Architectural intelligence最新文献

{"title":"Maximum entropy inverse reinforcement learning for campus spatial optimization from Wi-Fi probe trajectories: a case study of Southeast University Wuxi Campus","authors":"Guangjin Wang,&nbsp;Ruike Huang,&nbsp;Xiang Li,&nbsp;Li Li","doi":"10.1007/s44223-026-00117-7","DOIUrl":"10.1007/s44223-026-00117-7","url":null,"abstract":"<div><p>With the outward expansion of university campuses toward suburban areas, the modern campus has evolved into an increasingly independent social space, providing an organizational setting in which users’ daily activities rely on diverse on-campus facilities. Accordingly, the rationality of spatial organization is a critical determinant of quality of life and a central focus of campus optimization research. However, existing methods for campus space optimization predominantly rely on the experience of planners and pedestrian flow simulation tools based on spatial topology, rule-based models, deep learning, or reinforcement learning, while often failing to adequately incorporate the influence of environmental factors on behavior. In reality, the behavior of campus users tends to be goal-oriented, and neglecting environmental factors may therefore lead to design biases. Inverse Reinforcement Learning (IRL) has the capacity to capture human interactions with various environmental factors in real-world settings, offering a novel approach to pedestrian trajectory simulation on campuses. Thus, the Southeast University Wuxi Campus serves as the research site, with pedestrian trajectory data and environmental feature data collected. A maximum entropy inverse reinforcement learning (MaxEnt IRL) method is employed to construct a pedestrian trajectory simulation model, which is subsequently validated and applied. Robustness and modeling rationality are further examined through environmental representation analysis and multi-resolution sensitivity experiments. Experimental results demonstrate that the proposed model effectively simulates pedestrian behavior under the influence of environmental factors and quantifies their relative attractiveness, thereby providing an effective tool for optimizing campus spatial organization.</p></div>","PeriodicalId":72270,"journal":{"name":"Architectural intelligence","volume":"5 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2026-04-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s44223-026-00117-7.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147797182","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Digitizing Dementia-Friendly Environments (DFEs): the application of digital technologies in promoting inclusive spaces","authors":"Fei Chen,&nbsp;Bingxin Yang,&nbsp;Zhuoxin Jia,&nbsp;Fangzhou Zhao","doi":"10.1007/s44223-026-00115-9","DOIUrl":"10.1007/s44223-026-00115-9","url":null,"abstract":"<div><p>With the global rise in the number of people living with dementia, the creation of inclusive spaces that support independence and quality of life has become increasingly urgent. This systematic review synthesizes 76 peer-reviewed studies published between 2014 and 2024 on the use of digital technologies in dementia-friendly environments (DFEs). To make sense of a rapidly evolving field, the review adopts a practice-oriented, five-dimensional framework spanning smart building frameworks, virtual and augmented reality (VR/AR), assistive robotics and sensor integration, remote health and activity monitoring systems, and multisensory stimulation and user-experience design. These dimensions are explicitly derived from core DFEs design principles (safety and comfort, autonomy and activities of daily living, cognitive support and orientation, social participation, and affect regulation) and cover the full continuum from building-scale infrastructures to micro-level human–environment interactions. The review also distinguishes between early-generation systems (2014–2017), dominated by single-function ambient assisted living (AAL) prototypes and non-immersive VR, and new-generation systems (2018–2024), which increasingly employ head-mounted VR/AR, IoT-based multi-sensor smart homes and AI-enhanced decision support in real-world settings. Across these generations, the evidence shows that new-generation VR can improve spatial navigation and wayfinding in people with mild dementia, but benefits are far less clear for moderate-to-severe stages and are constrained by cybersickness, interface complexity and safety concerns. IoT-based sensor systems demonstrate more robust and consistent effects on safety outcomes (e.g. fall detection, wandering prevention) across home, residential and community environments. Multisensory environments and user-experience interventions support emotional regulation and engagement in daily activities, while assistive robots and remote monitoring systems show promise for reducing caregiver burden and supporting autonomy but raise significant questions about privacy, data governance and cost. Rather than offering generic claims that “technology is beneficial”, this review maps concrete technological configurations to specific spatial goals, settings and dementia stages before the introduction of complex immersive or AI-driven systems. The review concludes that while digital technologies have transformative potential for creating more supportive, engaging and safe environments, their deployment must be guided by nuanced, generation-sensitive evidence, explicit data-governance frameworks and a commitment to personalized, human-centred care.