Smart Cities

25 pages, 1004 KB

Open AccessArticle

From Open Urban Data to Locative Services: Eligibility Criteria and a Faceted Typology for Urban Digital Locative Elements

by José Eurico Vasconcelos Filho, Maurício Bezerra, Carlos Carvalho, Pedro Henrique Nunes and Rui José

Smart Cities 2026, 9(8), 135; https://doi.org/10.3390/smartcities9080135 - 21 Aug 2026

Viewed by 348

Abstract

Open urban data portals are increasingly proposed as infrastructures for citizen-facing locative services, yet there are no explicit criteria for deciding which georeferenced entities qualify as urban digital locative elements, nor a principled basis for organising them. This hinders semantic interoperability, discovery, and [...] Read more.

Open urban data portals are increasingly proposed as infrastructures for citizen-facing locative services, yet there are no explicit criteria for deciding which georeferenced entities qualify as urban digital locative elements, nor a principled basis for organising them. This hinders semantic interoperability, discovery, and reuse. This article pursues three objectives: to define eligibility criteria distinguishing such elements from other georeferenced data; to derive a faceted, multi-label typology organising them for discovery and reuse; and to assess operational feasibility in a real setting. Following a design-science approach, the artefact, five eligibility criteria and a nine-category typology, was derived by synthesising three evidence sources: a structured literature review, a comparative analysis of six CKAN-based portals in Portugal and Brazil, and an exploratory pilot in Fortaleza, with explicit mappings to FIWARE, schema.org/Place, OpenStreetMap, and CityGML/INSPIRE. The framework was then exercised on the portal corpus and in a working platform, complemented by a small in-situ user study (n = 17). The criteria filtered locative elements effectively, all categories were populated by real datasets, and category-based discovery was understandable in situ, though these findings are preliminary. Open government data thus emerges as an active layer for operationalising locative services, with broader validation left to future work. Full article

(This article belongs to the Collection Smart Governance and Policy)

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25 pages, 11254 KB

Open AccessArticle

MemGeoSeg: Location-Aware Semantic Segmentation with Spatially Indexed Memory for Repetitive Driving Scenarios

by Huei-Yung Lin and Jou-An Tsai

Smart Cities 2026, 9(8), 134; https://doi.org/10.3390/smartcities9080134 - 19 Aug 2026

Viewed by 284

Abstract

Current visual perception techniques for self-driving vehicles mainly focus on the generalization across diverse scenes, and they often overlook the valuable spatial consistency present in the repetitive driving routes such as public transit lines, delivery and shuttle services. In this paper, we introduce [...] Read more.

Current visual perception techniques for self-driving vehicles mainly focus on the generalization across diverse scenes, and they often overlook the valuable spatial consistency present in the repetitive driving routes such as public transit lines, delivery and shuttle services. In this paper, we introduce MemGeoSeg, which is a novel multi-modal framework that enhances semantic segmentation by exploiting scene repetitions through GPS-guided spatial priors and historical memory. Our approach introduces a hierarchical GPS embedding module, which is a spatially indexed memory bank that accumulates location-specific visual knowledge and a cross-modal fusion mechanism with contrastive learning. To validate the idea of improving visual perception with repetitive driving scenarios, a new dataset, RMTD-AD, is constructed for evaluation. It contains over 13,000 annotated images across various weather and lighting conditions on repeated routes. Extensive experiments conducted on the dataset have demonstrated that MemGeoSeg significantly outperforms the state-of-the-art baseline, achieving an mIoU of 76.5% compared to SegFormer’s 71.8% (a 4.7 percentage-point improvement), with particularly strong gains in challenging scenarios like low-light and adverse weather conditions. The result shows that there are substantial benefits to incorporating geographical contexts and historical memory for location-aware perception in intelligent vehicles. Full article

(This article belongs to the Special Issue AI-Enabled Sustainable and Resilient Intelligent Transportation Systems for Smart Cities)

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23 pages, 5773 KB

Open AccessArticle

Data-Driven Child-Friendly Street Renewal for Health Equity in Older Urban Districts: Latent Activity–Health Profiles in Xi’an, China

by Zhanhao Zhang, Xin Dong, Weijie Hou and Sitong Liu

Smart Cities 2026, 9(8), 133; https://doi.org/10.3390/smartcities9080133 - 18 Aug 2026

Viewed by 547

Abstract

Data-driven urban governance increasingly seeks to incorporate the needs of different population groups, yet child-sensitive evidence for public street-space renewal remains limited in older urban districts. Most studies still evaluate environmental conditions through population averages, with insufficient attention to heterogeneous child groups that [...] Read more.

