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

PDF papers
References

Hits 1 to 20 of 1681

Reformat results as: short short into frame detailed detailed into frame

_id	caadria2019_126
id	caadria2019_126
authors	Ng, Jennifer Mei Yee, Khean, Nariddh, Madden, David, Fabbri, Alessandra, Gardner, Nicole, Haeusler, M. Hank and Zavoleas, Yannis
year	2019
title	Optimising Image Classification - Implementation of Convolutional Neural Network Algorithms to Distinguish Between Plans and Sections within the Architectural, Engineering and Construction (AEC) Industry
doi	https://doi.org/10.52842/conf.caadria.2019.2.795
source	M. Haeusler, M. A. Schnabel, T. Fukuda (eds.), Intelligent & Informed - Proceedings of the 24th CAADRIA Conference - Volume 2, Victoria University of Wellington, Wellington, New Zealand, 15-18 April 2019, pp. 795-804
summary	Modern communication between built environment professionals are governed by the effective exchange of digital models, blueprints and technical drawings. However, the increasing quantity of such digital files, in conjunction with inconsistent filing systems, increases the potential for human-error upon their look-up and retrieval. Further, current methods are manual, thus slow and resource intensive. Evidently, the architectural, engineering and construction (AEC) industry lacks an automated classification system capable of systematically identifying and categorising different drawings. To intercede, we aim to investigate artificially intelligent solutions capable of automatically identifying and retrieving a wide set of AEC files from a company's resource library. We present a convolutional neural network (CNN) model capable of processing large sets of technical drawings - such as sections, plans and elevations - and recognise their individual patterns and features, ultimately minimising laboriousness.
keywords	Convolutional Neural Network; Artificial Intelligence; Machine Learning; Classification; Filing architectural drawings.
series	CAADRIA
email
last changed	2022/06/07 07:58

_id	cf2019_003
id	cf2019_003
authors	Steinfeld, Kyle; Katherine Park, Adam Menges and Samantha Walker
year	2019
title	Fresh Eyes A framework for the application of machine learning to generative architectural design, and a report of activities at Smartgeometry 2018
source	Ji-Hyun Lee (Eds.) "Hello, Culture!" [18th International Conference, CAAD Futures 2019, Proceedings / ISBN 978-89-89453-05-5] Daejeon, Korea, p. 22
summary	This paper presents a framework for the application of Machine Learning (ML) to Generative Architectural Design (GAD), and illustrates this framework through a description of a series of projects completed at the Smart Geometry conference in May of 2018 (SG 2018) in Toronto. Proposed here is a modest modification of a 3-step process that is well-known in generative architectural design, and that proceeds as: generate, evaluate, iterate. In place of the typical approaches to the evaluation step, we propose to employ a machine learning process: a neural net trained to perform image classification. This modified process is different enough from traditional methods as to warrant an adjustment of the terms of GAD. Through the development of this framework, we seek to demonstrate that generative evaluation may be seen as a new locus of subjectivity in design.
keywords	Machine Learning, Generative Design, Design Methods
series	CAAD Futures
email
last changed	2019/07/29 14:08

_id	cf2019_052
id	cf2019_052
authors	Abdelmohsen, Sherif ;Passaint Massoud, Rana El-Dabaa, Aly Ibrahim and Tasbeh Mokbel
year	2019
title	The Effect of Hygroscopic Design Parameters on the Programmability of Laminated Wood Composites for Adaptive Façades
source	Ji-Hyun Lee (Eds.) "Hello, Culture!" [18th International Conference, CAAD Futures 2019, Proceedings / ISBN 978-89-89453-05-5] Daejeon, Korea, p. 435
summary	Typical adaptive façades respond to external conditions to enhance indoor spaces based on complex mechanical actuators and programmable functions. Hygroscopic embedded properties of wood, as low-cost low-tech programmable material, have been utilized to induce passive motion mechanisms. Wood as anisotropic material allows for different passive programmable motion configurations that relies on several hygroscopic design parameters. This paper explores the effect of these parameters on programmability of laminated wood composites through physical experiments in controlled humidity environment. The paper studies variety of laminated configurations involving different grain orientations, and their effect on maximum angle of deflection and its durability. Angle of deflection is measured using image analysis software that is used for continuous tracking of deflection in relation to time. Durability is studied as the number of complete programmable cycles that wood could withstand before reaching point of failure. Results revealed that samples with highest deflection angle have least programmability durability.
keywords	Wood, hygroscopic design, lamination, deflection, durability, adaptive façades
series	CAAD Futures
email
last changed	2019/07/29 14:18

