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	ecaade2020_156
id	ecaade2020_156
authors	Hemmerling, Marco and Maris, Simon
year	2020
title	INTERCOM - A platform for collaborative design processes
doi	https://doi.org/10.52842/conf.ecaade.2020.2.173
source	Werner, L and Koering, D (eds.), Anthropologic: Architecture and Fabrication in the cognitive age - Proceedings of the 38th eCAADe Conference - Volume 2, TU Berlin, Berlin, Germany, 16-18 September 2020, pp. 173-180
summary	The INTERCOM project propounds a cloud-based collaboration platform for digital planning processes in architecture. The concept is based on an openBIM approach and ensures open access for all partners involved. At its core it provides IFC-based and model-related online tools for planning, communication and collaboration. The interaction with the model and the exchange with other project partners takes place in real-time via a model-related chat and BCF exports. In addition, the integration of e-learning modules (e.g. video tutorials, wikis, project documents) encourages problem solving through further education. Especially the integration of communication and collaboration tools is supposed to enhance the decision making throughout the design process and become a key factor for a successful and coordinated BIM process. Primarily INTERCOM has been developed as a prototype for teaching BIM in interdisciplinary teams. Subsequently, the application can also be adopted for professional practice. The paper evaluates previous experiences from BIM cloud teaching and discusses the conception and development of the proposed collaborative platform.
keywords	architecture curriculum; didactics; building information modeling (BIM); collaborative design process; common data environment (CDE)
series	eCAADe
email
last changed	2022/06/07 07:49

_id	ecaade2020_307
id	ecaade2020_307
authors	Caetano, Ines and Leitao, António
year	2020
title	When the Geometry Informs the Algorithm - A hybrid visual/textual programming framework for facade design
doi	https://doi.org/10.52842/conf.ecaade.2020.2.371
source	Werner, L and Koering, D (eds.), Anthropologic: Architecture and Fabrication in the cognitive age - Proceedings of the 38th eCAADe Conference - Volume 2, TU Berlin, Berlin, Germany, 16-18 September 2020, pp. 371-380
summary	Facade design is becoming increasingly complex, forcing architects to more frequently resort to analysis and optimization processes. However, these processes are time-consuming and require the coordination of multiple tools. Algorithmic Design (AD) has the potential to overcome these limitations through the use of algorithms implemented in Textual Programming Languages (TPLs) or Visual Programming Languages (VPLs). VPLs are more used in architecture due to their smoother learning curve and user-friendliness, but TPLs are better suited than VPLs for handling complex AD problems. To make TPLs more appealing to architects, we incorporated VPLs' features in the textual paradigm, namely, Visual Input Mechanisms (VIMs). In this paper, we propose an extension to an existing AD framework for the design exploration, analysis, and optimization of facades to support a TPL-based approach that handles VIMs.
keywords	Algorithmic Design; Facade Design; Textual Languages; Visual Input
series	eCAADe
email
last changed	2022/06/07 07:54

_id	sigradi2023_218
id	sigradi2023_218
authors	Leitao de Souza, Thiago, Gaspar Vereza, Carolina, Biz Medina, Jonatham, de Oliveira Milhm, Julio, Boner da Silva, Gabriel, Apostolo dos Santos Freire Salvador, Lucas, Ferreira Santos, Victor, Pousas Puig, Joao Gabriel and Henriques Monzatto de Mattos, Felipe
year	2023
title	Game Engines in the Historical Landscape: Interchangeable Layers of the City in Victor Meirelles and Henri Langerock's Panorama of Rio de Janeiro
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. 865–874
summary	This work is part of an ongoing research entitled “The 360- immersive: investigation, representation and digital immersion of Rio de Janeiro city during 19th and 20th centuries”, which aims at the theoretical, conceptual and instrumental analysis and discussion of the Panorama of Rio de Janeiro by Victor Meirelles and Henri Langerock in the Unity Game Engine. It presents an historical-interpretive method with application in Digital Graphics. To this end, it was considered necessary: to recreate the 360- immersive experience of the Panorama in real time; its context experience during the historical layers of 1885, 1915, 2020, and a fourth combination between previous layers, based in specific geometric models; programming in C# the movement of the player-observer, scenes, interaction with objects and the player's own navigation through the game menu.
keywords	Virtual Reality, City History, Immersive Experience in 360°, Panorama of Rio de Janeiro, Game Engines.
series	SIGraDi
email
last changed	2024/03/08 14:07

