Search Results (167)

Hyperloop ultra-high-speed transport presents a transformative opportunity for future mobility systems in smart cities. However, assessing its socio-economic impact remains challenging due to Hyperloop’s unique technological, modal, and operational characteristics. As a novel, fifth mode of transportation—distinct from both aviation and rail—Hyperloop requires tailored evaluation tools for policymakers. This study proposes a custom-designed framework to quantify its macroeconomic effects through changes in gross domestic product (GDP) at the city level. Unlike traditional economic models, the proposed approach is specifically adapted to Hyperloop’s multimodality, infrastructure, speed profile, and digital-green footprint. A Poisson pseudo-maximum likelihood (PPML) model is developed and applied at two technology readiness levels (TRL-6 and TRL-9). Case studies of Glasgow, Berlin, and Busan are used to simulate impacts based on geo-spatial features and city-specific trade and accessibility indicators. Results indicate substantial GDP increases driven by factors such as expanded 60 min commute catchment zones, improved trade flows, and connectivity node density. For instance, under TRL-9 conditions, GDP uplift reaches over 260% in certain scenarios. The framework offers a scalable, reproducible tool for policymakers and urban planners to evaluate the economic potential of Hyperloop within the context of sustainable smart city development. Full article

Urban areas are at the forefront in addressing global challenges such as climate change and biodiversity loss. Among the key responses are nature-based solutions, which are increasingly being integrated into policy frameworks but which require strong community engagement for their effective implementation. This paper presents the findings of surveys conducted within the Place Lab in Katowice, Poland, an initiative developed as part of an international project and used as a participatory tool for co-creating and implementing green infrastructure. The project applies both place-based and people-centred approaches to support European cities in their transition towards regenerative urbanism. Place Lab activities encourage collaboration between local authorities and residents, enhancing awareness and fostering participation in environmental initiatives. The survey data collected during the project allowed for the evaluation of changes in public attitudes and levels of engagement and for the identification of broader societal phenomena that may influence the implementation of nature-based solutions. The findings revealed, for instance, that more women were interested in supporting the project, that residents tended to be sceptical of governmental actions on climate change, and that views were divided on the trade-off between urban infrastructure such as parking and roads and the presence of green areas. Furthermore, questions of responsibility, awareness, and long-term commitment were frequently raised. Building on the survey results and the existing literature, the study proposes a set of indicators to assess the contribution of citizen participation to the adoption of nature-based solutions. While the effectiveness of nature-based solutions in mitigating climate change impacts can be assessed relatively directly, evaluating civic engagement is more complex. Nevertheless, when conducted transparently and interpreted by experts, indicator-based assessment can offer valuable insights. This study introduces a novel perspective by considering not only drivers of engagement but also the obstacles. The proposed indicators provide a foundation for evaluating community readiness and commitment to nature-based approaches and may be adapted for application in other urban settings and in future research on climate resilience strategies. Full article

Understanding automated vehicle (AV) behavior in complex road environments and user attitudes in such contexts is critical for their safe and effective integration into smart cities. Despite growing deployment, limited public data exist on AV performance in construction zones; highly dynamic settings marked by irregular lane markings, shifting detours, and unpredictable human presence. This study investigates AV behavior in these conditions through qualitative, video-based analysis of user-documented experiences on YouTube, focusing on Tesla’s supervised Full Self-Driving (FSD) and Waymo systems. Spoken narration, captions, and subtitles were examined to evaluate AV perception, decision-making, control, and interaction with humans. Findings reveal that while AVs excel in structured tasks such as obstacle detection, lane tracking, and cautious speed control, they face challenges in interpreting temporary infrastructure, responding to unpredictable human actions, and navigating low-visibility environments. These limitations not only impact performance but also influence user trust and acceptance. The study underscores the need for continued technological refinement, improved infrastructure design, and user-informed deployment strategies. By addressing current shortcomings, this research offers critical insights into AV readiness for real-world conditions and contributes to safer, more adaptive urban mobility systems. Full article

Robotics has emerged as a transformative discipline at the intersection of the engineering, computer science, and cognitive sciences. This state-of-the-art review explores the current trends, methodologies, and challenges in both robotics research and education. This paper presents a comprehensive review of the evolution of robotics, tracing its development from early automation to intelligent, autonomous systems. Key enabling technologies, such as Artificial Intelligence (AI), soft robotics, the Internet of Things (IoT), and swarm intelligence, are examined along with real-world applications in healthcare, manufacturing, agriculture, and sustainable smart cities. A central focus is placed on robotics education, where hands-on, interdisciplinary learning is reshaping curricula from K–12 to postgraduate levels. This paper analyzes instructional models including project-based learning, laboratory work, capstone design courses, and robotics competitions, highlighting their effectiveness in developing both technical and creative competencies. Widely adopted platforms such as the Robot Operating System (ROS) are briefly discussed in the context of their educational value and real-world alignment. Through case studies, institutional insights, and synthesis of academic and industry practices, this review underscores the vital role of robotics education in fostering innovation, systems thinking, and workforce readiness. The paper concludes by identifying the key challenges and future directions to guide researchers, educators, industry stakeholders, and policymakers in advancing robotics as both technological and educational frontiers. Full article