_id	caadria2019_413
id	caadria2019_413
authors	Ahrens, Chandler, Chamberlain, Roger, Mitchell, Scott, Barnstorff, Adam and Gelbard, Joshua
year	2019
title	Controlling Daylight Reflectance with Cyber-physical Systems
doi	https://doi.org/10.52842/conf.caadria.2019.1.433
source	M. Haeusler, M. A. Schnabel, T. Fukuda (eds.), Intelligent & Informed - Proceedings of the 24th CAADRIA Conference - Volume 1, Victoria University of Wellington, Wellington, New Zealand, 15-18 April 2019, pp. 433-442
summary	Cyber-physical systems increasingly inform and alter the perception of atmospheric conditions within interior environments. The Catoptric Surface research project uses computation and robotics to precisely control the location of reflected daylight through a building envelope to form an image-based pattern of light on the building interior's surfaces. In an attempt to amplify or reduce spatial perception, the daylighting reflected onto architectural surfaces within a built environment generates atmospheric effects. The modification of light patterns mapped onto existing or new surfaces enables the perception of space to not rely on form alone. The mapping of a new pattern that is independent of architectural surfaces creates a visual effect of a formless atmosphere and holds the potential to affect the way people interact with the space. People need different amounts and quality of daylight depending on physiological differences due to age or the types of tasks they perform. This research argues for an informed luminous and atmospheric environment that is relative both to the user and more conceptual architectural aspirations of spatial perception controlled by a cyber-physical robotic faÃ§ade system.
keywords	Contextual; Computation
series	CAADRIA
email
last changed	2022/06/07 07:54

_id	ecaadesigradi2019_605
id	ecaadesigradi2019_605
authors	Andrade Zandavali, Bárbara and Jiménez García, Manuel
year	2019
title	Automated Brick Pattern Generator for Robotic Assembly using Machine Learning and Images
doi	https://doi.org/10.52842/conf.ecaade.2019.3.217
source	Sousa, JP, Xavier, JP and Castro Henriques, G (eds.), Architecture in the Age of the 4th Industrial Revolution - Proceedings of the 37th eCAADe and 23rd SIGraDi Conference - Volume 3, University of Porto, Porto, Portugal, 11-13 September 2019, pp. 217-226
summary	Brickwork is the oldest construction method still in use. Digital technologies, in turn, enabled new methods of representation and automation for bricklaying. While automation explored different approaches, representation was limited to declarative methods, as parametric filling algorithms. Alternatively, this work proposes a framework for automated brickwork using a machine learning model based on image-to-image translation (Conditional Generative Adversarial Networks). The framework consists of creating a dataset, training a model for each bond, and converting the output images into vectorial data for robotic assembly. Criteria such as: reaching wall boundary accuracy, avoidance of unsupported bricks, and brick's position accuracy were individually evaluated for each bond. The results demonstrate that the proposed framework fulfils boundary filling and respects overall bonding structural rules. Size accuracy demonstrated inferior performance for the scale tested. The association of this method with 'self-calibrating' robots could overcome this problem and be easily implemented for on-site.
series	eCAADeSIGraDi
email
last changed	2022/06/07 07:54

