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	caadria2018_056
id	caadria2018_056
authors	Chirkin, Artem, Pishniy, Maxim and Sender, Arina
year	2018
title	Generilized Visibility-Based Design Evaluation Using GPU
source	T. Fukuda, W. Huang, P. Janssen, K. Crolla, S. Alhadidi (eds.), Learning, Adapting and Prototyping - Proceedings of the 23rd CAADRIA Conference - Volume 2, Tsinghua University, Beijing, China, 17-19 May 2018, pp. 483-492
doi	https://doi.org/10.52842/conf.caadria.2018.2.483
summary	Visibility plays an important role in perception and use of an urban design, and thus often becomes a target of design analysis. This work presents a fast method of evaluating various visibility-based design characteristics, such as isovists or insolation exploiting the GPU rendering pipeline and compute shaders. The proposed method employs a two-stage algorithm on each point of interest. First, it projects the visible space around a vantage point onto an equirectangular map. Second, it folds the map using a flexibly defined function into a single value that is associated with the vantage point. Being executed on a grid of points in a 3D scene, it can be visualized as a heat map or utilized by another algorithm for further design analysis. The developed system provides nearly real-time analysis tools for an early-stage design process to a broad audience via web services.
keywords	design analysis; design evaluation; GPU; isovist; insolation
series	CAADRIA
email
last changed	2022/06/07 07:55

_id	caadria2018_062
id	caadria2018_062
authors	Narengerel, Amartuvshin, Hong, Sukjoo, Lee, Chae-Seok and Lee, Ji-Hyun
year	2018
title	FBSMAP: The Spatial Representation Method for Intelligent Semantic Service in Indoor Environment
source	T. Fukuda, W. Huang, P. Janssen, K. Crolla, S. Alhadidi (eds.), Learning, Adapting and Prototyping - Proceedings of the 23rd CAADRIA Conference - Volume 2, Tsinghua University, Beijing, China, 17-19 May 2018, pp. 587-596
doi	https://doi.org/10.52842/conf.caadria.2018.2.587
summary	In order to provide intelligent services in complex and diverse indoor environments, it is necessary to understand spatial features of indoor objects: furniture and items. Function-Behavior-Structure Map (FBSMAP), which is a novel indoor representation method that focuses on space functionality for intelligent semantic services, is introduced in this study. The three steps of FBSMAP are defining spatial components, constructing semantic map for indoor environment, and securing spatial features. This novel implementation method is implemented and examined on 3D house models.
keywords	Indoor Representation Method; Semantic Space; Spatial Subdivision; IndoorGML; Furniture Semantics
series	CAADRIA
email
last changed	2022/06/07 07:58

_id	sigradi2018_1364
id	sigradi2018_1364
authors	Nunes de Vasconcelos, Guilherme; de Sousa Van Stralen, Mateus; Menezes, Alexandre; Gontijo Ramos, Fernando Murilo
year	2018
title	Perceive to learn to perceive: an experience with virtual reality devices for architecture design learning
source	SIGraDi 2018 [Proceedings of the 22nd Conference of the Iberoamerican Society of Digital Graphics - ISSN: 2318-6968] Brazil, São Carlos 7 - 9 November 2018, pp. 985-990
summary	This work investigates the potential use of low-cost virtual reality (VR) devices in architectural education to improve spatial perception of undergraduate architecture students. The experiment involved a gradual approach into the design process, starting with an intervention on a physical space, its bidimensional representation, 3d modelling and immersion in VR. After the immersion, students answered a questionnaire with open and closed-questions about their experience, and their evaluation of the use of VR in the designing. The findings point to the use of VR as a means to explore, perceive and reflect on decisions, allowing students a better understanding of designing.
keywords	Virtual reality; Architectural design; Architecture teaching; Representation; Low-cost devices
series	SIGRADI
email
last changed	2021/03/28 19:59

