Search Results (14)

The efficient management of urban parking systems has emerged as a pivotal issue in today’s smart cities, where increasing vehicle populations strain limited parking infrastructure and challenge sustainable urban mobility. Aligned with the United Nations 2030 Agenda for Sustainable Development and the strategic goals of smart city planning, this study presents a sustainability-driven, multiagent simulation-based framework to model, analyze, and optimize smart parking dynamics in congested urban settings. The system architecture integrates ground-level IoT sensors installed in parking spaces, enabling real-time occupancy detection and communication with a centralized system using low-power wide-area communication protocols (LPWAN). This study introduces an intelligent parking guidance mechanism that dynamically directs drivers to the nearest available slots based on location, historical traffic flow, and predicted availability. To manage real-time data flow, the framework incorporates message queuing telemetry transport (MQTT) protocols and edge processing units for low-latency updates. A predictive algorithm, combining spatial data, usage patterns, and time-series forecasting, supports decision-making for future slot allocation and dynamic pricing policies. Field simulations, calibrated with sensor data in a representative high-density urban district, assess system performance under peak and off-peak conditions. A comparative evaluation against traditional first-come-first-served and static parking systems highlights significant gains: average parking search time is reduced by 42%, vehicular congestion near parking zones declines by 35%, and emissions from circling vehicles drop by 27%. The system also improves user satisfaction by enabling mobile app-based reservation and payment options. These findings contribute to broader sustainability goals by supporting efficient land use, reducing environmental impacts, and enhancing urban livability—key dimensions emphasized in sustainable smart city strategies. The proposed framework offers a scalable, interdisciplinary solution for urban planners and policymakers striving to design inclusive, resilient, and environmentally responsible urban mobility systems. Full article

The convergence of blockchain and metaverse technologies is poised to redefine how Global Value Chains (GVCs) create, capture, and distribute value, yet scholarly insight into their joint impact remains scattered. Addressing this gap, the present study aims to clarify where, how, and under what conditions blockchain-enabled transparency and metaverse-enabled immersion enhance GVC performance. A systematic literature review (SLR), conducted according to PRISMA 2020 guidelines, screened 300 articles from ABI Global, Business Source Premier, and Web of Science records, yielding 65 peer-reviewed articles for in-depth analysis. The corpus was coded thematically and mapped against three theoretical lenses: transaction cost theory, resource-based view, and network/ecosystem perspectives. Key findings reveal the following: 1. digital twins anchored in immersive platforms reduce planning cycles by up to 30% and enable real-time, cross-border supply chain reconfiguration; 2. tokenized assets, micro-transactions, and decentralized finance (DeFi) are spawning new revenue models but simultaneously shift tax triggers and compliance burdens; 3. cross-chain protocols are critical for scalable trust, yet regulatory fragmentation—exemplified by divergent EU, U.S., and APAC rules—creates non-trivial coordination costs; and 4. traditional IB theories require extension to account for digital-capability orchestration, emerging cost centers (licensing, reserve backing, data audits), and metaverse-driven network effects. Based on these insights, this study recommends that managers adopt phased licensing and geo-aware tax engines, embed region-specific compliance flags in smart-contract metadata, and pilot digital-twin initiatives in sandbox-friendly jurisdictions. Policymakers are urged to accelerate work on interoperability and reporting standards to prevent systemic bottlenecks. Finally, researchers should pursue multi-case and longitudinal studies measuring the financial and ESG outcomes of integrated blockchain–metaverse deployments. By synthesizing disparate streams and articulating a forward agenda, this review provides a conceptual bridge for international business scholarship and a practical roadmap for firms navigating the next wave of digital GVC transformation. Full article