_id	ecaadesigradi2019_340
id	ecaadesigradi2019_340
authors	Azambuja Varela, Pedro and Sousa, José Pedro
year	2019
title	Digital Expansion of Stereotomy - A semantic classification
doi	https://doi.org/10.52842/conf.ecaade.2019.1.387
source	Sousa, JP, Xavier, JP and Castro Henriques, G (eds.), Architecture in the Age of the 4th Industrial Revolution - Proceedings of the 37th eCAADe and 23rd SIGraDi Conference - Volume 1, University of Porto, Porto, Portugal, 11-13 September 2019, pp. 387-396
summary	This paper presents a critical analysis and reflection on stereotomy with the purpose of updating its theoretical discourse. Having risen to the apex of architecture technological possibilities in the 17th century, stereotomic construction lost its importance in favour of iron, steel and other materials and construction techniques brought by the Industrial Revolution. More recently, much owing to the possibilities offered by digital technologies, a resurgence of interest in the subject has spawned various researches which bring stereotomy back to the architectural discourse. Although technological applications and design innovations in service of stereotomy have developed in multiple interesting paths, there is a lack of a common theory on the subject which is capable of relating these multiple apparently diverging stereotomic approaches between each other and, maybe even more importantly, to the classical practice which sparked the development this discipline. The research presented in this paper shows how the digital tools were instrumental in bringing this tradition to architecture contemporaneity and how a current stereotomy is largely supported by these technologies, while keeping strong relations to its classic origin.
keywords	stereotomy; classification; history; digital
series	eCAADeSIGraDi
email
last changed	2022/06/07 07:54

_id	caadria2019_459
id	caadria2019_459
authors	Behmanesh, Hossein and Brown, AndrÃ© G.P.
year	2019
title	Classification and Review of Software Applications in the Context of Urban Design Processes
doi	https://doi.org/10.52842/conf.caadria.2019.2.211
source	M. Haeusler, M. A. Schnabel, T. Fukuda (eds.), Intelligent & Informed - Proceedings of the 24th CAADRIA Conference - Volume 2, Victoria University of Wellington, Wellington, New Zealand, 15-18 April 2019, pp. 211-220
summary	We have seen increasing expectations from our cities: as we aim to enable them to become smarter, more efficient and more sustainable. Having these goals makes the urban designing process increasingly complex. Undertaking contemporary urban design and analysis requires a rounded and inclusive approach. In the discussion relating to the smart city there has been attention to infrastructure technology solutions. But ways of estimating the success of more comprehensive urban design interventions is also extremely important. In response to these needs, digital urban design simulation and analysis software packages have been developed to help urban designers model and evaluate their designs before they take shape in the real world. We analyse, and reflect on the current aids available, classifying the urban design software packages which were used in the body of knowledge. In addition, more influential urban design software packages have been reviewed to figure out in which stages of the urban design process, they have applied. This review also helpful for software developer to understand which software packages more useful and which ones need to be developed in future.
keywords	Smart city; Urban Design Process; software application; classification
series	CAADRIA
email
last changed	2022/06/07 07:54

_id	lasg_whitepapers_2019_089
id	lasg_whitepapers_2019_089
authors	Byrne, Daragh; and Dana Cupkova
year	2019
title	Towards Psychosomatic Architecture; Attuning Reactive Architectural Materials through Biofeedback
source	Living Architecture Systems Group White Papers 2019 [ISBN 978-1-988366-18-0] Riverside Architectural Press: Toronto, Canada 2019. pp.089 - 100
summary	The built environment is known to affect human health and wellbeing. Yet, architecture does not respond to our bodies or our minds. It tends to be static, ignoring the human occupant, their mood, behaviors, and emotions. There is evidence that this monotony of average space is harmful to human health. Additionally, differences in gender, race and cultural conditions vary the perception of and preferences for temperature and color. To improve the psychosomatic relationship with architectural spaces, there arises the necessity for it to have a greater range of spatial reactivity and better support for personalized thermoregulation and aesthetics. This paper proposes an architecture that operates like a mood-ring, one that creates rich feedback between architecture and occupant towards individualized reactivity and expression. [Sentient Concrete] ([Image 1]) is a prototype of a thermochromically treated concrete panel that is thermally actuated by embedded electromechanical systems and can dynamically produce localized thermally reactive responses. It serves as a test case for outlining further research agendas and possible design frameworks for psychosomatic architecture.
keywords	living architecture systems group, organicism, intelligent systems, design methods, engineering and art, new media art, interactive art, dissipative systems, technology, cognition, responsiveness, biomaterials, artificial natures, 4DSOUND, materials, virtual projections,
email
last changed	2019/07/29 14:02

