower plants is growing. Nevertheless, numerous challenges arise for these plants due to their aging infrastructure, impacting both their efficiency and structural stability. In order to tackle these issues, the present study has formulated a specialized real-time framework for identifying damage, with a particular focus on detecting corrosion in the conductors of generators within hydropower plants. It should be noted that corrosion processes can be highly complex and nonlinear, making it challenging to develop accurate physics-based models that capture all the nuances. Therefore, the proposed framework leverages autoencoder, an unsupervised, data-driven AI technology with the Mahalanobis distance, to capture the intricacies of corrosion and automate its detection. Rigorous testing shows that it can identify slight variations indicating conductor corrosion with over 80% sensitivity and a 5% false alarm rate for ‘medium’ to ‘high’ severity damage. By detecting and resolving corrosion early, the system reduces disruptions, streamlines maintenance, and mitigates unscheduled repairs’ negative effects on the environment. This enhances energy generation effectiveness, promotes hydroelectric facilities’ long-term viability, and fosters community prosperity.
      Citation: Smart Cities
      PubDate: 2024-02-06
      DOI: 10.3390/smartcities7010020
      Issue No: Vol. 7, No. 1 (2024)
       
  • Smart Cities, Vol. 7, Pages 518-540: Safety and Mobility Evaluation of
           Cumulative-Anticipative Car-Following Model for Connected Autonomous
           Vehicles

    • Authors: Hafiz Usman Ahmed, Salman Ahmad, Xinyi Yang, Pan Lu, Ying Huang
      First page: 518
      Abstract: In the typical landscape of road transportation, about 90% of traffic accidents result from human errors. Vehicle automation enhances road safety by reducing driver fatigue and errors and improves overall mobility efficiency. The advancement of autonomous vehicle technology will significantly impact traffic safety, potentially saving more than 30,000 lives annually in the United States alone. The widespread acceptance of autonomous and connected autonomous vehicles (AVs and CAVs) will be a process spanning multiple decades, requiring their coexistence with traditional vehicles. This study explores the mobility and safety performance of CAVs in mixed-traffic environments using the cumulative-anticipative car-following (CACF) model. This research compares the CACF model with established Wiedemann 99 and cooperative adaptive cruise control (CACC) models using a VISSIM platform. The simulations include single-lane and multi-lane networks, incorporating sensitivity tests for mobility and safety parameters. The study reveals increased throughput, reduced delays, and enhanced travel times with CACF, emphasizing its advantages over CACC. Safety analyses demonstrate CACF’s ability to prevent traffic shockwaves and bottlenecks, emphasizing the significance of communication range and acceleration coefficients. The research recommends early investment in vehicle-to-infrastructure (V2I) communication technology, refining CACC logic, and expanding the study to diverse road scenarios.
      Citation: Smart Cities
      PubDate: 2024-02-06
      DOI: 10.3390/smartcities7010021
      Issue No: Vol. 7, No. 1 (2024)
       
  • Smart Cities, Vol. 7, Pages 541-565: Enhancing Smart Cities through
           Third-Party Logistics: Predicting Delivery Intensity

    • Authors: Mariusz Kmiecik, Aleksandra Wierzbicka
      First page: 541
      Abstract: This article addresses the key and current issues of smart cities in the context of last-mile supply management. Specifically, it explores how third-party logistics (3PL) activities impact last-mile delivery management in smart cities. It examines how 3PL affects delivery volumes, expanding the predictive capabilities of logistics operators. A research question included in the Introduction of this paper is also posed to explore the problem in depth. The research conducted focuses mainly on a case study conducted on the operations of an international 3PL logistics operator. In addition, predictive methods are used to analyse the shipment volume data for individual barcodes in the two analysed cities in Poland. Currently, the concept of a smart city assumes the limited participation of logistics operators in creating improvements for cities. The case study analysis shows that in the cities studied, 3PL companies, through predictive actions, can regulate the flow of vehicles out of the logistics centre and into the city, thus influencing the traffic volume in the city. The research is limited to two cities in Poland implementing smart city solutions and one logistics operator. The research also does not include e-commerce. The authors acknowledge that the results obtained cannot be generalised to a larger scale. This paper bridges the research gap on 3PL activities for last-mile logistics improvements. In addition, the paper proposes the first concept related to the implementation of a 3PL company’s predictive activities associated with the operator’s ability to control the impact on urban traffic.
      Citation: Smart Cities
      PubDate: 2024-02-08
      DOI: 10.3390/smartcities7010022
      Issue No: Vol. 7, No. 1 (2024)
       
