Search Results (781)

Cities around the world are facing growing challenges related to climate change, urban sprawl, infrastructure strain, and digital transformation. In response, smart and sustainable urban development has become a global focus, aiming to integrate technology and environmental stewardship to improve the quality of life. The smart and sustainable city concept is typically applied at the city scale; however, its impact is most tangible at the neighborhood level, where residents interact directly with infrastructure, services, and community spaces. A variety of global frameworks have been developed to assess sustainability and technological integration. However, these models often fall short in addressing localized needs, particularly in regions with distinct environmental and cultural contexts. In Saudi Arabia, Vision 2030 emphasizes livability, sustainability, and digital transformation, yet there remains a lack of tailored tools to evaluate smart and sustainable progress at the neighborhood scale. This study develops HayyScore, a localized evaluation framework and prototype digital platform developed to assess neighborhood performance across five core categories: (i) Environment and Urban Resilience, (ii) Smart Infrastructure and Governance, (iii) Mobility and Accessibility, (iv) Quality of Life and Social Inclusion, and (v) Economy and Innovation. The HayyScore platform operationalizes this framework through an interactive web-based tool that allows users to input data through structured forms, calculate scores, receive category-based and overall certification levels, and view results through visual dashboards. The methodology involved a comprehensive review of global frameworks, expert input to define localized indicators, and iterative prototyping of the platform using Python 3.13.5 and Streamlit 1.45.1. To demonstrate its practical application, the prototype was tested on two Saudi neighborhoods: King Abdullah Petroleum Studies and Research Center (KAPSARC) and King Fahd University of Petroleum and Minerals (KFUPM). Key platform features include automated scoring logic, category weighting, certification generation, dynamic performance charts, and a rankings page for comparing multiple neighborhoods. The platform is designed to be scalable, with the ability to add new indicators, support multilingual access, and integrate with real-time data systems in future iterations. Full article

The development of smart sustainable cities is closely linked to the advancement of city manufacturing, which aims to meet local demand while maintaining economic, social, and environmental balance. This concept is realised in large cities through City Multifloor Manufacturing Clusters (CMFMCs) equipped with City Logistics Nodes (CLNs) that manage intra- and extra-cluster logistics. These flows depend on supplies arriving via Intermodal Logistics Nodes (ILNs) located on city outskirts, where disruptions caused by intermodal supply chain uncertainty can significantly affect production continuity and urban sustainability. This study aims to develop a stochastic inventory management model for city manufacturing clusters operating under intermodal supply chain uncertainty. The model is designed to ensure stable and resilient material supply to city manufacturers by optimising buffer stock (BS) levels, reducing delivery delays, and improving transport and storage efficiency. Based on the Multi-Layer Bayesian Network Method (MLBNM), the model integrates probabilistic reasoning and resilience principles to support decision-making under uncertainty. A simulation-based case study of a representative CMFMC system was used for model verification and validation. The results show that the MLBNM-based approach enhances Sustainable Supply Chain Resilience (SSCR), improves inventory flexibility, and reduces environmental impacts. The study contributes to theory and practice by providing a quantitative framework for ensuring resilient and sustainable inventory management in city manufacturing systems. Full article

Building Information Modeling (BIM) has established itself as a strategic and indispensable tool for designing and implementing smart buildings within the context of smart cities. This study explores the potentialities and challenges of using BIM across the main stages of the smart building lifecycle: design, construction, and operation and maintenance. We conducted comprehensive, detailed, and interpretative literature research to extract the main concepts and knowledge, enabling us to identify the main potentialities and challenges and classify them by life-cycle phase for smart buildings. Potentialities and challenges were prioritized based on the number of projects that cited them. The inclusion criteria for identifying potentialities and challenges were based on their key attributes: significant impact, information modeling potential, integration capability with other tools and methods, and improved performance in processes and services across all life cycle phases and BIM dimensions. The findings reveal that the main potentials include optimizing information management, reducing operating costs, enhancing environmental sustainability, and enhancing decision-making processes. Furthermore, the study highlights BIM’s role in integrating technologies such as IoT, augmented reality, and energy simulations, contributing to the development of more sustainable and functional buildings. However, challenges to its full adoption persist, including financial constraints, interoperability issues between systems, a lack of specialized technical skills, and organizational resistance to change. The dependence on advanced technological infrastructure and robust connectivity poses an additional challenge, especially in developing countries, where such resources may be scarce or inconsistent. Finally, this study suggests that future research should explore the integration of BIM with emerging technologies, such as artificial intelligence and digital twins, further expanding its applicability in the smart urban context. Full article