_id	caadria2018_316
id	caadria2018_316
authors	Yan, Chao, Zhang, Yunyu, Yuan, Philip F. and Yao, Jiawei
year	2018
title	Virtual Motion - Shifting Perspective as an Instrument for Geometrical Construction
source	T. Fukuda, W. Huang, P. Janssen, K. Crolla, S. Alhadidi (eds.), Learning, Adapting and Prototyping - Proceedings of the 23rd CAADRIA Conference - Volume 2, Tsinghua University, Beijing, China, 17-19 May 2018, pp. 471-480
doi	https://doi.org/10.52842/conf.caadria.2018.2.471
summary	From the invention of projection to the emergence of digital technology, there's a clear correspondences among the transformations of visual representation paradigm in art, the developments of design instrument in architecture, and the human perception of time/space. Base on the examination of this particular historical trajectory, this paper focuses the working mechanism of shifting perspective as an alternative design instrument to explore the possibility of embedding time and motion into static form in digital age. Firstly, the paper reviews how the shifting perspective was introduced to represent space in modern western painting and photography. Then based on the research on shifting perspective, the paper develops a design tool, which would be able to translate motion into the particular geometrical feature of a generated 3D object. In the end, the paper brings further discussions about the formal and spatial effects brought by this new tool, and its potential to incorporate the perceptive image of human being into design process.
keywords	Shape Study; Projective Geometry; Shifting Perspective; Motion; Time Dimension
series	CAADRIA
email
last changed	2022/06/07 07:57

_id	caadria2018_132
id	caadria2018_132
authors	Yan, Chao
year	2018
title	"Real Virtuality" in the Process of Digitally Embedded Perception
source	T. Fukuda, W. Huang, P. Janssen, K. Crolla, S. Alhadidi (eds.), Learning, Adapting and Prototyping - Proceedings of the 23rd CAADRIA Conference - Volume 1, Tsinghua University, Beijing, China, 17-19 May 2018, pp. 91-100
doi	https://doi.org/10.52842/conf.caadria.2018.1.091
summary	The "digital turn" in architecture is ontologically drawn from Deleuzian philosophy, particularly the thinking defined by Manuel Delanda as real virtuality. This philosophical thinking reflects the essential paradigm of digital design-a generative process driven by intensive difference to approach the singularity of form in a space of possibilities. However, no matter how dynamic the design process is in digital software, the construction result of a building is unavoidably static and permanent. Thus, the essence of digital design will always be misaligned with the material reality of its production. Addressing on this confliction, the research is trying to rethink the philosophical term "real virtuality" in the process of human perception. By examining different theories about the anti-static condition of perception, it forms a novel perspective to address the dynamic relationship between building form, virtual "information" and human perception, and extends the productivity of "becoming" from digital design process to the process of building colonization.
keywords	Digital Design Theory; Real Virtuality; New Materialism; Perception; Visual Uncertainty
series	CAADRIA
email
last changed	2022/06/07 07:57

_id	acadia18_186
id	acadia18_186
authors	Yin, Hao; Guo, Zhe; Zhao, Yao; Yuan, Philip F.
year	2018
title	Behavior Visualization System Based on UWB Positioning Technology
source	ACADIA // 2018: Recalibration. On imprecisionand infidelity. [Proceedings of the 38th Annual Conference of the Association for Computer Aided Design in Architecture (ACADIA) ISBN 978-0-692-17729-7] Mexico City, Mexico 18-20 October, 2018, pp. 186-195
doi	https://doi.org/10.52842/conf.acadia.2018.186
summary	This paper takes behavioral performance as a starting point and uses ultra-wideband (UWB) positioning technology and visualization methods to accurately collect and present in-place behavioral data so as to explore the behavioral characteristics of space users. In this process, we learned the observation, quantification, and presentation of behavioral data from the evolution of behavioral research. Secondly, after a comparative analysis of four types of indoor positioning technologies, we selected UWB-positioning technology and the JavaScript programming language as the development tools for a behavior visualization system. Next, we independently developed the behavior visualization system, which required a deep understanding of the working principle of UWB technology and the visualization method of the JavaScript programming language. Finally, the system was applied to an actual space, collecting and presenting users’ behavioral characteristics and habits in order to verify the applicability of the system in the field of behavioral research.
keywords	full paper, design tools, ai + machine learning, big data, behavioral performance + simulation
series	ACADIA
type	paper
email
last changed	2022/06/07 07:57

