• General Article

    A comparative analysis of carbon neutral effects in neighborhood planning models
    Seongwoo Nam and Boram Moon
    This study proposes strategies for achieving carbon neutrality not only at national, regional, and building levels, but also at the neighborhood scale—an … + READ MORE
    This study proposes strategies for achieving carbon neutrality not only at national, regional, and building levels, but also at the neighborhood scale—an essential unit of urban planning that encompasses spaces where people live and interact. First, a carbon emissions inventory tailored to neighborhood units was developed, and core spatial planning elements were identified. Through a comprehensive review of literature and case studies, a pool of carbon-neutral planning components was established across five domains: spatial structure, land use, transportation, green and open space, and building and energy systems. Second, spatial planning scenarios were created to support comparative analysis of carbon emissions across alternative neighborhood configurations. These scenarios combined planning elements to simulate changes in urban form and estimate associated emissions. Third, a typology of spatial models was constructed to reflect different configurations of planning strategies and enable quantitative evaluation of emissions outcomes. A major limitation of this study is its reliance on simulated neighborhood models, which makes the results sensitive to embedded assumptions. To improve the applicability and accuracy of these findings, future research should incorporate empirical data from real-world neighborhoods and examine the relationship between spatial planning strategies and observed carbon emissions more systematically. - COLLAPSE
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    31 March 2026

  • General Article

    Enhancing oil spill classification for sustainable environment: Leveraging CNNs and self-attention mechanisms
    Lavi Tyagi, Dinesh Singh and Nitin Goyal
    Effective detection and categorization are crucial for avoiding the adverse repercussions of oil spills, which pose a significant environmental hazard. This work … + READ MORE
    Effective detection and categorization are crucial for avoiding the adverse repercussions of oil spills, which pose a significant environmental hazard. This work presents two Deep Learning (DL) approaches to oil spill categorization: a standard Convolutional Neural Network (CNN) and an improved CNN with a self-attention mechanism. CNN uses deep feature extraction to differentiate between images with and without oil spills. Through enhancement in feature learning, the network takes advantage of the self-attention process, which it also employs to directly and precisely target critical regions of the image. The oil spill dataset comprises 2536 images. These models, both with and without attention mechanisms, demonstrated competitive results in terms of recall, accuracy, precision, and F1 score. The findings show that the self-attention model is more effective than the standard CNN. Potentially helpful for catastrophe management and environmental monitoring, it presents an innovative method to classify oil spills for a sustainable environment. - COLLAPSE
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    31 March 2026

  • General Article

    Enhancing urban architecture expertise through the master architect system: Focused on the Sejong educational complex in Korea and the siemens campus in Germany
    Hanyeol Baek
    This study explores strategies to enhance urban design expertise through the implementation of the Master Architect (MA) system in South Korea. By … + READ MORE
    This study explores strategies to enhance urban design expertise through the implementation of the Master Architect (MA) system in South Korea. By conducting a comparative analysis of two representative cases—the Educational Facility Complex in Sejong City, Korea, and the Siemens Campus in Erlangen, Germany—the research investigates how expert systems influence project planning, design governance, and multidisciplinary collaboration in large-scale urban development. The findings reveal that while Korea’s MA system offers the potential to reinforce design consistency and public value, it currently lacks institutional authority and integration with participatory planning frameworks. In contrast, Germany’s phased planning process and clear legal delegation of responsibilities to lead architects ensure greater design continuity and stakeholder engagement. Based on this analysis, the study proposes actionable strategies to strengthen the MA system in Korea, including legal revisions, enhanced institutional autonomy, and structured stakeholder participation. The research contributes to urban design policy by offering practical insights into professional governance models that balance design quality and democratic process in complex urban projects. - COLLAPSE
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    31 March 2026

  • General Article

    Experimental and numerical assessment of phase change materials for improving thermal comfort and reducing cooling demand in algerian residential buildings
    Nadia Nait, Fatiha Bourbia and Sarah Benharkat
    In the context of energy-efficient buildings, the incorporation of phase change materials (PCMs) into the building envelope represents a promising thermal energy … + READ MORE
    In the context of energy-efficient buildings, the incorporation of phase change materials (PCMs) into the building envelope represents a promising thermal energy storage strategy to reduce cooling demand and enhance thermal comfort. This study investigates the thermal performance of a residential building located in Constantine, Algeria, characterized by a semi-arid climate, by comparing a conventional envelope with one integrating Energain® PCM panels during the summer season . A combined experimental and numerical approach was adopted, using in situ field measurements and dynamic simulation with EDSL TAS software. Measurements conducted over the peak summer period (17 to 22 July) served to validate the simulation model, which was subsequently applied in two stages: two representative summer days were first simulated to analyze the envelope thermal behavior, followed by a full seasonal simulation using, typical meteorological year data for Constantine, with realistic boundary conditions including occupancy schedules, internal gains, natural ventilation, and infiltration rates. Performance was assessed degree-hours and thermal discomfort hours, computed over the entire summer season. The results demonstrate that PCM integration significantly enhances thermal comfort and reduces cooling energy demand, with cooling consumption decreasing by up to 34 percent. Degree hours were reduced by 64 and 80 percent in the northwest-facing living room and southeast-facing bedroom respectively, while discomfort hours decreased by 45 and 57 percent in these spaces. The findings highlight the potential of PCM integration as an effective passive strategy for enhancing thermal resilience and reducing energy demand in semi-arid residential contexts. - COLLAPSE
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    31 March 2026

