Cumincad : CUMINCAD Papers : Search Results

CumInCAD is a Cumulative Index about publications in Computer Aided Architectural Design
supported by the sibling associations ACADIA, CAADRIA, eCAADe, SIGraDi, ASCAAD and CAAD futures

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_id	sigradi2023_65
id	sigradi2023_65
authors	Cheung, Lok Hang, Dall'Asta, Juan Carlos and Di Marco, Giancarlo
year	2023
title	Exploring Large Language Model as a Design Partner through Verbal and Non-verbal Conversation in Architectural Design Process
source	García Amen, F, Goni Fitipaldo, A L and Armagno Gentile, Á (eds.), Accelerated Landscapes - Proceedings of the XXVII International Conference of the Ibero-American Society of Digital Graphics (SIGraDi 2023), Punta del Este, Maldonado, Uruguay, 29 November - 1 December 2023, pp. 1059–1070
summary	This paper proposes a framework for applying Large Language Models (LLM) as a design partner in architectural design processes instead of a passive question-answering machine. The proposed design framework integrates LLM and Conversation Theory (CT) into a standard parametric design tool for architectural designers. The program establishes an ongoing conversation with the designer through verbal and non-verbal feedback by tracking brain activity and modelling commands. The program can collect conversation data for fine-tuning, thus progressively improving conversation effectiveness. The paper contributes to the knowledge area of architectural design by introducing a novel approach to integrating LLM and CT into the design process, simulated as a proof-of-concept pilot study within a commonly used design software.
keywords	Large Language Model, Human-Computer Interaction, Conversation Theory, Architectural Design Process
series	SIGraDi
email
last changed	2024/03/08 14:08

_id	sigradi2023_439
id	sigradi2023_439
authors	Chornobai, Sara Regiane, Paiva Ponzio, Angelica, Miotto Bruscato, Léia and Machado Fagundes, Cristian Vinicius
year	2023
title	Fostering Sustainability in the Early Stages of the Architectural Design process: a Creative Exploration of AI Generative Models
source	García Amen, F, Goni Fitipaldo, A L and Armagno Gentile, Á (eds.), Accelerated Landscapes - Proceedings of the XXVII International Conference of the Ibero-American Society of Digital Graphics (SIGraDi 2023), Punta del Este, Maldonado, Uruguay, 29 November - 1 December 2023, pp. 831–842
summary	The field of architecture is experiencing transformative changes with the rise of Artificial Intelligence (AI). This study investigates the use of generative models like Large Language Models (LLM) and Generative Diffusion Models (GDM) in architectural design, focusing on sustainability. Utilizing the concept of “active human agency”, the research evaluates tools like DALL-E 2 (Bing) and ChatGPT (GPT-4) for creating environmentally responsive references in the early phases of the design process. Employing an explorative and qualitative methodology, the investigation includes architectural characteristics of climatic archetypes and concepts related to architecture-biology, applied to different environmental contexts. Initial findings reveal the AI potential in creating environmentally responsive references, with certain limitations in specific interactions and interpretations. The conclusion emphasizes these tools as collaborative aids in early design stages, and underscores the importance of "active human agency" for meaningful, responsible results, contributing to sustainability in early architectural design processes.
keywords	Artificial Intelligence, Generative Models, Architectural Design Process, Sustainability, Active Human Agency.
series	SIGraDi
email
last changed	2024/03/08 14:07

_id	ecaade2023_197
id	ecaade2023_197
authors	Kim, Frederick Chando, Johanes, Mikhael and Huang, Jeffrey
year	2023
title	Text2Form Diffusion: Framework for learning curated architectural vocabulary
doi	https://doi.org/10.52842/conf.ecaade.2023.1.079
source	Dokonal, W, Hirschberg, U and Wurzer, G (eds.), Digital Design Reconsidered - Proceedings of the 41st Conference on Education and Research in Computer Aided Architectural Design in Europe (eCAADe 2023) - Volume 1, Graz, 20-22 September 2023, pp. 79–88
summary	Stepping towards the machine learning age in architecture, many architects and researchers have developed creative ways of utilizing machine learning with domain-specific architectural datasets in recent years. With the rising popularity of large language-based text-to-image models, architects have relied on different strategies for developing the prompt to create satisfactory images representing architecture, which lessens the agency of the architects in the process. We explore alternative ways of working with such models and put forward the role of designers through the fine-tuning process. This research proses a fine-tuning framework of a pre-trained language model, namely Stable Diffusion, with a dataset of formal architectural vocabularies towards developing a new way of understanding architectural form through human-machine collaboration. This paper explores the creation of an annotation system for machines to learn and understand architectural forms. The results showcased a promising method combining different formal characteristics for architectural form generation and ultimately contributing to the discourse of form and language in architecture in the age of large deep learning models.
keywords	machine learning, diffusion model, architectural form, text-to-architecture
series	eCAADe
email
last changed	2023/12/10 10:49