While the ‘smart city’ concept is central to urban innovation, promising enhanced efficiency and livability, this paper interrogates a critical paradox: can cities be ‘smart’ yet ‘unlivable’? Existing indices, such as the IMD Smart City Index and the IESE Cities in Motion Index, while standard references, tend to prioritize technological and economic metrics, potentially failing to fully capture urban quality of life and sustainability. This study presents a preliminary attempt, based on an analysis of scientific literature, to critically examine current smart city indicators and propose a set of alternative indicators more representative of quality of life (QoL) and livability. The objective is not to overturn the rankings of cities like Zurich (high-ranking) and Athens (low-ranking), but to explore how a livability-focused approach, using more representative QoL indicators, might narrow the perceived gap between them, thereby highlighting diverse dimensions of urban performance. This research critically evaluates current smart city rankings. It aims to determine if livability-based indicators, supported by scientific literature, can provide a more balanced view of urban performance. This paper details how these alternative indicators were chosen, justifying their relevance to QoL with scientific support, and maps them to established smart city verticals (Smart Mobility, Smart Environment, Smart Governance, Smart Living, Smart People, Smart Economy). Finally, it outlines future research directions to further develop and validate this human-centric approach. Full article

City manufacturing (CM) is a key concept in smart sustainable cities. City multifloor manufacturing clusters (CMFMCs) are an integral part of large urban areas. Although smart sustainable CMFMCs attract growing attention, a major research gap remains. It concerns how different actors drive innovation within their supply chain ecosystems (SCEs). To address this gap, this paper examines the SCE of a CMFMC and knowledge management (KM) mechanisms of open innovation (OI), considering energy conservation (EC) policies. This qualitative study expands the understanding of the spatial configuration and key actors of the SCE of a CMFMC. It also analyses the role of the University Centre for Projects and Innovation (UCPI) as a physical orchestrator. The UCPI fosters innovation activity through KM based on OI and EC. Our findings contribute to the SCE literature by emphasizing the potential of its key actors. We show that an integrated approach to KM based on OI and EC enhances innovation in CMFMCs. This supports the sustainable development of smart cities. Full article

This study investigates the application and transformation potential of smart city concepts along Zhongyang Road in Hsinchu City, Taiwan. By introducing evaluation mechanisms such as the Smart City Maturity Index (SCMI) and the Composite Key Performance Indicator (CKPI), the research systematically analyzes the effectiveness of implementations across areas including transportation, energy, governance, and citizen engagement. Furthermore, Formula (1) is applied to assess the improvement in average delay time after the integration of smart technologies, while Formula (2) quantifies the annual energy savings achieved by replacing conventional streetlights with solar-powered ones, demonstrating tangible energy-saving and carbon-reduction benefits. The findings indicate that cross-sector collaboration and technological integration can significantly enhance urban operational efficiency and sustainability, providing valuable insights for the development of other new towns. Full article

Civil engineering today faces the challenge of responding to climate change, rapid urbanization, and the need to reduce environmental impacts. These factors drive the search for more sustainable approaches and the adoption of digital technologies. This article addresses three principal dimensions: advanced low-impact materials, resilient structural designs, and digital tools applied throughout the infrastructure life cycle. To this end, a systematic search was conducted considering studies published between 2020 and 2025, including both experimental and review works. The results show that materials such as geopolymers, biopolymers, natural fibers, and nanocomposites can significantly reduce the carbon footprint; however, they still face regulatory, cost, and adoption barriers. Likewise, modular, adaptable, and performance-based design proposals enhance infrastructure resilience against extreme climate events. Finally, digital tools such as Building Information Modeling, digital twins, artificial intelligence, the Internet of Things, and 3D printing provide improvements in planning, construction, and maintenance, though with limitations related to interoperability, investment, and training. In conclusion, the integration of materials, design, and digitalization presents a promising pathway toward safer, more resilient, and sustainable infrastructure, aligning with the Sustainable Development Goals and the concept of smart cities. Full article

