Smart Design Policies is an international, double-blind peer-reviewed journal published annually by Alanya University, offering an interdisciplinary platform to explore how smart design principles, advanced materials, AI-driven computational methods, and ethical, social, and regulatory frameworks shape human and habitat studies. Our mission is to foster rigorous research, engage diverse voices, and promote evidence-based policies that drive innovation in sustainable, inclusive, and responsible design. By bridging theory and practice, SDP envisions a future where cross-disciplinary collaboration and thoughtful policy-making lead to resilient and equitable solutions that benefit all. We warmly encourage researchers, scholars, practitioners, and policymakers to submit original research, reviews, theoretical studies, case analyses, and policy briefs that align with our commitment to advancing knowledge and sparking dialogue in this rapidly evolving field.
Parametric Design Approaches as Interfaces for Semi-Open Public Spaces in Historic Environments: The Metropol Parasol Case
Historic environments require contemporary interventions to negotiate new spatial demands without treating heritage, public use, climatic affordances, and structural logic as separate concerns. This study examines parametric design as an architectural interface in a historically layered semi-open public space. Interface denotes the built relational system through which rule-based geometry negotiates historic and archaeological constraints, public-space organization, environmental affordances, and structural-geometric requirements. A qualitative critical single-case analysis of Metropol Parasol in Seville applies a literature-informed 12-criterion framework to published drawings, sections, photographs, project and engineering documentation, and academic sources. The project is not reconstructed through parametric modelling; no simulation, measurement, user survey, behavioural observation, accessibility audit, or comparative canopy test is conducted. Evidence is coded as supported, qualified, not supported, or not established and synthesized across spatial mediation, environmental responsiveness, and structural-geometric logic. The analysis supports relationships among variable grid geometry, support placement, ground-level permeability, programmatic layering, shading affordance, modular coordination, and documented constructability. Contextual continuity, access provision, daylight mediation, ventilation affordance, and structural organization remain qualified, while thermal-comfort outcomes are not established. The study contributes an interface-centred analytical lens that integrates domains usually treated separately in HBIM, performance-led parametric research, and historic public-space studies. Its transferability is methodological and conditional rather than predictive; the findings do not verify social vitality, universal accessibility, environmental performance, visual acceptance, or conservation outcomes.
Copyright (c) 2026 Seyed Babak Ehsani Oskouei, Hatice Fulya Cebecioğlu Avcı, Pınar Tabak (Author) https://creativecommons.org/licenses/by/4.0/
AI-Driven Parametric Evaluation of Thermal Comfort in Vernacular Heritage: A courtyard-centric study of Unnati School, Ahmedabad, India
This research investigates how courtyards of traditional Ahmedabad pol houses that have been adaptively reused as institutional spaces regulate microclimates. Focusing on Unnati School, the study addresses how high occupancy (213 users) and modern materials such as steel roofing impact heritage cooling performance. The methodology bridges vernacular wisdom with computational synthesis, employing AI-driven voxel simulations via the Infrared.city platform to calculate the Universal Thermal Climate Index (UTCI). To ensure technical accuracy, digital simulations are verified against on site thermometer readings. The study contributes to heritage and climate-responsive design research by proposing a rapid, scalable framework for evaluating thermal comfort in adaptively reused heritage buildings and by demonstrating the applicability of AI-driven environmental simulations as an alternative to more resource-intensive Computational Fluid Dynamics (CFD) approaches. Findings identify thermal tipping points where modern interventions diminish the cooling benefits of traditional courtyard systems. By comparing AI-based and conventional thermal assessment methods, the research provides new evidence on the reliability of emerging digital tools for heritage performance evaluation. The study further demonstrates that the courtyard stack effect functions as a measurable and effective passive cooling mechanism, offering a data-driven basis for integrating vernacular design principles into contemporary heritage conservation and climate adaptation strategies.
Copyright (c) 2026 Vrutti Patel, Nishant Kansagara , Tithi Solandhara (Author) https://creativecommons.org/licenses/by/4.0/
Satellite-Based Assessment of Vegetation Dynamics and their Potential Drivers in Lochinvar National Park Using Google Earth Engine
This study examines vegetation dynamics and their potential environmental drivers in Lochinvar National Park, Zambia, over a 41-year period (1984 to 2025), using Landsat imagery processed on Google Earth Engine (GEE). The specific objectives were to: (1) quantify long-term land-cover change across six classes, namely water, grassland, woodland, floodplain, Mimosa pigra, and mine area; (2) characterise vegetation greenness trends using the Normalized Difference Vegetation Index (NDVI); and (3) examine the spatial association between these changes and hydrological alteration, invasive species spread, and human activity. The guiding research question was: how have vegetation cover and greenness in Lochinvar National Park changed since 1984, and to what extent are these changes spatially associated with hydrological, biological, and anthropogenic pressures? Using a Random Forest classifier (500 trees) applied to nine dry-season composite periods, grassland increased from 161.85 km² (39.31%) in 1984-1988 to 185.21 km² (44.99%) in 2024-2025, a net gain of 23.36 km² (+5.68 percentage points), while floodplain area declined from 114.32 km² (27.77%) to 76.89 km² (18.68%), a net loss of 37.43 km² (-9.09 percentage points). Mimosa pigra extent fell from a peak of 42.05 km² (10.22%) in 1994-1998 to 31.87 km² (7.74%) by 2024-2025. Classification accuracy reached 92% overall in the final period. Maximum NDVI fluctuated between 0.385 and 0.447 across the record, with a shallow positive linear trend of approximately +0.0004 NDVI units per year. These patterns are spatially consistent with, though not statistically proven to be caused by, altered flooding regimes downstream of the Itezhi-Tezhi and Kafue Gorge dams, sustained Mimosa pigra control efforts, and continued anthropogenic pressure. The study contributes an empirical, cloud-based monitoring framework that can inform smart, data-driven, and evidence-based land-management policy for wetland protected areas in Zambia and comparable floodplain systems in the region.