As part of its modernisation and economic diversification policies, Saudi Arabia is building smart, sustainable cities intended to improve quality of life and meet environmental goals. However, involving the public in urban planning remains complex, with traditional methods often proving expensive, time-consuming, and inaccessible to many groups. Integrating artificial intelligence (AI) into public participation may help to address these limitations. This study explores whether Saudi residents are ready to engage with AI-driven tools in urban planning, how they prefer to interact with them, and what ethical concerns may arise. Using a quantitative, survey-based approach, the study collected data from 232 Saudi residents using non-probability stratified sampling. The survey assessed demographic influences on AI readiness, preferred engagement methods, and perceptions of ethical risks. The results showed a strong willingness among participants (200 respondents, 86%)—especially younger and university-educated respondents—to engage through AI platforms. Visual tools such as image and video analysis were the most preferred (96 respondents, 41%), while chatbots were less favoured (16 respondents, 17%). However, concerns were raised about privacy (76 respondents, 33%), bias (52 respondents, 22%), and over-reliance on technology (84 respondents, 36%). By exploring the intersection of generative AI and participatory urban governance, this study contributes directly to the discourse on inclusive smart city development. The research also offers insights into how AI-driven public engagement tools can be integrated into urban planning workflows to enhance the design, governance, and performance of the built environment. The findings suggest that AI has the potential to improve inclusivity and responsiveness in urban planning, but that its success depends on public trust, ethical safeguards, and the thoughtful design of accessible, user-friendly engagement platforms. Full article

This paper analyzes the factors affecting the willingness to pay of urban households concerned with efficient waste management in Bangladesh. The multistage random sampling approach selected 1400 families from seven major cities in Bangladesh. This study addresses the socioeconomic and environmental factors that influence urban households’ willingness to pay for improved waste management services in Bangladesh. This study uniquely contributes to the literature by providing a large-scale empirical analysis of 1470 households using a logit model, revealing income, education, and environmental awareness as key predictors of WTP. Detailed survey data from respondents were then analyzed using a logit model based on the contingent valuation method. Indeed, the logit model showed that six variables (education, monthly income, value of the asset, knowledge of environment, and climate change) had a statistically significant effect on the WTP of the households. The results show that 63% of respondents were willing to pay BDT 250 or more per month. The most influential factors driving this willingness to pay were income (OR = 1.35), education level (OR = 1.45), and environmental awareness (OR = 3.56). These variables all contribute positively towards WTP. The idea is that families have some socioeconomic characteristics, regardless of which they are ready to pay for a higher level of waste collection. It is recommended that government interference be affected through various approaches, as listed below: support for public–private sector undertaking and disposal, an extensive cleaning campaign, decentralized management, cutting waste transport costs, and privatization of some waste management systems. These could be used to develop solutions to better waste management systems and improve public health. Full article

Indonesia’s commitment to digital transformation is exemplified by the Gerakan 100 Smart City program, aiming to enhance public sector performance through technology integration. This study examines how information technology capability and 21st century digital skills influence public sector performance, mediated by managerial digital readiness and moderated by digital leadership. Grounded in Dynamic Capability Theory and Upper Echelon Theory, data from 1380 civil servants were analyzed using PLS-SEM via SmartPLS 4.1.0.9. Results show that both IT capability and digital skills significantly improve managerial digital readiness, which in turn positively impacts public sector performance. Managerial readiness mediates the effect of both predictors on performance, while digital leadership strengthens these relationships. Theoretically, this study frames managerial digital readiness as a dynamic capability shaped by leadership cognition. Practically, it highlights the importance of aligning infrastructure, skills, and leadership development to advance digital governance. Future research should consider longitudinal, multilevel, and qualitative designs to deepen insights. Full article

