Smart Cities: Infrastructure, Innovation, Technology, Governance and Citizenship

Vehicular transportation is one of the most widely used modes in modern cities for reaching key destinations such as workplaces, healthcare facilities, recreational areas, and educational institutions, among others. However, the performance of vehicular traffic on these roads can vary significantly due to the influence of different environmental variables. In the literature, factors such as traffic incidents, weather conditions, road infrastructure, and driving habits, among others, have been identified as impacting vehicular traffic performance. In this context, predictive models have been developed to anticipate congestion at specific points in cities based on statistics, machine learning, simulation, and complex networks. This study proposes a novel index aimed at assessing the level of performance of vehicular traffic on streets based on the relationship among relevant urban environmental variables. This index is generated through Genetic Programming, considering a set of variables related to traffic, incidents, and services. The case study will focus on the streets of the Tlalpan Municipality in Mexico City. Full article

In the realm of construction site monitoring, ensuring the proper use of safety helmets is crucial. Addressing the issues of high parameter values and sluggish detection speed in current safety helmet detection algorithms, a feature-enhanced lightweight algorithm, LG-YOLOv8, was introduced. Firstly, we introduce C2f-GhostDynamicConv as a powerful tool. This module enhances feature extraction to represent safety helmet wearing features, aiming to improve the efficiency of computing resource utilization. Secondly, the Bi-directional Feature Pyramid (BiFPN) was employed to further enrich the feature information, integrating feature maps from various levels to achieve more comprehensive semantic information. Finally, to enhance the training speed of the model and achieve a more lightweight outcome, we introduce a novel lightweight asymmetric detection head (LADH-Head) to optimize the original YOLOv8-n’s detection head. Evaluations on the SWHD dataset confirm the effectiveness of the LG-YOLOv8 algorithm. Compared to the original YOLOv8-n algorithm, our approach achieves a mean Average Precision (mAP) of 94.1%, a 59.8% reduction in parameters, a 54.3% decrease in FLOPs, a 44.2% increase in FPS, and a 2.7 MB compression of the model size. Therefore, LG-YOLOv8 has high accuracy and fast detection speed for safety helmet detection, which realizes real-time accurate detection of safety helmets and an ideal lightweight effect. Full article

Mixed non-motorized traffic is largely unaffected by motor vehicle congestion, offering high accessibility and convenience, and thus serving as a primary mode of “last-mile” transportation in urban areas. To advance stochastic capacity estimation methods and provide reliable assessments of non-motorized roadway capacity, this study proposes a stochastic capacity estimation model based on power spectral analysis. The model treats discrete traffic flow data as a time-series signal and employs a stochastic signal parameter model to fit stochastic traffic flow patterns. Initially, UAVs and video cameras are used to capture videos of mixed non-motorized traffic flow. The video data were processed with an image detection algorithm based on the YOLO convolutional neural network and a video tracking algorithm using the DeepSORT multi-target tracking model, extracting data on traffic flow, density, speed, and rider characteristics. Then, the autocorrelation and partial autocorrelation functions of the signal are employed to distinguish among four classical stochastic signal parameter models. The model parameters are optimized by minimizing the AIC information criterion to identify the model with optimal fit. The fitted parametric models are analyzed by transforming them from the time domain to the frequency domain, and the power spectrum estimation model is then calculated. The experimental results show that the stochastic capacity model yields a pure EV capacity of 2060–3297 bikes/(h·m) and a pure bicycle capacity of 1538–2460 bikes/(h·m). The density–flow model calculates a pure EV capacity of 2349–2897 bikes/(h·m) and a pure bicycle capacity of 1753–2173 bikes/(h·m). The minimal difference between these estimates validates the effectiveness of the proposed model. These findings hold practical significance in addressing urban road congestion. Full article