</p></div>","PeriodicalId":72270,"journal":{"name":"Architectural intelligence","volume":"5 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2026-04-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s44223-026-00115-9.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147737648","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Symbiotic intelligence: human-technology co-agency in the built environment","authors":"Hua Chai,&nbsp;Philip F. Yuan","doi":"10.1007/s44223-026-00116-8","DOIUrl":"10.1007/s44223-026-00116-8","url":null,"abstract":"","PeriodicalId":72270,"journal":{"name":"Architectural intelligence","volume":"5 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2026-03-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s44223-026-00116-8.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147561107","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Intelligence assessment for diffusion-based generation of gymnasium field-level plans using deep learning","authors":"Zhenyu Wang,&nbsp;Yufan Meng,&nbsp;Chen Xu,&nbsp;Fang Zheng","doi":"10.1007/s44223-026-00114-w","DOIUrl":"10.1007/s44223-026-00114-w","url":null,"abstract":"<div><p>Field-level plan design for large and medium-sized gymnasiums is highly complex and inefficient under traditional manual workflows, motivating the use of generative AI. This study proposes a diffusion-based, stepwise assessment framework for gymnasium plan design. In the first stage, Stable Diffusion fine-tuned with LoRA and constrained by ControlNet is used to generate block plans. A rule-based screening module removes outputs with poor visual quality or missing essential functions, while the CNN-based model further ranks the remaining results by topological similarity to 149 exemplary built cases. Finally, the high-quality alternatives were determined by architects. These assessment phases between generation steps improve semantic and functional alignment with building code and reference cases. In the second stage, these selected block plans are further translated into detailed plans with room-level separations through image-to-image diffusion. The two level evaluation system checks how well the detailed plans match the block plan and architectural standards. Architects then choose the scheme that best fits the design intent. The proposed method was applied to the plan generation of the Beijing Jiaotong University Campus Gymnasium in Xiong’an. The generated plan is comparable to the winning bid implemented plan in terms of functional zoning and spatial organization. By embedding assessment phases between generation steps, the framework forms an integrated, feedback-enabled generative assessment paradigm for human computer interaction. Its multi-level, constraint-aware representation links block and detailed plans, maintaining consistency from functional zoning to room-level layouts while reducing manual screening effort.</p></div>","PeriodicalId":72270,"journal":{"name":"Architectural intelligence","volume":"5 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2026-03-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s44223-026-00114-w.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147441506","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A qualitative evaluation and structural analysis of multiple and additive load cases for two-dimensional Multi-Material Topology Optimisation in Grasshopper using the Generalised SIMP method","authors":"Efstathios Damtsas,&nbsp;Thanh T. Banh,&nbsp;Michael Herrmann","doi":"10.1007/s44223-026-00113-x","DOIUrl":"10.1007/s44223-026-00113-x","url":null,"abstract":"<div><p>In the physical world, it is common for Multiple Load Cases (MLC) to act on a body either simultaneously or at different points in time. While MLC has been widely addressed in the literature, it has been identified that MLC in 2D Multi-Material Topology Optimised (MMTO) examples using the Solid Isotropic Material with Penalisation (SIMP) method is understudied, with the majority of examples not evaluating their structural performance. It is also identified that there are currently no MLC-ready MMTO software tailored to Architects that can perform Finite Element Analysis (FEA). The current research investigates how MLC can be addressed within “Stag”, our newly developed MMTO plugin for Grasshopper, and how its results compare topologically to benchmark examples from the literature. Furthermore, an overlaying method (ALC) of individual load case results is compared to MLC. This study addresses the identified gap in the literature by evaluating and comparing the structural performance of Stag’s MMTO MLC and ALC results with those from the literature by performing FEA within the same platform using the Grasshopper plugin “Karamba3D”. It is found that Stag produces MMTO MLC results that have a similar topology and structural performance to the benchmark examples from the literature. While the ALC result surpasses the target volume fraction, it performs structurally better than the MLC result.