_id	caadria2019_396
id	caadria2019_396
authors	Cao, Rui, Fukuda, Tomohiro and Yabuki, Nobuyoshi
year	2019
title	Quantifying Visual Environment by Semantic Segmentation Using Deep Learning - A Prototype for Sky View Factor
doi	https://doi.org/10.52842/conf.caadria.2019.2.623
source	M. Haeusler, M. A. Schnabel, T. Fukuda (eds.), Intelligent & Informed - Proceedings of the 24th CAADRIA Conference - Volume 2, Victoria University of Wellington, Wellington, New Zealand, 15-18 April 2019, pp. 623-632
summary	Sky view factor (SVF) is the ratio of radiation received by a planar surface from the sky to that received from the entire hemispheric radiating environment, in the past 20 years, it was more applied to urban-climatic areas such as urban air temperature analysis. With the urbanization and the development of cities, SVF has been paid more and more attention on as the important parameter in urban construction and city planning area because of increasing building coverage ratio to promote urban forms and help creating a more comfortable and sustainable urban residential building environment to citizens. Therefore, efficient, low cost, high precision, easy to operate, rapid building-wide SVF estimation method is necessary. In the field of image processing, semantic segmentation based on deep learning have attracted considerable research attention. This study presents a new method to estimate the SVF of residential environment by constructing a deep learning network for segmenting the sky areas from 360-degree camera images. As the result of this research, an easy-to-operate estimation system for SVF based on high efficiency sky label mask images database was developed.
keywords	Visual environment; Sky view factor; Semantic segmentation; Deep learning; Landscape simulation
series	CAADRIA
email
last changed	2022/06/07 07:54

_id	cf2019_002
id	cf2019_002
authors	De Luca, Francesco
year	2019
title	Environmental Performance-Driven Urban Design Parametric Design Method for the Integration of Daylight and Urban Comfort Analysis in Cold Climates
source	Ji-Hyun Lee (Eds.) "Hello, Culture!" [18th International Conference, CAAD Futures 2019, Proceedings / ISBN 978-89-89453-05-5] Daejeon, Korea, p. 21
summary	Shape of built environment and image of cities are significantly influenced by environmental factors such as access to natural light, air temperature and wind. Adequate quantity of daylight in building interiors is important for occupant wellbeing and energy saving. In Estonia minimum quantity of daylight is required by building standards. Wind speed increased by urban environment at northern latitudes can significantly reduce pedestrian perceived temperature during winter inducing strong cold stress. This paper presents a method for the integration of parametric modeling and environmental simulations to analyze interiors and exteriors comfort of tower building cluster variations in different urban areas in Tallinn. Optimal pattern characteristics such as buildings distance and alignment favoring improvement of interiors daylight and decrease of pedestrian cold stress are presented and discussed.
keywords	Daylight, Urban Comfort, Environmental Analysis, PerformanceDriven Urban Design, Parametric Design
series	CAAD Futures
email
last changed	2019/07/29 14:08