_id	ijac202321202
id	ijac202321202
authors	Koehler, Daniel
year	2023
title	More than anything: Advocating for synthetic architectures within large-scale language-image models
source	International Journal of Architectural Computing 2023, Vol. 21 - no. 2, 242–255
summary	Large-scale language-image (LLI) models have the potential to open new forms of critical practice through architectural research. Their success enables designers to research within discourses that are profoundly connected to the built environment but did not previously have the resources to engage in spatial research. Although LLI models do not generate coherent building ensembles, they offer an esthetic experience of an AI infused design practice. This paper contextualizes diffusion models architecturally. Through a comparison of approaches to diffusion models in architecture, this paper outlines data-centric methods that allow architects to design critically using computation. The design of text-driven latent spaces extends the histories of typological design to synthetic environments including non-building data into an architectural space. More than synthesizing quantic ratios in various arrangements, the architect contributes by assessing new categorical differences into generated work. The architects’ creativity can elevate LLI models with a synthetic architecture, nonexistent in the data sets the models learned from.
keywords	diffusion models, large-scale language-image models, data-centric, access to data, discrete computation, critical computational practice, synthetic architecture
series	journal
last changed	2024/04/17 14:30

_id	ijac202321203
id	ijac202321203
authors	Kudless, Andrew
year	2023
title	Hierarchies of bias in artificial intelligence architecture: Collective, computational, and cognitive
source	International Journal of Architectural Computing 2023, Vol. 21 - no. 2, 256–279
summary	This paper examines the prevalence of bias in artificial intelligence text-to-image models utilized in the architecture and design disciplines. The rapid pace of advancements in machine learning technologies, particularly in text-to-image generators, has significantly increased over the past year, making these tools more accessible to the design community. Accordingly, this paper aims to critically document and analyze the collective, computational, and cognitive biases that designers may encounter when working with these tools at this time. The paper delves into three hierarchical levels of operation and investigates the possible biases present at each level. Starting with the training data for large language models (LLM), the paper explores how these models may create biases privileging English-language users and perspectives. The paper subsequently investigates the digital materiality of models and how their weights generate specific aesthetic results. Finally, the report concludes by examining user biases through their prompt and image selections and the potential for platforms to perpetuate these biases through the application of user data during training.
keywords	Bias in artificial intelligence, language bias, aesthetic bias, latent diffusion models, digital materiality
series	journal
last changed	2024/04/17 14:30

_id	ecaade2023_284
id	ecaade2023_284
authors	Turhan, Gozde Damla
year	2023
title	Life Cycle Assessment for the Unconventional Construction Materials in Collaboration with a Large Language Model
doi	https://doi.org/10.52842/conf.ecaade.2023.2.039
source	Dokonal, W, Hirschberg, U and Wurzer, G (eds.), Digital Design Reconsidered - Proceedings of the 41st Conference on Education and Research in Computer Aided Architectural Design in Europe (eCAADe 2023) - Volume 2, Graz, 20-22 September 2023, pp. 39–48
summary	In this paper, developing an online tool for the Life Cycle Assessment (LCA) of unconventional construction materials in collaboration with Large Language Models (LLMs) is proposed. The LCA provides information on the environmental impact of a product throughout its entire life cycle, from the extraction of raw materials to disposal or recycling. The LLMs are neural network architectures, typically utilizing variants of recurrent neural networks such as the transformer, which are trained on large bodies of textual data using techniques such as pre-training and fine-tuning. This study focuses on the use of bacterial cellulose composites as a biobased unconventional construction material. The methodology of developing an LLM-aided LCA tool is divided into five stages: Defining the functional unit; identifying the life cycle stages; collecting environmental and social impact data; interpreting and evaluating; developing a web-based tool. The results of this study have shown that the designers can incorporate sustainable thinking in the design process by using LLMs integrated to LCA, ultimately contributing to a more sustainable future against the impacts of the Anthropocene. Overall, the outcomes demonstrated the value of human-computer interaction (HCI) as a tool for exploring new possibilities with biobased materials and for inspiring designers to reconsider the material evaluation in their work. Future studies can delve into the integration of this tool into building information modeling software or computational design software in order to perform LCA for 3D structures. Different scales of such applications in design practices, such as fashion design, product design or service design can also be conducted by questioning how LCA can be combined with LLMs to leverage novel sustainable design solutions.
keywords	Machine Learning (ML), Large Language Models (LLMs), Human-computer interaction (HCI), Life Cycle Assessment (LCA)
series	eCAADe
email
last changed	2023/12/10 10:49