_id	caadria2018_217
id	caadria2018_217
authors	Zhang, Le-Min, Jeng, Tay-Sheng and Zhang, Ruo-Xi
year	2018
title	Integration of Virtual Reality, 3-D Eye-Tracking, and Protocol Analysis for Re-Designing Street Space
source	T. Fukuda, W. Huang, P. Janssen, K. Crolla, S. Alhadidi (eds.), Learning, Adapting and Prototyping - Proceedings of the 23rd CAADRIA Conference - Volume 1, Tsinghua University, Beijing, China, 17-19 May 2018, pp. 431-440
doi	https://doi.org/10.52842/conf.caadria.2018.1.431
summary	The objective of this paper is to develop an eye-tracking technology combined with a virtual reality system for an experimental study of an historical street design. Using protocol analysis, a set of design objects, parameters, and subjects are randomly selected for evaluation of the virtual street space of an ancient city. 3-D point-cloud data of spatial behaviors are tracked and analyzed. It is concluded that people with different cultural backgrounds each have a considerably different perception of the street space's characteristics. The methodology described in this paper can be used for spatial design of urban space in the future.
keywords	Virtual Reality; Eye-Tracking; Protocol Analysis; Street Space
series	CAADRIA
email
last changed	2022/06/07 07:57

_id	caadria2018_211
id	caadria2018_211
authors	Zhao, Yao, Guo, Zhe, Yin, Hao, Yao, Jiawei and Yuan, Philip F.
year	2018
title	Behavioral Data Analysis and Visualization System Base on UWB Interior Positioning Technology
source	T. Fukuda, W. Huang, P. Janssen, K. Crolla, S. Alhadidi (eds.), Learning, Adapting and Prototyping - Proceedings of the 23rd CAADRIA Conference - Volume 2, Tsinghua University, Beijing, China, 17-19 May 2018, pp. 217-226
doi	https://doi.org/10.52842/conf.caadria.2018.2.217
summary	The behavioral patterns of human in buildings influence the rational setting of space and function dramatically. However, due to the lack of data acquisition methods and data accuracy, big data analysis and visualization research in the microscopic aspects of indoor space is hampered. With the maturity of indoor positioning technology, UWB (Ultra Wideband) positioning technology based on narrow pulse has the characteristics of high transmission rate, low transmit power and strong penetrating ability, which provides more accurate results for the behavior data acquisition in indoor space. In this research, the big data thinking has been introduced into the behavioral performance analysis process. Therefore, data acquisition, data storage and management, behavioral data visualization and machine learning algorithms are integrated into a set of behavioral data analysis and visualization system, to quantitative research the behavioral characteristics of visitors in the exhibition hall by the on-site experiment .
keywords	UWB interior positioning technology; Behavior Data Visualization; on-site experiment
series	CAADRIA
email
last changed	2022/06/07 07:57

_id	ijac201816406
id	ijac201816406
authors	As, Imdat; Siddharth Pal and Prithwish Basu
year	2018
title	Artificial intelligence in architecture: Generating conceptual design via deep learning
source	International Journal of Architectural Computing vol. 16 - no. 4, 306-327
summary	Artificial intelligence, and in particular machine learning, is a fast-emerging field. Research on artificial intelligence focuses mainly on image-, text- and voice-based applications, leading to breakthrough developments in self-driving cars, voice recognition algorithms and recommendation systems. In this article, we present the research of an alternative graph- based machine learning system that deals with three-dimensional space, which is more structured and combinatorial than images, text or voice. Specifically, we present a function-driven deep learning approach to generate conceptual design. We trained and used deep neural networks to evaluate existing designs encoded as graphs, extract significant building blocks as subgraphs and merge them into new compositions. Finally, we explored the application of generative adversarial networks to generate entirely new and unique designs.
keywords	Architectural design, conceptual design, deep learning, artificial intelligence, generative design
series	journal
email
last changed	2019/08/07 14:04