  • Smart Cities, Vol. 7, Pages 566-596: Climate Change Mitigation through
           Modular Construction

    • Authors: Zeerak Waryam Sajid, Fahim Ullah, Siddra Qayyum, Rehan Masood
      First page: 566
      Abstract: Modular construction (MC) is a promising concept with the potential to revolutionize the construction industry (CI). The sustainability aspects of MC, among its other encouraging facets, have garnered escalated interest and acclaim among the research community, especially in the context of climate change (CC) mitigation efforts. Despite numerous scholarly studies contributing to the understanding of MC, a holistic review of the prevailing literature that systematically documents the impact of utilizing MC on CC mitigation remains scarce. The study conducts a systematic literature review (SLR) of the pertinent literature retrieved from the Scopus repository to explore the relationship between MC and CC mitigation. Employing the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) protocol, the SLR was conducted on 31 shortlisted articles published between 2010 and 2023. The findings of the study reveal that MC can mitigate the climate crisis by reducing GHG emissions, curtailing resource intensiveness by enabling a circular economy (CE), fomenting energy efficiency, and fostering resourceful land use and management in the CI. A conceptual framework based on the findings of the previous literature is proposed in this study, which outlines several strategies for CC mitigation that can be implemented by the adoption of MC in the CI. The current study is a humble effort to review various offerings of MC to help mitigate CC in the era of striving for global sustainability. For industry practitioners and policymakers, this study highlights the viability of leveraging MC for CC mitigation, aiming to inspire better decision making for sustainable development in the CI. Similarly, for researchers, it presents MC as a potential tool for CC mitigation that can be further explored in terms of its associated factors, and focused frameworks can be developed.
      Citation: Smart Cities
      PubDate: 2024-02-08
      DOI: 10.3390/smartcities7010023
      Issue No: Vol. 7, No. 1 (2024)
       
  • Smart Cities, Vol. 7, Pages 597-614: Bibliometric Study on the
           Conceptualisation of Smart City and Education

    • Authors: Debora Scala, Ángel Ignacio Aguilar Cuesta, Maria Ángeles Rodríguez-Domenech, María del Carmen Cañizares Ruiz
      First page: 597
      Abstract: In recent years, research in the smart city sector has experienced exponential growth, establishing itself as a fundamental and multifaceted field of study. Education is one of the sectors of interest in smart cities. Concurrently, the extensive academic literature on smart cities makes identifying the main areas of interest related to education, leading institutions and authors, potential interconnections between different disciplines, and existing gaps more complicated. This article maps the knowledge domain of education in smart cities through a bibliometric analysis to identify current trends, research networks, and topics of greatest interest. A total of 88 articles, published between 2000 and 2023, were examined using an interdisciplinary approach. The leading countries are mainly located in Europe and North America and include China. Bibliometrics provides an intellectual configuration of knowledge on education in smart cities; a co-word analysis identifies conceptual sub-domains in specific themes. In general, education within smart cities represents a universal challenge that requires a structured and interdisciplinary approach at all levels. Finally, this paper offers some suggestions for future research, adopting a more comprehensive view of the areas of investigation through a holistic analysis of stakeholders.
      Citation: Smart Cities
      PubDate: 2024-02-10
      DOI: 10.3390/smartcities7010024
      Issue No: Vol. 7, No. 1 (2024)
       
  • Smart Cities, Vol. 7, Pages 615-632: Urban Design and Planning
           Participation in the Digital Age: Lessons from an Experimental Online
           Platform

    • Authors: Marshall, Farndon, Hudson-Smith, Kourniotis, Karadimitriou
      First page: 615
      Abstract: There is increasing use of digital technologies in urban planning, including in the generation of designs and the participative side of planning. We examine this digital planning by reporting on the application of an experimental online participatory platform in the regeneration of a London housing estate, enabling reflection on participation processes and outcomes. Drawing on lessons learned, the paper synthesises a conceptual representation of online participation and a relational framework for understanding the participatory platform and its context. We subsequently develop a ‘matrix of participative space’, building on Arnstein’s ‘ladder of participation’, to present a two-dimensional framework of online participation, identifying cases of ‘participative deficit’ and ‘democratic deficit’. We conclude with implications for future digital participation in urban planning and design.
      Citation: Smart Cities
      PubDate: 2024-02-13
      DOI: 10.3390/smartcities7010025
      Issue No: Vol. 7, No. 1 (2024)
       