_id	acadia23_v2_430
id	acadia23_v2_430
authors	Vaidhyanathan, Vishal; T R, Radhakrishnan; Garcia del Castillo Lopez, Jose Luis
year	2023
title	Spacify: A Generative Framework for Spatial Comprehension, Articulation and Visualization using Large Language Models (LLMs) and eXtended Reality (XR)
source	ACADIA 2023: Habits of the Anthropocene: Scarcity and Abundance in a Post-Material Economy [Volume 2: Proceedings of the 43rd Annual Conference for the Association for Computer Aided Design in Architecture (ACADIA) ISBN 979-8-9891764-0-3]. Denver. 26-28 October 2023. edited by A. Crawford, N. Diniz, R. Beckett, J. Vanucchi, M. Swackhamer 430-443.
summary	Spatial design, the thoughtful planning and creation of built environments, typically requires advanced technical knowledge and visuospatial skills, making it largely exclusive to professionals like architects, interior designers, and urban designers. This exclusivity limits non-experts' access to spatial design, despite their ability to describe requirements and suggestions in natural language. Recent advancements in generative artificial intelligence (AI), particularly large language models (LLMs), and extended reality, (XR) offer the potential to address this limitation. This paper introduces Spacify (Figure 1), a framework that utilizes the generalizing capabilities of LLMs, 3D data-processing, and XR interfaces to create an immersive medium for language-driven spatial understanding, design, and visualization for non-experts. This paper describes the five components of Spacify: External Data, User Input, Spatial Interface, Large Language Model, and Current Spatial Design; which enable the use of generative AI models in a) question/ answering about 3D spaces with reasoning, b) (re)generating 3D spatial designs with natural language prompts, and c) visualizing designed 3D spaces with natural language descriptions. An implementation of Spacify is demonstrated via an XR smartphone application, allowing for an end-to-end, language-driven interior design process. User survey results from non-experts redesigning their spaces in 3D using this application suggest that Spacify can make spatial design accessible using natural language prompts, thereby pioneering a new realm of spatial design that is naturally language-driven.
series	ACADIA
type	paper
email
last changed	2024/12/20 09:12

_id	ascaad2023_090
id	ascaad2023_090
authors	Busbait, Omar; Reinhardt, Dagmar; Globa, Anastasia
year	2023
title	Human-Robot Craft Transfer: Learning from Nabateans Carving Out Methods,Techniques, and Tools
source	C+++: Computation, Culture, and Context – Proceedings of the 11th International Conference of the Arab Society for Computation in Architecture, Art and Design (ASCAAD), University of Petra, Amman, Jordan [Hybrid Conference] 7-9 November 2023, pp. 154-165.
summary	Traditional methods of carving trenches have been used by Nabateans in quarries locations for centuries, including carving out a large block out of a mass solid of sandstone and continuing carving out processes. This research explores the strategies for sculpting and the structural feasibility needed to assist methods of design generation in tangent. It traces tools and processes used in cutting large blocks for stone quarries and rock-cut buildings for efficient and sustainable methods to train an industrial robot. The research aims to support a revival of the historical global phenomenon approach of carved-out buildings through advanced technologies for fabrication. Through knowledge derived from traditional stone cutting, robotic subtractive/additive processes and robotic fabrication and assembly, the paper aims to develop case studies. By reviewing the current state of the art in digital sandstone carving, and prototyping, the paper discusses craftsmanship and technological development through the concept of carved-out in solid, applied in the context of advanced fabrication and robotic adaptation. This paper reports on a parallel study of the traditional methods of cutting a block out of a solid from one side and the robot adoption of the ancient tools and methods by testing processes iteratively; first through manual investigation and secondly through robotic simulation and tooling with Styrofoam as homogeneous material replacement. The paper discusses the results of digital fabrication and novel knowledge for the human–robot craft transfer.
series	ASCAAD
email
last changed	2024/02/13 14:40