_id	caadria2018_342
id	caadria2018_342
authors	Bhagat, Nikita, Rybkowski, Zofia, Kalantar, Negar, Dixit, Manish, Bryant, John and Mansoori, Maryam
year	2018
title	Modulating Natural Ventilation to Enhance Resilience Through Modifying Nozzle Profiles - Exploring Rapid Prototyping Through 3D-Printing
source	T. Fukuda, W. Huang, P. Janssen, K. Crolla, S. Alhadidi (eds.), Learning, Adapting and Prototyping - Proceedings of the 23rd CAADRIA Conference - Volume 2, Tsinghua University, Beijing, China, 17-19 May 2018, pp. 185-194
doi	https://doi.org/10.52842/conf.caadria.2018.2.185
summary	The study aimed to develop and test an environmentally friendly, easily deployable, and affordable solution for socio-economically challenged populations of the world. 3D-printing (additive manufacturing) was used as a rapid prototyping tool to develop and test a façade system that would modulate air velocity through modifying nozzle profiles to utilize natural cross ventilation techniques in order to improve human comfort in buildings. Constrained by seasonal weather and interior partitions which block the ability to cross ventilate, buildings can be equipped to perform at reduced energy loads and improved internal human comfort by using a façade system composed of retractable nozzles developed through this empirical research. This paper outlines the various stages of development and results obtained from physically testing different profiles of nozzle-forms that would populate the façade system. In addition to optimizing nozzle profiles, the team investigated the potential of collapsible tube systems to permit precise placement of natural ventilation directed at occupants of the built space.
keywords	Natural ventilation; Wind velocity; Rapid prototyping; 3D-printing; Nozzle profiles
series	CAADRIA
email
last changed	2022/06/07 07:52

_id	acadia18_176
id	acadia18_176
authors	Bidgoli, Ardavan; Veloso,Pedro
year	2018
title	DeepCloud. The Application of a Data-driven, Generative Model in Design
source	ACADIA // 2018: Recalibration. On imprecisionand infidelity. [Proceedings of the 38th Annual Conference of the Association for Computer Aided Design in Architecture (ACADIA) ISBN 978-0-692-17729-7] Mexico City, Mexico 18-20 October, 2018, pp. 176-185
doi	https://doi.org/10.52842/conf.acadia.2018.176
summary	Generative systems have a significant potential to synthesize innovative design alternatives. Still, most of the common systems that have been adopted in design require the designer to explicitly define the specifications of the procedures and in some cases the design space. In contrast, a generative system could potentially learn both aspects through processing a database of existing solutions without the supervision of the designer. To explore this possibility, we review recent advancements of generative models in machine learning and current applications of learning techniques in design. Then, we describe the development of a data-driven generative system titled DeepCloud. It combines an autoencoder architecture for point clouds with a web-based interface and analog input devices to provide an intuitive experience for data-driven generation of design alternatives. We delineate the implementation of two prototypes of DeepCloud, their contributions, and potentials for generative design.
keywords	full paper, design tools software computing + gaming, ai & machine learning, generative design, autoencoders
series	ACADIA
type	paper
email
last changed	2022/06/07 07:52

_id	ecaade2018_164
id	ecaade2018_164
authors	Chang, Mei-Chih, Buš, Peter, Tartar, Ayça, Chirkin, Artem and Schmitt, Gerhard
year	2018
title	Big-Data Informed Citizen Participatory Urban Identity Design
source	Kepczynska-Walczak, A, Bialkowski, S (eds.), Computing for a better tomorrow - Proceedings of the 36th eCAADe Conference - Volume 2, Lodz University of Technology, Lodz, Poland, 19-21 September 2018, pp. 669-678
doi	https://doi.org/10.52842/conf.ecaade.2018.2.669
summary	The identity of an urban environment is important because it contributes to self-identity, a sense of community, and a sense of place. However, under present-day conditions, the identities of expanding cities are rapidly deteriorating and vanishing, especially in the case of Asian cities. Therefore, cities need to build their urban identity, which includes the past and points to the future. At the same time, cities need to add new features to improve their livability, sustainability, and resilience. In this paper, using data mining technologies for various types of geo-referenced big data and combine them with the space syntax analysis for observing and learning about the socioeconomic behavior and the quality of space. The observed and learned features are identified as the urban identity. The numeric features obtained from data mining are transformed into catalogued levels for designers to understand, which will allow them to propose proper designs that will complement or improve the local traditional features. A workshop in Taiwan, which focuses on a traditional area, demonstrates the result of the proposed methodology and how to transform a traditional area into a livable area. At the same time, we introduce a website platform, Quick Urban Analysis Kit (qua-kit), as a tool for citizens to participate in designs. After the workshop, citizens can view, comment, and vote on different design proposals to provide city authorities and stakeholders with their ideas in a more convenient and responsive way. Therefore, the citizens may deliver their opinions, knowledge, and suggestions for improvements to the investigated neighborhood from their own design perspective.
keywords	Urban identity; unsupervised machine learning; Principal Component Analysis (PCA); citizen participated design; space syntax
series	eCAADe
email
last changed	2022/06/07 07:56

