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	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
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
doi	https://doi.org/10.52842/conf.caadria.2019.2.795
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	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
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
doi	https://doi.org/10.52842/conf.ecaade.2019.1.267
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_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
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
doi	https://doi.org/10.52842/conf.caadria.2019.1.433
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
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
doi	https://doi.org/10.52842/conf.ecaade.2019.3.217
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	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
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
doi	https://doi.org/10.52842/conf.caadria.2019.2.623
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	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
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
doi	https://doi.org/10.52842/conf.caadria.2019.2.081
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	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
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
doi	https://doi.org/10.52842/conf.ecaade.2019.2.061
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	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

_id	caadria2020_259
id	caadria2020_259
authors	Rhee, Jinmo, Veloso, Pedro and Krishnamurti, Ramesh
year	2020
title	Integrating building footprint prediction and building massing - an experiment in Pittsburgh
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. 669-678
doi	https://doi.org/10.52842/conf.caadria.2020.2.669
summary	We present a novel method for generating building geometry using deep learning techniques based on contextual geometry in urban context and explore its potential to support building massing. For contextual geometry, we opted to investigate the building footprint, a main interface between urban and architectural forms. For training, we collected GIS data of building footprints and geometries of parcels from Pittsburgh and created a large dataset of Diagrammatic Image Dataset (DID). We employed a modified version of a VGG neural network to model the relationship between (c) a diagrammatic image of a building parcel and context without the footprint, and (q) a quadrilateral representing the original footprint. The option for simple geometrical output enables direct integration with custom design workflows because it obviates image processing and increases training speed. After training the neural network with a curated dataset, we explore a generative workflow for building massing that integrates contextual and programmatic data. As trained model can suggest a contextual boundary for a new site, we used Massigner (Rhee and Chung 2019) to recommend massing alternatives based on the subtraction of voids inside the contextual boundary that satisfy design constraints and programmatic requirements. This new method suggests the potential that learning-based method can be an alternative of rule-based design methods to grasp the complex relationships between design elements.
keywords	Deep Learning; Prediction; Building Footprint; Massing; Generative Design
series	CAADRIA
email
last changed	2022/06/07 07:56

_id	ecaadesigradi2019_630
id	ecaadesigradi2019_630
authors	Saad, Carla
year	2019
title	If Only Wood Could Speak... - Explorations in digital fabrication processes based on timber grain and patterns
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. 227-234
doi	https://doi.org/10.52842/conf.ecaade.2019.3.227
summary	This paper presents an exploration following wood patterns applied to traditional woodworking techniques such as steam bending and carving. It builds on a digital fabrication process where the patterns that are unique to each wood strip and which constitutes their structural geometry are also used within fabrication processes and applied machinery such as the zund machine. The experiments were done in two series where the earlier set focuses on routing along the wood patterns of thin wood strips and steam bending the different pieces. The second set experimented with carving thick wood strips on passes generated from the extracted patterns. An automated technique based in computer vision and specifically OpenCV was developed using different filters in order to extract the patterns and transfer the results into CAD software where the lines where further manipulated for variable exploration. The results of this study led to a better understanding of wood patterns from a geometrical perspective thus enriching the aesthetic composition of a design while being authentic to the unique nature of each piece of wood.
keywords	Timber; pattern recognition; grain; image; carving ; digital fabrication
series	eCAADeSIGraDi
email
last changed	2022/06/07 07:56

_id	cf2019_036
id	cf2019_036
authors	Schwartz, Mathew
year	2019
title	Visualization of Occupant Behavior in an Open Academic Space through Image Analysis
source	Ji-Hyun Lee (Eds.) "Hello, Culture!" [18th International Conference, CAAD Futures 2019, Proceedings / ISBN 978-89-89453-05-5] Daejeon, Korea, p. 272
summary	Between agent simulation and circulation diagrams within design pedagogy, the prediction of occupant movement in space is integral to the informed design process. At the same time, trends in higher education have led to more open-ended spaces that are then studied for the unexpected ways in which students collaborate. These studies, by the unpredictable nature, must be done post-occupancy. In this paper, occupant behavior is visualized from an image dataset over a 9 day period in an open student environment. The methods for extracting behavior through this large dataset are presented. The results are then re?ected on in regard to the role of circulation diagrams for interior design and spatial planning.
keywords	occupant behavior, circulation, computation, post-occupancy evaluation, interior design
series	CAAD Futures
email
last changed	2019/07/29 14:15

_id	caadria2019_464
id	caadria2019_464
authors	Scott, Sophie, Doherty, Ben, Fabbri, Alessandra, Gardner, Nicole and Haeusler, M. Hank
year	2019
title	Discoverable Desks - Finding location and orientation in a mobile workplace
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. 653-662
doi	https://doi.org/10.52842/conf.caadria.2019.2.653
summary	The drive towards increasing productivity through collaborative ways of working has spurred a parallel trend in flexible and adaptable workplace environments. Mobile desks are one feasible solution to this but workplaces that adopt mobile desks risk creating spatial inefficiencies. These range from overcrowding or underutilization, to potential compliance issues in terms of fire egress requirements and health and safety regulations. While there is a need to understand mobile desking configurations there are currently no well-established ways to track the location and orientation of mobile desks within workplaces. Consequently, this paper describes a research project that adopts an action research methodology as an iterative and participatory framework to investigate and develop a unique method for capturing the location and orientation of freely moveable desks in an open workplace environment. This uses an ensemble of Bluetooth location beacons and computer vision techniques to provide a finer resolution than either method alone can currently provide. The demonstration of this ensemble method is the main contribution of this work. This paper demonstrates that combining these methods can enhance the advantages of each; computer vision gives higher resolution and beacons reduce the scope of the image search task
keywords	Indoor Positioning Systems; Office Space Planning; Location Data; Computer vision; activity-based working
series	CAADRIA
email
last changed	2022/06/07 07:56