Data-driven urban governance increasingly seeks to incorporate the needs of different population groups, yet child-sensitive evidence for public street-space renewal remains limited in older urban districts. Most studies still evaluate environmental conditions through population averages, with insufficient attention to heterogeneous child groups that may require differentiated planning responses. Based on an analytic sample of 314 children retained from 343 usable questionnaire responses collected from children aged 6–12 in the older urban districts of Xi’an, China, this study integrates street-activity characteristics and age- and sex-standardized body mass index (zBMI) using an established person-centered analytical approach. Latent Class Analysis (LCA) was used to identify children’s activity–health profiles, and multinomial logistic regression was used to examine associations between individual, family, and perceived street-environment factors and profile membership. Three profiles were identified: high-activity–healthy, high-intensity active, and low-activity–high-risk. The model-estimated low-activity–high-risk profile represented 35.7% of the analytic sample, and children assigned to this profile reported the lowest perceived safety and convenience. The findings suggest that profile-based analysis may inform child-sensitive street-renewal prioritization. Perceived safety and convenience showed the strongest and most consistent associations with membership in either the high-activity–healthy or high-intensity active profile relative to the low-activity–high-risk profile. These findings are associative and do not establish the effects of street interventions. The study therefore represents a context-specific extension and planning application of established analytical methods. Full article

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38 pages, 18697 KB

Open AccessArticle

Definition of Charging Fee for Drainage Services and Incentives Based on LID Simulation

by Ana Paula Camargo de Vicente and Klebber Teodomiro Martins Formiga

Smart Cities 2026, 9(8), 132; https://doi.org/10.3390/smartcities9080132 - 18 Aug 2026

Viewed by 336

Abstract

Given the scarcity of initiatives to charge for urban stormwater services in Brazil and the need to recognise users’ efforts in adopting technologies such as Low Impact Development (LID), a proposal was developed for a stormwater drainage fee and incentives for environmental services [...] Read more.

Given the scarcity of initiatives to charge for urban stormwater services in Brazil and the need to recognise users’ efforts in adopting technologies such as Low Impact Development (LID), a proposal was developed for a stormwater drainage fee and incentives for environmental services in a Brazilian municipality, based on flows retained by LIDs, specifically infiltration wells. To this end, simulations were carried out using the Storm Water Management Model (SWMM) for a 0.5 km² area in a Brazilian city that does not yet implement such charges. Based on the identification of the total flow retained by users within the watershed, the avoided cost to the drainage system was estimated. The charging model was defined using the avoided cost method associated with the Simplified Equivalent Residential Unit (SERU). In the baseline scenario that allocates the operation and maintenance cost, the estimated annual fee was USD 17.22 per household without LID and USD 14.64 per household with LID, and the SERU area was 371.11 m², used as a property-area reference; in an incentive scenario designed to reduce the user payback period to approximately 10 years, the fee for households without LID was set at USD 73.78. An economic incentive policy was identified, consisting of fee discounts upon adoption of LIDs, as well as support for their installation and maintenance. Thus, it was validated that combining a drainage fee with economic incentives is both feasible and motivating for both system users and managers. Full article

(This article belongs to the Special Issue Smart Sustainable Cities: Pioneering Novel Frontiers for Green Urban Living)

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23 pages, 1028 KB

Open AccessArticle

SEMG-Net: State-Event Guided Multi-Scale Gated Network for Non-Intrusive Load Monitoring in Smart Buildings

by Keqin Li and Chengyuan Sun

Smart Cities 2026, 9(8), 131; https://doi.org/10.3390/smartcities9080131 - 15 Aug 2026

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Abstract

Non-intrusive load monitoring (NILM) provides a cost-effective way to obtain appliance-level electricity information from aggregate smart-meter measurements and is therefore important for energy management, demand-side response, and sustainable operation in smart buildings. However, accurate appliance-level power disaggregation remains challenging because residential load signals [...] Read more.