As cities strive to become smarter and more sustainable, it becomes crucial to understand how residents perceive and engage with smart city initiatives. This study intends to ascertain citizens’ perceptions and priorities regarding smart city initiatives in the district of Porto (Portugal). To achieve this objective, a quantitative methodology was employed. The population’s understanding of the “smart city” concept and their satisfaction with smart urban services’ availability, were analyzed through an online questionnaire answered by 171 inhabitants of the region. The results reveal that 61.4% of participants identified theirs as a smart city, with significant differences in perception between men and women and different age groups. Services related to environment and sustainability were the most frequently recognized (77.8%), while those related to “Economy and Innovation” received less recognition (53.2%). In a hierarchy of priorities for improvements, participants highlighted “Quality of Life”, “Security and Privacy” and “Environment and Sustainability” as fundamental axes. This study suggests the need for greater alignment between municipal initiatives and citizen expectations, highlighting the importance of citizen participation in the development of strategies for smart cities. Full article

This paper examines the transformative role of the Digital Twin-Computer Vision combination (DT-CV combo) in industrial operations, focusing on its applications, challenges, and future directions. It aims to synthesize the existing literature and explore the practical use cases in operations management (OM). A comprehensive systematic literature review is conducted using PRISMA guidelines to analyze the DT-CV combo across the classification of industrial OM. However, given the breadth and importance of manufacturing and the OM field, the study excludes the literature on the DT-CV combo applied to other domains such as healthcare, smart buildings and cities, and transportation. We found that the DT-CV combo in OM is a relatively young but growing field of research. To date, only 29 articles have examined DT-CV combo solutions from various OM perspectives. Case studies are rare, with most studies relying on experimentation and laboratory testing to investigate DT-CV applications in the OM context. According to the cases and methods reviewed in the literature, the DT-CV combo has applications in different OM areas such as design, prototyping, simulation, real-time production monitoring, defect detection, process optimization, hazard detection and mitigation, safety training, emergency response simulation, optimal resource allocation, condition monitoring, inventory management, and scheduling maintenance. We also identified several benefits of DT-CV combo solutions in OM, including reducing human error, ensuring compliance with quality standards, lowering maintenance costs, mitigating production downtime, eliminating operational bottlenecks, and decreasing workplace accidents, while simultaneously improving the effectiveness of training. In this paper, we classify current applications of the DT-CV combo in OM, highlight gaps in the existing literature, and propose research questions to guide future studies in this domain. By considering the rapid phase of AI technology development and combining it with the current state of the art applications of the DT-CV combo in OM, we suggest novel concepts and future directions. The digital twin-vision language model (DT-VLM) combo as a future direction, emphasizing its potential to bridge physical–digital interfaces in industrial workflows, is one of the future development directions. Full article

The rapid increase in the aging population presents significant challenges to sustainable development. This is particularly true in relation to the areas of social inclusion, healthcare, and lifelong learning. As societies try to adapt to demographic change, it is important to develop innovative approaches that improve the quality of life of older adults while promoting their active participation in community life. Firstly, this paper examines current methods of activating seniors through social and technical engagement, with a particular focus on the concept of men’s sheds—a concept originating in Australia, in which a space where older adults men can socialize and engage in woodworking and other technical activities is offered. Despite the benefits of such initiatives, digital exclusion remains a key barrier that limits the full participation of seniors in a rapidly digitizing world. This paper explores the potential of integrating augmented reality (AR) into men’s sheds as a tool to limit digital gaps and support inclusive, active aging. The authors present a proposal and a practical implementation scenario for the use of AR in men’s sheds as a new concept to activate seniors. This paper examines the example of metal processing performed in men’s sheds using AR. The concept was then evaluated by experts. This paper presents the results of these experts’ opinions. The authors conducted interviews with seven experts. There were ten questions: seven closed-ended (rated on a scale from 1 to 5) and three open-ended questions. This study aligns with the concept of smart cities and the wider goals of sustainable development by promoting lifelong learning, intergenerational exchange, and improved well-being among seniors. Full article

In recent years, home energy management systems (HEMSs) have emerged as critical components within the concept of smart cities and grids. Within HEMSs, load flow analysis represents one of the fundamental tools for smart grid studies, forming the basis for a wide range of advanced applications, including state estimation, fault diagnosis, and optimal power flow computation. To achieve high levels of load flow accuracy and reliability, HEMSs must incorporate detailed models of all electrical elements found in modern residential units, including appliances, wiring, and energy resources. This paper proposes a load flow solution for smart home networks, featuring detailed models of wiring, appliances, and on-site generation systems. Moreover, a detailed appliance model derived from smart meter data, capable of representing both static-load devices and complex appliances with time-varying consumption profiles, is introduced. Additionally, a measurement-based validation of residential electrical wiring model is presented. The proposed models and calculation procedures have been verified by comparing the simulated results with the literature, yielding a deviation of approximately 0.7%. Analyses of a large-scale network have shown that this approach is up to six times faster compared to state-of-the-art procedures. The developed solution demonstrates practical applicability for use in industry-grade smart power management software. Full article