Assessing the importance of nodes in urban rail transit systems helps enhance their ability to respond to emergencies and improve reliability in view of the fact that most of the existing methods for evaluating the importance of rail transit nodes ignore the disturbance effect of signaling system failures and are unable to objectively identify critical stations in specific disturbance scenarios. Therefore, this paper proposed a method for evaluating the importance of urban rail transit nodes in signaling system failure scenarios. The method was based on the research background of the signaling system failure that occurs most frequently and analyzed the network failure mechanism after the occurrence of a disturbance. The node importance evaluation indices were selected from the network topology and network operation performance in two aspects. The variation coefficient–VIKOR method was employed to comprehensively assess the significance of urban rail transit stations during signaling system failures. The Nanjing Metro network was also used as an example to evaluate the importance of network stations. The results showed that under the attack method of signaling system failure, most ECC and interlocking stations experienced significantly higher network performance losses compared to the original attack method, and a few interchange stations showed smaller performance losses. The critical stations identified based on the proposed method are mainly distributed in the passenger flow backbone of the Nanjing Metro and were constructed in the early stage; of these, 85% are ECC stations or interlocking stations, which are easily neglected in daily management, in contrast to interchange stations with heavy passenger flow. The results of this study can provide an important reference for the stable operation and sustainable construction of urban rail transit. Full article

Sound planning for urban mobility is a key facet of securing a sustainable future for our urban systems, and requires the careful and comprehensive assessment of its components, such as the status of the cities’ public transportation network, and how urban planners should invest in developing it. We use agent-based modelling, a tried and true method for such endeavours, for studying the history, planned future works and possible evolution of the tram line network in the Greater Geneva region. We couple these models with knowledge graphs, in a way that both are able to mutually enrich each other. Results show that the information organisation powers of knowledge graphs are highly relevant for effortlessly recounting past events and designing scenarios to be directly incorporated inside the agent-based model. The model features all 5 tram lines from the current real-world network, servicing a total of 15 communes. In turn, the model is capable of replaying past events, predicting future developments and exploring user-defined scenarios. It also harnesses its self-organisation properties to autonomously reconstruct an artificial public transportation network for the region based on two different initial networks, servicing up to 29 communes depending on the scenario. The data gathered from the simulation is effortlessly imported back into the initial knowledge graphs. The artificial networks closely resemble their real-world counterparts and demonstrate the predictive and prescriptive powers of our agent-based model. They constitute valuable assets towards a comprehensive assessment of urban mobility systems, compelling progress for the agent-based modelling field, and a convincing demonstration of its technical capabilities. Full article

This research, conducted as part of the European project PA-MAP (Participatory Approach to Monitoring Air Quality in Urban Environments), investigates citizens’ perceptions of air pollution in two European cities: Turin (Italy) and Dublin (Ireland). We systematically collected social data through semi-structured surveys distributed via online platforms. Our aim was to gather comprehensive information on the perception of pollution sources and the effectiveness of control systems. We examined citizens’ habits and their suggestions to improve air quality. The results revealed the following: (1) In Turin, the perception of air pollution significantly influences individuals’ self-assessments of health. Consequently, increased vigilance is required to mitigate environmental health risks and to disseminate information on air quality and effective practices for reducing air pollution. (2) The use of sustainable transportation in Turin is hindered due to the inadequate maintenance of cycling infrastructure. Citizens prefer to use cars or trains, which facilitate rapid travel. (3) In Dublin, greater sensitivity to the problem of air pollution has emerged, and the use of sustainable means of transport is facilitated via ad hoc infrastructure. These results provide empirical evidence to policymakers to support the promotion of concrete local actions through which to improve air quality. Full article