This article analyzes the service distribution imbalance within the Metropolitan District of Quito (DMQ) and its impact on urban mobility, aiming to propose strategies for more equitable territorial planning. The data were gathered from sources such as the National Institute of Statistics and Census (INEC), the Ministry of Health, the Ministry of Education, and OpenStreetMap. These data were integrated with GIS tools to model patterns of accessibility and mobility. Through a comprehensive approach, the study assessed education, banking services, employment, and healthcare, identifying how inequitable access to these services drives increased travel demand, especially in rural and peri-urban areas. In the education field, over 500 neighborhoods faced a shortage of institutions, compelling students to commute to other neighborhoods. For financial services, only 67% of neighborhoods had adequate access, with disparities across different socioeconomic zones. Additionally, employment-related mobility posed another challenge, with 88% of workers commuting outside their residential parish. Finally, access to healthcare was also unequal across the DMQ, particularly in peripheral areas where residents must travel long distances. In this context, it can be concluded that more efficient urban planning in the Metropolitan District of Quito (DMQ) is crucial to address imbalances in the distribution of services and enhance quality of life. Proposed strategies include establishing a land reserve, decentralizing services to underserved areas, integrating smart technologies, and promoting incentives for remote work, sustainable mobility, and public transport. These actions aim to foster greater territorial equity and accessibility. Full article

As waterflooding multi-layer reservoirs reach the high-water-cut stage, inter-layer conflicts become increasingly serious, leading to a worsening development effect over time. Production layer regrouping is an effective approach for resolving inter-layer conflicts and improving waterflooding efficiency. At the current stage, there are limitations to most of the methods of production layer regrouping. This article proposes a smart method for optimizing the layer regroup plan based on a genetic algorithm. Comprehensively considering various factors that affect the regroup of layers, such as layer thickness, porosity, permeability, remaining oil saturation, remaining reserves, recovery ratio, water cut, etc., based on the combination principle of “smaller intra-group variance and larger inter-group variance of each influencing factor are expected”, a genetic algorithm is used to calculate the fitness value of the initial combination schemes, and the advantageous schemes with higher fitness values are selected as the basis of the next generation. Then, crossover and mutation operations are performed on those advantageous schemes to generate new schemes. Through continuous selection and evolution, until the global optimal solution with the highest fitness value is found, the optimal combination scheme is determined. Comparative analysis with numerical simulation results demonstrates the reliability of this intelligent method, with an increased oil recovery of 4.34% for the sample reservoir. Unlike selecting a preferable plan from a limited number of predefined combination schemes, this method is an automatic optimization to solve the optimal solution of the problem. It improves both efficiency and accuracy as compared to conventional reservoir engineering methods, numerical simulation methods, and most mathematical methods, thus providing effective guidance for EOR strategies of waterflooding reservoirs in the high-water-cut stage. Full article

Estimation of the power obtained from intermittent renewable energy sources (IRESs) is an important issue for the integration of these power plants into the power system. In this study, the expected power not served (EPNS) formula, a reliability criterion for power systems, is developed with a new method that takes into consideration the power generated from IRESs and the consumed power (CP) estimation errors. In the proposed method, CP, generated wind power (GWP), and generated solar power (GSP) predictions made with machine learning methods are included in the EPNS formulation. The most accurate prediction results were obtained with the Multi Layer Perceptron (MLP), Long-Short Term Memory (LSTM), and Convolutional Neural Network (CNN) algorithms used for prediction, and these results were compared. Using different forecasting methods, the relation between forecast accuracy, reserve requirement, and total cost was examined. Reliability, smart reserve planning (SRP), and total cost analysis for power systems were carried out with the CNN algorithm, which provides the most successful prediction result among the prediction algorithms used. The effect of increasing the limit EPNS value allowed by the power system operator, that is, reducing the system reliability, on the reserve requirement and total cost has been revealed. This study provides a useful proposal for the integration of IRESs, such as solar and wind power plants, into power systems. Full article

The diffusion of electric vehicles is fundamental for transport sector decarbonization. However, a major concern about electric vehicles is their compatibility with power grids. Adopting a whole-power-system approach, this work presents a comprehensive analysis of the impacts and benefits of electric vehicles’ diffusion on a national power system, i.e., Italy. Demand and flexibility profiles are estimated with a detailed review of the literature on the topic, allowing us to put forward reliable charging profiles and the resulting flexibility, compatible with the Italian regulatory framework. Distribution network planning and power system dispatching are handled with dedicated models, while the uncertainty associated with EV charging behavior is managed with a Monte Carlo approach. The novelty of this study is considering a nationwide context, considering both transmission and distribution systems, and proposing a set of policies suitable for enabling flexibility provision. The results show that the power and energy demand created by the spread of EVs will have localized impacts on power and voltage limits of the distribution network, while the consequences for transmission grids and dispatching will be negligible. In 2030 scenarios, smart charging reduces grid elements’ violations (−23%, −100%), dispatching costs (−43%), and RES curtailment (−50%). Full article