Non-intrusive load monitoring (NILM) provides a cost-effective way to obtain appliance-level electricity information from aggregate smart-meter measurements and is therefore important for energy management, demand-side response, and sustainable operation in smart buildings. However, accurate appliance-level power disaggregation remains challenging because residential load signals usually involve overlapping appliance signatures, sparse activations, heterogeneous temporal patterns, and transient switching events. To address these challenges, this paper proposes a State-Event-Guided Multi-Scale Gated Network (SEMG-Net) for NILM. The proposed framework integrates a residual temporal encoder, multi-scale dilated convolutional blocks, and a state-event-guided gating mechanism within a unified multi-task learning architecture. The shared encoder extracts hierarchical temporal representations from aggregate mains windows, while task-specific branches jointly estimate appliance power, on/off state, and switching event type. The predicted state probability, three-class event probability distribution, and shared temporal representation are jointly used to construct a continuous gate that modulates the raw power estimate, thereby directly incorporating behavioral predictions into final power estimation. Experimental results on public datasets show that SEMG-Net achieves competitive overall performance, with clear advantages in power estimation, energy consistency, and state identification, particularly for appliances with complex operating stages or transient switching behavior. The ablation results further demonstrate the benefits of multi-scale feature extraction and auxiliary supervision, as well as the effectiveness of the proposed state-event-guided power modulation mechanism. Full article

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40 pages, 7597 KB

Open AccessArticle

Curbside Parking Use, Turnover, and Regulatory Compliance in an Intermediate Latin American City: Field Evidence from Loja, Ecuador

by Yasmany García-Ramírez, Juan Diego Ríos-Arévalo, Michael Sanmartín-Jaramillo and Eduardo Romero-Aguilar

Smart Cities 2026, 9(8), 130; https://doi.org/10.3390/smartcities9080130 - 14 Aug 2026

Viewed by 335

Abstract

Direct evidence on curbside parking use in intermediate Latin American cities remains limited. This study characterized parking duration, purpose, turnover, accumulation, and regulatory compliance across six segment–date sessions in central Loja, Ecuador. Of 1426 observed curbside events, 1397 were retained after quality control. [...] Read more.

Direct evidence on curbside parking use in intermediate Latin American cities remains limited. This study characterized parking duration, purpose, turnover, accumulation, and regulatory compliance across six segment–date sessions in central Loja, Ecuador. Of 1426 observed curbside events, 1397 were retained after quality control. Analyses included descriptive and non-parametric tests, multivariable models with CR2 standard errors clustered by segment–date, and sensitivity analyses. Duration was strongly right-skewed (median 4 min; interquartile range 1–13 min; mean 36.3 min; P95 332.6 min), while passenger pick-up/drop-off accounted for 54.5% of events. Non-permitted maneuvers represented 64.0%. The four segment-sessions containing SIMERT coverage comprised 862 valid events, of which 776 occurred within marked SIMERT locations. Among the 644 marked-location events observed during payment-required hours, visible SIMERT use was recorded in 70 events (10.9%). After restricting the SIMERT component to marked locations during payment-required hours, composite non-compliance was identified in 1167 events (83.5%). During the common 06:30–18:30 comparison window, hourly turnover ranged from 0.54 to 1.96 events per legal space per hour, while cumulative space–time demand ranged from 11.6% to 154.8% of nominal legal space–time capacity. The value above 100% represents summed parking duration relative to nominal legal capacity and does not indicate simultaneous occupancy above 100%. Excluding session-boundary proxies left the median and interquartile range unchanged, although upper-tail estimates remained sensitive. Because each segment was observed on a single date, between-session differences cannot be interpreted as independent corridor effects. Natural-spline specifications provided better temporal fit than linear-hour specifications for both non-permitted maneuvers and revised composite non-compliance. These findings provide a reproducible local baseline for testing conventional and smart curb-management measures through repeated pilot studies. Full article

(This article belongs to the Special Issue Cost-Effective Transportation Planning for Smart Cities, 2nd Edition)

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27 pages, 62000 KB

Open AccessArticle

Urban Lifeline Security Projects: Research on the Holistic Governance Model of Urban Public Security Empowered by Digital Technology

by Qi Zou, Shuai Liu, Hongyong Yuan and Jiaojiao Liu

Smart Cities 2026, 9(8), 129; https://doi.org/10.3390/smartcities9080129 - 13 Aug 2026

Viewed by 251

Abstract

With the rapid advancement of urbanization, the density and vulnerability of urban lifeline networks are increasing, and urban lifeline security risks have become a major challenge to urban public security governance. The backward governance means and fragmented governance mechanisms cannot adapt to the [...] Read more.