  • Smart Cities, Vol. 7, Pages 633-661: Toward Establishing a Tourism Data
           Space: Innovative Geo-Dashboard Development for Tourism Research and
           Management

    • Authors: Dolores Ordóñez-Martínez, Joana Maria Seguí-Pons, Maurici Ruiz-Pérez
      First page: 633
      Abstract: The data sharing strategy involves understanding the challenges and problems that can be solved through the collaboration of different entities sharing their data. The implementation of a data space in Mallorca is based on understanding the available data and identifying the problems that can be solved using them. The use of data through data spaces will contribute to the transformation of destinations into smart tourism destinations. Smart tourism destinations are considered as smart cities in which the tourism industry offers a new layer of complexity in which technologies, digitalization, and intelligence are powered by data. This study analyzes four scenarios in which geo-dashboards are developed: flood exposure of tourist accommodation, land-cover changes, human pressure, and tourist uses in urban areas. The results of applying the geo-dashboards to these different scenarios provide tourists and destination managers with valuable information for decision-making, highlighting the utility of this type of tool, and laying the foundations for a future tourism data space in Mallorca.
      Citation: Smart Cities
      PubDate: 2024-02-14
      DOI: 10.3390/smartcities7010026
      Issue No: Vol. 7, No. 1 (2024)
       
  • Smart Cities, Vol. 7, Pages 662-679: Flood-Resilient Smart Cities: A
           Data-Driven Risk Assessment Approach Based on Geographical Risks and
           Emergency Response Infrastructure

    • Authors: João Paulo Just Peixoto, Daniel G. Costa, Paulo Portugal, Francisco Vasques
      First page: 662
      Abstract: Flooding in urban areas is expected to become even more common due to climatic changes, putting pressure on cities to implement effective response measures. Practical mechanisms for assessing flood risk have become highly desired, but existing solutions have been devoted to evaluating only specific cities and consider only limited risk perspectives, constraining their general applicability. This article presents an innovative approach for assessing the flood risk of delimited urban areas by exploiting geospatial information from publicly available databases, providing a method that is applicable to any city in the world and requiring minimum configurations. A set of mathematical equations is defined for numerically assessing risk levels based on elevation, slope, and proximity to rivers, while the existence of emergency-related urban infrastructure is considered as a risk reduction factor. Then, computed risk levels are used to classify areas, allowing easy visualisation of flood risk for a city. This smart city approach not only serves as a valuable tool for assessing the expected flood risk based on different parameters but also facilitates the implementation of cutting-edge strategies to effectively mitigate critical situations, ultimately enhancing urban resilience to flood-related disaster.
      Citation: Smart Cities
      PubDate: 2024-02-16
      DOI: 10.3390/smartcities7010027
      Issue No: Vol. 7, No. 1 (2024)
       
  • Smart Cities, Vol. 7, Pages 1-32: The Intersection of the Green and the
           Smart City: A Data Platform for Health and Well-Being through Nature-Based
           Solutions

    • Authors: Dionysia Kolokotsa, Aikaterini Lilli, Elisavet Tsekeri, Kostas Gobakis, Minas Katsiokalis, Aikaterini Mania, Neil Baldacchino, Sevasti Polychronaki, Niall Buckley, Daniel Micallef, Kurt Calleja, Emma Clarke, Edward Duca, Luka Mali, Adriano Bisello
      First page: 1
      Abstract: An increasingly important aspect of analyzing the challenges facing cities today is the integration of nature. Nature-based solutions have the potential to successfully cope with the adverse effects of extensive urbanization and climatic change. On the other hand, the incorporation of smartness in cities is a critical issue. This paper aims to analyze the steps towards integrating nature-based solutions and smart city aspects to develop a web-based data platform that focuses on tackling and investigating the role of nature-based solutions in city health and well-being and returns a digital twin of the natural and built environment, including health-related key performance indicators. Seven pilot cities are used as a basis for the analysis. The architecture of a smart green city data platform is described. The interaction with the citizens is ensured through apps and games. The paper lays the foundation for a future “phygital” NBS world.
      Citation: Smart Cities
      PubDate: 2023-12-20
      DOI: 10.3390/smartcities7010001
      Issue No: Vol. 7, No. 1 (2023)
       