_id	architectural_intelligence2023_18
id	architectural_intelligence2023_18
authors	Lars Spuybroek
year	2023
title	Matter and image: the pharmacology of architecture
doi	https://doi.org/https://doi.org/10.1007/s44223-023-00035-y
source	Architectural Intelligence Journal
summary	In the history of technologies and materials the transfer from soft to hard plays a central role. From a dialectic point of view it seems to be a clear-cut matter of one overpowering the other, yet conceptually things are more convoluted. What we call the chiastic model of history is driven by the exchange of empowerings where the one inhabits the other. By taking the most antithetical examples of materiality from architectural history, the plastic and the lithic, we begin to understand the psychological aspects of this exchange: a history of dreams, imagination and even hallucination. The technologies involving the plastic offer an enormous array of such imagery, which we start to analyze as part of a fundamental aspect of technology itself. Using the notion of the pharmakon, as developed by Derrida and Stiegler, we study its ambiguities: technology by its nature is both remedy and poison, cure and addiction. Accepting this ambivalence is the explicit goal of pharmacology, which makes the history of soft and hard one of prosthetic extension as much as of mimetic absorption. We will be guided by two architectural fantasists to investigate the what we call the pharmacology of architecture, J. G. Ballard’s fantasy of a house automaton in the case of the plastic, and G. B. Piranesi’s hallucinations of a reversed archeology in that of the lithic.
series	Architectural Intelligence
email
last changed	2025/01/09 15:03

_id	acadia23_v3_49
id	acadia23_v3_49
authors	A. Noel, Vernelle; Dortdivanlioglu, Hayri
year	2023
title	Text-to-image generators: Semiotics, Semantics, Syntax, and Society
source	ACADIA 2023: Habits of the Anthropocene: Scarcity and Abundance in a Post-Material Economy [Volume 3: Proceedings of the 43rd Annual Conference for the Association for Computer Aided Design in Architecture (ACADIA) ISBN 979-8-9891764-1-0]. Denver. 26-28 October 2023. edited by A. Crawford, N. Diniz, R. Beckett, J. Vanucchi, M. Swackhamer 24-32.
summary	Text-to-image generators, such as Midjourney, DALL-E, and Stable Diffusion, are becoming increasingly popular. These generators, whose models are trained on large datasets of text-image pairs, often scraped from the web, take text prompts as input, and use them to generate images—text-to-image prompting. In this visual essay, we raise questions about the entanglement of semiotics, semantics, syntax, and society in these text-to-image generator tools. We are intrigued by how these technologies are “intrawoven” with social and cultural contexts. How are their constructions and presentations reconfigurations? How do, or might they, inform pedagogy, theory, methods, and our publics? To explore these questions, we entered six prompts related to the built environment in six different languages, eight months apart in Midjourney (“Midjourney” n.d.). The generated images (Figure 1), require that we ask deep questions of each image, in comparison with each other, across each group of four, and across time (eight months apart). We argue that text-to-image generators call for a rigorous exploration of semiotics, semantics, syntax, and the society, with implications for pedagogy, theory-building, methodologies, and public enlightenment. Furthermore, we assert that these tools can facilitate pertinent questions about the relationships between technology and society. This is just the beginning. For now, we have questions.
series	ACADIA
type	field note
email
last changed	2024/04/17 13:59