_id	acadia20_178
id	acadia20_178
authors	Meeran, Ahmed; Conrad Joyce, Sam
year	2020
title	Machine Learning for Comparative Urban Planning at Scale: An Aviation Case Study
doi	https://doi.org/10.52842/conf.acadia.2020.1.178
source	ACADIA 2020: Distributed Proximities / Volume I: Technical Papers [Proceedings of the 40th Annual Conference of the Association of Computer Aided Design in Architecture (ACADIA) ISBN 978-0-578-95213-0]. Online and Global. 24-30 October 2020. edited by B. Slocum, V. Ago, S. Doyle, A. Marcus, M. Yablonina, and M. del Campo. 178-187.
summary	Aviation is in flux, experiencing 5.4% yearly growth over the last two decades. However, with COVID-19 aviation was hard hit. This, along with its contribution to global warming, has led to louder calls to limit its use. This situation emphasizes how urban planners and technologists could contribute to understanding and responding to this change. This paper explores a novel workflow of performing image-based machine learning (ML) on satellite images of over 1,000 world airports that were algorithmically collated using European Space Agency Sentinel2 API. From these, the top 350 United States airports were analyzed with land use parameters extracted around the airport using computer vision, which were mapped against their passenger footfall numbers. The results demonstrate a scalable approach to identify how easy and beneficial it would be for certain airports to expand or contract and how this would impact the surrounding urban environment in terms of pollution and congestion. The generic nature of this workflow makes it possible to potentially extend this method to any large infrastructure and compare and analyze specific features across a large number of images while being able to understand the same feature through time. This is critical in answering key typology-based urban design challenges at a higher level and without needing to perform on-ground studies, which could be expensive and time-consuming.
series	ACADIA
type	paper
email
last changed	2023/10/22 12:06

_id	caadria2020_313
id	caadria2020_313
authors	Sanatani, Rohit Priyadarshi
year	2020
title	A Machine-Learning driven Design Assistance Framework for the Affective Analysis of Spatial Enclosures
doi	https://doi.org/10.52842/conf.caadria.2020.1.741
source	D. Holzer, W. Nakapan, A. Globa, I. Koh (eds.), RE: Anthropocene, Design in the Age of Humans - Proceedings of the 25th CAADRIA Conference - Volume 1, Chulalongkorn University, Bangkok, Thailand, 5-6 August 2020, pp. 741-750
summary	There is a growing research direction that adopts an empirical approach to affective response in space, and aims at generating bodies of quantitative data regarding the correlations between spatial features and emotional states. This paper demonstrates a machine-learning driven computational framework that draws upon training data sets to predict the 'affective impact' of designed enclosures. For demonstration, it has been scripted as a Rhinoceros + Grasshopper based design tool that uses existing training data collected by the author. The data comprises of the spatial parameters of Enclosure Volume (V), Length/Width ratio (P) and Window Area/Total Internal Surface Area ratio (D) - and the corresponding emotional parameters of Valence and Arousal. The test values of these parameters are computed by defining the components of the test enclosure (walls, windows, floors and ceilings) in the script. Nonlinear regression components are run on the training datasets and the test input data is used to compute and display the real time predicted affective state on the circumplex model of affect.
keywords	Affective Analysis; Affective Computing; Design Assistance; Machine Learning; Spatial Enclosures
series	CAADRIA
email
last changed	2022/06/07 07:56