This paper introduces an innovative response to the pressing challenge of rapid and effective incident detection and management in urban settings. The proposed solution is a decentralized incident reporting system (IRS) harnessing blockchain technology and decentralized data storage systems. By empowering residents to report incidents, the proposed IRS enables seamless real-time monitoring and intervention by relevant departments. Built on a blockchain foundation, the proposed solution ensures immutability, transparency, security, and auditability, enhancing data resilience and comprehensive applicability. The proposed system leverages the InterPlanetary File System (IPFS) for the storage of incident proofs to manage the blockchain size effectively. Through the proposed IRS, transparency is upheld, enabling complete auditability of incident details and required interventions by citizens, societal bodies, and governmental bodies. Moreover, an incentive model is introduced to encourage active participation in incident reporting, thereby enhancing the system’s overall effectiveness and long-term sustainability. The proposed IRS integrates mobile technology to facilitate user engagement and data submission, essential for urban emergency management. Empirical validation using the Quorum–Raft blockchain demonstrates the feasibility of the proposed approach in terms of system throughput, incident reporting delay, blockchain size, and deployment cost. Specifically, the system maintains a latency of under 15 s even at high transaction rates, can handle up to 200 incidents per second, and is cost-effective, with deployment estimates for 16 organizations over five years being under 1.99 million USD. The method involves extensive testing with simulated incidents and user interactions to ensure robustness and scalability, showcasing the system’s potential for effective emergency management in urban environments. Full article

Urban development relies on the promotion of innovation, while sustainable development is an inevitable requirement for green urban development. As the primary carrier of innovation and sustainable development, cities have seen the construction of smart cities become a hotspot topic of public concern against the backdrop of rapid advancements in information technology. Based on the Chinese smart-city pilot policies, this paper selects data from 278 prefecture-level cities between 2007 and 2020, employing difference-in-difference (DID), epsilon-based measures and global Malmquist–Luenberger index (EBM-GLM), and the Spatial Durbin Model (SDM) to analyze the direct impact, spatial effects, and regional differences of smart-city construction on urban innovation capacity and sustainable development. The research results indicate the following: (1) the implementation of smart-city policies significantly enhances the urban innovation capacity ($UCI$), but its impact on green total-factor productivity ($GTFP$) is unstable and even insignificant; (2) the $UCI$ and $GTFP$ of smart cities have spillover effects, and the implementation of policies may inhibit the improvement of $UCI$ and $GTFP$ in neighboring cities; (3) the impact of smart-city construction varies across different regions, with a more significant promotion effect on the innovation capacity of economically developed cities. Full article

Roads are the most heavily affected aspect of urban infrastructure given the ever-increasing number of vehicles needed to provide mobility to residents, supply them with goods, and help sustain urban growth. An important indicator of degrading road infrastructure is the so-called bump features of the road surface (BFRS), which have affected transportation safety and driving experience. To collect BFRS, we can collect discrete-sampled, non-homogeneous multi-sensor stream data. We propose a BFRS detection method based on spectrum modeling and multi-dimensional features. With the sampling rate of GPS at 1 Hz and a gyroscope and accelerometer at 100 Hz, multi-sensor stream data are recorded at three different urban areas of Nanjing, China, using the smartphone mounted on a vehicle. The recorded stream data captures a geometric feature modeling movement and the respective driving conditions. Derived features also include acceleration, orientation, and speed information. To capture bump features, we develop a deep-learning-based approach based on so-called spectrum features. BFRS detection experiments using multi-sensor stream data from smartphones are conducted, and 4, 14, and 17 BFRS are correctly detected in three different areas, with the precision as 100%, 70.00%, and 77.27%, respectively. Then, comparisons are conducted between the proposed method and three other methods, and the F-score of the proposed method is computed as 1.0000, 0.6363, and 0.7555 at three different areas, which hold the highest value among all results. Finally, it shows that the proposed method performs well in different geographic areas. Full article