_id	caadria2018_052
id	caadria2018_052
authors	Fung, Enrica and Crolla, Kristof
year	2018
title	Choreographed Architecture - Body-Spatial Exploration
source	T. Fukuda, W. Huang, P. Janssen, K. Crolla, S. Alhadidi (eds.), Learning, Adapting and Prototyping - Proceedings of the 23rd CAADRIA Conference - Volume 1, Tsinghua University, Beijing, China, 17-19 May 2018, pp. 101-110
doi	https://doi.org/10.52842/conf.caadria.2018.1.101
summary	This paper presents a design-methodological case study that looks into the practical expansion of conventional conceptual architectural design media by incorporating contemporary technology of motion capture. It discusses challenges of integrating dance movement as a real-time input parameter for architectural design that aims at translating body motion into space. The paper consists of four parts, beginning with a historic background overview of scientists, physiologists, artists, choreographers, and architects who have attempted capturing body motion and turning the motion into space. The second part of the paper discusses the iterative development of the 'Dance Machine' as a methodological tool for the integration of motion capture into conceptual architectural design. Thirdly, the paper discusses tested design applications of the 'Dance Machine' by looking at two sited applications. Finally, the overall methodology is critically assessed and discussed in the light of continuous development of creative applications of motion capturing technology. The paper concludes by highlighting the architectural potential found in specific qualities of dance and by advocating for a broader palette of tools, techniques, and input methods for the conceptual design of architecture.
keywords	Choreographed architecture; Motion capture; Conceptual design media; Space design; Human body
series	CAADRIA
email
last changed	2022/06/07 07:50

_id	caadria2018_010
id	caadria2018_010
authors	Han, Lu and Cardoso Llach, Daniel
year	2018
title	Ludi: A Concurrent Physical and Digital Modeling Environment
source	T. Fukuda, W. Huang, P. Janssen, K. Crolla, S. Alhadidi (eds.), Learning, Adapting and Prototyping - Proceedings of the 23rd CAADRIA Conference - Volume 1, Tsinghua University, Beijing, China, 17-19 May 2018, pp. 515-523
doi	https://doi.org/10.52842/conf.caadria.2018.1.515
summary	This paper explores the potential of a concurrent physical and digital modeling environment. We describe a prototype for a novel design modeling interface where users can take advantage of the affordances of both physical and digital modeling environments, and work back and forth between the two. Using Processing, along with the Kinect depth sensor, the system uses depth data read from a physical modeling space to produce an enhanced digital representation in real time. Users can design by moving and stacking wooden blocks in a physical space, which is represented (and enhanced) digitally as a "voxel space," which can in turn be edited digitally. The result is a proof-of-concept concurrent physical and digital modeling environment combining design affordances specific to each media: the physical space offers tactile and embodied forms of design inter-action, and the digital space offers parametric editing capabilities, along with the capacity to view the modeling space from different perspectives, and perform basic analyses on designs. Following a brief review of experimental computational and tangible interaction design interfaces, the paper discusses the system's implementation, its limitations, and future steps.
keywords	Computational Design; Processing; Concurrent Modeling Environment; Tangible Interaction
series	CAADRIA
email
last changed	2022/06/07 07:50

_id	acadia20_382
id	acadia20_382
authors	Hosmer, Tyson; Tigas, Panagiotis; Reeves, David; He, Ziming
year	2020
title	Spatial Assembly with Self-Play Reinforcement Learning
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. 382-393.
doi	https://doi.org/10.52842/conf.acadia.2020.1.382
summary	We present a framework to generate intelligent spatial assemblies from sets of digitally encoded spatial parts designed by the architect with embedded principles of prefabrication, assembly awareness, and reconfigurability. The methodology includes a bespoke constraint-solving algorithm for autonomously assembling 3D geometries into larger spatial compositions for the built environment. A series of graph-based analysis methods are applied to each assembly to extract performance metrics related to architectural space-making goals, including structural stability, material density, spatial segmentation, connectivity, and spatial distribution. Together with the constraint-based assembly algorithm and analysis methods, we have integrated a novel application of deep reinforcement (RL) learning for training the models to improve at matching the multiperformance goals established by the user through self-play. RL is applied to improve the selection and sequencing of parts while considering local and global objectives. The user’s design intent is embedded through the design of partial units of 3D space with embedded fabrication principles and their relational constraints over how they connect to each other and the quantifiable goals to drive the distribution of effective features. The methodology has been developed over three years through three case study projects called ArchiGo (2017–2018), NoMAS (2018–2019), and IRSILA (2019-2020). Each demonstrates the potential for buildings with reconfigurable and adaptive life cycles.
series	ACADIA
type	paper
email
last changed	2023/10/22 12:06