Copyright (c) 2026 Grace Viswamo, Timothy Mwaanga, Musoka Nyongolo, Penjani Hopkins Nyimbili, Masauso Sakala, Anastasia Kilundo, Erastus Misheng’u Mwanaumo (Author) https://creativecommons.org/licenses/by/4.0/
GIS and Remote Sensing-Based Assessment and Mapping of Industrial Pollution Impacts: A Case Study of the Kafue River, Zambia
This study applies GIS and multi-temporal satellite remote sensing to trace the environmental signature of the February 2025 Sino-Metals tailings dam failure along Zambia's Kafue River, and considers what the resulting evidence implies for the design of a low-cost, satellite-based early-warning monitoring policy. Landsat 8/9 and Sentinel-2 imagery across six temporal windows (three pre-incident, three post-incident) were used to compute the Normalised Difference Turbidity Index (NDTI) and Normalised Difference Vegetation Index (NDVI), with the Normalised Difference Water Index (NDWI) applied as a binary water mask to separate the open-water pixels used for NDTI from the riparian land pixels used for NDVI. Mean NDTI rose sharply from a pre-incident rainy-season-onset value of −0.008 to +0.210 in March 2025, before returning to near-baseline levels (+0.018) within a month and to clear-water conditions (−0.009) by June 2025 a pattern consistent with the river's hydrological flushing capacity. Riparian NDVI, in contrast, declined from a rainy-season peak of 0.345 in December 2024 to 0.313 immediately after the spill and had not returned to that baseline five months later. Because no concurrent in-situ water-chemistry or soil heavy-metal sampling was available, and because only a single pre-incident rainy-season observation exists, these patterns are interpreted as consistent with, rather than statistically confirmatory of, pollution-driven vegetation stress. The differential recovery signatures of NDTI and NDVI are nonetheless proposed as a candidate design feature for a dual-index, satellite-based early-warning trigger for Zambia's Environmental Management Agency (ZEMA) and Water Resources Management Authority (WARMA), and the data, validation, and institutional requirements for operationalising such a system are discussed.
GIS, Remote Sensing, Water Pollution, Kafue River, NDVI, NDTI, Smart Environmental Monitoring, Zambia.
Copyright (c) 2026 Stanley Kapota, Dabwitso Miti, Musoka Nyongolo, Dr. Penjani Hopkins Nyimbili, Prof. Dr. Erastus Misheng’u Mwanaumo, Prof. Dr. Wellington Didibhuku Thwala, Masauso Sakala (Author) https://creativecommons.org/licenses/by/4.0/
Feasibility of using Artificial intelligence to minimise cost and time in Arbitration process in the Zambian construction industry
The Zambian construction industry (ZCI) is characterised by lengthy and costly dispute resolution procedures, caused by manual and inefficient practices. This study investigated the potential of artificial intelligence (AI) application in minimising cost and time of arbitration in the ZCI. The methodology adopted for this study was mixed method, employing both qualitative and quantitative approaches. Quantitative data was collected using a self-administered structured questionnaire from 65 respondents sampled from contractors and arbitrators. Qualitative data was collected through interviews with 5 respondents drawn from the regulator-chartered institute of arbitrators and the Judiciary. Findings revealed that arbitration is the second most preferred dispute resolution procedure. Furthermore, there is a growing awareness of AI potential in dispute resolution. 80% of the respondents recognized its potential in addressing procedural inefficiencies, which lead to high costs and lengthy arbitration processes. Infrastructure limitations, ethical concerns particularly regarding data security and the loss of human judgment, pose significant challenges to AI adoption. To overcome these challenges, the study recommends that the Government and relevant stakeholders, develop an adoption framework for AI application in arbitration. The paper highlights areas in which policy interventions should be focused, in promoting digital integration in dispute resolution from developing country’s perspective.
Copyright (c) 2026 Lawrence Mutale, Elijah Mweemba, Sampa Chisumbe (Author) https://creativecommons.org/licenses/by/4.0/
Spyra-20B: A Proof-of-Concept for Explicit Architectural Design Reasoning in Domain-Specialised LLMs
Domain-specifically fine-tuned language models (BloombergGPT, Med-PaLM) have proven a viable route to adapting vocabulary and specialist knowledge to particular fields of application. For architectural practice, however, the central challenge is not terminology but the deliberative structure of the design decision: the weighing of competing objectives across building law, quality of use, cost and sustainability. This paper presents Spyra-20B, a proof-of-concept produced by QLoRA fine-tuning of gpt-oss-20B on 1,693 architecture- and planning-specific dialogue examples. Two features characterise the approach: a three-level deliberation depth controllable by metadata (reasoning_effort), and a strict separation of analysis and answer channels that renders the deliberative process inspectable. An evaluation on 50 law- and planning-related items across four conditions (base model vs. Spyra-20B, closed-book vs. open-book with RAG; 4,000 requests) yields a negative headline result: the fine-tuned model attains roughly six percentage points lower answer accuracy (Spyra 61.1% / 70.4%, base 67.3% / 76.3%; p < 0.001), while retrieval improves both models by about nine percentage points. Fine-tuning changes the form of the output: more schematic, twice as fast at the median, but with a sixfold increase in unrecoverable format failures. We derive four governance requirements: reasoning transparency, external factual grounding, local executability and multi-sample verification, and conclude that such systems should be assessed along architectural properties rather than scores on individual benchmarks.