This empirical investigation explores the complex interdependencies between the concept of the Smart University Campus and the broader ecosystem of Smart City policies, with a particular focus on the New European Bauhaus initiative as a catalyst for educational transformation. The study examines how university campuses can evolve into paradigmatic models of innovation, sustainability, and inclusion through the strategic integration of emerging technologies, circular bioeconomy principles, and holistic ecological strategies. A comprehensive case study, grounded in rigorous quantitative analysis, including Principal Component Analysis (PCA), Importance-Performance Analysis (IPA), and Cluster Analysis (CA), based on questionnaires administered to a sample of 245 high school and university students—primarily from the academic community of the “King Mihai I” University of Life Sciences in Timișoara (USVT)—provides empirical insights into perceptions and expectations regarding the Smart Campus ecosystem and its core components: Smart Learning, Smart Living, Smart Safety and Security, Smart Socialization and Smart Health. The distinctive contribution of this research lies in its empirical demonstration that the strategic alignment between university campuses and Smart City initiatives, guided by the principles of the New European Bauhaus, can enhance educational efficiency by creating integrated learning ecosystems that simultaneously address academic needs, sustainability imperatives, and goals of sustainable urban development. Full article

Aware of the nefarious effects of excessive exploitation of natural resources and the greenhouse gases emissions linked to building sector, the concept of smart buildings emerged, referring to a building that uses clean energy efficiently. This requires intelligent control systems to manage the use of residential energy consuming devices, namely the HVAC (Heating, Ventilation, Air-conditioning) system. This system consumes up to 50% of the total energy used by a building. In this paper, we introduce a RL (Reinforcement Learning) and MPC-LSTM (Model Predictive Control-Long-Short Term Memory) hybrid control system that combines DNNs (Deep Neural Networks), through RL, with LSTM’s long-short memory technique and MPC’s control characteristics. The goal of our model is to maintain thermal comfort of residents while optimizing energy consumption. Consequently, to train and test our model, we generate our own dataset using a building model of a corporate building in Casablanca, Morocco, combined with weather data of the same city. Simulations confirm the robustness of our model as it outperforms basic control methods in terms of thermal comfort and energy consumption especially during summer. Compared to conventional methods, our approach resulted in a 45.4% and 70.9% reduction in energy consumption, in winter and summer, respectively. Our approach also resulted in 26 less comfort violations during winter. On the other hand, during summer, our approach found a compromise between energy consumption and comfort with no more than 2.5 °C above ideal temperature limit. Full article

Water is an essential resource for life and is also a necessary resource for the sustainable economic competitiveness of any country. In recent decades, climate change, economic development, and rising population have led to water scarcity in certain regions. In response, new technologies and water management techniques have been researched and developed, which are now incorporated into the concept of smart cities. These innovations, called smart water systems, aim to enhance water management by monitoring consumption, quality, reservoir levels, leaks, and asset conditions, and optimizing water processes to maximize water system resilience. The first systems were based on smart meters and have advanced to so-called digital twins for water systems. This review aims to present a comprehensive review of smart water system developments, the geographic distribution of the works, their technological readiness level, and their implementation challenges. Full article

This article presents a proposal for blending natural gas and biogas with a control system with feedback to ensure a constant mixture density. To achieve this, we propose the following: a mathematical model to determine the gas density based on its composition; a control system whose main components are a gas mixer, valves, and a natural gas storage tank to regulate the biogas density, where its inputs are gases from biomass plants and the natural gas grid; mathematical models to calculate the volume of natural gas required in the storage tank. It is assumed that the composition at the outlet of the biogas plants is measured and that there are no losses of any kind; a case study simulation is then performed. All models consider random variation in gas composition over time. The main results are as follows: (a) reduced natural gas consumption, the promotion of biogas production and use and of mixtures of lower methane compared to natural gas, and the facilitation of the pumping of the gas mixtures; (b) all the biogas produced is used; (c) different piping, sources, storage tanks, consumers, and mixer schemes, considering the concepts of cities, microgrids, smart grids, and smart cities. Full article