_id	acadia20_290
id	acadia20_290
authors	Stuart-Smith, Robert; Danahy, Patrick; Revelo La Rotta, Natalia
year	2020
title	Topological and Material Formation
doi	https://doi.org/10.52842/conf.acadia.2020.1.290
source	ACADIA 2020: Distributed Proximities / Volume I: Technical Papers [Proceedings of the 40th Annual Conference of the Association of Computer Aided Design in Architecture (ACADIA) ISBN 978-0-578-95213-0]. Online and Global. 24-30 October 2020. edited by B. Slocum, V. Ago, S. Doyle, A. Marcus, M. Yablonina, and M. del Campo. 290-299.
summary	Extrusion-based additive manufacturing (AM) is gaining traction in the construction industry, offering lower environmental and economic costs through reductions in material and production time. AM designs achieve these reductions by increasing topological and geometric complexity, and through variable material distribution via custom-programmed robot tool paths. Limited approaches are available to develop AM building designs within a topologically free design search or to leverage material affects relative to structural performance. Established methods such as topological structural optimization (TSO) operate primarily within design rationalization, demonstrating less formal or aesthetic diversity than agent-based methods that exhibit behavioral character. While material-extrusion gravitational affects have been explored in AM research using viscous materials such as concrete and ceramics, established methods are not sufficiently integrated into simulation and structural analysis workflows. A novel three-part method is proposed for the design and simulation of extrusion-based AM that includes topoForm, an evolutionary multi-agent software capable of generating diverse topological designs; matForm, an agent-based AM robot tool-path generator that is geometrically agnostic and adapts material effects to local structural and geometric data; and matSim, a material-physics simulation environment that enables high-resolution AM material effects to be simulated and structurally and aesthetically analyzed. The research enables designers to incorporate and simulate material behavior prior to fabrication and produce instructions suitable for industrial robot AM. The approach is demonstrated in the generative design of four AM column-like elements.
series	ACADIA
type	paper
email
last changed	2023/10/22 12:06

_id	caadria2020_234
id	caadria2020_234
authors	Zhang, Hang and Blasetti, Ezio
year	2020
title	3D Architectural Form Style Transfer through Machine Learning
doi	https://doi.org/10.52842/conf.caadria.2020.2.659
source	D. Holzer, W. Nakapan, A. Globa, I. Koh (eds.), RE: Anthropocene, Design in the Age of Humans - Proceedings of the 25th CAADRIA Conference - Volume 2, Chulalongkorn University, Bangkok, Thailand, 5-6 August 2020, pp. 659-668
summary	In recent years, a tremendous amount of progress is being made in the field of machine learning, but it is still very hard to directly apply 3D Machine Learning on the architectural design due to the practical constraints on model resolution and training time. Based on the past several years' development of GAN (Generative Adversarial Network), also the method of spatial sequence rules, the authors mainly introduces 3D architectural form style transfer on 2 levels of scale (overall and detailed) through multiple methods of machine learning algorithms which are trained with 2 types of 2D training data set (serial stack and multi-view) at a relatively decent resolution. By exploring how styles interact and influence the original content in neural networks on the 2D level, it is possible for designers to manually control the expected output of 2D images, result in creating the new style 3D architectural model with a clear designing approach.
keywords	3D; Form Finding; Style Transfer; Machine Learning; Architectural Design
series	CAADRIA
email
last changed	2022/06/07 07:57

_id	acadia20_228
id	acadia20_228
authors	Alawadhi, Mohammad; Yan, Wei
year	2020
title	BIM Hyperreality
doi	https://doi.org/10.52842/conf.acadia.2020.1.228
source	ACADIA 2020: Distributed Proximities / Volume I: Technical Papers [Proceedings of the 40th Annual Conference of the Association of Computer Aided Design in Architecture (ACADIA) ISBN 978-0-578-95213-0]. Online and Global. 24-30 October 2020. edited by B. Slocum, V. Ago, S. Doyle, A. Marcus, M. Yablonina, and M. del Campo. 228-236.
summary	Deep learning is expected to offer new opportunities and a new paradigm for the field of architecture. One such opportunity is teaching neural networks to visually understand architectural elements from the built environment. However, the availability of large training datasets is one of the biggest limitations of neural networks. Also, the vast majority of training data for visual recognition tasks is annotated by humans. In order to resolve this bottleneck, we present a concept of a hybrid system—using both building information modeling (BIM) and hyperrealistic (photorealistic) rendering—to synthesize datasets for training a neural network for building object recognition in photos. For generating our training dataset, BIMrAI, we used an existing BIM model and a corresponding photorealistically rendered model of the same building. We created methods for using renderings to train a deep learning model, trained a generative adversarial network (GAN) model using these methods, and tested the output model on real-world photos. For the specific case study presented in this paper, our results show that a neural network trained with synthetic data (i.e., photorealistic renderings and BIM-based semantic labels) can be used to identify building objects from photos without using photos in the training data. Future work can enhance the presented methods using available BIM models and renderings for more generalized mapping and description of photographed built environments.
series	ACADIA
type	paper
email
last changed	2023/10/22 12:06