With the rapid advancement of urbanization, the density and vulnerability of urban lifeline networks are increasing, and urban lifeline security risks have become a major challenge to urban public security governance. The backward governance means and fragmented governance mechanisms cannot adapt to the complex emerging urban public security risks. Digital empowerment is considered to be a new solution for the holistic governance of urban lifeline security, but related research has only focused on a single scenario, a single risk type or a single risk management link. This study shifted from a single perspective to a holistic perspective and explored how to use digital technology to develop the urban lifeline security project from three levels, that is, overall methods, key supporting technology, and governance mechanism innovation, so as to enable a holistic governance model for lifeline security. Specifically, this study constructed the main processes and methods for constructing urban lifeline security projects, the key supporting technology system for the scenario-driven urban lifeline security project, and the overall governance mechanism for the urban lifeline security project. The case from Hefei, China, further verifies the effectiveness of urban lifeline security engineering. The contribution of this study is to promote the collaborative innovation and integrated application of engineering technology and governance mechanisms in the field of holistic governance of urban lifeline security. Full article

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Graphical abstract

31 pages, 12219 KB

Open AccessArticle

Impact of Spatial Knowledge on Fire Evacuation Performance in Large Buildings: An Integrated Simulation Approach

by Rodrigo Ternero, Miguel Alfaro, Gabriel Larrain, Guillermo Fuertes, Juan Pablo Torres and Pavlo Santander

Smart Cities 2026, 9(8), 128; https://doi.org/10.3390/smartcities9080128 - 5 Aug 2026

Viewed by 634

Abstract

This study examines human evacuation performance in complex building environments under highly uncertain fire conditions, with a focus on how spatial knowledge and decision-making strategies influence exposure to hazardous conditions during emergencies in smart building contexts. A hybrid simulation framework integrating physical fire [...] Read more.

This study examines human evacuation performance in complex building environments under highly uncertain fire conditions, with a focus on how spatial knowledge and decision-making strategies influence exposure to hazardous conditions during emergencies in smart building contexts. A hybrid simulation framework integrating physical fire modeling, agent-based simulation (ABM), and data-driven analysis is applied to a large academic building in Santiago, Chile, incorporating heterogeneous occupant profiles with different levels of spatial knowledge while evaluating key environmental variables such as temperature, oxygen (O₂) concentration, carbon dioxide (CO₂) levels, and carbon monoxide (CO) concentrations. Stochastic behavioral variability is captured through Monte Carlo simulation, and associations between environmental conditions and evacuation responses are analyzed using Kendall’s correlation. Results show that evacuation strategies based on optimal route knowledge significantly reduce exposure to life-threatening conditions and decrease evacuation times by 34% for adults and 8.5% for young occupants compared with scenarios without prior spatial information. These findings highlight the critical role of spatial knowledge in evacuation decision-making and provide a transferable methodological framework for improving smart building safety systems and data-driven evacuation planning in high-occupancy urban environments. Full article

(This article belongs to the Topic Machine Learning and Big Data Analytics for Natural Disaster Reduction and Resilience)

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52 pages, 5112 KB

Open AccessReview

Impact of Electrical Vehicle Charging Stations on the Electric Grid: Lessons Learnt and Challenges

by Andrea Mariscotti, Alexander Gallarreta, Yljon Seferi, Sahil Bhagat, Brian G. Stewart, Igor Fernandez, David De la Vega and Graeme Burt

Smart Cities 2026, 9(8), 127; https://doi.org/10.3390/smartcities9080127 - 4 Aug 2026

Viewed by 592

Abstract

The ambitious roadmap for a sustainable transport system adopted by the European Commission (EC) by 2050 includes the deployment of an extensive Electric Vehicle Charging Stations (EVCSs) infrastructure, which introduces significant challenges for distribution power grids. High power demand, particularly from fast-charging systems, [...] Read more.