_id	ecaade2023_71
id	ecaade2023_71
authors	Austern, Guy, Yosifof, Roei and Fisher-Gewirtzman, Dafna
year	2023
title	A Dataset for Training Machine Learning Models to Analyze Urban Visual Spatial Experience
doi	https://doi.org/10.52842/conf.ecaade.2023.2.781
source	Dokonal, W, Hirschberg, U and Wurzer, G (eds.), Digital Design Reconsidered - Proceedings of the 41st Conference on Education and Research in Computer Aided Architectural Design in Europe (eCAADe 2023) - Volume 2, Graz, 20-22 September 2023, pp. 781–790
summary	Previous studies have described the effects of urban attributes such as the Spatial Openness Index (SOI) on pedestrians’ experience. SOI uses 3-dimensional ray casting to quantify the volume of visible space from a single viewpoint. The higher the SOI value, the higher the perceived openness and the lower the perceived density. However, the ray casting simulation on an urban-sized sampling grid is computationally intensive, making this method difficult to use in real-time design tools. Convolutional Neural Networks (CNN), have excellent performance in computer vision in image processing applications. They can be trained to predict the SOI analysis for large urban fabrics in real-time. However, these supervised learning models need a substantial amount of labeled data to train on. For this purpose, we developed a method to generate a large series of height maps and SOI maps of urban fabrics in New York City and encoded them as images using colour information. These height map - SOI analysis image pairs can be used as training data for a CNN to provide rapid, precise visibility simulations on an urban scale.
keywords	Visibility Analysis, Machine Learning, CNN, Perceived Density
series	eCAADe
email
last changed	2023/12/10 10:49

_id	sigradi2023_446
id	sigradi2023_446
authors	Chalmes Braga, Karine, Borda Almeida da Silva, Adriane, Benedetti Santiago, Gustavo, da Costa Ferreira, Aline, dos Santos Nunes, Cristiane and Kruger da Costa, Vinicius
year	2023
title	Heritage goes to School: Technological Reproducibility, Tangible Interfaces and Cultural Inclusion for Individuals with Visual Impairments
source	García Amen, F, Goni Fitipaldo, A L and Armagno Gentile, Á (eds.), Accelerated Landscapes - Proceedings of the XXVII International Conference of the Ibero-American Society of Digital Graphics (SIGraDi 2023), Punta del Este, Maldonado, Uruguay, 29 November - 1 December 2023, pp. 1621–1632
summary	This work reports on the development of assistive resources aimed at representing and interpreting the architectural language of a cultural heritage that houses a museum. The resources are designed to enhance the inclusion of visually impaired individuals through a codesign approach, involving this group in the development process. The tactile models produced represent the three-dimensionality of each room within the house, highlighting its proportions, and serve as fitting elements in a tactile map, which corresponds to the first floor of the building. These materials were designed to interact on a tangible table located in the Museum. The three-dimensional models include a fiducial on their base, which, when inserted into the tactile map, placed on the tangible table, triggers an audio description. The integration of these resources facilitates communication through a multi-format and multisensory approach, contributing to the inclusion of diverse audiences and promoting the greater access to culture and knowledge.
keywords	Codesign, Tactile Models, Tangible User Interface, Museum, Heritage
series	SIGraDi
email
last changed	2024/03/08 14:09

_id	acadia23_v1_122
id	acadia23_v1_122
authors	Crawford, Assia
year	2023
title	Mycelium Making: An exploration in Growing Modular Interiors
source	ACADIA 2023: Habits of the Anthropocene: Scarcity and Abundance in a Post-Material Economy [Volume 1: Projects Catalog of the 43rd Annual Conference of the Association of Computer Aided Design in Architecture (ACADIA) ISBN 979-8-9860805-8-1]. Denver. 26-28 October 2023. edited by A. Crawford, N. Diniz, R. Beckett, J. Vanucchi, M. Swackhamer 122-127.
summary	The project was developed as part of an MArch Architecture design studio that looked at emerging bio-degradable living materials in the form of mycelium bio-composites as a way of manufacturing temporary structures. The project introduced students to laboratory methods for material development and bio-material cultivation. Students were asked to consider the implications of designing with a material that has agency and needs. The studio explored what it means to “make kin” (Haraway 2016) on a planet that has reached a tipping point. It approached the topic from the assumption that the breakdown of existing economic models and resource scarcity offers potent ground for new forms of space making to emerge. The studio looked to nature’s ability to respond to environmental stimuli and design constraints. Students harnessed advances in our scientific understanding to cultivate an architectural language that captures the transient and unstable nature of this new family of biomaterials
series	ACADIA
type	project
email
last changed	2024/04/17 13:58