_id	ecaade2020_089
id	ecaade2020_089
authors	Ardic, Sabiha Irem, Kirdar, Gulce and Lima, Angela Barros
year	2020
title	An Exploratory Urban Analysis via Big Data Approach: Eindhoven Case - Measuring popularity based on POIs, accessibility and perceptual quality parameters
doi	https://doi.org/10.52842/conf.ecaade.2020.2.309
source	Werner, L and Koering, D (eds.), Anthropologic: Architecture and Fabrication in the cognitive age - Proceedings of the 38th eCAADe Conference - Volume 2, TU Berlin, Berlin, Germany, 16-18 September 2020, pp. 309-318
summary	The cities are equipped with the data as a result of the individuals' sharings and application usage. This significant amount of data has the potential to reveal relations and support user-centric decision making. The focus of the research is to examine the relational factors of the neighborhoods' popularity by implementing a big data approach to contribute to the problem of urban areas' degradation. This paper presents an exploratory urban analysis for Eindhoven at the neighborhood level by considering variables of popularity: density and diversity of points of interest (POI), accessibility, and perceptual qualities. The multi-sourced data are composed of geotagged photos, the location and types of POIs, travel time data, and survey data. These different datasets are evaluated using BBN (Bayesian Belief Network) to understand the relationships between the parameters. The results showed a positive and relatively high connection between popularity - population change, accessibility by walk - density of POIs, and the feeling of safety - social cohesion. For further studies, this approach can contribute to the decision-making process in urban development, specifically in real estate and tourism development decisions to evaluate the land prices or the hot-spot touristic places.
keywords	big data approach; neighborhood analysis; popularity; point of interest (POI); accessibility; perceptual quality
series	eCAADe
email
last changed	2022/06/07 07:54

_id	sigradi2020_783
id	sigradi2020_783
authors	Asevedo, Laíze Fernandes de; Medeiros, Deisyanne Câmara A. de; Barbosa, Gabriele Mislaine; Silva, Marylia Ketyllee
year	2020
title	Parametric modeling as a supporting tool for teaching in a technical drawing course
source	SIGraDi 2020 [Proceedings of the 24th Conference of the Iberoamerican Society of Digital Graphics - ISSN: 2318-6968] Online Conference 18 - 20 November 2020, pp. 783-790
summary	Despite the complexity of parametric modeling, used potentially to generate non-standard geometries, this paper presents a simple approach to adopt this tool as a support for teaching technical drawing contents. This experimental study was applied in a technical and high school education context, focusing on three subjects: 1) irregular polyhedra, 2) points in descriptive geometry, and 3) line in descriptive geometry. Exercises were implemented before and after the parametric experience with students, and the answers to both scenarios were compared. The results addressed to the efficiency of parametric modeling as a supporting tool in the teaching/learning process.
keywords	Parametric modeling, Didactic experiment, Technical drawing course, Irregular polyhedra, Descriptive geometry
series	SIGraDi
email
last changed	2021/07/16 11:53