The electrification of the transportation sector contributes to a cleaner environment in non-interconnected island (NII) systems or standalone islands. Moreover, e-mobility can significantly contribute to achieving very high renewable energy source (RES) penetration levels in islands, allowing a reduction both in the emissions due to the conventional generation and the system’s cost. Ιncreased RES penetration, however, can pose technical challenges for an island’s system. In order to overcome these challenges, new technologies like grid-forming converters are important. Moreover, the provision of new ancillary services in relation to battery storage systems might be considered, while novel control and protection schemes are needed to ensure secure operation. E-mobility can also contribute to solving technical problems that arise from very high RES penetration by providing frequency containment reserves or reactive power compensation. Since EV charging demand introduces modifications in the system’s load curve, e-mobility may affect the power grid for long-term planning and short-term operation, i.e., line loading and voltages. The application of specifically developed smart charging methodologies can mitigate the relevant grid impact, while effective exploitation of EV–RES synergies can achieve higher RES penetration levels. This paper examines how e-mobility can contribute to increasing RES penetration in islands while considering the technical issues caused. In particular, this paper takes into account the distinct characteristics of NIIs towards the identification of solutions that will achieve very high RES penetration while also addressing the relevant technical challenges (voltage control, frequency control, short circuit protection, etc.). The effect of e-mobility in the power grid of NII systems is evaluated, while smart charging methodologies to mitigate the relevant impact and further increase RES penetration are identified. Full article

It is helpful to have a replacement strategy by predicting the number of failures of in-service electricity meters. This paper presents a failure number prediction method for smart electricity meters based on on-site fault data. The prediction model was constructed by combining Weibull distribution with odds ratios, then the distribution parameters, failure prediction number, and confidence intervals of prediction number were calculated. A strategy of meter replacement and reserve were developed according to the prediction results. To avoid the uncertainty of prediction results due to the small amount of field data information, a Bayesian failure number prediction method was developed. The research results have value for making operation plans and reserve strategies for electricity meters. Full article

Efficient electronic waste (e-waste) management is one of the vital strategies to save materials, including critical minerals and precious metals with limited global reserves. The e-waste collection issue has gained increasing attention in recent years, especially in developing countries, due to low collection rates. This study aims to search for progressive solutions in the e-waste collection sphere with close-to-zero transport and infrastructure costs and the minimization of consumers’ efforts towards an enhanced e-waste management efficiency and collection rate. Along these lines, the present paper develops a smart reverse system of e-waste from end-of-life electronics holders to local recycling infrastructures based on intelligent information technology (IT) tools involving local delivery services to collect e-waste and connecting with interactive online maps of users’ requests. This system considers the vehicles of local delivery services as potential mobile collection points that collect and deliver e-waste to a local recycling enterprise with a minimum deviation from the planned routes. Besides e-waste transport and infrastructure costs minimization, the proposed smart e-waste reverse system supports the reduction of CO₂ through the optimal deployment of e-waste collection vehicles. The present study also advances a solid rationale for involving local e-waste operators as key stakeholders of the smart e-waste reverse system. Deploying the business model canvas (BMC) toolkit, a business model of the developed system has been built for the case of Sumy city, Ukraine, and discussed in light of recent studies. Full article

Indonesia’s new planned capital in East Kalimantan is being touted as a “smart, green, beautiful and sustainable city” but has stoked fears of massive environmental damage to the island of Borneo, one of the world’s most important biodiversity hotspots and carbon sinks. Precedents of other planned capitals can contribute to an understanding of the potential long-term impacts of Indonesia’s new capital. We used historical nighttime lights to quantitatively assess the spatial growth footprint of 12 previous planned capitals, and conducted land-use analyses to identify the potential environmental impacts on Borneo’s natural environment. Our assessment suggests that it is likely that the direct footprint of the new capital could grow rapidly, expanding over 10 km from its core in less than two decades and over 30 km before mid-century. We identified sensitive ecosystems which may be affected by the new capital’s direct and indirect footprint, such as forest reserves, mangrove and peat. Deforestation emissions from the new capital’s direct (30 km) and indirect (200 km) footprint could be approximately 50 MtCO_2e and 2326 MtCO_2e respectively, equivalent to 2.7% and 126% of Indonesia’s 2014 greenhouse gas emissions. We discuss how planned capitals can spatially restructure the socio-political geographies of cities and nation-states by interacting with meanings, symbolisms and power relations, which may aggravate environmental impacts but also be seized upon as a catalyst for improving environmental performance in Borneo and Indonesia. Finally, we recommend the use of best practices in impact assessment and sustainability as a necessary first step towards protecting Borneo. Full article