</p></div>","PeriodicalId":72270,"journal":{"name":"Architectural intelligence","volume":"5 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2026-02-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s44223-026-00113-x.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147338495","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Integrating computational fluid dynamics and topological optimization for generative design of artificial reefs","authors":"Ding Wen Bao,&nbsp;Jiacheng Yu,&nbsp;Dan Luo","doi":"10.1007/s44223-025-00109-z","DOIUrl":"10.1007/s44223-025-00109-z","url":null,"abstract":"<div><p>This paper investigates the development and optimization of artificial reefs through a new generative design method that integrates Computational Fluid Dynamics (CFD) with Bi-directional Evolutionary Structural Optimization (BESO). Since the 1950s, artificial reefs have been deployed to enhance marine ecosystems, and this study begins with a survey of existing reef designs. In response to limitations in current design approaches, we adopt a topology optimization strategy aimed at improving spatial allocation for polyphony expansion within reef structures. By coupling fluid-dynamic analysis with an iterative optimization loop, we evaluate the effectiveness of material exchange enabled by these artificial formations—an essential consideration given advanced manufacturing constraints and the need for rapid production of natural-like geometries. To extend artificial reef design into new possibilities, we propose a generative workflow in which reef morphology emerges from the interaction between CFD and BESO, iteratively removing and adding material in accordance with external loading conditions. The resulting reef is then compared with representative benchmarks from current artificial reef designs to assess material efficiency, structural performance, and geometric characteristics under complex underwater conditions.</p></div>","PeriodicalId":72270,"journal":{"name":"Architectural intelligence","volume":"5 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2026-01-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s44223-025-00109-z.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146026927","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Designing tailored knitted textiles using nonlinear Force Density Method","authors":"Nikoletta Christidi,&nbsp;Christian Louter,&nbsp;Mariana Popescu","doi":"10.1007/s44223-025-00111-5","DOIUrl":"10.1007/s44223-025-00111-5","url":null,"abstract":"<div><p>Computer Numerical Control (CNC)-knitted textiles are flexible, lightweight, and highly customisable, which makes them promising materials for architectural and construction applications. In the context of tensile structures, both the final shape and the mechanical properties of knitted textiles can be controlled to follow a specific design intent. However, predicting their mechanical behaviour is challenging and currently requires experience, domain-specific knowledge, and extensive prototyping. Developing a computational method to design bespoke knitted textiles for a target geometry and behaviour is therefore essential. The proof-of-concept workflow introduced in this paper uses the Force Density Method (FDM) combined with gradient-based optimisation to compute force density distributions for a target geometry abstracted as a mesh. These force densities are discretised into domains and mapped to knit architectures with distinct deformation capacities, resulting in functionally graded textiles. The workflow is tested on a non-symmetric target geometry and evaluated through physical prototyping. The results highlight both the potential of the approach and the need for refined force density–knit architecture mapping and alternatives to prototyping. This computational method paves the way for material-informed form-finding, which can facilitate the integration of CNC-knitted textiles into architectural applications, such as flexible formwork.</p></div>","PeriodicalId":72270,"journal":{"name":"Architectural intelligence","volume":"5 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2026-01-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s44223-025-00111-5.