_id	acadia18_232
id	acadia18_232
authors	Kilian, Axel
year	2018
title	The Flexing Room Architectural Robot. An Actuated Active-Bending Robotic Structure using Human Feedback
source	ACADIA // 2018: Recalibration. On imprecisionand infidelity. [Proceedings of the 38th Annual Conference of the Association for Computer Aided Design in Architecture (ACADIA) ISBN 978-0-692-17729-7] Mexico City, Mexico 18-20 October, 2018, pp. 232-241
doi	https://doi.org/10.52842/conf.acadia.2018.232
summary	Advances in autonomous control of object-scale robots, both anthropomorphic and vehicular, are posing new human–machine interface challenges. In architecture, very few examples of autonomous inhabitable robotic architecture exist. A number of factors likely contribute to this condition, among them the scale and cost of architectural adaptive systems, but on a more fundamental conceptual level also the questions of how architectural robots would communicate with their human inhabitants. The Flexing Room installation is a room-sized actuated active-bending skeleton structure. It uses rudimentary social feedback by counting people to inform its behavior in the form of actuated poses of the room enclosure. An operational full-scale prototype was constructed and tested. To operate it no geometric-based simulation was used; the only communication between computer and structure was in sending values for the air pressure settings and in gathering sensor feedback. The structure’s physical state was resolved through the embodied computation of its interconnected parts, and the people-counting sensor feedback influences its next action. Future work will explore the development of learning processes to improve the human–machine coexistence in space.
keywords	full paper, fabrication & robotics, non-production robotics, materials/adaptive systems, flexible structures
series	ACADIA
type	paper
email
last changed	2022/06/07 07:52

_id	caadria2018_297
id	caadria2018_297
authors	Kim, Eonyong
year	2018
title	Field Survey System for Facility Management Using BIM Model - IoT Management for Facility Management
source	T. Fukuda, W. Huang, P. Janssen, K. Crolla, S. Alhadidi (eds.), Learning, Adapting and Prototyping - Proceedings of the 23rd CAADRIA Conference - Volume 2, Tsinghua University, Beijing, China, 17-19 May 2018, pp. 535-544
doi	https://doi.org/10.52842/conf.caadria.2018.2.535
summary	Combining IoT technology with the BIM paradigm can enhance the data collection that BIM strives for by enabling real-time monitoring of building conditions. This data collection can be used very effectively for managing facilities. However, many IoT devices must be installed in buildings to achieve such results and therefore, a management system is required. The purpose of this study is to suggest an IoT management system that uses the drawing information extracted from a BIM model to allow effective management from initial installation of IoT devices to maintenance. In the pursuit of this purpose, a converter and an IoT device which developed in the research is used. The converter extracts space information and 2D floor drawing from BIM model and the IoT device is developed based on ESP 8266 chip which consist of one computer and WIFI module. To store the data which collected by the IoT devices, IoT service of AWS(Amazon Web Service) is used.
keywords	Facility Management; IoT; Management System; BIM
series	CAADRIA
email
last changed	2022/06/07 07:52