_id	ecaade2020_115
id	ecaade2020_115
authors	Azambuja Varela, Pedro and Sousa, José Pedro
year	2020
title	Liquid Stereotomy - the Tamandua Vault
doi	https://doi.org/10.52842/conf.ecaade.2020.2.361
source	Werner, L and Koering, D (eds.), Anthropologic: Architecture and Fabrication in the cognitive age - Proceedings of the 38th eCAADe Conference - Volume 2, TU Berlin, Berlin, Germany, 16-18 September 2020, pp. 361-370
summary	A renewed interest in stereotomy, narrowly entwined with digital technologies, has allowed for the recovery and proposal of new techniques and expressions in this building approach. A new classification scheme for stereotomy research allows for the framing of various aspects related to this discipline, including a newly developed fabrication system specially tailored for the wedge-shaped voussoirs. This fabrication system is based in a reusable mould which may assume an infinite number of geometries, avoiding the wasteful discarding of material found in subtractive strategies. The usage of a mould also allows for more sustainable materials to be employed, catering to current challenges. The strategies subject for demonstration in this project rely on various bottom-up approaches, which involve particle physic simulations such as a hanging model to compute an optimal stereo-funicular shape, or spring mechanisms to find optimal coplanar solutions. The proposed mechanisms work in a parametric algorithmically environment, able to handle dozens of uniquely different voussoirs at the same time. Together with the automatic translation to fabrication data, the proposed shape complexity would hardly be built with classic tools. The Tamandua Vault project has the purpose of exemplifying the possibilities of an updated stereotomy, while its design demonstrates current strategies that may be employed in the resolution of complex geometrical problems and bespoke fabrication of construction components for stereotomy.
keywords	stereotomy; digital design; digital fabrication; compression; sustainability
series	eCAADe
email
last changed	2022/06/07 07:54

_id	acadia20_120
id	acadia20_120
authors	Barsan-Pipu, Claudiu; Sleiman, Nathalie; Moldovan, Theodor
year	2020
title	Affective Computing for Generating Virtual Procedural Environments Using Game Technologies
doi	https://doi.org/10.52842/conf.acadia.2020.2.120
source	ACADIA 2020: Distributed Proximities / Volume I: Technical Papers [Proceedings of the 40th Annual Conference of the Association of Computer Aided Design in Architecture (ACADIA) ISBN 978-0-578-95213-0]. Online and Global. 24-30 October 2020. edited by B. Slocum, V. Ago, S. Doyle, A. Marcus, M. Yablonina, and M. del Campo. 120-129.
summary	Architects have long sought to create spaces that can relate to or even induce specific emotional conditions in their users, such as states of relaxation or engagement. Dynamic or calming qualities were given to these spaces by controlling form, perspective, lighting, color, and materiality. The actual impact of these complex design decisions has been challenging to assess, from both quantitative and qualitative standpoints, because neural empathic responses, defined in this paper by feature indexes (FIs) and mind indexes (MIs), are highly subjective experiences. Recent advances in the fields of virtual procedural environments (VPEs) and virtual reality (VR), supported by powerful game engine (GE) technologies, provide computational designers with a new set of design instruments that, when combined with brain-computing interfacing (BCI) and eye-tracking (E-T) hardware, can be used to assess complex empathic reactions. As the COVID-19 health crisis showed, virtual social interaction becomes increasingly relevant, and the social catalytic potential of VPEs can open new design possibilities. The research presented in this paper introduces the cyber-physical design of such an affective computing system. It focuses on how relevant empathic data can be acquired in real time by exposing subjects within a dynamic VR-based VPE and assessing their emotional responses while controlling the actual generative parameters via a live feedback loop. A combination of VR, BCI, and E-T solutions integrated within a GE is proposed and discussed. By using a VPE inside a BCI system that can be accurately correlated with E-T, this paper proposes to identify potential morphological and lighting factors that either alone or combined can have an empathic effect expressed by the relevant responses of the MIs.
series	ACADIA
type	paper
email
last changed	2023/10/22 12:06