The ambitious roadmap for a sustainable transport system adopted by the European Commission (EC) by 2050 includes the deployment of an extensive Electric Vehicle Charging Stations (EVCSs) infrastructure, which introduces significant challenges for distribution power grids. High power demand, particularly from fast-charging systems, may lead to network overloading and voltage unbalance. In addition, recent measurement campaigns highlight substantial changes in grid impedance and the emergence of resonance phenomena, together with the injection and propagation of high-frequency conducted disturbances. These effects extend over a wide frequency range, up to several hundreds of kHz, causing degradation, aging and malfunction of network assets, in particular Power Line Communications. This paper provides a comprehensive and updated review of the impact of EVCSs on electrical grids, covering power flow, power quality, stability, and impedance-related interactions. Particular attention is given to the role of power-electronic converters, high-frequency emissions, and the associated challenges in measurement and standardization. The analysis highlights that EVCS integration fundamentally alters the nature of electrical loads, requiring new approaches for grid planning, monitoring, and regulation. The study identifies key research gaps and outlines future directions to ensure the reliable and sustainable integration of electromobility into modern power systems. Full article

(This article belongs to the Topic Electric Vehicles Smart Charging: Strategies, Technologies, and Challenges)

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21 pages, 2837 KB

Open AccessArticle

Development of an RAG-Integrated Agentic BIM System for Intelligent Railway Maintenance

by Minjae Jeon, Yonggun Kim and Seok Kim

Smart Cities 2026, 9(8), 126; https://doi.org/10.3390/smartcities9080126 - 4 Aug 2026

Viewed by 478

Abstract

Modern railway maintenance is transitioning toward a condition-based maintenance system to stably operate the core infrastructure of sustainable smart cities. However, technical limitations remain in manually converting and analyzing massive amounts of inspection data into Building Information Modeling (BIM) objects. This causes information [...] Read more.

Modern railway maintenance is transitioning toward a condition-based maintenance system to stably operate the core infrastructure of sustainable smart cities. However, technical limitations remain in manually converting and analyzing massive amounts of inspection data into Building Information Modeling (BIM) objects. This causes information delays and technical severance in data-driven smart-city infrastructure. To address these challenges, this study proposes an Agentic BIM framework that integrates Large Language Model (LLM), Model Context Protocol (MCP), and Retrieval Augmented Generation (RAG) technologies. The proposed methodology standardizes the control channel between the LLM and BIM software through a central MCP server, while securing the accuracy of engineering judgments by utilizing the RAG pipeline to reference national railway-track-maintenance guidelines. System validation results demonstrated that geometric inspection data, including gauge and alignment, were automatically generated as BIM objects without human intervention. Furthermore, the maintenance grades and deadlines for sections exceeding thresholds were immediately highlighted within the model as visual attributes. Consequently, this framework proves an autonomous decision-making system that organically links inspection data with maintenance regulations. By transforming static, manual-labor-centered maintenance workflows into intelligent automated models, it increases the efficiency of railway infrastructure management while providing a scalable technical foundation for overall asset management of future smart-city infrastructure. Full article

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26 pages, 2276 KB

Open AccessArticle

Hierarchical Reinforcement Learning with Hungarian Assignment for Reliable Urban Smart Metering Under Cognitive Spectrum Access

by Muhammed Al-Ali, Esteban Inga, Juan Inga and Elias Yaacoub

Smart Cities 2026, 9(8), 125; https://doi.org/10.3390/smartcities9080125 - 31 Jul 2026

Viewed by 454

Abstract

Advanced metering infrastructure (AMI) is the sensing backbone of the smart grid, and its reliability underpins urban energy services such as state estimation, demand response, and distributed-energy integration. When AMI uses cellular spectrum leased through a cognitive mobile virtual network operator (C-MVNO), allocating [...] Read more.

Advanced metering infrastructure (AMI) is the sensing backbone of the smart grid, and its reliability underpins urban energy services such as state estimation, demand response, and distributed-energy integration. When AMI uses cellular spectrum leased through a cognitive mobile virtual network operator (C-MVNO), allocating channels to data aggregation points (DAPs) each frame is difficult because three uncertainties interact: imperfect spectrum sensing, time-varying and cross-channel-correlated primary-user activity, and stochastic urban propagation. Classical Hungarian assignment is optimal per frame but blind to primary-user dynamics, while cognitive-radio heuristics ignore queue state and cross-channel structure. We propose a two-timescale hierarchy that couples these established tools in a new way: a Proximal Policy Optimization (PPO) agent decides, once per epoch, which opportunistic channels to expose, and an exact Hungarian solver performs the per-frame DAP-to-channel assignment. To our knowledge this is the first coupling of a learned cognitive layer with exact Hungarian assignment for cognitive-radio resource allocation. On a 3GPP TR 38.901-compliant simulator, PPO significantly outperforms a Bayesian-belief baseline and the Hungarian-only configuration in delivery ratio, latency, and a strict per-meter satisfaction metric, and is robust across independent seeds and sensitivity sweeps. An architectural ablation shows the DAP tier is a precondition for viability, not merely an optimization. Full article