_id	ijac202321412
id	ijac202321412
authors	Damla Turhan, Gozde; Guzden Varinlioglu and Murat Bengisu
year	2023
title	Bio-based material integration into computational form-finding tools by introducing tensile properties in the case of bacterial cellulose-based composites
source	International Journal of Architectural Computing 2023, Vol. 21 - no. 4, 781-794
summary	Recent studies in digital design and fabrication processes focus on the potentials of using biological systems in nature as mathematical models or more recently as bio-based materials and composites in various applications. The reciprocal integration between mechanical and digital media for designing and manufacturing bio-based products is still open to development. The current digital form-finding scripts involve an extensive material list, although bio-based materials have not been fully integrated yet. This paper explores a customized form-finding process by suggesting a framework through mechanically informed material-based computation. Bacterial cellulose, an unconventional yet potential material for design, was explored across its biological growth, tensile properties, and the integration of datasets into digital form finding. The initial results of the comparison between digital form finding with conventional materials versus mechanically informed digital form finding revealed a huge difference in terms of both the resulting optimum geometry and the maximum axial forces that the geometry could actually handle. Although this integration is relatively novel in the literature, the proposed methodology has proven effective for enhancing the structural optimization process within digital design and fabrication and for bringing us closer to real-life applications. This approach allows conventional and limited material lists in various digital form finding and structural optimization scripts to cover novel materials once the quantitative mechanical properties are obtained. This method has the potential to develop into a commercial algorithm for a large number of bio-based and customized prototypes within the context of digital form finding of complex geometries.
keywords	Digital design, digital fabrication, structural optimization, form finding, bacterial cellulose
series	journal
last changed	2024/04/17 14:30

_id	caadria2023_446
id	caadria2023_446
authors	Guida, George
year	2023
title	Multimodal Architecture: Applications of Language in a Machine Learning Aided Design Process
doi	https://doi.org/10.52842/conf.caadria.2023.2.561
source	Immanuel Koh, Dagmar Reinhardt, Mohammed Makki, Mona Khakhar, Nic Bao (eds.), HUMAN-CENTRIC - Proceedings of the 28th CAADRIA Conference, Ahmedabad, 18-24 March 2023, pp. 561–570
summary	Recent advances in Natural Language Processing (NLP) and Diffusion Models (DMs) are leading to a significant change in the way architecture is conceived. With capabilities that surpass those of current generative models, it is now possible to produce an unlimited number of high-quality images (Dhariwal and Nichol 2021). This opens up new opportunities for using synthetic images and marks a new phase in the creation of multimodal 3D forms, central to architectural concept design stages. Presented here are three methodologies of generation of meaningful 2D and 3D designs, merging text-to-image diffusion models Stable Diffusion, and DALL-E 2 with computational methods. These allow designers to intuitively navigate through a multimodal feedback loop of information originating from language and aided by artificial intelligence tools. This paper contributes to our understanding of machine-augmented design processes and the importance of intuitive user interfaces (UI) in enabling new dialogues between humans and machines. Through the creation of a prototype of an accessible UI, this exchange of information can empower designers, build trust in these tools, and increase control over the design process.
keywords	Machine Learning, Diffusion Models, Concept Design, Semantics, User Interface, Design Agency
series	CAADRIA
email
last changed	2023/06/15 23:14