This paper elicits and analyzes the main requirements for Smart Pedestrian applications designed to enhance the pedestrian experience in urban environments by offering optimized walking routes, improved accessibility, and support for social inclusion and connectivity. Utilizing a mixed-methods approach, the research combines qualitative insights with quantitative data analysis based on surveys conducted in two strategically selected urban areas of Nicosia, Cyprus. Through the survey, the requirements and potential use of Smart Pedestrian apps are investigated while accounting for the quality of service of the urban infrastructure in a medium-sized city context. Additionally, the study contrasts the current smartphone applications, as they predominantly facilitate vehicular transportation, with the potential use of ICT/ITS to support pedestrians for sustainable mobility. The findings reveal a significant demand for a Pedestrian Smartphone app, driven by its ability to provide relevant information on optimum pedestrian routes, as well as act as a citizen’s voice for spotting infrastructure problems and improving the pedestrian network. Further, it is also revealed that limitations in the pedestrian infrastructure substantially restrict walking preferences, emphasizing the need for urgent city-level urban planning solutions to support active mobility. Additionally, the research carried out underscores the importance of a sustainable business model to support the successful deployment of Smart Pedestrian apps. Ultimately, the results of the study suggest prioritizing a smart technology leverage with a crowdsourcing social network business model to promote pedestrian mobility, thereby reducing vehicular dependence, enhancing public health, and improving the quality of life. Such an approach would act as catalyst for policymakers to concentrate on sustainability by investing in digital technology for integrated pedestrian networks, fostering the emergence of genuine smart cities. Full article

Inland areas have been affected by demographic and economic decline over the past decades. New economic models, which are more focused on a humane quality of life, encourage a revival of these territories as newer, healthier places for living. This paper focuses on minor centers, rethought as energy communities and how these can sustain themselves and become new places of living. The first part of the research critically analyzes current strategies of SECAPs (Sustainable Energy and Climate Action Plans) in smaller historic urban centers. The second part of the paper starts with the typological, morphological, and technological interscalar analysis of two case studies, testing a repeatable expeditious knowledge collection and an intervention method on them. For urban environments, the hypothesized interventions include the management of energy production from renewable sources that are compatible with the presence and value of urban and built heritage; concerning rural territories, an agro-energy park is proposed. The document aims to provide a repeatable method for planning strategic actions within SECAPs in smaller urban centers with a high historical connotation. The case studies show that energy self-sufficiency can be an opportunity to valorize the urban center while favoring environmental sustainability and local development. Full article

This study examines the optimization of ground source heat pump (GSHP) systems and energy piles for sustainable urban development, focusing on Southeast Asia. GSHPs, which utilize geothermal energy for indoor HVAC needs, offer a sustainable alternative to traditional systems by utilizing consistent subsurface temperatures for heating and cooling. The study highlights the importance of understanding thermal movement within the soil, especially in soft marine clays prevalent in Southeast Asia, to improve GSHP system efficiency. Using a one-dimensional finite difference model, the study examines the effects of soil thermal conductivity and density on system performance. The results show that GSHP systems, especially when integrated with energy piles, significantly reduce electricity consumption and greenhouse gas emissions, underscoring their potential to mitigate the urban heat island effect in densely populated areas. Despite challenges posed by the region’s hot and humid climate, which could affect long-term effectiveness, the study highlights the need for further study, including field experiments and advanced modeling techniques, to optimize GSHP configurations and fully exploit geothermal energy in urban environments. The study’s insights into soil thermal dynamics and system design optimization contribute to advancing sustainable urban infrastructure development. Full article