Copyright (c) 2026 Nik Ansre, Yara Hiresekorn, Gregor Grunwald (Author) https://creativecommons.org/licenses/by/4.0/
Exploring the Role of AR-Integrated BIM Systems in Construction Site Error Management
Managing construction-related errors has become increasingly important as construction projects continue to grow in scale and technical complexity. Digital technologies, particularly the combined use of Building Information Modeling (BIM) and Augmented Reality (AR), offer new opportunities to strengthen inspection procedures and facilitate more effective construction error management. Accordingly, this study evaluates the applicability of BIM–AR integration within the broader framework of smart design and digitally enabled construction management. The research employed a mixed-method design that integrated two complementary components: a bibliometric review of studies on BIM–AR integration and an empirical investigation involving a BIM–AR inspection framework implemented within a residential construction project in Ankara, Türkiye. The empirical stage was further supported through semi-structured interviews conducted with practitioners possessing experience in BIM-enabled construction processes. The bibliometric analysis identified dominant research themes, conceptual relationships, and emerging directions in BIM–AR research, while highlighting the limited empirical investigation of AR-supported inspection workflows from practitioner perspectives. The empirical phase involved BIM model preparation, AR integration, and professional evaluation of the potential contribution of the proposed workflow to construction inspection processes. Findings indicate that BIM–AR-supported approaches may facilitate visualization, improve access to project information, support model-based verification, and contribute to inspection-related decision-making. Due to the exploratory nature of the study and the limited participant group (n = 15), the findings are not intended for statistical generalization. Rather than drawing broadly generalizable conclusions, this research offers an initial understanding of practical implementation issues, professional experiences, and the ways in which AR-enabled BIM workflows may support construction inspection and digital quality assurance. The research contributes by integrating bibliometric mapping, workflow evaluation, and practitioner feedback to examine how BIM–AR technologies may support information management and smart construction practices.
Copyright (c) 2026 Sezen Aksu, Aslı ER AKAN (Author) https://creativecommons.org/licenses/by/4.0/
From BIM to LIM: A Structured Review of Revit’s Landscape Modelling Capacity and Ecological Information Gaps
Landscape Information Modelling (LIM) extends Building Information Modelling (BIM) to represent topography, vegetation, hydrology, and ecological processes in support of sustainable design. Landscape architecture has adopted BIM-based workflows more slowly than building disciplines, and the specific capacity of Autodesk Revit, the most widely used commercial BIM authoring tool, to function as a LIM platform remains fragmented across the literature rather than assessed as a single, structured question. This study addresses that fragmentation through a structured, PRISMA-informed literature review. Formal database searching covered Scopus, Web of Science, ScienceDirect, and SpringerLink; Google Scholar and ResearchGate were used as supplementary discovery and retrieval tools rather than as primary databases. Sources published between 2013 and 2026 were screened for relevance to BIM, LIM, or Revit-based landscape modelling. Twenty-nine studies (18 journal articles and 11 conference papers) met the eligibility criteria, from an initial pool of 100 records identified across six sources and narrowed through deduplication and screening, and were coded across five review-based dimensions: geometric modelling, data integration, ecological intelligence, interoperability, and sustainability support. Screening and coding followed a predefined study-level protocol; ambiguous records were reassessed against the eligibility criteria, while reviewer-level agreement statistics were not available and are not claimed. The reviewed evidence suggests that Revit is effective for coordinated geometric representation and BIM-based documentation of several landscape components, including terrain, hardscape, and built infrastructure, but its native capacity for temporal vegetation change, ecological process modelling, and performance indicators linked to SDG 13 and SDG 15 remains limited according to the studies reviewed. Complementary civil engineering, GIS, and ecological simulation tools reported in the literature are used to extend Revit-based workflows toward these functions. The study’s contribution is a structured synthesis that distinguishes geometric and documentation capacity from temporal and ecological intelligence, clarifies the difference between building-oriented Levels of Detail and the information needs of living landscape systems, and sets out a conceptual hybrid workflow proposed for future empirical validation. The review is limited by its literature-based method and its dependence on secondary evidence; empirical software testing is needed to confirm these review-based findings. SDGs 9, 11, 13, and 15 are interpreted here through defined capability indicators linking software function to measurable landscape tasks, rather than treated as outcomes achieved through software use alone.
Copyright (c) 2026 Fatema Nafeed, Weldy Eka Saputra (Author) https://creativecommons.org/licenses/by/4.0/
AI-Enhanced Emotional Prediction in Interior Design: Bridging Emotion and Architecture for Personalized Environments
Artificial Intelligence can help in creating environments that adapt to users’ emotional states and personal preferences. This paper proposes an Artificial Intelligence-based framework to predict and personalize emotional experiences in interior spaces, addressing the limitations of subjective emotional architecture. The proposed framework integrates Kansei Engineering, fuzzy analytic hierarchy process (FAHP), and the Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS) to translate users' emotional responses into weighted interior design parameters. These prioritized parameters are incorporated into an AI-based generative design model that produces personalized interior configurations. Emotional predictions are subsequently evaluated through immersive virtual reality (VR) environments by comparing AI-predicted emotional responses with physiological indicators and self-reported questionnaire data. The findings indicate that AI-assisted generative models effectively support participant-specific modifications to environmental design characteristics, including lighting, materials, color palettes, and biophilic integration. However, the framework demonstrated limited capability in generating coherent architectural floor plans, indicating that current AI systems are better suited to environmental personalization than comprehensive spatial planning.The research paper establishes a scalable model linking emotion prediction with adaptive, human-centered interior design to enhance well-being.