  • Smart Cities, Vol. 7, Pages 33-50: Vision-Based Object Localization and
           Classification for Electric Vehicle Driving Assistance

    • Authors: Alfredo Medina-Garcia, Jonathan Duarte-Jasso, Juan-Jose Cardenas-Cornejo, Yair A. Andrade-Ambriz, Marco-Antonio Garcia-Montoya, Mario-Alberto Ibarra-Manzano, Dora-Luz Almanza-Ojeda
      First page: 33
      Abstract: The continuous advances in intelligent systems and cutting-edge technology have greatly influenced the development of intelligent vehicles. Recently, integrating multiple sensors in cars has improved and spread the advanced drive-assistance systems (ADAS) solutions for achieving the goal of total autonomy. Despite current self-driving approaches and systems, autonomous driving is still an open research issue that must guarantee the safety and reliability of drivers. This work employs images from two cameras and Global Positioning System (GPS) data to propose a 3D vision-based object localization and classification method for assisting a car during driving. The experimental platform is a prototype of a two-sitter electric vehicle designed and assembled for navigating the campus under controlled mobility conditions. Simultaneously, color and depth images from the primary camera are combined to extract 2D features, which are reprojected into 3D space. Road detection and depth features isolate point clouds representing the objects to construct the occupancy map of the environment. A convolutional neural network was trained to classify typical urban objects in the color images. Experimental tests validate car and object pose in the occupancy map for different scenarios, reinforcing the car position visually estimated with GPS measurements.
      Citation: Smart Cities
      PubDate: 2023-12-22
      DOI: 10.3390/smartcities7010002
      Issue No: Vol. 7, No. 1 (2023)
       
  • Smart Cities, Vol. 7, Pages 51-77: Smart Grid Resilience for
           Grid-Connected PV and Protection Systems under Cyber Threats

    • Authors: Feras Alasali, Awni Itradat, Salah Abu Ghalyon, Mohammad Abudayyeh, Naser El-Naily, Ali M. Hayajneh, Anas AlMajali
      First page: 51
      Abstract: In recent years, the integration of Distributed Energy Resources (DERs) and communication networks has presented significant challenges to power system control and protection, primarily as a result of the emergence of smart grids and cyber threats. As the use of grid-connected solar Photovoltaic (PV) systems continues to increase with the use of intelligent PV inverters, the susceptibility of these systems to cyber attacks and their potential impact on grid stability emerges as a critical concern based on the inverter control models. This study explores the cyber-threat consequences of selectively targeting the components of PV systems, with a special focus on the inverter and Overcurrent Protection Relay (OCR). This research also evaluates the interconnectedness between these two components under different cyber-attack scenarios. A three-phase radial Electromagnetic Transients Program (EMTP) is employed for grid modeling and transient analysis under different cyber attacks. The findings of our analysis highlight the complex relationship between vulnerabilities in inverters and relays, emphasizing the consequential consequences of affecting one of the components on the other. In addition, this work aims to evaluate the impact of cyber attacks on the overall performance and stability of grid-connected PV systems. For example, in the attack on the PV inverters, the OCR failed to identify and eliminate the fault during a pulse signal attack with a short duration of 0.1 s. This resulted in considerable harmonic distortion and substantial power losses as a result of the protection system’s failure to recognize and respond to the irregular attack signal. Our study provides significant contributions to the understanding of cybersecurity in grid-connected solar PV systems. It highlights the importance of implementing improved protective measures and resilience techniques in response to the changing energy environment towards smart grids.
      Citation: Smart Cities
      PubDate: 2023-12-22
      DOI: 10.3390/smartcities7010003
      Issue No: Vol. 7, No. 1 (2023)
       
  • Smart Cities, Vol. 7, Pages 78-98: Intelligent Waste-Volume Management
           Method in the Smart City Concept