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35 pages, 4492 KB

Open AccessArticle

Intelligent Community Monitoring Through Citizen Science and AI: An ISO 37120-Based Framework for Sustainable Development in Ecuador

by Segundo Benitez-Hurtado, Daniel Guamán, Priscila Valdiviezo-Diaz and Janneth Chicaiza

Smart Cities 2026, 9(8), 124; https://doi.org/10.3390/smartcities9080124 - 31 Jul 2026

Viewed by 438

Abstract

This paper proposes a comprehensive approach for data-driven participatory community monitoring based on “Citizen Science” (CS), ISO 37120, and artificial intelligence (AI). The design integrates AI with the CS six-stage life cycle and citizen data governance principles through an AI-CS framework, aligning with [...] Read more.

This paper proposes a comprehensive approach for data-driven participatory community monitoring based on “Citizen Science” (CS), ISO 37120, and artificial intelligence (AI). The design integrates AI with the CS six-stage life cycle and citizen data governance principles through an AI-CS framework, aligning with the Copenhagen Social Summit. The framework was developed for local governments in Ecuador, a country where territorial planning lacks citizen data disaggregated by territorial, sociodemographic, and contextual variables. This fact limits the capacity of local governments to make evidence-based decisions. Between October 2025 and February 2026, data from 30,253 events were collected in 22 provinces and 93 cantons of the country. The data were analyzed by means of ordinal logistic regression to identify predictors of perceived severity and by means of DBSCAN, an unsupervised machine learning clustering algorithm, to characterize territorial patterns. The results suggest that citizen perception is organized into systemic and predictable patterns when structured using ISO 37120 categories. The spatial analysis reveals heterogeneous territorial patterns with levels of urgency that differ depending on the canton and the urban–rural context. The proposed approach allows local governments to obtain disaggregated territorial data for participatory planning. Its design may be transferable to other Global South contexts facing similar data gaps and is aligned with SDGs 9, 11, 16, and 17. Full article

(This article belongs to the Topic Sustainable Development and Artificial Intelligence in Smart Cities)

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41 pages, 17754 KB

Open AccessReview

Digital Twins in Intelligent Transport Systems: A Systematic Review of Resilience Mechanisms and Smart City Implications

by Badr Machkour, Naoufal Rouky, Ahmed Abriane, Mouhsene Fri and Othmane Benmoussa

Smart Cities 2026, 9(8), 123; https://doi.org/10.3390/smartcities9080123 - 31 Jul 2026

Viewed by 960

Abstract

The intensification of urbanization, the growth in mobility demand and the multiplication of disruptions expose intelligent transport systems to new operational vulnerabilities, making resilience a central issue for the management of transport networks. By conducting a systematic literature review, in accordance with the [...] Read more.

The intensification of urbanization, the growth in mobility demand and the multiplication of disruptions expose intelligent transport systems to new operational vulnerabilities, making resilience a central issue for the management of transport networks. By conducting a systematic literature review, in accordance with the PRISMA 2020 and PRISMA-S recommendations, this article examines the extent to which, through which functions, under which conditions, and with what level of evidence digital twins can support the resilience of intelligent transport systems. The literature search covered the 2020–2025 period across Scopus, IEEE Xplore, and TRID and was complemented by backward and forward citation chaining, targeting research and review articles dealing with digital twins in transport, mobility, transport infrastructures, or ITS, as well as their links with resilience mechanisms. After screening and eligibility assessment, 61 studies were included in the final analytical corpus. The results show that digital twins are no longer limited to a simple virtual representation of the physical system but are increasingly established as service-oriented cyber–physical layers capable of supporting functions that may contribute to resilience, including real-time visibility, disruption anticipation, scenario simulation, dynamic optimization, decision support, service continuity, and post-disruption learning. The study also highlights several persistent limitations, notably conceptual instability, the sectoral concentration of studies, the lack of large-scale empirical validation, and the insufficient consideration of organizational, human, and governance dimensions. It concludes that digital twins should not be interpreted as automatically enhancing the resilience of ITS, but rather as having the potential to support resilience when they are associated with reliable data, interoperability, synchronization, model reliability, and the ability of stakeholders to transform digital intelligence into coordinated operational responses. Full article