Copyright (c) 2026 Reem Mahmoud, Ziad Elsayes (Author) https://creativecommons.org/licenses/by/4.0/
Comparing Microclimate Dynamics in Urban Areas with Distinct Morphological Changes Using AI-Based Predictions and Climate Scenarios
Rapid urbanization and climate change are reshaping urban microclimates, yet existing assessments of future outdoor thermal comfort predominantly rely on annual or seasonal climate averages, overlooking extreme summer heat conditions — the periods of greatest risk to public health and outdoor livability. Moreover, studies projecting future thermal comfort typically hold urban morphology fixed, applying future climate scenarios to present-day city form, without accounting for how distinct growth mechanisms reshape building volume, height, and density over time. This study addresses both gaps by examining peak summer heat extremes in Tabriz through 2050, comparing two districts undergoing distinct growth mechanisms: Khavaran, developing through both new infill construction and building height increases, and Baghshomal, growing solely through vertical renovation of existing buildings. District-specific future morphology is simulated using AI-based prediction models calibrated to each district's observed growth pattern, and future climate scenarios are generated using the CCWorld WeatherGen tool; both are jointly input into ENVI-met to assess microclimatic conditions and outdoor thermal comfort under extreme summer heat. Results show that Baghshomal, despite its slower growth, is more vulnerable to extreme heat than Khavaran. Compared with 2025, maximum air temperature increased by 3.52°C in Baghshomal and 4.66°C in Khavaran, while maximum relative humidity decreased by 8.73% and 14.22%, respectively. This is driven by street-level morphology rather than growth rate: Khavaran's higher street height-to-width ratio and denser vegetation cover provide greater shading and lower solar exposure during peak heat hours, while Baghshomal's wider, lower-density streets remain more exposed. These findings indicate that the mechanism and morphological configuration of urban growth, not only its rate, shape future thermal resilience, offering a growth-mechanism-sensitive framework for evaluating extreme-heat vulnerability in Tabriz's rapidly transforming districts, with potential relevance to similar semi-arid cities after local calibration.
Copyright (c) 2026 Paria Saadatjoo, kiomars Fathi majd (Author) https://creativecommons.org/licenses/by/4.0/
The Digital Past: Assessing University Students’ Perception Toward VR Heritage Tours
This paper explores the perception of university students towards the use of Virtual Reality (VR) in cultural heritage tourism. The research particularly focuses on students’ perceived appeal, influence on physical visit intention, and potential to encourage cultural heritage appreciation. Using a cross-sectional survey of 82 respondents and 6 semi-structured interviews, the study applied descriptive statistics, and multiple regression models to examine the relationship between perceived VR benefits, concerns, adoption factors, and tourism-related outcomes. The findings indicate that respondents generally considered VR heritage tours as a positive addition to the tourism experience with 70.7% rated VR as moderately appealing or higher, 73.2% indicated that a high-quality VR experience would make them at least slightly more likely to visit a heritage site in person, and 87.8% believed that VR could encourage cultural heritage appreciation. The analysis identified accessibility as the most significant and consistent explanatory factor. The study concludes that VR should be placed not as a replacement for physical heritage tourism, but as a complementary smart design tool that supports accessibility, education, pre-visit engagement, and inclusive cultural participation. The findings of this research contribute to smart policy design by providing evidence for how evolving technologies can be governed and employed in ways that balance accessibility, advancement, cultural authenticity, and responsible heritage management.
Copyright (c) 2026 Manal Khalaf (Author) https://creativecommons.org/licenses/by/4.0/
AI-Integrated Self-Help Rural Housing and Livelihood Resilience System: A Bottom-Up Approach for Climate-Vulnerable Communities in Southwest Bangladesh
This study investigates the conceptual potential of AI-driven generative design as an advanced design-policy tool for developing personalized, climate-resilient rural housing in the disaster-prone southwest region of Bangladesh. Centered on Nalian village in Dacope, Khulna, the research integrates field survey data, vernacular housing analysis, functional layout extraction, and climate-responsive design principles to propose a hypothetical digital resilience model for self-help housing adaptation. The model applies Graph Neural Network (GNN) and Convolutional Neural Network (CNN) principles for plan-generation logic, incorporates aerodynamic form considerations for cyclone-responsive three-dimensional massing, and establishes context-based material selection criteria. The academic contribution of this research is the integration of artificial intelligence, vernacular spatial knowledge, and community-based housing resilience within a unified conceptual framework. The study's originality is demonstrated by positioning AI not only as a form-generating tool but also as a decision-support mechanism that translates local needs, climatic risks, and construction practices into adaptable housing strategies. This research expands the scope of smart design policies by illustrating how digital design systems can facilitate participatory, scalable, and context-sensitive housing decision-making for climate-vulnerable communities. The findings indicate that integrating AI-assisted design with local knowledge can enhance access to resilient housing solutions, reinforce disaster preparedness strategies, and inform future policy frameworks for sustainable rural settlement planning in Bangladesh and similar global contexts.
Copyright (c) 2026 Liasa Yeasmin Lia, Shayer Ghafur, Dipannita Nandi (Author) https://creativecommons.org/licenses/by/4.0/
Posthuman Learning in the Age of AI: Rethinking Agency, Knowledge, and Policy in Architectural Education
Architectural education is being reshaped as Artificial Intelligence (AI) challenges human-centered conceptions of creativity, authorship, and knowledge production. However, current discussions on AI-supported architectural education remain largely focused on tool adoption, productivity, creativity, and student perception, while the policy implications of AI for curriculum design, studio governance, assessment, educator training, and ethical accountability remain underdeveloped. Addressing this gap, the study develops a policy-oriented posthuman framework for interpreting AI integration in architectural pedagogy and translating it into responsible design education principles. The study adopts a two-stage review design that combines a conceptual framing review of posthuman pedagogy with a systematic synthesis of empirical and pedagogical studies on AI, computational design, and architectural education published between 2010 and 2025. The review identifies three interrelated dimensions of AI-supported posthuman learning: distributed agency, in which design intelligence is shared across students, educators, AI systems, datasets, interfaces, materials, and studio environments; situated knowing, in which AI becomes pedagogically meaningful only when embedded in reflective, material, and context-sensitive design inquiry; and ethical entanglement, in which authorship, bias, accountability, originality, dependency, and environmental responsibility become core educational concerns. Based on these findings, the paper proposes ecological intelligence as a design education policy principle: the capacity to think, design, evaluate, and act responsibly within interconnected human, technological, material, environmental, and institutional systems. The contribution of the study is twofold. First, it clarifies the theoretical relevance of posthuman pedagogy for AI-supported architectural education. Second, it translates this theoretical perspective into a policy-oriented pedagogical framework that can inform curriculum development, studio pedagogy, assessment criteria, and ethical governance in architectural education.