_id	acadia18_166
id	acadia18_166
authors	Kvochick, Tyler
year	2018
title	Sneaky Spatial Segmentation. Reading Architectural Drawings with Deep Neural Networks and Without Labeling Data
source	ACADIA // 2018: Recalibration. On imprecisionand infidelity. [Proceedings of the 38th Annual Conference of the Association for Computer Aided Design in Architecture (ACADIA) ISBN 978-0-692-17729-7] Mexico City, Mexico 18-20 October, 2018, pp. 166-175
doi	https://doi.org/10.52842/conf.acadia.2018.166
summary	Currently, it is nearly impossible for an artificial neural network to generalize a task from very few examples. Humans, however, excel at this. For instance, it is not necessary for a designer to see thousands or millions of unique examples of how to place a given drawing symbol in a way that meets the economic, aesthetic, and performative goals of the project. In fact, the goals can be (and usually are) communicated abstractly in natural language. Machine learning (ML) models, however, do need numerous examples. The methods that we explore here are an attempt to circumvent this in order to make ML models more immediately useful. In this work, we present progress on the application of contemporary ML techniques to the design process in the architecture, engineering, and construction (AEC) industry. We introduce a technique to partially circumvent the data hungriness of neural networks, which is a significant impediment to their application outside of the ML research community. We also show results on the applicability of this technique to real-world drawings and present research that addresses how some fundamental attributes of drawings as images affect the way they are interpreted in deep neural networks. Our primary contribution is a technique to train a neural network to segment real-world architectural drawings after using only generated pseudodrawings.
keywords	full paper, representation + perception, computation, ai & machine learning
series	ACADIA
type	paper
email
last changed	2022/06/07 07:51

_id	caadria2018_174
id	caadria2018_174
authors	Lagemann, Dennis
year	2018
title	The Syntopy - An Information-Based Model of Space
source	T. Fukuda, W. Huang, P. Janssen, K. Crolla, S. Alhadidi (eds.), Learning, Adapting and Prototyping - Proceedings of the 23rd CAADRIA Conference - Volume 2, Tsinghua University, Beijing, China, 17-19 May 2018, pp. 443-452
doi	https://doi.org/10.52842/conf.caadria.2018.2.443
summary	The paper argues that Modernism has produced a manifoldness of theories about spaces or spatial configurations which resemble valuable facets. Yet, they all shed a light on single aspects of spatiality. This raises the question if not in the age of information, there could be a common ground for theories of space that might serve as a model to purport a more general view. Speaking with French philosopher Michel Serres, when the old model of time collapsed at the end of Modernity, it has left the underlying concepts as scattered elements to the beginning of Modernism. The most promising approach to reconcile these elements in spatiotemporality appears to be Category Theory in mathematics. It defines four categorically differentiated domains which exactly resemble the scattered elements. In search for a common ground to build up a new model, the Syntopy is being developed for thinking space, based on the way information is encoded within these four domains.
keywords	Space; Information and Data; Lambda Calculus; Topography and Topology; Synthesis
series	CAADRIA
email
last changed	2022/06/07 07:52

_id	caadria2018_302
id	caadria2018_302
authors	Lee, Alric, Tei, Hirokazu and Hotta, Kensuke
year	2018
title	Body-Borne Assistive Robots for Human-Dependent Precision Construction - The Compensation of Human Imprecision in Navigating 3-Dimensional Space with a Stand-Alone, Adaptive Robotic System
source	T. Fukuda, W. Huang, P. Janssen, K. Crolla, S. Alhadidi (eds.), Learning, Adapting and Prototyping - Proceedings of the 23rd CAADRIA Conference - Volume 1, Tsinghua University, Beijing, China, 17-19 May 2018, pp. 545-554
doi	https://doi.org/10.52842/conf.caadria.2018.1.545
summary	The rapid growth of complex contemporary architecture design, contributed by the advance in parametric CAD/CAM software, is accompanied by challenges in the production process; it demands both highly trained workers and technical equipments. This paper reviews current technologies in robotics-aided construction and wearable computers for generic purposes, and proposes the design of a robotic device for construction guidance. It guides the user, the worker, through the assembly process of precision modular constructions, by providing procedural mechanical or haptic assistance in the 3-dimensional positioning of building components. The device is designed to be wearable, portable, and operable as a completely stand-alone system that requires no external infrastructure. A prototype of the device is tested with a mock-up masonry construction experiment, the result of which is reported in this paper, along with discussion for future improvement and application opportunities within the context of highly developed, condensed Japanese urban environments. A greater objective of this paper is to bridge current studies in Human-Computer Interaction (HCI) and digital fabrication in architecture and promote the potentials of human workers in future construction scenes.
keywords	digital fabrication; human-computer interaction; 3d positioning; wearable robotics; guided construction
series	CAADRIA
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last changed	2022/06/07 07:52

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