    • Authors: Khrystyna Lipianina-Honcharenko, Myroslav Komar, Oleksandr Osolinskyi, Volodymyr Shymanskyi, Myroslav Havryliuk, Vita Semaniuk
      First page: 78
      Abstract: This research paper proposes an innovative approach to urban waste management using intelligent methods of classification, clustering, and forecasting. The application of this approach allows for more efficient waste management and contributes to the sustainable development of the urban environment. The aim of this research is to develop an intelligent method for urban waste management, which includes clustering of waste sources, accurate forecasting of waste volumes, and evaluation of forecast results. To achieve this goal, a real dataset with city characteristics and waste data was used. On account of the war in Ukraine, the authors faced the problem of obtaining open data on waste in Ukraine, so it was decided to use data from another city (Singapore). The results show the high efficiency of the developed method. Comparison of the obtained results with the results of the nearest similar works shows that the main feature of this study is the high accuracy of waste-volume forecasting using the XGBoost model, which reached a level of up to 98%.
      Citation: Smart Cities
      PubDate: 2023-12-29
      DOI: 10.3390/smartcities7010004
      Issue No: Vol. 7, No. 1 (2023)
       
  • Smart Cities, Vol. 7, Pages 99-140: Implementation of a Trust-Based
           Framework for Substation Defense in the Smart Grid

    • Authors: Kwasi Boakye-Boateng, Ali A. Ghorbani, Arash Habibi Lashkari
      First page: 99
      Abstract: The Smart Grid is a cyber-integrated power grid that manages electricity generation, transmission, and distribution to consumers and central to its functioning is the substation. However, integrating cyber-infrastructure into the substation has increased its attack surface. Notably, sophisticated attacks such as the PipeDream APT exploit multiple device protocols, such as Modbus, DNP3, and IEC61850. The substation’s constraints pose challenges for implementing security measures such as encryption and intrusion detection systems. To address this, we propose a comprehensive trust-based framework aimed at enhancing substation security. The framework comprises a trust model, a risk posture model, and a trust transferability model. The trust model detects protocol-based attacks on Intelligent Electronic Devices and SCADA HMI systems, while the risk posture model dynamically assesses the substation’s risk posture. The trust transferability model evaluates the feasibility of transferring and integrating a device and its trust capabilities into a different substation. The practical substation emulation involves a Docker-based testbed, employing a multi-agent architecture with a real-time Security Operations Center-influenced dashboard. Assessment involves testing against attacks guided by the MITRE ICS ATT&CK framework. Our framework displays resilience against diverse attacks, identifies malicious behavior, and rewards trustworthy devices.
      Citation: Smart Cities
      PubDate: 2023-12-30
      DOI: 10.3390/smartcities7010005
      Issue No: Vol. 7, No. 1 (2023)
       
  • 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 3393-3410: Real-Time Recognition and
           Localization of Apples for Robotic Picking Based on Structural Light and
           Deep Learning

    • Authors: Quan Zhang, Wen-Hao Su
      First page: 3393
      Abstract: The apple is a delicious fruit with high nutritional value that is widely grown around the world. Apples are traditionally picked by hand, which is very inefficient. The development of advanced fruit-picking robots has great potential to replace manual labor. A major prerequisite for a robot to successfully pick fruits the accurate identification and positioning of the target fruit. The active laser vision systems based on structured algorithms can achieve higher recognition rates by quickly capturing the three-dimensional information of objects. This study proposes to combine the laser active vision system with the YOLOv5 neural network model to recognize and locate apples on trees. The method obtained accurate two-dimensional pixel coordinates, which, when combined with the active laser vision system, can be converted into three-dimensional world coordinates for apple recognition and positioning. On this basis, we built a picking robot platform equipped with this visual recognition system, and carried out a robot picking experiment. The experimental findings showcase the efficacy of the neural network recognition algorithm proposed in this study, which achieves a precision rate of 94%, an average precision mAP% of 92.86%, and a spatial localization accuracy of approximately 4 mm for the visual system. The implementation of this control method in simulated harvesting operations shows the promise of more precise and successful fruit positioning. In summary, the integration of the YOLOv5 neural network model with an active laser vision system presents a novel and effective approach for the accurate identification and positioning of apples. The achieved precision and spatial accuracy indicate the potential for enhanced fruit-harvesting operations, marking a significant step towards the automation of fruit-picking processes.
      Citation: Smart Cities
      PubDate: 2023-12-04
      DOI: 10.3390/smartcities6060150
      Issue No: Vol. 6, No. 6 (2023)
       
  • Smart Cities, Vol. 6, Pages 3411-3426: Development of a Microservice-Based
           Storm Sewer Simulation System with IoT Devices for Early Warning in Urban
           Areas