Copyright (c) 2026 Hakan Tong, Ayşegül Kıdık, Sema Alaçam (Author) https://creativecommons.org/licenses/by/4.0/
Evolving Power Structures in Megaproject Governance: A Temporal SNA and Powercube Analysis of the BSCU Project
Megaprojects are crucial for developing urban systems, yet their governance is often characterised by disputed authority, shifting coalitions, and uneven stakeholder influence. This paper examines the evolution of power structures in megaproject governance through an integrated methodological approach, that combines temporal social network analysis with the PowerCube framework. Using the Bank Station Capacity Upgrade project in London as a case study, the research traces how visible, hidden, and invisible forms of power interacted across two stages of the project, identifying turning points where stakeholder centrality and influence shifted. This study contributes new knowledge to urban management and governance in three ways. First, it demonstrates that power in large infrastructure projects is not fixed but changes over time as new actors join, coalitions change, and governance spaces are reconfigured. Second, it introduces a novel way of studying these changes by combining social network analysis, which maps relationships between actors, with the PowerCube framework, which highlights visible, hidden, and invisible forms of power. Third, the paper provides original evidence from the Bank Station Capacity Upgrade project, demonstrating how governance mechanisms shaped decision-making and stakeholder legitimacy in one of London’s most complex transport systems. By connecting megaproject governance to urban management concerns, the paper offers both scholarly insights and practical recommendations for policymakers and practitioners seeking to enhance transparency, adaptability, and stakeholder engagement in complex infrastructure delivery.
Copyright (c) 2025 Huda Almadhoob (Author) https://creativecommons.org/licenses/by/4.0/
Implementing an Intelligent Monitoring System to Enhance Energy Efficiency and Support Decarbonization in Sustainable Buildings
This paper presents the development and implementation of IoT HEAT, an intelligent, low-cost thermal monitoring system designed to enhance energy efficiency and support decarbonisation strategies in sustainable buildings. Recognizing the critical role of the built environment in global carbon reduction efforts, this study introduces a novel integration of the Temperature-Based Method (TBM) with real-time IoT-based sensing architecture to estimate the thermal transmittance (U-value) of building envelopes. Unlike conventional approaches that rely on expensive heat flux meters, this system leverages compact, affordable sensors to continuously monitor key temperature parameters interior air, surface, and exterior air across building façades with varying orientations. The originality of this work lies in its demonstration of how open-source, scalable technology can be used to perform reliable envelope diagnostics without the need for specialized equipment or complex setups. Academic contributions include validating TBM under real-world, dynamic conditions and providing a replicable framework for deploying intelligent building performance assessment systems. Results confirm the system’s potential to detect inefficiencies, inform retrofitting decisions, and significantly reduce operational energy losses. This study contributes to both academic discourse and practical applications by bridging the gap between simplified theoretical methods and cost-effective, real-time implementation for energy-efficient building design and renovation.
Copyright (c) 2025 Abdollah Mobaraki, Mojdeh Nikoofam, Zahra Mobaraki, Ehsan Hosseinzadehfard, Behnam Mobaraki (Author) https://creativecommons.org/licenses/by/4.0/
Extended Reality (XR) Technology in ADHD-Friendly Classroom Design
The educational environment in elementary schools significantly impacts the learning process, children's physical and mental health, and student achievements. Architectural design plays a vital role in supporting ADHD (Attention Deficit Hyperactivity Disorder) students, creating spaces that promote focus and engagement. This study seeks to discover how Extended Reality (XR) technology transforms classroom design into customizable learning environments. It uses qualitative methodology in collecting data from four schools in the United States to understand the current classroom challenges for ADHD students aged between 6 and 11. Moreover, the research applies a quantitative approach through a comprehensive survey that reveals educators' perspectives on using Extended Reality (XR) as a tool for ADHD-friendly classroom design. The results highlight both enthusiasm and concerns regarding XR implementation. It summarizes the key findings and proposes a roadmap for incorporating XR in classroom layout and the needed infrastructure to enhance the motivation and involvement of learners. To optimize XR for students with ADHD, classrooms should prioritize flexibility, movement, and sensory regulation.
Extended Reality (XR) as a learning tool
Copyright (c) 2025 Hebatallah Hamdy Mohamed (Author) https://creativecommons.org/licenses/by/4.0/
Integrated Approaches to Urban Energy Efficiency and Carbon Sequestration: A Framework for Implementing Urban Digital Twins
Energy efficiency and carbon sequestration are fundamental components of sustainable urban development, as cities account for majority of global energy consumption and carbon emissions. This research explores Urban Digital Twins (UDTs) as an innovative approach to optimizing operational energy use and enhancing carbon sequestration in urban environments. UDTs integrate real-time data processing, simulation models, and public participation to drive sustainable energy management and emissions reduction. The study examines two pilot buildings in Thailand and Vietnam, using energy data to evaluate the feasibility of UDTs. Key implementation challenges, including regulatory barriers, setup costs, and limited public engagement, are analyzed, with proposed strategies to address them. A digital twin-based energy framework enables cities to integrate renewable energy systems, intelligent controls, and carbon sequestration strategies, optimizing energy use while reducing emissions and costs. This research aligns with UN Sustainable Development Goals (SDGs) 7 and 11, supporting clean energy adoption and sustainable urban development.