This research aims to assess the contribution of artificial intelligence (AI)-driven digital twin technology in improving the predictive planning of European smart cities, particularly in Greece. It considers the effect of specific elements including simulation accuracy, real-time data processing, artificial intelligence tools, and system readiness on the urban planning process. Structured questionnaires were administered to 301 urban professionals working in smart cities across Greece, focusing on their perceptions of the impact of digital twin features on predictive urban planning effectiveness. Respondents were asked how crucial they found the different features of digital twins in actually improving predictive urban planning. Measurement data were described using the arithmetic mean, standard deviation, and coefficient of variation, while categorical data were described using frequency distribution tables and percentages. This study revealed that the simulation fidelity, available real-time data integration, artificial intelligence analytics, and results- oriented monitoring system maturity have a positive impact on the accuracy, speed, and flexibility of urban planning. Some of the respondents noted these features as very useful for the prediction of urban conditions and decision-making purposes. Nevertheless, some drawbacks related to the computational load and data flow were also revealed. AI-driven digital twins are useful for improving the effectiveness of urban planning. However, they encounter technical issues; therefore, seeking to focus on system maturity and data integration is necessary for their successful implementation. Cities should adopt advanced digital twin technologies and enhance the compatibility of data and maintain AI transparency for better urban planning results. Full article

In the development process of the power industry, accurately assessing the level of development of the electricity business environment is of great significance. However, traditional evaluation systems have limitations, with the issue of “data silos” being prominent, and user privacy under federated learning is also at risk. This paper proposes a federated learning-based data protection method for the electricity business environment to address these challenges. Based on the World Bank’s B-READY framework, this paper constructs an electricity business environment evaluation system containing nine indicators, focusing on three aspects: electricity regulations, public services, and operational efficiency. The indicators are weighted using the Sequence Relation and Entropy Weight Method. To address the issue of sensitive data protection, we first use federated learning technology to build a distributed modeling framework, ensuring that raw data never leaves the local environment during the collaborative modeling process. Next, we embed a differential privacy mechanism in the model parameter transmission stage, encrypting the model parameters by adding controlled noise. Finally, an incentive mechanism based on contribution quantification is implemented to encourage participation from all parties. This paper conducts experiments using the data of Shenzhen City, Guangdong Province. Compared with the FNN model and the SVR model, the MLP model reduces MAE by 78.9% and 94.12%, respectively, and increases R² by 37.95% and 55.62%, respectively. The superiority of the method proposed in this paper has been proved. Full article

The digital transition and decarbonization are strategic European objectives, supported at different levels by the Green Deal, the Energy Performance Building Directive (EPBD), and policies and tools such as the Energy Performance Certificate (EPC) and the Smart Readiness Indicator (SRI). The SRI measures a building’s ability to use intelligent technologies to reduce its consumption and increase the energy awareness of occupants for energy efficiency. Furthermore, today, it has a limited impact on national regulations and public decision-making. Its application presents challenges including those related to heritage conservation. This paper contributes to the Italian SRI framework through an experimental application in the renovation of a historic building in the metropolitan city of Reggio Calabria (Italy). The analysis evaluates the SRI’s adaptability by comparing its pre-renovated state, current state, and pre-design plan. The SRI calculation integrates assessment tools with BIM models for a potential future digital twin approach. The study, part of a funded national research project, aims to enhance policies for digitalization in the green transition. The paper is organized into the Introduction; Materials and Methods, which contains the methodological approach; Results; and Discussion and Conclusions. Following the experimental application, the results show that standardizing the SRI approach could enhance energy efficiency and digitalization in buildings. Full article

This paper explores the relationship between digital readiness and sustainable development in European Union (EU) countries through a two-level cluster analysis based on the 2024 Network Readiness Index (NRI) and selected Sustainable Development Goals (SDGs). The first analysis groups countries by digital maturity across the NRI pillars: Technology, People, Governance, and Impact. The second focuses on SDG performance in areas such as health, education, gender equality, clean energy, and sustainable cities. Results reveal significant disparities between digital readiness and SDG achievements: some digitally advanced countries underperform in sustainability, while others with lower digital scores excel in SDG outcomes. The study identifies regional patterns, confirms a moderate positive correlation between NRI and SDG clusters (r_s = 0.526), and underscores the need for integrated digital and sustainability policies. Recommendations are provided for targeted policymaking and international cooperation. Full article