The built environment’s impact on human activities has been a hot issue in urban research. Compared to motorized spaces, the built environment of pedestrian and cycling street spaces dramatically influences people’s travel experience and travel mode choice. The streets’ built environment data play a vital role in urban design and management. However, the multi-source, heterogeneous, and massive data acquisition methods and tools for the built environment have become obstacles for urban design and management. To better realize the data acquisition and for deeper understanding of the urban built environment, this study develops a new portable, low-cost Arduino-based multi-sensor array integrated into a single portable unit for built environment measurements of street cycling spaces. The system consists of five sensors and an Arduino Mega board, aimed at measuring the characteristics of the street cycling space. It takes air quality, human sensation, road quality, and greenery as the detection objects. An integrated particulate matter laser sensor, a light intensity sensor, a temperature and humidity sensor, noise sensors, and an 8K panoramic camera are used for multi-source data acquisition in the street. The device has a mobile power supply display and a secure digital card to improve its portability. The study took Beijing as a sample case. A total of 127.97 G of video data and 4794 Kb of txt records were acquired in 36 working hours using the street built environment data acquisition device. The efficiency rose to 8474.21% compared to last year. As an alternative to conventional hardware used for this similar purpose, the device avoids the need to carry multiple types and models of sensing devices, making it possible to target multi-sensor data-based street built environment research. Second, the device’s power and storage capabilities make it portable, independent, and scalable, accelerating self-motivated development. Third, it dramatically reduces the cost. The device provides a methodological and technological basis for conceptualizing new research scenarios and potential applications. Full article

This paper details the comprehensive activities conducted in a laboratory setting to assess the structural health monitoring (SHM) of prefabricated building envelopes. Integrating sensors into building components like curtain wall facades poses challenges but offers opportunities for monitoring structural health, requiring compliance with regulatory standards. The research investigates the possibility of defining a kit of conventional and multi-parameter sensors integrated within the building envelope to monitor its behavior during the performance test conducted. The kit of sensors also includes Fiber Optic Sensors for effectively monitoring building envelope behavior and structural integrity. In this context, the European project InComEss (H2020-GA862597) aims to define a stand-alone solution for SHM using Piezoelectric Energy Harvesting Systems (PE-EHS) for façade monitoring through FBG/FOS system. After analyzing the main façade structural stress, a series of FBGs, accelerometers, and force washers were integrated within a 1:1 scale façade prototype and tested in a laboratory following the test sequence parameters required by the curtain wall standard EN 13830. The data collected were analyzed with the aim of monitoring the façade behavior before and after the tests. The results show that the façade’s performance passed the assessing test criteria without reporting any damages. In addition, the outcomes demonstrated the effectiveness of the defined kit of multi-parameter sensors for the building envelope’s SHM. Full article

The continuous growth of urban populations and the complexities of their current management in Africa have driven local governments to explore new technologies to optimize their urban and territorial performance. These governments and related stakeholders’ resort to the term “smart city” to orient the current urban planning policies and practices to be more efficient and adequate. Nevertheless, the issue that remains is how to contextualize this global term that has not yet been fully adopted by African cities that have claimed to be “Smart”. This contextualization becomes more complex in this critical context, where the city has not yet reached an ideal performance. Therefore, to reach this prospective African smart city, a critical review of how it would be both human-centered and techno-centered is imperative. This paper would review accordingly the above argument and set key performance indicator-based methodology on how to evaluate the smartness of a city in the African context. Full article

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. Full article

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. Full article

The incorporation of renewable energy sources necessitates the upgrade of the electrical grid to a smart grid, which involves the implementation of smart meters. Although smart meters provide benefits to users, many smart meter implementation projects have failed to be accepted by users. This article assesses the factors influencing the acceptance of household smart meters in Joinville, a city in the south of Brazil. Based on the Unified and Extended Theory of Acceptance and Use of Technology (UTAUT2), a structural equation model was estimated using data from a sample of 136 respondents in the city of Joinville. The results indicate that Performance Expectancy, Hedonic Motivation, and Social Influence constructs have a more substantial effect on the Intention to Use smart meters. The results provide evidence for planning the upgrade of the electrical grid by implementing smart meters in southern Brazil. Full article