Copyright (c) 2025 Muhammad Rahat Jamil (Author) https://creativecommons.org/licenses/by/4.0/
AI-Driven Knowledge Transfer in Architectural Education
The use of large language models (LLMs) in architecture is still at an early stage, but is becoming increasingly important due to the need for local, domain-specific assistance systems. This study investigates how such models can be developed and extended under local hardware conditions in order to provide architecture-specific knowledge in a context-appropriate manner. For this purpose, a methodological approach was chosen that combines lightweight fine-tuning with a two-stage retrieval augmented generation system (RAG). Two model series were tested: Mini-Spyra for dialogue-oriented knowledge retrieval and IwI-Spyra for semantic analysis of structured planning data (e.g. IFC). The results show that domain-specific training in combination with dynamic knowledge integration leads to significantly more precise, comprehensible answers. The article provides a transferable model for the use of AI in teaching and planning practice - data protection-compliant, locally executable and didactically comprehensible. The study thus contributes to the development of explainable AI tools in an architectural context. This research was conducted within a "Young Researchers" project supported by the Jade University of Applied Sciences.
Copyright (c) 2025 Yara Hirsekorn, Nik Ansre, Prof. Dr.-Ing. Gregor Grunwald (Author) https://creativecommons.org/licenses/by/4.0/
Review on the Integration of Artificial Intelligence in Parametric Urban Design and Outdoor Thermal Comfort
Artificial Intelligence (AI) is increasingly recognised for its ability to accelerate physics-based simulation tasks, making it particularly promising in urban design processes, where simulation often hinders iterative development. This review explores the intersection of AI, parametric urban design (PUD), and outdoor thermal comfort (OTC), assessed using the Universal Thermal Climate Index (UTCI) or other indices. We identify emerging methods and tools used to optimise comfort outcomes through intelligent design frameworks. By systematically analysing 40 studies from 2018 to 2025 and leveraging bibliometric analysis, the review categorises contributions into predictive modelling, generative design, parametric optimisation, and integration strategies. The limitation is the niche and novel nature of the subject, which reduces the number of eligible studies. We highlight how AI, particularly machine learning, acts as both a surrogate for environmental simulation and a driver for design generation. Although full integration of AI with parametric and comfort modelling remains limited, recent progress suggests strong potential. This paper presents a conceptual pipeline for integrating AI into PUD to support comfort optimisation, emphasising the need for open datasets, interpretable models, and design tool interoperability. This review establishes the first interdisciplinary synthesis of parametric urban design, artificial intelligence, and outdoor thermal comfort research, providing urban planners with a framework to leverage emerging technologies for climate-resilient cities. Limitations include the niche nature of AI-PUD-OTC integration (41 studies met criteria) and the lack of longitudinal validation in built projects.
Copyright (c) 2025 Mohammed Lamine, Nassira BENHASSINE, Atef Ahriz (Author) https://creativecommons.org/licenses/by/4.0/
Reimagining Architecture: A Semiotic Study of Sound in Ai-Generated Spatial Design
This study examines how artificial intelligence (AI) interprets spoken architectural language by analysing vocal features—such as pitch, tone, and magnitude—and translating them into visual representations. Situated within the field of architectural semiotics, the research investigates how sound functions not merely as an acoustic phenomenon but as a symbolic agent in AI-mediated design. Five ambiguous architectural terms (vault, shell, column, plan, story) were recorded in two distinct sentence contexts and vocal styles (neutral vs. expressive). Using the Librosa Python library, pitch range and vocal magnitude were extracted as prosodic features. These metrics informed the construction of emotionally nuanced text prompts for MidJourney, a generative AI model, to produce architectural images reflecting vocal delivery. The results reveal consistent correlations between vocal variation and visual form: high pitch and strong vocal energy led to expressive, fluid, and emotionally charged spaces; lower pitch and stable magnitude generated grounded, monumental, or contemplative structures. These outcomes suggest that vocal expression can serve as a semiotic input in cross-modal AI workflows, where speech acts as both data and design material. By bridging sound and space, the study expands the semiotic framework of architectural representation and introduces voice as a generative modality in AI-assisted urban and spatial design. The findings support a multi-sensory design paradigm where not only what is said, but how it is said, shapes architectural meaning.
Copyright (c) 2025 Hidayet Softaoglu (Author) https://creativecommons.org/licenses/by/4.0/
Artificial Intelligence-Enhanced Innovation: Blending Contemporary Aesthetics with Islamic Heritage
Artificial intelligence has transformed various disciplines, including architecture. This study examines the potential of three generative artificial intelligence tools — Midjourney, Leonardo AI, and Prome AI — in representing modern Islamic architectural designs that draw inspiration from traditional principles. The contribution of this study is based on both quantitative and qualitative approaches. The quantitative methodology was conducted through two surveys that assessed public awareness and perceptions of Islamic architecture and evaluated AI-generated designs in terms of architectural authenticity, cultural relevance, and spiritual identity. The study also adopts an experimental and comparative approach as a qualitative methodology to analyse how each AI-driven tool interprets Islamic principles within a contemporary context, focusing on visual aesthetics and cultural appropriateness. The results demonstrate how artificial intelligence tools can support designers and architects in blending innovation with heritage, offering new possibilities for enhancing design solutions and creativity in Islamic architecture. However, the study indicates some limitations, including a lack of deep understanding of the cultural and authentic aspects of Islamic architectural principles. This research adds value to the integration of artificial intelligence in Architectural and interior design schools. It concludes with futuristic possibilities for integrating AI-driven design into the architecture and interior design industry.