_id	sigradi2023_179
id	sigradi2023_179
authors	He, Mingyi, Su, Zixin, Xie, Yantong and Tu, Han
year	2023
title	Linguistic Landscape Research on the Relationship of Urban Language and Commerce Based on Large-scale Street View Images
source	García Amen, F, Goni Fitipaldo, A L and Armagno Gentile, Á (eds.), Accelerated Landscapes - Proceedings of the XXVII International Conference of the Ibero-American Society of Digital Graphics (SIGraDi 2023), Punta del Este, Maldonado, Uruguay, 29 November - 1 December 2023, pp. 1737–1748
summary	Urban linguistic landscape studies examine visible written languages in urban areas, revealing socio-economic information, such as the place identity of minority groups and the localization processes of exotic language varieties. However, studies mainly utilize qualitative analysis or small-scale image acquisition without integrating socioeconomic quantitative analysis. Our research aims to expand the quantitative indicators of linguistic landscape in city-wide scale to explore the relationship between detailed quantitative text analysis and consumer prices in spatially differentiated and temporally controlled urban street view images. We examine such correlation through street view images scrapping of historical Baidu Street View images, semantic segmentation machine learning tools, and Optical Character Recognition. Our study reveals a negative correlation between linguistic landscape indicators in street signage and consumption levels. This research provides quantitative methods for large-scale and repeatable study of linguistic landscape, introducing a novel perspective on linguistic landscape evidence for further urban economic development and urban segmentation.
keywords	Cultural landscapes and new technologies, Linguistic landscape, Machine learning, Urban economy, Street view
series	SIGraDi
email
last changed	2024/03/08 14:09

_id	acadia23_v2_508
id	acadia23_v2_508
authors	Koehler, Daniel; liu, Zidong
year	2023
title	Exploring Building Typologies and their Socioeconomic Contexts: Compositional Insights from Large-Scale-Text-to-Image Models
source	ACADIA 2023: Habits of the Anthropocene: Scarcity and Abundance in a Post-Material Economy [Volume 2: Proceedings of the 43rd Annual Conference for the Association for Computer Aided Design in Architecture (ACADIA) ISBN 979-8-9891764-0-3]. Denver. 26-28 October 2023. edited by A. Crawford, N. Diniz, R. Beckett, J. Vanucchi, M. Swackhamer 508-517.
summary	This study utilizes large-scale-text-to-image (LLI) models to investigate possibilities to describe building types data-centric. With the introduction of ""data-centric typologies"" we hope to challenge traditional architectural classification systems, while reviving type as an architectural strategy to link socio-economic contexts to the physical form of a place. By examining artificial intelligence (AI)-generated images of various city buildings, the research explores compositional characteristics, realism, and model limitations. We generated and segmented a synthetic dataset of 15,000 images into individual building segments, conducting a statistical analysis of compositional features across 500 cities. Despite dataset biases and limitations, our results indicate that synthetic databases provide a deeper analytical basis than traditional methods. The generated dataset alone paints forensic landscapes of locales that are not typically showcased. Particularly from a pedagogical perspective, data-centric investigations can serve as a valuable tool for illustrating the diversity of cities and living modes. The findings show that socio-economic attributes, like quality of life, are more closely tied to neighborhoods or projects than entire cities. Consequently, architectural typologies are most effective at a human-ori- ented scale, interfacing city with architecture.
series	ACADIA
type	paper
email
last changed	2024/12/20 09:13

_id	caadria2023_292
id	caadria2023_292
authors	Langenhan, Christoph, Bielski, Jessica, Ziegler, Christoph, Eisenstadt, Viktor, Althoff, Klaus-Dieter and Dengel, Andreas
year	2023
title	Cross-Disciplinary Semantic Building Fingerprints ‚ AI Knowledge Graphs to Store Topological Building Information Derived From Semantic Building Models (BIM) to Apply Methods of Artificial Intelligence (AI)
doi	https://doi.org/10.52842/conf.caadria.2023.1.129
source	Immanuel Koh, Dagmar Reinhardt, Mohammed Makki, Mona Khakhar, Nic Bao (eds.), HUMAN-CENTRIC - Proceedings of the 28th CAADRIA Conference, Ahmedabad, 18-24 March 2023, pp. 129–138
summary	The advancing digitalization in the building sector with the possibility to store and retrieve large amounts of data has the potential to digitally support planners with extensive design and construction information. Large amounts of semi-structured three-dimensional geometric data of buildings are usually available today, but the topological relationships are rarely explicitly described and thus not directly usable with computational methods of AI. To this end, we propose methods for indexing spatial configurations inspired by the similarity analysis of incomplete human fingerprints, since the early design stage of architectural design is characterized by incomplete information. For this, the topology of spatial configurations is extracted from Building Information Modelling (BIM) data and represented as graphs. In this paper, Semantic Building Fingerprints (SBFs) and Semantic Urban Fingerprints (SUFs), as well as use cases for AI methods are described.
keywords	Conceptual design, building information modelling, knowledge graph, artificial intelligence
series	CAADRIA
email
last changed	2023/06/15 23:14