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22 pages, 4845 KB

Open AccessArticle

Mapping the Affordability of Campus Digital Twin Implementation in the United States

by Yuchen Wang, Xinyue Ye, Sicheng Wang and Devika Jain

Smart Cities 2026, 9(8), 122; https://doi.org/10.3390/smartcities9080122 - 29 Jul 2026

Viewed by 685

Abstract

Digital Twin technologies hold significant promise for advancing smart campus initiatives by enabling data-driven management of facilities, sustainability planning, and safety monitoring. Despite this potential, affordability remains a critical barrier to widespread adoption across higher education institutions. This study introduces an initial exploratory [...] Read more.

Digital Twin technologies hold significant promise for advancing smart campus initiatives by enabling data-driven management of facilities, sustainability planning, and safety monitoring. Despite this potential, affordability remains a critical barrier to widespread adoption across higher education institutions. This study introduces an initial exploratory scenario-based affordability index for campus digital twin and maps the affordability of implementing campus digital twin across 1872 U.S. higher education institutions using spatial analysis techniques. Sensitivity analysis is also conducted to evaluate the robustness of the results. Our analysis yields three key findings: (1) Under the baseline scenario, most campuses show moderate-to-high affordability with spatial clusters concentrated in coastal and metropolitan regions, while nearly one-quarter remain unaffordable or marginally affordable, with clusters located in the Midwest. (2) Private institutions demonstrate relatively greater affordability than public institutions, with for-profit private institutions exhibiting higher affordability than their non-profit counterparts. Spatial aggregation patterns further reveal heterogeneity in affordability between these sectors. (3) States with strong economic and educational infrastructures, such as California, contain a greater number of affordable campuses for digital twin implementation, while resource-constrained states face significant barriers. These findings remain generally robust and consistent across the baseline and sensitivity scenarios. The results underscore the need for standardized cost models, public cost databases, targeted policy guidance, and multi-stakeholder collaboration to promote equitable adoption. By positioning digital twins as strategic tools for campus resilience, efficiency, and innovation, this study advances the conceptual understanding of their role in higher education and provides exploratory yet actionable insights for institutional leaders and policymakers to support inclusive digital transformation. Full article

(This article belongs to the Collection Digital Twins for Smart Cities)

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18 pages, 377 KB

Open AccessArticle

Agent-Based Analysis of Cryptocurrency Adoption in Transit Systems

by Mahdieh Allahviranloo

Smart Cities 2026, 9(8), 121; https://doi.org/10.3390/smartcities9080121 - 26 Jul 2026

Viewed by 672

Abstract

As cryptocurrency adoption accelerates globally, cities face a critical question: can digital currencies be adapted by different agencies without compromising financial stability? This paper develops an agent-based modeling framework that enables transit authorities to systematically explore cryptocurrency integration strategies. We simulate 1000 heterogeneous [...] Read more.

As cryptocurrency adoption accelerates globally, cities face a critical question: can digital currencies be adapted by different agencies without compromising financial stability? This paper develops an agent-based modeling framework that enables transit authorities to systematically explore cryptocurrency integration strategies. We simulate 1000 heterogeneous agents with varying risk tolerance, technological proficiency, and social influence susceptibility over 365 days, testing five policy regimes across a comprehensive scenario matrix comprising four risk-attitude compositions, four technology-adoption levels, four social-influence intensities, and three market conditions (bullish, neutral, bearish)—creating 192 distinct population-market configurations evaluated across all five policies with 15 independent replications per configuration (14,400 total simulation runs). The framework produces adoption outcomes ranging from near-zero to over 49% depending on scenario assumptions, with technology familiarity emerging as the dominant driver. The framework provides transit authorities with a practical tool for scenario-based planning: testing policy interventions, stress-testing financial stability under various market conditions, identifying potential vulnerabilities before deployment, and comparing alternative strategies across diverse demographic contexts. This simulation-based approach enables data-driven decision-making in the absence of real-world precedent, offering a structured methodology for evaluating cryptocurrency integration while managing financial stability risks. Full article

(This article belongs to the Special Issue Smart Mobility: Linking Research, Regulation, Innovation and Practice)

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Smart Cities, Volume 9, Issue 8 (August 2026) – 15 articles

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