_id	acadia19_392
id	acadia19_392
authors	Steinfeld, Kyle
year	2019
title	GAN Loci
source	ACADIA 19:UBIQUITY AND AUTONOMY [Proceedings of the 39th Annual Conference of the Association for Computer Aided Design in Architecture (ACADIA) ISBN 978-0-578-59179-7] (The University of Texas at Austin School of Architecture, Austin, Texas 21-26 October, 2019) pp. 392-403
doi	https://doi.org/10.52842/conf.acadia.2019.392
summary	This project applies techniques in machine learning, specifically generative adversarial networks (or GANs), to produce synthetic images intended to capture the predominant visual properties of urban places. We propose that imaging cities in this manner represents the first computational approach to documenting the Genius Loci of a city (Norberg-Schulz, 1980), which is understood to include those forms, textures, colors, and qualities of light that exemplify a particular urban location and that set it apart from similar places. Presented here are methods for the collection of urban image data, for the necessary processing and formatting of this data, and for the training of two known computational statistical models (StyleGAN (Karras et al., 2018) and Pix2Pix (Isola et al., 2016)) that identify visual patterns distinct to a given site and that reproduce these patterns to generate new images. These methods have been applied to image nine distinct urban contexts across six cities in the US and Europe, the results of which are presented here. While the product of this work is not a tool for the design of cities or building forms, but rather a method for the synthetic imaging of existing places, we nevertheless seek to situate the work in terms of computer-assisted design (CAD). In this regard, the project is demonstrative of a new approach to CAD tools. In contrast with existing tools that seek to capture the explicit intention of their user (Aish, Glynn, Sheil 2017), in applying computational statistical methods to the production of images that speak to the implicit qualities that constitute a place, this project demonstrates the unique advantages offered by such methods in capturing and expressing the tacit.
series	ACADIA
type	normal paper
email
last changed	2022/06/07 07:56

_id	ecaadesigradi2019_298
id	ecaadesigradi2019_298
authors	Zboinska, Malgorzata A.
year	2019
title	Artistic computational design featuring imprecision - A method supporting digital and physical explorations of esthetic features in robotic single-point incremental forming of polymer sheets
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. 719-728
doi	https://doi.org/10.52842/conf.ecaade.2019.1.719
summary	Design strategies that employ digital and material imprecision to achieve esthetic innovation exhibit high potential to transform the current precision-oriented practices of computation and digital fabrication in architecture. However, such strategies are still in their infancy. We present a design method facilitating intentionally-imprecise esthetic explorations within the framework of digital design and robotic single-point incremental forming. Our method gives access to the esthetic fine-tuning of molds from which architectural objects are cast. Semi-precise computational operations of extending, limiting, deepening and shallowing the geometrical deformations of the mold through robot toolpath fine-tuning are enabled by a digital toolkit featuring parametric modeling, surface curvature analyses, photogrammetry, digital photography and bitmap image retouching and painting. Our method demonstrates the shift of focus from geometric accuracy and control of material behaviors towards intentionally-imprecise digital explorations that yield novel esthetic features of architectural designs. By demonstrating the results of applying our method in the context of an exploration-driven design process, we argue that imprecision can be equally valid to accuracy, opening a vast, excitingly unknown territory for material-mediated esthetic explorations within digital fabrication. Such explorations can interestingly alter the esthetic canons and computational design methods of digital architecture in the nearest future.
keywords	Artistic architectural design; artistic digital crafting; creative robotics; material agency; fabrication inaccuracies; robotic single-point incremental forming of polymers
series	eCAADeSIGraDi
email
last changed	2022/06/07 07:57

_id	acadia19_380
id	acadia19_380
authors	Özel, Güvenç; Ennemoser, Benjamin
year	2019
title	Interdisciplinary AI
source	ACADIA 19:UBIQUITY AND AUTONOMY [Proceedings of the 39th Annual Conference of the Association for Computer Aided Design in Architecture (ACADIA) ISBN 978-0-578-59179-7] (The University of Texas at Austin School of Architecture, Austin, Texas 21-26 October, 2019) pp. 380- 391
doi	https://doi.org/10.52842/conf.acadia.2019.380
summary	Architecture does not exist in a vacuum. Its cultural, conceptual, and aesthetic agendas are constantly influenced by other visual and artistic disciplines ranging from film, photography, painting and sculpture to fashion, graphic and industrial design. The formal qualities of the cultural zeitgeist are perpetually influencing contemporary architectural aesthetics. In this paper, we aim to introduce a radical yet methodical approach toward regulating the relationship between human agency and computational form-making by using Machine Learning (ML) as a conceptual design tool for interdisciplinary collaboration and engagement. Through the use of a highly calibrated and customized ML systems that can classify and iterate stylistic approaches that exist outside the disciplinary boundaries of architecture, the technique allows for machine intelligence to design, coordinate, randomize, and iterate external formal and aesthetic qualities as they relate to pattern, color, proportion, hierarchy, and formal language. The human engagement in this design process is limited to the initial curation of input data in the form of image repositories of non-architectural disciplines that the Machine Learning system can extrapolate from, and consequently in regulating and choosing from the iterations of images the Artificial Neural Networks are capable of producing. In this process the architect becomes a curator that samples and streamlines external cultural influences while regulating their significance and weight in the final design. By questioning the notion of human agency in the design process and providing creative license to Artificial Intelligence in the conceptual design phase, we aim to develop a novel approach toward human-machine collaboration that rejects traditional notions of disciplinary autonomy and streamlines the influence of external aesthetic disciplines on contemporary architectural production.
series	ACADIA
type	normal paper
email
last changed	2022/06/07 07:57

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