_id	ecaade2020_227
id	ecaade2020_227
authors	Bielski, Jessica, Langenhan, Christoph, Weyand, Babara, Neuber, Markus, Eisenstadt, Viktor and Althoff, Klaus-Dieter
year	2020
title	Topological Queries and Analysis of School Buildings Based on Building Information Modeling (BIM) Using Parametric Design Tools and Visual Programming to Develop New Building Typologies
doi	https://doi.org/10.52842/conf.ecaade.2020.2.279
source	Werner, L and Koering, D (eds.), Anthropologic: Architecture and Fabrication in the cognitive age - Proceedings of the 38th eCAADe Conference - Volume 2, TU Berlin, Berlin, Germany, 16-18 September 2020, pp. 279-288
summary	School buildings are currently one of the largest portions of planning and building projects in Germany. In order to reflect the continuous developments in school building construction with constantly changing spatial requirements, an approach to analyse, derive and combine patterns of schools is proposed to adapt school typologies accordingly. Therefore, the topology is analysed, concerning interconnection methods, such as adjacency, accessibility, depth, and flow. The geometric analysis of e.g. room sizes or spatial proportions is enhanced by including grouping of rooms, estimated room clusters, or room shapes. Furthermore, text-matching is used to determine e.g. room program fulfilment, or assigning functional room descriptions to predefined room types, revealing huge differences of terms throughout time and architects. First results of the analyses show a relevant correlation between spatial proportion and room types.
keywords	school building typologies; building information modeling (BIM); artificial intelligence (AI); topology; spatial analysis; digital semantic model
series	eCAADe
email
last changed	2022/06/07 07:52

_id	ecaade2020_180
id	ecaade2020_180
authors	Bolshakova, Veronika, Besançon, Franck, Guerriero, Annie and Halin, Gilles
year	2020
title	Use of a Digital Collaboration Tool for Project Review - A pedagogical experiment with multidisciplinary teams
doi	https://doi.org/10.52842/conf.ecaade.2020.2.651
source	Werner, L and Koering, D (eds.), Anthropologic: Architecture and Fabrication in the cognitive age - Proceedings of the 38th eCAADe Conference - Volume 2, TU Berlin, Berlin, Germany, 16-18 September 2020, pp. 651-660
summary	This paper emphasizes feedback from a pedagogical experiment in the context of teaching collaboration and design to multidisciplinary teams. A digital collaboration tool, a multi-touch table and collaboration software, was used as a support for discussion and decision-making for weekly project review meetings. The experiment participants' feedback on the use and usability of the digital collaboration tool highlights the potential for the use of synchronous collaboration technology and project-based learning for higher-level education. It also highlights the need for a transition towards implementation of digital tools at project review sessions.
keywords	: Synchronous collaboration; Pedagogical experiment; Project-based learning; CSCW; NUI; BIM
series	eCAADe
email
last changed	2022/06/07 07:54

_id	ecaade2020_253
id	ecaade2020_253
authors	Buš, Peter
year	2020
title	User-driven Configurable Architectural Assemblies - Towards artificial intelligence-embedded responsive environments
doi	https://doi.org/10.52842/conf.ecaade.2020.2.483
source	Werner, L and Koering, D (eds.), Anthropologic: Architecture and Fabrication in the cognitive age - Proceedings of the 38th eCAADe Conference - Volume 2, TU Berlin, Berlin, Germany, 16-18 September 2020, pp. 483-490
summary	The paper theoretically elaborates the idea of individual users' customisation activities to create and configure responsive spatial scenarios by means of reconfigurable interactive adaptive assemblies. It reflects Gordon Pask's concept of human and device interaction based on its unpredictable notion speculating a potential to be enhanced by artificial intelligence learning approach of an assembly linked with human activator's participative inputs. Such a link of artificial intelligence, human agency and interactive assembly capable to generate its own spatial configurations by itself and users' stimuli may lead to a new understanding of humans' role in the creation of spatial scenarios. The occupants take the prime role in the evolution of spatial conditions in this respect. The paper aims to position an interaction between the human agents and artificial devices as a participatory and responsive design act to facilitate creative potential of participants as unique individuals without pre-specified or pre-programmed goal set by the designer. Such an approach will pave a way towards true autonomy of responsive built environments, determined by an individual human agent and behaviour of the spatial assemblies to create authentic responsive built forms in a digital and physical space.
keywords	deployable systems; responsive assemblies; embedded intelligence; Learning-to-Design-and-Assembly method; Conversation Theory
series	eCAADe
email
last changed	2022/06/07 07:54