This paper explores a future perspective to foster the provision of balancing services to the electricity grid by distributed assets. One recent test case, initiated by the Dutch Transmission System Operator (TSO), was to operate an Electric Vehicle (EV) fleet on the automatic Frequency Restoration Reserve (aFRR) market, which entails fast and automated reserves. To achieve that in a decentralised, automated and transparent manner, the role of blockchain technology for this specific application is explored. We propose a novel configuration that can serve as a basis for deploying distributed assets for aFRR markets using blockchain or any alternative Distributed Ledger Technology (DLT). Automation can be achieved via the deployment of smart contracts, which also results in transparency in the system. The blockchain configurations are designed for three phases in the aFRR market, namely: (i) Operational planning and scheduling by a balancing service provider (i.e., formulation and submission of aFRR bid), (ii) Real-time operations (i.e., activation and measurements), and (iii) Verification and settlement (i.e., imbalance correction and financial settlement). The paper concludes that the scalability of distributed assets that can participate in the system, combined with the large transaction times and energy consumption of some consensus mechanisms, could put limitations on the proposed architecture. Future research should address benchmarking studies of other alternatives (e.g., DLTs, such as the ones based on directed acyclic graphs, and non-DLT solutions) with the proposed blockchain solution. Full article

In recent years, most cities have experienced rapid population growth. Concurrently, international policies have called for substantial reductions of greenhouse gas emissions. Additionally, the resilience of energy-supply systems has become more important. Consequently, solutions to exhaust locally-available sources must be developed to minimize the fraction of fossil fuels for heating, cooling and electricity. This article shows an example of designing a low-temperature heating and cooling grid based on locally-available renewables and waste heat and introduces general hypotheses concerning smart energy planning in urban development zones. Taking an urban development area in Vienna, Austria, as example, it is shown that wastewater, geothermal and (office) waste heat, solar energy, and the heat content of ambient air can play an important role within a climate-friendly urban energy concept and that heating and cooling demand can be covered completely on-site. From an environmental point of view, the concept is promising, as greenhouse gas emissions and the non-renewable primary energy consumption can be reduced by over 70% compared to conventional gas heating, while, based on current (fossil) energy prices, it is economically not fully competitive. The gap could be closed e.g. by CO₂ taxes on fossil energy sources or (temporal) subsidies for renewables. Additionally, reservations of stakeholders in the energy sector against this innovative approach must be dismantled. Full article

This paper presents the development of a parking occupancy simulator to support a smart parking system. The simulator uses an agent-based approach to model drivers who follow activity plans and who may or may not use the smart parking system. We illustrate how the process of developing our simulator helped in the design and implementation of the smart parking system components. The paper also shows how the simulator was used to study the possible usage of the smart parking system in a university campus, foreseeing (1) support for the smart parking system’s overall suitability, (2) reservation guarantee violation problems, and (3) the value of using total traveled distance as a metric for the smart parking evaluation. The experience presented in this paper may prove valuable to teams planning the development of a smart parking system for similar contexts. Full article

The smart and resilient city evolves by slow procedures of mutation without radical changes, increasing the livability of its territory. The value of the city center in a Smart City can increase through urban lighting systems: its elements on the territory can collect and convey data to increase services to city users; the electrical system becomes the so-called Smart Grid. This paper presents a study of smart lighting for a small town, a touristic location inside a nature reserve on the Italian coast. Three different approaches have been proposed, from minimal to more invasive interventions, and their effect on the territory has been investigated. Based on street typology and its surroundings, the work analyzes the opportunity to introduce smart and useful services for the citizens starting from a retrofitting intervention. Smart city capabilities are examined, showing how it is possible to provide new services to the cities through ICT (Information and Communication Technology) without deep changes and simplifying the control of basic city functions. The results evidence an important impact on annual energy costs, suggesting smart grid planning not only for metropolis applications, but also in smaller towns, such as the examined one. Full article