Copyright (c) 2025 Maryam Obaid, Osama Omar (Author) https://creativecommons.org/licenses/by/4.0/
Smart Integration of XR Technologies in Architectural Education: Metaverse Opportunities and Challenges
Extended Reality (XR) technologies—encompassing Virtual Reality (VR), Augmented Reality (AR), and Mixed Reality (MR)—are transforming architectural education by offering interactive, student-centered learning within immersive Metaverse environments. This study examines the level of adoption, benefits, and challenges of XR integration in Middle Eastern architecture programs, highlighting both qualitative and quantitative insights derived from comprehensive literature reviews and a questionnaire survey of 266 participants. Results indicate that although 35% of respondents are highly familiar with XR, broader curriculum-wide integration remains fragmented. XR-based design studios are the primary area of adoption, emphasizing immersive, hands-on training that facilitates spatial understanding and sustainable design insights. Nonetheless, institutional barriers—such as limited infrastructure, substantial cost outlays, and the need for faculty training—constrain widescale implementation. Student-specific challenges include accessibility concerns, health implications of prolonged VR usage, and the scarcity of high-speed internet in some educational contexts. Despite these hurdles, XR fosters enhanced collaboration, global engagement, and real-time design prototyping, foreshadowing significant pedagogical shifts. The study recommends establishing dedicated XR labs, faculty development programs, and strong industry partnerships to support large-scale XR adoption. Future research should focus on in-depth frameworks and Participatory Action Research (PAR) to systematically integrate XR across architectural curricula. Adapting to these immersive platforms could reshape how architectural students conceive, create, and critique built environments.
Copyright (c) 2024 Hebatallah Hamdy Mohamed (Author) https://creativecommons.org/licenses/by/4.0/
Augmented Reality as a Design Tool in Enhancing Community Engagement: A Case Study of Souq Al Muharraq
This research explores the potential of Augmented Reality (AR) as a participatory design approach to the revitalization of the historic market space, the Souq Al Muharraq in Bahrain. The research is positioned at the intersection of digital innovation and heritage preservation, investigating how AR can be used to improve the field of inclusive architecture and urban design, intersecting a range of knowledge levels between communities and professional planning. The mixed method approach made use of spatial observations, twelve semi-structured interviews, and three participatory workshops with eighteen stakeholders (locals, shopkeepers, and visitors). Printed overlays and annotated maps as analog AR simulations were deployed to receive feedback by users who had varied levels of digital literacy. Results indicate that AR-assisted approaches boosted spatial literacy and brought out culturally informed insights and allowed co-creation inclusively, especially among digitally excluded populations. The paper proposes a Smart Design Engagement Model that can bridge the gap between professional planning and lived experience of heritage sites. In the context of advancing research in participatory urbanism and smart governance of heritage, this paper is able to illustrate how low-barrier AR interfaces can be used as decision-making tools and in cultural-sensitive settings.
Copyright (c) 2025 Mashael AlDoy, Najla Allani (Author) https://creativecommons.org/licenses/by/4.0/
AI-Driven Sustainable Habitat Design: Key Policy Frameworks and Ethical Safeguards
Artificial intelligence (AI) is transforming the field of sustainable habitat design by enabling data-driven strategies that reduce resource consumption, enhance occupant comfort, and optimize urban infrastructures. This study examines how AI-driven tools, including machine learning algorithms, generative design models, and IoT-based sensors, can be integrated into design workflows to achieve energy efficiency, promote circular economies, and foster climate resilience. Through a mixed-method approach incorporating systematic literature review, policy analysis, and conceptual modeling, we identified critical policy imperatives—such as data governance, standards, and incentives—that guide responsible AI adoption. Findings indicate that robust data governance frameworks are essential for balancing privacy concerns with the need for high-quality datasets, while transparency and accountability standards mitigate algorithmic biases and performance uncertainties. Additionally, public-private partnerships and financial incentives can accelerate innovation by bridging research and real-world application. Ethically, stakeholders must tackle algorithmic bias, ensure equitable data representation, and maintain transparent decision-making to prevent marginalization of vulnerable populations. By demonstrating the potential of AI to drive holistic sustainability targets, our research underscores the importance of comprehensive policy guidelines and ethical safeguards in shaping equitable, efficient, and resilient built environments. Ultimately, these frameworks unify innovation and equity.
Copyright (c) 2024 Mustafa Aziz Amen (Author) https://creativecommons.org/licenses/by/4.0/
Human-Centric Smart Cities for Inclusive and Ethical Urban Development
The rapid development of smart cities, driven by digital infrastructure and data-centric systems, offers innovative solutions to urban challenges but often neglects critical ethical considerations such as inclusivity, equity, and privacy. This study integrates a literature-based policy analysis and selective case studies from Amsterdam, Tokyo, Medellín, and Toronto to explore the human-centric approach to smart city development. The findings reveal fragmented regulatory frameworks, gaps in adaptive governance, and varying levels of inclusivity in current initiatives. A framework of best practices is proposed to embed ethical principles, equitable access, and sustainable policies into smart city projects. By emphasizing community engagement, data transparency, and adaptability, this research underscores the necessity of aligning technological advancements with human-centric values to ensure long-term urban sustainability and equity. The study provides actionable insights for policymakers, researchers, and urban planners seeking to bridge the gap between aspirational visions and tangible outcomes in smart city design.
Copyright (c) 2024 Rokhsaneh Rahbarianyazd (Author) https://creativecommons.org/licenses/by/4.0/
The Role of Artificial Intelligence in Enhancing Design Innovation and Sustainability
Artificial Intelligence (AI) is reshaping the design landscape, bridging computational efficiency with human creativity to revolutionize fields such as architecture, graphic design, and product development. This paper explores AI’s transformative impact, focusing on its ability to enhance productivity, foster innovation, and personalize user experiences. Objectives include identifying the benefits of AI-driven tools, analyzing their applications across domains such as architecture, graphic design, and product development, and evaluating ethical concerns related to AI in design. The research adopts a qualitative approach, to examine AI’s role as a creative collaborator and its implications for design methodologies. Results reveal that AI optimizes design iterations, accelerates prototyping, and democratizes access to high-quality resources, making design processes more inclusive and efficient. Findings also highlight ethical concerns, such as bias in AI systems and intellectual property disputes, which require balanced and responsible integration strategies. AI serves as a creative collaborator, enhancing ideation and prototyping processes. Despite its benefits, AI integration raises ethical concerns, including data bias, intellectual property disputes, and potential job displacement. These challenges necessitate equitable frameworks to ensure inclusive and responsible AI use. The future of AI in design promises even greater innovation with emerging technologies like augmented reality and the metaverse, fostering collaborative human-machine interactions. By embracing AI, designers can expand creative boundaries, producing solutions that are not only functional and visually compelling but also socially and environmentally sustainable. This study underscores the need for balanced integration, ensuring AI complements human ingenuity while redefining creativity in the evolving design landscape.