_id	caadria2020_446
id	caadria2020_446
authors	Cho, Dahngyu, Kim, Jinsung, Shin, Eunseo, Choi, Jungsik and Lee, Jin-Kook
year	2020
title	Recognizing Architectural Objects in Floor-plan Drawings Using Deep-learning Style-transfer Algorithms
doi	https://doi.org/10.52842/conf.caadria.2020.2.717
source	D. Holzer, W. Nakapan, A. Globa, I. Koh (eds.), RE: Anthropocene, Design in the Age of Humans - Proceedings of the 25th CAADRIA Conference - Volume 2, Chulalongkorn University, Bangkok, Thailand, 5-6 August 2020, pp. 717-725
summary	This paper describes an approach of recognizing floor plans by assorting essential objects of the plan using deep-learning based style transfer algorithms. Previously, the recognition of floor plans in the design and remodeling phase was labor-intensive, requiring expert-dependent and manual interpretation. For a computer to take in the imaged architectural plan information, the symbols in the plan must be understood. However, the computer has difficulty in extracting information directly from the preexisting plans due to the different conditions of the plans. The goal is to change the preexisting plans to an integrated format to improve the readability by transferring their style into a comprehensible way using Conditional Generative Adversarial Networks (cGAN). About 100-floor plans were used for the dataset which was previously constructed by the Ministry of Land, Infrastructure, and Transport of Korea. The proposed approach has such two steps: (1) to define the important objects contained in the floor plan which needs to be extracted and (2) to use the defined objects as training input data for the cGAN style transfer model. In this paper, wall, door, and window objects were selected as the target for extraction. The preexisting floor plans would be segmented into each part, altered into a consistent format which would then contribute to automatically extracting information for further utilization.
keywords	Architectural objects; floor plan recognition; deep-learning; style-transfer
series	CAADRIA
email
last changed	2022/06/07 07:56

_id	acadia20_638
id	acadia20_638
authors	Claypool, Mollie; Jimenez Garcia, Manuel; Retsin, Gilles; Jaschke, Clara; Saey, Kevin
year	2020
title	Discrete Automation
doi	https://doi.org/10.52842/conf.acadia.2020.1.638
source	ACADIA 2020: Distributed Proximities / Volume I: Technical Papers [Proceedings of the 40th Annual Conference of the Association of Computer Aided Design in Architecture (ACADIA) ISBN 978-0-578-95213-0]. Online and Global. 24-30 October 2020. edited by B. Slocum, V. Ago, S. Doyle, A. Marcus, M. Yablonina, and M. del Campo. 638-647.
summary	Globally, the built environment is inequitable. And while construction automation is often heralded as the solution to labor shortages and the housing crisis, such methods tend to focus on technology, neglecting the wider socioeconomic contexts. Automated Architecture (AUAR), a spinoff of AUAR Labs at The Bartlett School of Architecture, UCL, asserts that a values-centered, decentralized approach to automation centered around local communities can begin to address this material hegemony. The paper introduces and discusses AUAR’s platform-based framework, Discrete Automation, which subverts the status quo of automation that excludes those who are already disadvantaged into an inclusive network capable of providing solutions to both the automation gap and the assembly problem. Through both the wider context of existing modular housing platforms and issues of the current use of automated technologies in architectural production, Discrete Automation is discussed through the example of Block Type A, a discrete timber building system, which in conjunction with its combinatorial app constitutes the base of a community-led housing platform developed by AUAR. Built case studies are introduced alongside a discussion of the applied methodologies and an outlook on the platform’s potential for scalability in an equitable, sustainable manner.
series	ACADIA
type	paper
email
last changed	2023/10/22 12:06