_id	ecaadesigradi2019_296
id	ecaadesigradi2019_296
authors	Dounas, Theodoros, Lombardi, Davide and Jabi, Wassim
year	2019
title	Towards Blockchains for architectural design - Consensus mechanisms for collaboration in BIM
doi	https://doi.org/10.52842/conf.ecaade.2019.1.267
source	Sousa, JP, Xavier, JP and Castro Henriques, G (eds.), Architecture in the Age of the 4th Industrial Revolution - Proceedings of the 37th eCAADe and 23rd SIGraDi Conference - Volume 1, University of Porto, Porto, Portugal, 11-13 September 2019, pp. 267-274
summary	We present a Blockchain collaboration mechanism on optimisation problems between distributed participants who work with building information modelling tools. The blockchain mechanism is capable of executing smart contracts, acting as a reward mechanism of independent designers attempting to collaborate or compete on optimising a design performance problem. Earlier work has described the potential integration through different levels of Computer Aided Design and Blockchain. We present an expanded version of that integration and we showcase how a team can collaboratively and competitively work, using BIM tools, through the blockchain. The original contribution of the paper is the use of the design optimisation performance as a consensus mechanism for block writing in blockchains. To accomplish that we introduce mechanisms for BIM to Blockchain Integration but also describe a special category of blockchains for architectural design and the built environment. The paper concludes with an analysis of the relationship between trust and values as encapsulated in the blockchain and how these could affect the design collaboration.
keywords	Blockchain; BIM; agent; collaboration; competition
series	eCAADeSIGraDi
email
last changed	2022/06/07 07:55

_id	cf2019_014
id	cf2019_014
authors	Ferrando, Cecilia; Niccolo Dalmasso, Jiawei Mai, Daniel Cardoso Llach
year	2019
title	Architectural Distant Reading Using Machine Learning to Identify Typological Traits Across Multiple Buildings
source	Ji-Hyun Lee (Eds.) "Hello, Culture!" [18th International Conference, CAAD Futures 2019, Proceedings / ISBN 978-89-89453-05-5] Daejeon, Korea, pp. 114-127
summary	This paper introduces an approach to architectural “distant reading”: the use of computational methods to analyze architectural data in order to derive spatial insights from—and explore new questions concerning—large collections of architectural work. Through a case study comprising a dataset of religious buildings, we show how we may use machine learning techniques to identify typological and functional traits from building plans. We find that spatial structure, rather than local features, is particularly effective in supporting this type of analysis. Further, we speculate on the potential of this computational method to enrich architectural design, research, and criticism by, for example, enabling new ways of thinking about architectural concepts such as typology in ways that reflect gradual variations, rather than sharp distinctions.
keywords	Architectural Analytics, Machine Learning, Classification, Religious buildings, Space Syntax
series	CAAD Futures
email
last changed	2019/07/29 14:08

_id	sigradi2020_392
id	sigradi2020_392
authors	Fialho, Beatriz Campos; Codinhoto, Ricardo; Fabricio, Márcio Minto
year	2020
title	BIM and IoT for the AEC Industry: A systematic literature mapping
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. 392-399
summary	The AEC industry has been facing a digital transformation for improving services involved in buildings lifecycle, fostered by two disruptive technologies: Building Information Modelling (BIM) and Internet of Things (IoT). However, the literature lacks discussions regarding applications and challenges of BIM and IoT systems in the AEC. This Systematic Literature Mapping addresses this gap through search, analysis, and classification of 75 journal article abstracts published between 2015 and 2019. An increase of articles over the period is observed, predominantly with technical and processual solutions for Construction and Operation and Maintenance. The interoperability of data is a key challenge to organizations.
keywords	Building Information Modelling, Internet of Things, Integration, Network, Smart Cities
series	SIGraDi
email
last changed	2021/07/16 11:49