This study investigates the relationship between climate change, urban greening, and health perceptions among university students within higher education. Grounded in environmental psychology and sustainability science, it explores how well-being is shaped by climate–health awareness, eco-anxiety, and perceived access to urban green spaces. A mixed-methods approach was employed, using structured questionnaires to assess cognitive, emotional, and behavioral responses to climate change and sustainability. The findings indicate a high awareness of the health impacts of climate change, especially concerning mental well-being. Urban green spaces were recognized as positively influencing emotional resilience, physical activity, and environmental quality. However, despite this awareness, limited engagement in sustainability-oriented behaviors was identified, indicating an action gap. The study suggests the creation of a Climate Health Assessment Indicator to evaluate climate–health literacy and behavioral readiness among academic populations systematically. It also emphasizes integrating identity-based interventions into educational frameworks to support the transition from awareness to sustainable action. Positioned within the broader framework of the Sustainable Development Goals—particularly SDG 3 (Good Health and Well-Being), SDG 11 (Sustainable Cities), SDG 12 (Responsible Consumption), and SDG 13 (Climate Action)—this research contributes to the interdisciplinary discourse on integrating sustainability and human well-being in academic and urban contexts. Full article

The circular economy has emerged as a pivotal strategy for cities to reconcile economic growth with environmental sustainability. However, its implementation in resource-dependent Gulf Cooperation Council contexts remains underexplored. This study is among the first to empirically assess circular economy readiness in a Gulf Cooperation Council industrial hub through a mixed-method approach, bridging the gap between expert perceptions and localized policy implementation. Focusing on the Dammam Metropolitan Area, Saudi Arabia, a critical industrial anchor for Saudi Vision 2030, this study combines a cross-sectional survey of 230 policymakers, industry leaders, and academics with descriptive/inferential statistics (SPSS) and qualitative thematic coding (NVivo). The findings identify renewable energy (mean = 4.10) and municipal waste management (mean = 3.78) as top sectoral priorities, aligning with national sustainability goals. Yet systemic challenges, including fragmented governance, limited public awareness (mean = 3.65), and funding gaps (mean = 3.52), underscore disparities between Vision 2030’s ambitions and localized capacities. Statistical analyses reveal strong associations between institutional fragmentation and financial inefficiencies (χ² = 23.45, * p = 0.010), while mid-career workforce dominance (54.8%) and underrepresentation of policymakers (6.5%) highlight governance gaps. The current study advocates hybrid strategies: stricter waste regulations (40.0% stakeholder priority), circular economy training programs, and public–private partnerships to scale waste-to-energy infrastructure and industrial symbiosis. Despite pragmatic optimism (48.7% foresee 21–40% recycling by 2030), limitations such as reliance on expert perspectives and exclusion of citizen voices necessitate future interdisciplinary and longitudinal research. By aligning regulatory rigor with inclusive governance, the Dammam Metropolitan Area can model a Gulf-centric circular economy transition, advancing regional sustainability while contributing actionable insights for resource-dependent economies globally. Full article

Rapid urbanization and car dependency have transformed Riyadh into a sprawling metropolis, straining mobility, sustainability, and land use efficiency. Investments in metro and Bus Rapid Transit (BRT) systems present an opportunity to shift toward transit-oriented development (TOD), making strategic urban planning essential. This study assesses Riyadh’s TOD potential by analyzing its urban structure, transport accessibility, and regulatory framework while drawing lessons from successful global models. This study applies GIS-based spatial analysis, policy review, and AI-driven clustering techniques (e.g., DBSCAN, K-Means) to evaluate TOD readiness and inform actionable strategies for Riyadh. The findings indicate that transit investments alone are insufficient due to gaps in zoning policies, pedestrian connectivity, and urban density. Enhancing compact, mixed-use developments, improving first- and last-mile accessibility, and leveraging AI-driven planning can reshape the city’s mobility ecosystem and foster sustainable urban growth. Vision 2030 provides a pivotal opportunity to align infrastructure investments with urban planning policies, ensuring Riyadh evolves into a modern, efficient, and transit-friendly city. Full article

Integrating autonomous vehicles (AVs) into urban traffic systems presents significant opportunities for optimizing traffic flow, reducing congestion, and enhancing transportation efficiency. This study proposes a comprehensive framework that combines mathematical optimization techniques, policy planning, and AV adoption modeling to improve urban mobility. Using Highway Capacity Manual (HCM) Optimization methods, the research fine-tunes traffic signal timings, dynamically allocates green time, and enhances intersection coordination to maximize throughput. The study evaluates the impact of AV penetration on traffic flow efficiency, congestion reduction, and infrastructure readiness using real-world urban data from Riyadh. The results indicate that AV integration leads to a 40% increase in traffic throughput, a 60% reduction in congestion levels, and a 45% improvement in infrastructure readiness, highlighting the effectiveness of AV-driven traffic optimization strategies. Additionally, policy interventions aimed at reducing legal constraints and increasing societal acceptance contribute to the successful implementation of AV technology. The findings provide a data-driven roadmap for city planners and policymakers, demonstrating how a well-structured AV deployment strategy can significantly enhance urban transportation efficiency. Full article