_id	cdrf2019_36
id	cdrf2019_36
authors	Dan Luo, Joseph M. Gattas, and Poah Shiun Shawn Tan
year	2020
title	Real-Time Defect Recognition and Optimized Decision Making for Structural Timber Jointing
doi	https://doi.org/https://doi.org/10.1007/978-981-33-4400-6_4
source	Proceedings of the 2020 DigitalFUTURES The 2nd International Conference on Computational Design and Robotic Fabrication (CDRF 2020)
summary	Non-structural or out-of-grade timber framing material contains a large proportion of visual and natural defects. A common strategy to recover usable material from these timbers is the marking and removing of defects, with the generated intermediate lengths of clear wood then joined into a single piece of fulllength structural timber. This paper presents a novel workflow that uses machine learning based image recognition and a computational decision-making algorithm to enhance the automation and efficiency of current defect identification and rejoining processes. The proposed workflow allows the knowledge of worker to be translated into a classifier that automatically recognizes and removes areas of defects based on image capture. In addition, a real-time optimization algorithm in decision making is developed to assign a joining sequence of fragmented timber from a dynamic inventory, creating a single piece of targeted length with a significant reduction in material waste. In addition to an industrial application, this workflow also allows for future inventory-constrained customizable fabrication, for example in production of non-standard architectural components or adaptive reuse or defect-avoidance in out-of-grade timber construction.
series	cdrf
email
last changed	2022/09/29 07:51

_id	cdrf2019_189
id	cdrf2019_189
authors	Dasong Wang and Roland Snooks
year	2020
title	Artificial Intuitions of Generative Design: An Approach Based on Reinforcement Learning
doi	https://doi.org/https://doi.org/10.1007/978-981-33-4400-6_18
source	Proceedings of the 2020 DigitalFUTURES The 2nd International Conference on Computational Design and Robotic Fabrication (CDRF 2020)
summary	This paper proposes a Reinforcement Learning (RL) based design approach that augments existing algorithmic generative processes through the emergence of a form of artificial design intuition. The research presented in the paper is embedded within a highly speculative research project, Artificial Agency, exploring the operation of Machine Learning (ML) in generative design and digital fabrication. After describing the inherent limitations of contemporary generative design processes, the paper compares the three fundamental types of machine learning frameworks in terms of their characteristics and potential impact on generative design. A theoretical framework is defined to demonstrate the methodology of integrating RL with existing generative design procedures, which is further explained with a Random Walk based experimental design example. The paper includes detailed RL definitions as well as critical reflections on its impact and the effects of its implementation. The proposed artificial intuition within this generative approach is currently being further developed through a series of ongoing and proposed research trajectories noted in the conclusion. The ambition of this research is to deepen the integration of intention with machine learning in generative design.
series	cdrf
email
last changed	2022/09/29 07:51

_id	caadria2020_098
id	caadria2020_098
authors	Davidova, Marie and McMeel, Dermott
year	2020
title	Codesigning with Blockchain for Synergetic Landscapes - The CoCreation of Blockchain Circular Economy through Systemic Design
doi	https://doi.org/10.52842/conf.caadria.2020.2.333
source	D. Holzer, W. Nakapan, A. Globa, I. Koh (eds.), RE: Anthropocene, Design in the Age of Humans - Proceedings of the 25th CAADRIA Conference - Volume 2, Chulalongkorn University, Bangkok, Thailand, 5-6 August 2020, pp. 333-342
summary	The paper is exploring methodology within the work in progress research by design through teaching project called 'Synergetic Landscapes'. It discusses codesign and cocreation processes that are crossing the academia, NGOs and applied practice within so called 'real life codesign laboratory' (DavidovÃ¡, PÃ¡nek, & PÃ¡nkovÃ¡, 2018). This laboratory performs in real time and real life environment. The work investigates synergised bio-digital (living, non-living, physical, analogue, digital and virtual) prototypical interventions in urban environment that are linked to circular economy and life cycles systems running on blockchain. It represents a holistic systemic interactive and performing approach to design processes that involve living, habitational and edible, social and reproductive, circular and token economic systems. Those together are to cogenerate synergetic landscapes.
keywords	codesign; blockchain; systemic design; prototyping; bio-digital design
series	CAADRIA
email
last changed	2022/06/07 07:55

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