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. Full article

Nowadays, the measurement of heat stress indices is of principal importance due to the escalating impact of global warming. As temperatures continue to rise, the well-being and health of individuals are increasingly at risk, which can lead to a detrimental effect on human performance and behavior. Hence, monitoring and assessing heat stress indices have become necessary for ensuring the safety and comfort of individuals. Thermal comfort indices, such as wet-bulb globe temperature (WBGT), Tropical Summer Index (TSI), and Predicted Heat Strain (PHS), as well as parameters like mean radiant temperature (MRT), are typically used for assessing and controlling heat stress conditions in working and urban environments. Therefore, measurement and monitoring of these parameters should be obtained for any environment in which people are constantly exposed. Modern cities collect and publish this relevant information following the Smart City concept. To monitor large cities, cost-effective solutions must be developed. This work presents the results of a Heat Stress Monitoring (HSM) system prototype network tested in the Benicalap-Ciutat Fallera district in Valencia, Spain. The scope of this work is to design, commission, and test a low-cost prototype that is able to measure heat stress indices. The Heat Stress Monitoring system comprises a central unit or receiver and several transmitters communicating via radiofrequency. The transmitter accurately measures wind speed, air temperature, relative humidity, atmospheric pressure, solar irradiation, and black globe temperature. The receiver has a 4G modem that sends the data to an SQL database in the cloud. The devices were tested over one year, showing that radio data transmission is reliable up to 700 m from the receiver. The system’s power supply, composed of a Photovoltaic panel and Lithium-ion batteries, provided off-grid capabilities to the transmitter, with a tested backup autonomy of up to 36 days per charge. Then, indicators such as WBGT, TSI, and MRT were successfully estimated using the data collected by the devices. The material cost of a 12-point network is around EUR 2430 with a competitive price of EUR 190 per device. Full article

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. Full article

The urban planning process is complex, involving social, economic, environmental, and political systems. Knowledge of how these systems interact is the domain of professional planners. Advances in artificial intelligence (AI) present planners with a ripe opportunity to critically assess their approaches and explore how new data collection, analysis, and methods can augment the understanding of places as they seek to anticipate futures with improved quality of life. AI can offer access to more and better information about travel patterns, energy consumption, land utilization, and environmental impacts, while also helping to better integrate these systems, which is what planners do. The adoption process will likely be gradual and involve significant time and resources. This article highlights several topics and issues that should be considered during this process. It is argued that planners will be well-served by approaching AI tools in a strategic manner that involves the topics discussed here. Full article

This paper provides an overview of the current state of research on the evaluation methods of participatory processes in smart cities. Specifically, it aims to identify and analyze existing evaluation methods and frameworks for public participation (PP) in smart city development. The study focuses on the evaluation of participatory processes to find key indicators and enable an assessment of PP from multiple perspectives. A scoping literature review was conducted to analyze the past ten years of scientific literature on the topic. Relevant literature was retrieved from Scopus, Web of Science, and Google Scholar, and articles were selected based on a set of criteria to ensure quality and relevance. We found that digital participation, also known as “e-participation”, is the most used method either exclusively or mixed with in-person methods. The level of participation achieved was mostly limited to the first two degrees of PP (i.e., information and consultation), and only a few papers addressed the highest degrees (i.e., agenda-setting and co-management). The impact on participants was mostly related to knowledge and skills, awareness raising, and satisfaction with the process and method. This paper highlights the potential to upskill citizens and enhance their understanding of sustainable urban development, fostering their commitment to achieving the United Nations’ sustainability goals for climate change mitigation in the urban context. Full article