_id	lasg_whitepapers_2019_111
id	lasg_whitepapers_2019_111
authors	Gruber, Petra
year	2019
title	Living Wall System (LIWAS)
source	Living Architecture Systems Group White Papers 2019 [ISBN 978-1-988366-18-0] Riverside Architectural Press: Toronto, Canada 2019. pp.111 - 122
summary	This proposal is about the design and prototyping of a Living Wall System (LIWAS) as a test bed for integrating concepts from biology into architectural design. The "Living Wall” is a new way of interpreting a wall system that we use in architecture and building. We try to integrate characteristics of living organisms into the wall design to harness some of the intriguing qualities of life into our built surroundings. Living Walls may include flows of water; they may move, adapt geometry and change appearance; they may be inhabited by algae, plants and other organisms and in general be “alive.” The framework of the proposal is the overlap between architectural design and biological research, using biomimicry as a methodology for information transfer between the fields (Image 1).
keywords	living architecture systems group, organicism, intelligent systems, design methods, engineering and art, new media art, interactive art, dissipative systems, technology, cognition, responsiveness, biomaterials, artificial natures, 4DSOUND, materials, virtual projections,
email
last changed	2019/07/29 14:02

_id	caadria2019_143
id	caadria2019_143
authors	Kato, Yuri and Matsukawa, Shohei
year	2019
title	Development of Generating System for Architectural Color Icons Using Google Map Platform and Tensorflow-Segmentation
doi	https://doi.org/10.52842/conf.caadria.2019.2.081
source	M. Haeusler, M. A. Schnabel, T. Fukuda (eds.), Intelligent & Informed - Proceedings of the 24th CAADRIA Conference - Volume 2, Victoria University of Wellington, Wellington, New Zealand, 15-18 April 2019, pp. 81-90
summary	In this research, the goal is to develop a generating system for architectural color icons using Google Map Platform and Tensorflow-Segmentation. There has been no case of developing a system that allows users to visualize the color tendency of buildings as architectural color icons for each building element from images of various regions. It is considered meaningful to be able to create criteria for decision making in architecture and the urban design by developing a system to clarify the current state of the architectural colors. It will contribute a rise in the consciousness of landscape conservation and be essential for the design of architectures and public objects. This paper includes the explanation of development method, use experiments, and consideration of five problems among architectural color icons creation. It is assumed that the accuracy of the present system will be better as the technology improves.
keywords	Google street view; machine learning; image segmentation; color palette; color analysis
series	CAADRIA
email
last changed	2022/06/07 07:52

_id	cf2019_004
id	cf2019_004
authors	Kim, Jinsung; Jaeyeol Song and Jin-Kook Lee
year	2019
title	Recognizing and Classifying Unknown Object in BIM using 2D CNN
source	Ji-Hyun Lee (Eds.) "Hello, Culture!" [18th International Conference, CAAD Futures 2019, Proceedings / ISBN 978-89-89453-05-5] Daejeon, Korea, p. 23
summary	This paper aims to propose an approach to automated classifying building element instance in BIM using deep learning-based 3D object classification algorithm. Recently, studies related to checking or validating engine of BIM object for ensuring data integrity of BIM instances are getting attention. As a part of this research, this paper train recognition models that are targeted at basic building element and interior element using 3D object recognition technique that uses images of objects as inputs. Object recognition is executed in two stages; 1) class of object (e.g. wall, window, seating furniture, toilet fixture and etc.), 2) sub-type of specific classes (e.g. Toilet or Urinal). Using the trained models, BIM plug-in prototype is developed and the performance of this AI-based approach with test BIM model is checked. We expect this recognition approach to help ensure the integrity of BIM data and contribute to the practical use of BIM.
keywords	3D object classification, Building element, Building information modeling, Data integrity, Interior element
series	CAAD Futures
email
last changed	2019/07/29 14:08