Copyright (c) 2024 Oluwagbemiga Paul Agboola (Author) https://creativecommons.org/licenses/by/4.0/
Smart Design Policies: Shaping the Future of Human Habitats in the AI Era
Smart Design Policies represent a vital intersection of technology, design, and policymaking, especially in the context of rapidly advancing artificial intelligence (AI). This article explores how SDP, as an annually published, double-blind peer-reviewed journal by Alanya University, contributes to shaping the future of human habitats in the AI era. By examining various dimensions—ranging from policy frameworks and computational design to ethical, social, and sustainability considerations—the journal fosters a platform for researchers, practitioners, and policymakers to collaboratively navigate emerging opportunities and challenges. Through an interdisciplinary lens, SDP addresses the convergence of intelligent design and governance, emphasizing adaptive policy mechanisms that leverage AI-driven insights for real-time decision-making. The discussion presented here underscores the significance of balancing innovation with regulatory oversight, ensuring that human-centered values and equity remain at the forefront.
Copyright (c) 2024 Salar Salah Muhy Al-Din (Author) https://creativecommons.org/licenses/by/4.0/
Reproduction of Nature-Inspired Architectural Forms through Artificial Intelligence
This study aims to evaluate the effectiveness of AI-based visualization tools in reinterpreting biomimetic architectural designs. To this end, three iconic nature-inspired buildings—Eastgate Building, Clyde Auditorium, and the Bahá'í Temple—were selected. For each, visual representations were generated using different AI models: DALL-E, DeepAI, and Midjourney. These AI-generated visuals were compared with the original structures based on architectural criteria, including form similarity, structural feasibility, scale and proportion, environmental integration, and SSIM (Structural Similarity Index Measure) scores.The findings demonstrate that while AI models can interpret and reproduce formal diversity inspired by nature, their architectural realism, scale coherence, and environmental responsiveness vary considerably. Midjourney stood out for its integration with landscape, DALL-E achieved the highest visual similarity scores, and DeepAI produced simplified forms with limited detailing. Overall, AI-generated biomimetic designs show promise in conceptual design phases, but to enhance practical applicability, more integrated approaches with engineering systems are needed.
Copyright (c) 2025 Gül Şebnem Tutal, Fatma Demet Aykal (Author) https://creativecommons.org/licenses/by/4.0/
The Role of Computer-Aided Design in Architectural Education
Computer-Aided Design (CAD) tools have fundamentally transformed architectural education by offering greater precision, efficiency, and flexibility compared to traditional hand-drawing techniques. This study investigates the impact of CAD _programs on architectural training, focusing on their influence on students’ technical knowledge, spatial perception, and creativity. A mixed-method approach was employed, combining literature review and an empirical survey. The survey was administered to 40 first-year architecture students at Bursa Technical University following the completion of their introductory CAD course. Quantitative results revealed that 95% of the students reported an improvement in their technical knowledge, 90% stated enhanced drawing abilities, and 73% observed better spatial perception. However, only 65% felt that CAD improved their creativity, with qualitative feedback indicating mixed experiences regarding creative freedom. While many students valued CAD’s capacity for precise, iterative design, others felt constrained by software limitations. The majority (85%) favored a hybrid approach, combining CAD with hand-drawing techniques. The originality of this study lies in its integration of quantitative and qualitative data to assess both the benefits and perceived limitations of CAD in early design education. The findings underscore the importance of pedagogical strategies that blend digital tools with traditional methods, supporting both efficiency and creative exploration. This study contributes to the architectural education literature by offering empirical insights into students’ evolving design practices and by proposing a framework for balanced digital-traditional integration in design pedagogy.
Copyright (c) 2025 imran GUMUS BATTAL (Author) https://creativecommons.org/licenses/by/4.0/
Smart City and Sustainable Development in Iskele City, North Cyprus
Rapid urbanization has generated multifaceted challenges, including traffic congestion, environmental degradation, urban sprawl, and declining urban livability, thereby complicating effective city management. In response, peripheral areas surrounding city cores have seen the emergence of high-rise developments that markedly diverge in structure and appearance from the historical urban fabric. These new developments often claim to embody the principles of smart buildings and smart neighborhoods. However, the extent to which they are spatially prepared to adopt smart city strategies remains unclear. This study investigates the spatial readiness of İskele, a mid-sized city in Northern Cyprus, for smart city implementation by employing space syntax theory. It aims to identify priority zones for strategic intervention and to develop a transferable framework applicable to similar urban contexts. The research adopts a mixed-methods approach, incorporating field observations, archival research, and spatial analysis using DepthMap software. It examines the relationship between spatial integration, connectivity, and core smart city dimensions. The findings highlight the Royal Sun Residence as the most spatially integrated area, making it the most suitable candidate for initiating a pilot smart city project. This research contributes to academic discourse by proposing a replicable methodological framework for assessing spatial-smart city alignment in rapidly developing urban environments, offering practical insights for urban planners and policymakers.
Copyright (c) 2025 Marjan Alikhanzadeh (Author) https://creativecommons.org/licenses/by/4.0/