This study aims to explore the challenges and issues in adopting cybersecurity practices in smart Saudi cities and to develop and validate a newly developed cybersecurity-based unified theory of acceptance and use of technology 3 (UTAUT3) model. The study has a twofold purpose. First, it identified the key challenges and issues in adopting smart cities in Saudi smart cities. Second, it developed a technology-based model to adopt cybersecurity practices in Saudi smart cities. Two surveys were conducted to achieve these objectives. The first survey identified challenges and gaps in adopting cybersecurity practices in smart cities, revealing concerns about weak cybersecurity platforms, privacy breaches, and the impact of IT infrastructure advancements on Saudi culture (N = 554: common public). The second survey focused on developing and validating a cybersecurity-based UTAUT3 model (N = 108: IT professionals), emphasizing nine factors: performance expectancy, effort expectancy, social influence, facilitating conditions, safety, resiliency, availability, confidentiality, and integrity of cybersecurity. The model’s validity and reliability were assessed, demonstrating its potential for understanding user behavior and adoption patterns in smart cities. The study findings provide valuable insights into the factors influencing the adoption of cybersecurity measures in smart Saudi cities, highlighting the need for targeted strategies, effective awareness programs, and collaboration between stakeholders to promote a secure and resilient digital environment. Future research may focus on refining the model, extending its applicability to other regions or countries, and investigating the impact of emerging technologies and evolving cyber threats on user behavior and cybersecurity practices. Full article

The construction of smart cities is an imperative trend for high-quality urban development and represents a crucial solution to various problems that afflict urbanization, such as population growth pressure, resource scarcity, environmental degradation, and economic frailty. To create a smart city, it is essential to gain a profound understanding of the evolution and experiences of urban development and have a clear grasp of the concept, emphasis, and developmental trajectory of smart cities. However, previous research and theoretical frameworks have mainly focused on the digital transformation of cities, the application of new generation information technologies, and the comprehensive intelligence of cities, neglecting the fundamental positioning and value of cities, which is the people’s central position and pursuit of happiness. This has led to many situations where intelligence is pursued for the sake of intelligence, resulting in inefficient use and allocation of resources. This paper puts forth a framework for the three generations of smart city construction and their meanings at the conceptual level, conducts an in-depth analysis of the development process and challenges of smart cities in China, and provides suggestions for improvement. Full article

Approximately 15% of the world’s population suffers from different types of disabilities. These people face many challenges when trying to interact with their home appliances. Various solutions are introduced to increase their quality of life, such as controlling their devices remotely through their voices. However, these solutions use command templates that fail to understand the unstructured or semi-structured command. Many authors have recently integrated intelligent personal assistant (IPA) systems, such as Google Assistant, Siri, and Alexa, with control circuits to exploit the advantages of the NLP of these IPAs to control traditional home appliances. However, this solution still struggles with understanding unstructured commands and requires the internet to be available for controlling the devices. This research proposes a new IPA system integrated with IoT, called IRON, for disabled people to use to control customizable devices with a structured and unstructured voice command. The proposed algorithm receives voice orders from the person in a structured or unstructured form and transforms them into text based on the Google Speech-to-Text API. The natural language processing technique splits the commands into tokens to determine the device name and the command type, whether it is a question about device status or a statement. Afterward, the logistic regression classifies the rest of the tokens as positive or negative to turn on or off the device, then sends the command to a Raspberry Pi to control the device. The proposed IRON system is implemented using logistic regression, naïve Bayes, and the support vector machine and is trained on a created dataset consisting of 3000 normal, negative, and unstructured commands. The simulation results show that the IRON system can determine 90% of the device’s names for all commands. Moreover, the IRON correctly classifies 100% of the commands as positive or negative within approximately 30 s. Full article

“Open Data” efforts are growing, especially in Europe, where open data are seen as a possible ethical driver of innovation. As smart cities continue to develop, it is important to explore how open data will affect the stakeholders of smart public spaces. Making data open and accessible not only has a managerial and technical component but also creates opportunities to shift power dynamics by granting individuals (and entities) access to data they might not otherwise be able to obtain. The scope of those who could access these data is wide, including data-illiterate citizens, burgeoning startups, and foreign militaries. This paper details the process of making data “open” from the MX3D smart bridge in Amsterdam through a “datathon”. The development and outcomes of opening the data and the event itself bring us closer to understanding the complexity of open data access and the extent to which it is useful or empowering for members of the public. While open data research continues to expand, there is still a dearth of studies that qualitatively detail the process and stakeholder concerns for a modern smart city project. This article serves to fill this gap. Full article