  • General Article

    Examining the nonlinear relationship between urban built environment and commuting distance in Seoul, South Korea
    Sangyeon Nam, Tai-Jin Song and Sungjo Hong
    Substantial empirical evidence has been presented regarding the relationship between built environments and commuting distance; however, conflicting conclusions still exist for certain … + READ MORE
    Substantial empirical evidence has been presented regarding the relationship between built environments and commuting distance; however, conflicting conclusions still exist for certain variables. Therefore, our study aims to identify the relationship between built environments and commuting distance by leveraging mobile phone data, providing a large commuting sample, and explainable machine learning techniques capable of capturing complex relationships between variables. Initially, we constructed a commuting distance prediction model using the XGBoost algorithm. Subsequently, we used explainable machine learning techniques, namely SHapley Additive exPlanations (SHAP) and Partial Dependence Plot (PDP), to identify the built environment factors that influence commuting distance. The results highlighted the distance from the residence to the employment center as the most crucial built environment factor. Additionally, the land use mix and job-population balance at the residence were found to have nonlinear relationships with commuting distance. Contrary to the empirical evidence from Western cities, population density was found to have a positive relationship with commuting distance. Our findings emphasize the need for customized urban and transportation planning strategies in various urban contexts. - COLLAPSE
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    31 March 2026

  • General Article

    Development of eco-efficient concrete using supplementary cementitious materials, waste aggregates, crumb rubber, and fibers
    Mohd Rafiq Mir and Parameshwar Neelkantayya Hiremath
    The extensive use of concrete imposes significant environmental burdens, primarily due to high CO2 emissions from cement production and excessive consumption … + READ MORE
    The extensive use of concrete imposes significant environmental burdens, primarily due to high CO2 emissions from cement production and excessive consumption of natural resources. This study aims to enhance the sustainability of concrete through systematic use of supplementary cementitious materials (SCMs) such as fly ash (FA) and ground granulated blast furnace slag (GGBS), along with crumb rubber, copper slag (CS), and recycled coarse aggregates (RCA), as partial replacements for binders and aggregates. A five-stage optimization approach was adopted. Cement was replaced up to 50% using FA (10–50%), GGBS (10–50%), and RHA (10–30%); fine aggregate were replaced with crumb rubber (10–20%) and copper slag sand (25–50%); and coarse aggregate were replaced up to 50% with recycled aggregates and copper slag aggregates (25–50%). Steel fibers (1–2%) were incorporated to improve mechanical performance. All replacements were carried out on a volume basis. The optimum binder composition of 50% cement, 35% GGBS, and 15% FA achieved strength superior than control mix at 56 days. A combination of 10% crumb rubber and 25% copper slag sand showed no adverse effect on strength, while copper slag aggregates performed better than recycled aggregates. Steel fiber inclusion at 1.5% further enhanced flexural performance. Life cycle assessment confirmed notable reductions in embodied energy and global warming potential, demonstrating improved eco-efficiency. - COLLAPSE
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    31 March 2026

  • General Article

    Blockchain-enabled IoT and machine learning framework for health prediction in smart and healthy urban environments
    Jainendra Singh, Nitin Goyal, Atamkur Anitha, Shikha Rani, Gaurav Sharma, Bharti Sharma, Ravneet Kaur, Praveen Yadav and Mukta Garg
    As part of the movement toward healthier and more sustainable built environments, emerging digital technologies offer powerful solutions for proactive health monitoring … + READ MORE
    As part of the movement toward healthier and more sustainable built environments, emerging digital technologies offer powerful solutions for proactive health monitoring and disease prevention. This study presents an integrated framework that leverages Internet of Things (IoT) sensor systems, machine learning (ML) models, and blockchain-enabled data management to support real-time cardiovascular risk prediction and secure health information handling within smart and health-oriented urban settings. In the proposed system, IoT-based wearable sensors such as smartwatches continuously capture physiological signals relevant to cardiovascular health, enabling seamless monitoring within daily living environments. The collected data are processed using multiple ML algorithms, including Random Forest, Decision Tree, Logistic Regression, Multi-layer Perceptron, K-Nearest Neighbour, and Gradient Boosting, trained on a Kaggle-sourced cardiovascular disease (CVD) dataset securely stored in a cloud repository. Among these, the Gradient Boosting classifier achieved the highest prediction accuracy of 72%, supporting timely identification of at-risk individuals and enabling early preventive interventions. To ensure data integrity, privacy, and traceability across healthcare ecosystems, blockchain technology is incorporated as a secure layer for storing and managing sensitive patient information. This enhances trust, transparency, and compliance in digital health services integrated within sustainable smart buildings and urban infrastructures. Overall, the proposed approach strengthens the role of IoT-enabled health monitoring as an integral component of sustainable living environments, contributing to improved healthcare accessibility, reduced clinical burden, and better long-term management of cardiovascular conditions. The integration of sensor technologies, ML-based analytics, and secure data architectures supports the development of future-ready healthy buildings and smart urban systems designed to enhance occupant well-being. - COLLAPSE
    PDFCitation
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    31 March 2026