_id	ecaadesigradi2019_339
id	ecaadesigradi2019_339
authors	Kinugawa, Hina and Takizawa, Atsushi
year	2019
title	Deep Learning Model for Predicting Preference of Space by Estimating the Depth Information of Space using Omnidirectional Images
doi	https://doi.org/10.52842/conf.ecaade.2019.2.061
source	Sousa, JP, Xavier, JP and Castro Henriques, G (eds.), Architecture in the Age of the 4th Industrial Revolution - Proceedings of the 37th eCAADe and 23rd SIGraDi Conference - Volume 2, University of Porto, Porto, Portugal, 11-13 September 2019, pp. 61-68
summary	In this study, we developed a method for generating omnidirectional depth images from corresponding omnidirectional RGB images of streetscapes by learning each pair of omnidirectional RGB and depth images created by computer graphics using pix2pix. Then, the models trained with different series of images shot under different site and weather conditions were applied to Google street view images to generate depth images. The validity of the generated depth images was then evaluated visually. In addition, we conducted experiments to evaluate Google street view images using multiple participants. We constructed a model that estimates the evaluation value of these images with and without the depth images using the learning-to-rank method with deep convolutional neural network. The results demonstrate the extent to which the generalization performance of the streetscape evaluation model changes depending on the presence or absence of depth images.
keywords	Omnidirectional image; depth image; Unity; Google street view; pix2pix; RankNet
series	eCAADeSIGraDi
email
last changed	2022/06/07 07:52

_id	acadia20_136p
id	acadia20_136p
authors	López Lobato, Déborah; Charbel, Hadin
year	2020
title	Foll(i)cle
source	ACADIA 2020: Distributed Proximities / Volume II: Projects [Proceedings of the 40th Annual Conference of the Association of Computer Aided Design in Architecture (ACADIA) ISBN 978-0-578-95253-6]. Online and Global. 24-30 October 2020. edited by M. Yablonina, A. Marcus, S. Doyle, M. del Campo, V. Ago, B. Slocum. 136-141
summary	In the early months of 2019, air pollution in Bangkok reached a record high, bringing national and international attention to the air quality in the South East Asian cosmopolitan. Although applications such as real-time pollution maps provide an environmental reading from the exterior, such information reveals the ‘here and now,’ where its record is inevitably lost through the ‘refreshing’ process of the live update and does not take increment and accumulation as factors to consider. The project was conceived around understanding the human body as precisely that medium that resists classification as either an interior or exterior environment that inherently performs as an impressionable record of its surroundings. Can a city’s toxicity be read through its living constituents? Can the living bodies that dwell, navigate, breathe, and process habitable environments be accessed? Can architecture retain a degree of independence while also performing as a beacon for the collective? Along this line of questioning, it was found that human hair can be transformed from a material that is effortlessly and continuously grown, cut, stylized, and discarded, and instead be intercepted and used in the production of public information gathering. Foll(i)cle is a collective being made of discarded human hair. Performing as a parliament for collectivity embedded with a protocol; the hairy pavilion invites the public in and presents them with a device at the center that hosts all the necessary equipment and information for anonymously and voluntarily providing hair samples for heavy metal analysis, the data of which is used in making a publically accessible toxi-cartography. Although humans are the primary subject for this study, the results suggest that extending the methodology to non-humans could prove useful in reading urban toxicity through various life forms.
series	ACADIA
type	project
email
last changed	2021/10/26 08:03