    • Authors: Shiu-Shin Lin, Kai-Yang Zhu, Xian-Hao Zhang, Yi-Chuan Liu, Chen-Yu Wang
      First page: 3411
      Abstract: This study proposes an integrated approach to developing a Microservice, Cloud Computing, and Software as a Service (SaaS)-based Real-Time Storm Sewer Simulation System (MBSS). The MBSS combined the Storm Water Management Model (SWMM) microservice running on the EC2 Amazon Web Services (AWS) cloud platform and an Internet of Things (IoT) monitoring device to prevent disasters in smart cities. The Python language and Docker container were used to develop the MBSS and Web API of the SWMM microservice. The IoT comprised a pressure water level meter, an Arduino, and a Raspberry Pi. After laboratory channel testing, the simulated and IoT-monitored water levels under different flow rates indicate that the simulated water level in MBSS was such as that monitored by the IoT. These findings suggest that MBSS is feasible and can be further used as a reference for smart urban early warning systems. The MBSS can be applied in on-site stormwater sewers during heavy rain, with the goal of issuing early warnings and reducing disaster damage. The use case can be the process by which the SWMM model parameters will be optimized based on the water level data from IoT monitoring devices in stormwater sewer systems. The predicted rainfall will then be used by the SWMM microservices of MBSS to simulate the water levels at all manholes. The status of the water levels will finally be applied to early warning.
      Citation: Smart Cities
      PubDate: 2023-12-05
      DOI: 10.3390/smartcities6060151
      Issue No: Vol. 6, No. 6 (2023)
       
  • Smart Cities, Vol. 6, Pages 3427-3453: Grid Impact of Wastewater Resource
           Recovery Facilities-Based Community Microgrids

    • Authors: Ahmed Ali A. Mohamed, Kirn Zafar, Dhavalkumar Vaidya, Lizzette Salmeron, Ondrea Kanwhen, Yusef Esa, Mohamed Kamaludeen
      First page: 3427
      Abstract: The overarching goal of this paper is to explore innovative ways to adapt existing urban infrastructure to achieve a greener and more resilient city, specifically on synergies between the power grid, the wastewater treatment system, and community development in low-lying coastal areas. This study addresses the technical feasibility, benefits, and barriers of using wastewater resource recovery facilities (WRRFs) as community-scale microgrids. These microgrids will act as central resilience and community development hubs, enabling the adoption of renewable energy and the provision of ongoing services under emergency conditions. Load flow modeling and analysis were carried out using real network data for a case study in New York City (NYC). The results validate the hypothesis that distributed energy resources (DERs) at WRRFs can play a role in improving grid operation and resiliency.
      Citation: Smart Cities
      PubDate: 2023-12-11
      DOI: 10.3390/smartcities6060152
      Issue No: Vol. 6, No. 6 (2023)
       
  • Smart Cities, Vol. 6, Pages 3454-3492: Tech Giants’ Responsible
           Innovation and Technology Strategy: An International Policy Review

    • Authors: Wenda Li, Tan Yigitcanlar, Alireza Nili, Will Browne
      First page: 3454
      Abstract: As digital technology continues to evolve rapidly and get integrated into various aspects of our cities and societies, the alignment of technological advancements with societal values becomes paramount. The evolving socio-technical landscape has prompted an increased focus on responsible innovation and technology (RIT) among technology companies, driven by mounting public scrutiny, regulatory pressure, and concerns about reputation and long-term sustainability. This study contributes to the ongoing discourse on responsible practices by conducting a policy review that delves into insights from the most influential high-tech companies’—so-called tech giants’—RIT guidance. The findings disclose that (a) leading high-tech companies have started to focus on RIT; (b) the main RIT policy focus of the leading high-tech companies is artificial intelligence; (c) trustworthiness and acceptability of technology are the most common policy areas; (d) affordability related to technology outcomes and adoption is almost absent from the policy; and (e) sustainability considerations are rarely part of the RIT policy, but are included in annual corporate reporting. Additionally, this paper proposes a RIT assessment framework that integrates views from the policy community, academia, and the industry and can be used for evaluating how well high-tech companies adhere to RIT practices. The knowledge assembled in this study is instrumental in advancing RIT practices, ultimately contributing to technology-driven cities and societies that prioritise human and social well-being.
      Citation: Smart Cities
      PubDate: 2023-12-18
      DOI: 10.3390/smartcities6060153
      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 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)
       
 
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Heriot-Watt University
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