  • General Article

    Social network link prediction techniques for smart urban infrastructure management: Factors, parameters, and applications
    Mukesh Kumar, Kulvinder Singh and Sanjeev Dhawan
    A social network represents a dynamic system of interpersonal interactions among individuals, communities, or organizations. These networks support diverse activities such as … + READ MORE
    A social network represents a dynamic system of interpersonal interactions among individuals, communities, or organizations. These networks support diverse activities such as information sharing, public communication, service coordination, and citizen engagement. In smart urban environments, social networks play a crucial role in understanding human behavior, optimizing resource usage, and enhancing service delivery. However, one of the major challenges is to identify and strengthen meaningful connections among users that facilitate efficient information flow and improved system performance. Link prediction addresses this challenge by estimating the likelihood of future or missing connections between currently unconnected nodes. It contributes to several smart city applications, including community-based decision making and intelligent transportation systems. The objective of this work is to review state-of-the-art techniques used for link prediction in social networks ranging from similarity-based heuristics to advanced machine learning methods and to analyze the key factors and parameters influencing the prediction of missing links within smart urban systems. - COLLAPSE
    PDFCitation
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    31 March 2026

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    Privacy-preserving blockchain healthcare systems for healthy and sustainable smart buildings
    Yogesh Kushwaha, Niranjan Lal and Manisha Manjul
    The swift digitization of Healthcare 4.0 smart building environments has intensified apprehensions about secure storage, privacy-preserving analytics, and responsible sharing of Electronic … + READ MORE
    The swift digitization of Healthcare 4.0 smart building environments has intensified apprehensions about secure storage, privacy-preserving analytics, and responsible sharing of Electronic Health Records. Traditional deep learning systems handle plaintext data, so revealing sensitive information, whereas current blockchain-based solutions enhance traceability but do not facilitate computation in an encrypted environment. Likewise, the majority of homomorphic encryption methodologies concentrate on independent inference, lacking integrated consent enforcement or comprehensive system evaluation. A privacy-preserving Deep Learning-as-a-Service system that integrates CKKS-based homomorphic inference with permissioned blockchain governance is presented to overcome these issues. A BiLSTM model is utilized for longitudinal EHR modeling, whereas smart contracts facilitate consent validation and provide tamper-evident access recording inside a Healthcare 4.0 tiered architecture. In plaintext evaluation, the BiLSTM attained a precision of 0.882, a recall of 0.781, and an F1-score of 0.828, surpassing the GRU baseline by nearly 7 percent. Encrypted inference maintained predictive performance while elevating average latency from 71.3 ms to 720.0 ms per record, with the entire blockchain-integrated workflow averaging 760 ms. The system illustrates that secure, auditable, and confidentiality-preserving disease prediction is achievable with manageable computational costs, providing a unique advancement beyond standalone blockchain or homomorphic healthcare solutions. - COLLAPSE
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    31 March 2026

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    Spatial disparities in housing satisfaction among national rental and happy housing residents in Seoul’s living zones
    Changho Kweon and Hyekyung Lee
    This study examines spatial disparities in the determinants of housing satisfaction among residents of Seoul’s public rental housing, focusing on the National … + READ MORE
    This study examines spatial disparities in the determinants of housing satisfaction among residents of Seoul’s public rental housing, focusing on the National Rental Housing and Happy Housing programs. As Seoul faces rapid urban growth and escalating housing costs, ensuring residential stability and satisfaction for diverse and vulnerable populations is increasingly crucial. Using the 4th wave data from the Seoul Public Rental Housing Tenant Panel survey collected in 2021 and ordinal logistic regression analysis, the research investigates how residential environment, economic characteristics, housing quality, and social relations shape housing satisfaction, comparing variations across housing programs and between affluent Southeast zone and other areas of Seoul. The findings show that residential environment and economic burden consistently influence satisfaction, although their impacts vary by program and location. In the Southeast, National Rental Housing residents are more affected by economic conditions and floor area, while environmental and social factors play a more significant role in other regions. In Happy Housing, the residential environment emerges as the primarily determinant, particularly in the Southeast. For National Rental Housing, larger exclusive floor area enhances satisfaction, whereas more rooms are linked to lower satisfaction, reflecting potential mismatches in unit design. Overall, the results highlight the interplay of spatial context, program type, and household composition, underscoring the need for regionally adaptive housing policies responsive to local needs and amenities. - COLLAPSE
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    31 March 2026
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