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145982828","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Deploying FloaTree: computational design-to-construction workflow of a low-tech tensegrity system","authors":"Alberto Pugnale,&nbsp;Gabriele Mirra,&nbsp;Jack Halls,&nbsp;Michael Minghi Park,&nbsp;Michael Mack,&nbsp;Sofia Colabella","doi":"10.1007/s44223-025-00112-4","DOIUrl":"10.1007/s44223-025-00112-4","url":null,"abstract":"<div><p>Large old trees provide essential habitats for birds and many other species, yet they are rapidly disappearing from many landscapes. While artificial habitat structures have been trialled, their design rarely captures the morphological complexity of natural habitats. This limitation stems from both challenges in extracting relevant features from natural forms and the difficulty of developing cost-effective systems that can be reproduced at scale. This paper addresses this gap by presenting <i>FloaTree</i>, an experimental example of a human–machine design workflow to generate, optimise, and construct tensegrity structures derived from AI-generated visual abstractions of large trees. We developed a parametric workflow that translates such AI-generated polyline abstractions into X-module tensegrity configurations, refined through structural optimisation and represented via connectivity matrices. Iterative prototyping, from small-scale tests to an eight-module pavilion, validated the structural and constructability aspects of this workflow and culminated in the winning entry of the 2024 IASS “Design Competition and Exhibition of Innovative Lightweight Structures” in Zurich. The results demonstrate that tensegrity structures, typically confined to artistic installations or used with limitations as surrogates for other typologies, can be designed for packability, transport, and rapid low-tech assembly to enable their potential application in artificial habitat structures. The project also advances tensegrity design methods through a novel human–machine workflow and a visualisation technique based on connectivity matrices. It shows how the analogue and digital domains can co-exist in design workflows alongside emerging forms of human–AI collaboration. While ecological performance requires future field testing, the significance of this work lies in reframing tensegrity not only as an experimental artefact but as a transferable design framework integrating form abstraction, structural logic, and constructability, thereby suggesting broader applications for computationally optimised yet low-tech structures in disturbed landscapes.</p></div>","PeriodicalId":72270,"journal":{"name":"Architectural intelligence","volume":"5 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2026-01-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s44223-025-00112-4.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145930612","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Woven elastic interlayer for 3D‑printed hygroscopic tiles","authors":"Julia A. H. Barnoin,&nbsp;Jenny E. Sabin,&nbsp;Jonathan T. Butcher","doi":"10.1007/s44223-025-00110-6","DOIUrl":"10.1007/s44223-025-00110-6","url":null,"abstract":"<div><p>Conventional 4D printed actuators often embed programmability in a single hygroscopic layer. As a result they bend mainly in one direction and recover slowly. In this paper we explore the integration of a myocardium inspired thermoplastic polyurethane (TPU) matrix between a rigid PLA base and a hygroscopic cellulose PLA active layer, forming a three material layered system that delivers rapid multi axis deformation without external power. Tile geometry and material assignment are generated in Rhino and Grasshopper and exported as G code, yielding lightweight modules suitable for large scale fabrication. Humidity cycling demonstrates three programmable motion modes (doming, slit opening, and hinge like rotation) obtained solely by adjusting the geometry of the TPU matrix. Tiles that incorporate the TPU matrix return more quickly to their initial flat shape and maintain a stable deformation amplitude within a given specimen over repeated cycles, because the matrix limits over curvature and prevents reverse bending in over dry conditions. By adding this strategically placed TPU matrix, the system converts simple bending elements into durable, zero energy actuators capable of complex and reversible transformations, offering a potential route toward self shaping facade elements for sustainable kinetic architecture.</p></div>","PeriodicalId":72270,"journal":{"name":"Architectural intelligence","volume":"5 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2026-01-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s44223-025-00110-6.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145898472","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"AI for green and active healthy futures in architecture","authors":"Philip F. Yuan","doi":"10.1007/s44223-025-00108-0","DOIUrl":"10.1007/s44223-025-00108-0","url":null,"abstract":"","PeriodicalId":72270,"journal":{"name":"Architectural intelligence","volume":"4 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-12-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s44223-025-00108-0.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145887110","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}