_id	ecaade2023_256
id	ecaade2023_256
authors	Panya, David Stephen, Kim, Taehoon, Hyeongmo, Gu and Choo, Seungyeon
year	2023
title	Development of a Real-time BIM-VR Multi-Collaborative Design Environment
doi	https://doi.org/10.52842/conf.ecaade.2023.2.733
source	Dokonal, W, Hirschberg, U and Wurzer, G (eds.), Digital Design Reconsidered - Proceedings of the 41st Conference on Education and Research in Computer Aided Architectural Design in Europe (eCAADe 2023) - Volume 2, Graz, 20-22 September 2023, pp. 733–739
summary	Construction 4.0 technologies are transforming AEC designs and processes. Metaverses are developing rapidly and are being adopted in various industries as the future of the internet. The metaverse is an augmented world that allows individuals to penetrate and engage. Nevertheless, many people and businesses are still unaware of the potential uses of this technology. Virtual Reality, which is part of the fundamentals of the metaverse convergence with BIM technology, has improved in research and application in the AEC industry. The AEC industry has recently adopted both Building Information Modeling (BIM) and Virtual Reality (VR) as combined tools aiming at increasing collaboration ability among project team members as well as detecting clashes and correcting flaws before construction begins. This presents a multi-collaborative design as a potential requirement for BIM processes in the metaverse. The authors presented a platform that connects multiple VR environments through an online network to create a real-time-shared VR space that supports BIM models in real-time for collaborative design. The BIM-VR environment uses a game engine to create a session where individuals can upload their 3D BIM models in real-time which can be viewed by all users. This study presents that a collaborative environment that supports users and BIM models is the initial step to a BIM-based metaverse in the AEC industry.
keywords	BIM, Virtual Reality, Metaverse, Collaborative Design
series	eCAADe
email
last changed	2023/12/10 10:49

_id	acadia23_v2_560
id	acadia23_v2_560
authors	Saldana Ochoa, Karla; Huang, Lee-Su; Guo, Zifeng; Bokhari, Adil
year	2023
title	Playing Dimensions: Images / Models / Maps: Conceptualizing Architecture with Big Data and Artificial Intelligence
source	ACADIA 2023: Habits of the Anthropocene: Scarcity and Abundance in a Post-Material Economy [Volume 2: Proceedings of the 43rd Annual Conference for the Association for Computer Aided Design in Architecture (ACADIA) ISBN 979-8-9891764-0-3]. Denver. 26-28 October 2023. edited by A. Crawford, N. Diniz, R. Beckett, J. Vanucchi, M. Swackhamer 560-568.
summary	This article presents a novel architecture design workflow that explores the intersection of Big Data, Artificial Intelligence (AI), and storytelling by scraping, encoding, and mapping data, which can then be implemented through Virtual Reality (VR) and Augmented Reality (AR) technologies. In contrast to conventional approaches that consider AI solely as an optimization tool, this workflow embraces AI as an instrument for critical thinking and idea generation. Rather than creating new AI models, this workflow encourages architects to experiment with existing ones as part of their practice. The workflow revolves around the concept of ""Canonical architecture,"" where data-driven techniques serve to traverse dimensions and representations, encompassing text, images, and 3D objects. The data utilized consists of information specific to the project, gathered from social media posts, including both images and text, which provide insights into user needs and site charac- teristics. Additionally, roughly 9,000 3D models of architectural details extracted from 38 different architectural projects were used. The primary objective is to assist architects in developing a workflow that does not suggest starting from scratch or a tabula rasa, but to work with already hyper-connected objects, be it text, images, 3D models, et cetera. These conceptualizations can then be enacted in game engines and/or experimented with in AR/ VR platforms, while keeping their connections alive. Through this process, the framework aims to develop a sensibility of working with large amounts of data without losing focus, and letting the electric grounds of the internet help us in articulating projects.
series	ACADIA
type	paper
email
last changed	2024/12/20 09:13

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