_id	sigradi2023_416
id	sigradi2023_416
authors	Machado Fagundes, Cristian Vinicius, Miotto Bruscato, Léia, Paiva Ponzio, Angelica and Chornobai, Sara Regiane
year	2023
title	Parametric environment for internalization and classification of models generated by the Shap-E tool
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. 1689–1698
summary	Computing has been increasingly employed in design environments, primarily to perform calculations and logical decisions faster than humans could, enabling tasks that would be impossible or too time-consuming to execute manually. Various studies highlight the use of digital tools and technologies in diverse methods, such as parametric modeling and evolutionary algorithms, for exploring and optimizing alternatives in architecture, design, and engineering (Martino, 2015; Fagundes, 2019). Currently, there is a growing emergence of intelligent models that increasingly integrate computers into the design process. Demonstrating great potential for initial ideation, artificial intelligence (AI) models like Shap-E (Nichol et al., 2023) by OpenAI stand out. Although this model falls short of state-of-the-art sample quality, it is among the most efficient orders of magnitude for generating three-dimensional models through AI interfaces, offering practical balance for certain use cases. Thus, aiming to explore this gap, the presented study proposes an innovative design agency framework by employing Shap-E connected with parametric modeling in the design process. The generation tool has shown promising results; through generations of synthetic views conditioned by text captions, its final output is a mesh. However, due to the lack of topological information in models generated by Shap-E, we propose to fill this gap by transferring data to a parametric three-dimensional surface modeling environment. Consequently, this interaction's use aims to enable the transformation of the mesh into quantifiable surfaces, subject to collection and optimization of dimensional data of objects. Moreover, this work seeks to enable the creation of artificial databases through formal categorization of parameterized outputs using the K-means algorithm. For this purpose, the study methodologically orients itself in a four-step exploratory experimental process: (1) creation of models generated by Shap-E in a pressing manner; (2) use of parametric modeling to internalize models into the Grasshopper environment; (3) generation of optimized alternatives using the evolutionary algorithm (Biomorpher); (4) and classification of models using the K-means algorithm. Thus, the presented study proposes, through an environment of internalization and classification of models generated by the Shap-E tool, to contribute to the construction of a new design agency methodology in the decision-making process of design. So far, this research has resulted in the generation and classification of a diverse set of three-dimensional shapes. These shapes are grouped for potential applications in machine learning, in addition to providing insights for the refinement and detailed exploration of forms.
keywords	Shap-E, Parametric Design, Evolutionary Algorithm, Synthetic Database, Artificial Intelligence
series	SIGraDi
email
last changed	2024/03/08 14:09

_id	ijac201917104
id	ijac201917104
authors	Matthews, Linda and Gavin Perin
year	2019
title	Exploiting ambiguity: The diffraction artefact and the architectural surface
source	International Journal of Architectural Computing vol. 17 - no. 1, 103-115
summary	In the contemporary ‘envisioned’ environment, Internet webcams, low- and high-altitude unmanned aerial vehicles and satellites are the new vantage points from which to construct the image of the city. Armed with hi-resolution digital optical technologies, these vantage points effectively constitute a ubiquitous visioning apparatus serving either the politics of promotion or surveillance. Given the political dimensions of this apparatus, it is important to note that this digital imaging of public urban space refers to the human visual system model. In order to mimic human vision, a set of algorithm patterns are used to direct numerous ‘soft’ and ‘hard’ technologies. Mimicry thus has a cost because this insistence on the human visual system model necessitates multiple transformative moments in the production and transmission pipeline. If each transformative moment opens a potential vulnerability within the visioning apparatus, then every glitch testifies to the artificiality of the image. Moreover, every glitch potentially interrupts the political narratives be communicated in contemporary image production and transmission. Paradoxically, the current use of scripting to create glitch-like images has reimagined glitches as a discrete aesthetic category. This article counters this aestheticisation by asserting glitching as a disruption in communication. The argument will rely on scaled tests produced by one of the authors who show how duplicating the digital algorithmic patterns used within the digital imaging pipeline on any exterior building surface glitches the visual data captured within that image. Referencing image-based techniques drawn from the Baroque and contemporary modes of camouflage, it will be argued that the visual aberrations created by these algorithm-based patterned facades can modify strategically the ‘emission signature’ of selected parts of the urban fabric. In this way, the glitch becomes a way to intercede in the digital portrayal of city.
keywords	Surveillance, algorithms, diffraction, pattern, disruptive, optics
series	journal
email
last changed	2019/08/07 14:04

For more results click below: