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	acadia18_156
id	acadia18_156
authors	Huang, Weixin; Zheng, Hao
year	2018
title	Architectural Drawings Recognition and Generation through Machine Learning
doi	https://doi.org/10.52842/conf.acadia.2018.156
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. 156-165
summary	With the development of information technology, the ideas of programming and mass calculation were introduced into the design field, resulting in the growth of computer- aided design. With the idea of designing by data, we began to manipulate data directly, and interpret data through design works. Machine Learning as a decision making tool has been widely used in many fields. It can be used to analyze large amounts of data and predict future changes. Generative Adversarial Network (GAN) is a model framework in machine learning. It’s specially designed to learn and generate output data with similar or identical characteristics. Pix2pixHD is a modified version of GAN that learns image data in pairs and generates new images based on the input. The author applied pix2pixHD in recognizing and generating architectural drawings, marking rooms with different colors and then generating apartment plans through two convolutional neural networks. Next, in order to understand how these networks work, the author analyzed their framework, and provided an explanation of the three working principles of the networks, convolution layer, residual network layer and deconvolution layer. Lastly, in order to visualize the networks in architectural drawings, the author derived data from different layer and different training epochs, and visualized the findings as gray scale images. It was found that the features of the architectural plan drawings have been gradually learned and stored as parameters in the networks. As the networks get deeper and the training epoch increases, the features in the graph become more concise and clearer. This phenomenon may be inspiring in understanding the designing behavior of humans.
keywords	full paper, design study, generative design, ai + machine learning, ai & machine learning
series	ACADIA
type	paper
email
last changed	2022/06/07 07:49

_id	ecaade2018_399
id	ecaade2018_399
authors	Cutellic, Pierre
year	2018
title	UCHRON - An Event-Based Generative Design Software Implementing Fast Discriminative Cognitive Responses from Visual ERP BCI
doi	https://doi.org/10.52842/conf.ecaade.2018.2.131
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. 131-138
summary	This research aims at investigating BCI technologies in the broad scope of CAAD applications exploiting early visual cognition in computational design. More precisely, this paper will describe the investigation of key BCI and ML components for the implementation and development of a software supporting this research : Uchron. It will be organised as follows. Firstly, it will introduce the pursued interest and contribution that visual-ERP EEG based BCI application for Generative Design may provide through a synthetic review of precedents and BCI technology. Secondly, selected BCI components will be described and a methodology will be presented to provide an appropriate framework for a CAAD software approach. This section main focus is on the processing component of the BCI. It distinguishes two key aspects of discrimination and generation in its design and proposes a new model based on GAN for modulated adversarial design. Emphasis will be made on the explicit use of inference loops integrating fast human cognitive responses and its individual capitalisation through time in order to reflect towards the generation of design and architectural features.
keywords	Human Computer Interaction; Neurodesign; Generative Design; Design Computing and Cognition; Machine Learning
series	eCAADe
email
last changed	2022/06/07 07:56

_id	caadria2018_197
id	caadria2018_197
authors	Rogers, Jessie, Schnabel, Marc Aurel and Lo, Tian Tian
year	2018
title	Digital Culture - An Interconnective Design Methodology Ecosystem
doi	https://doi.org/10.52842/conf.caadria.2018.1.493
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. 493-502
summary	Transitioning away from traditional design methodology, for example, paper sketching, CAAD works, and 'flat screen' rendering, this paper proposes a new methodological ecosystem of which tests its validity within a studio-based case study. The focus will prove whether dynamic implementation and interconnectivity of evolving design tools can create richness and complexity of a design outcome through arbitrary phases of a generative design methodology ecosystem. Processes tested include combinations of agent simulations, artistic image processing analysis, site photogrammetry, 3D immersive sketching both abstract and to site-scale, parametric design generation, and virtual reality style presentations. Enhancing the process of design with evolving techniques in a generative way which dynamically interconnects will stimulate a digital culture of design generation that includes new aspects of interest and introduces innovative opportunities within all corners of the architectural realm. Methodology components within this ecosystem of interaction prove that the architecture cannot be as rich and complex without the utilisation of all strengths within each unique design tool.
keywords	Methodology Ecosystem; Simulation; Immersive; Virtual Reality; Photogrammetry
series	CAADRIA
email
last changed	2022/06/07 07:56

_id	ecaade2018_370
id	ecaade2018_370
authors	Abdelmohsen, Sherif, Massoud, Passaint, El-Dabaa, Rana, Ibrahim, Aly and Mokbel, Tasbeh
year	2018
title	A Computational Method for Tracking the Hygroscopic Motion of Wood to develop Adaptive Architectural Skins
doi	https://doi.org/10.52842/conf.ecaade.2018.2.253
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. 253-262
summary	Low-cost programmable materials such as wood have been utilized to replace mechanical actuators of adaptive architectural skins. Although research investigated ways to understand the hygroscopic response of wood to variations in humidity levels, there are still no clear methods developed to track and analyze such response. This paper introduces a computational method to analyze, track and store the hygroscopic response of wood through image analysis and continuous tracking of angular measurements in relation to time. This is done through a computational closed loop that links the smart material interface (SMI) representing hygroscopic response with a digital and tangible interface comprising a Flex sensor, Arduino kit, and FireFly plugin. Results show no significant difference between the proposed sensing mechanism and conventional image analysis tracking systems. Using the described method, acquiring real-time data can be utilized to develop learning mechanisms and predict the controlled motion of programmable material for adaptive architectural skins.
keywords	Hygroscopic properties of wood; Adaptive architecture; Programmable materials; Real-time tracking
series	eCAADe
email
last changed	2022/06/07 07:54

_id	acadia18_216
id	acadia18_216
authors	Ahrens, Chandler; Chamberlain, Roger; Mitchell, Scott; Barnstorff, Adam
year	2018
title	Catoptric Surface
doi	https://doi.org/10.52842/conf.acadia.2018.216
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. 216-225
summary	The Catoptric Surface research project explores methods of reflecting daylight through a building envelope to form an image-based pattern of light on the interior environment. This research investigates the generation of atmospheric effects from daylighting projected onto architectural surfaces within a built environment in an attempt to amplify or reduce spatial perception. The mapping of variable organizations of light onto existing or new surfaces creates a condition where the perception of space does not rely on form alone. This condition creates a visual effect of a formless atmosphere and affects the way people use the space. Often the desired quantity and quality of daylight varies due to factors such as physiological differences due to age or the types of tasks people perform (Lechner 2009). Yet the dominant mode of thought toward the use of daylighting tends to promote a homogeneous environment, in that the resulting lighting level is the same throughout a space. This research project questions the desire for uniform lighting levels in favor of variegated and heterogeneous conditions. The main objective of this research is the production of a unique facade system that is capable of dynamically redirecting daylight to key locations deep within a building. Mirrors in a vertical array are individually adjusted via stepper motors in order to reflect more or less intense daylight into the interior space according to sun position and an image-based map. The image-based approach provides a way to specifically target lighting conditions, atmospheric effects, and the perception of space.
keywords	full paper, non-production robotics, representation + perception, performance + simulation, building technologies
series	ACADIA
type	paper
email
last changed	2022/06/07 07:54

_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_008
id	caadria2018_008
authors	Crolla, Kristof, Cheng, Paul Hung Hon, Chan, Ding Yuen Shan, Chan, Arthur Ngo Foon and Lau, Darwin
year	2018
title	Inflatable Architecture Production with Cable-Driven Robots
doi	https://doi.org/10.52842/conf.caadria.2018.1.009
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. 9-18
summary	This paper argues for alternative methods for the in-situ integration of robotics in architectural construction. Rather than promoting off-site pre-fabrication through industrial robot applications, it advocates for suspended, light-weight, cable-driven robots that allow flexible and safe onsite implementation. This paper uses the topic of large-scale inflatable architectural realisation as a study case to test the application of such a robot, here with a laser-cutter as end-effecter. This preliminary study covers the design, development, prototyping, and practical testing of an inherently scale-less cable-driven laser-cutter setup. This setup allows for the non-size specific cutting of inflatable structures' components which can be designed with common physics simulation engines. The developed robotic proof of concept forms the basis for several further and future study possibilities that merge the field of architectural design and implementation with mechanical and automation engineering.
keywords	Cable-driven robots; In-situ robotic fabrication; Large-scale fabrication; Inflatable architecture; Cross-disciplinarily
series	CAADRIA
email
last changed	2022/06/07 07:56

_id	ecaade2018_297
id	ecaade2018_297
authors	Elesawy, Amr, Caranovic, Stefan, Zarb, Justin, Jayathissa, Prageeth and Schlueter, Arno
year	2018
title	HIVE Parametric Tool - A simplified energy simulation tool for educating architecture students
doi	https://doi.org/10.52842/conf.ecaade.2018.1.657
source	Kepczynska-Walczak, A, Bialkowski, S (eds.), Computing for a better tomorrow - Proceedings of the 36th eCAADe Conference - Volume 1, Lodz University of Technology, Lodz, Poland, 19-21 September 2018, pp. 657-666
summary	This paper presents HIVE, a new open source design toolbox, which focuses on teaching concepts of Energy and Climate Systems integration in buildings. .The aim is to empower architecture students to integrate aspects of energy efficiency during the architectural design process. The tool employs a simplified input format designed for ease of use and provides almost instantaneous, direct feedback to support students of all experience levels in the early, conceptual building design stages, where numerous iterations need to be conducted efficiently within a short period of time.The project aims to create a robust toolbox that will become an innovative reference in architecture and engineering - lectures, design studios, and project-based learning - through its capacity to quickly, and effectively, translate building energy systems concepts into graphic formats central to building design teaching and practice. The fast feedback that the users receive to their design parameters changes will enable an effective and quick build-up of tacit knowledge about building energy systems, complementary to the explicit, theoretical knowledge that is usually taught in courses, thus creating a more complete learning experience.
keywords	Building Simulation; Low-energy architecture; Integrated curriculum; PV Assessment; Simplified GUI; Architecture Education
series	eCAADe
email
last changed	2022/06/07 07:55

_id	caadria2018_301
id	caadria2018_301
authors	Fereos, Pavlos, Tsiliakos, Marios and Jaschke, Clara
year	2018
title	Spaceship Architecture - A Sci-Fi Pedagogical Approach to Design Computation
doi	https://doi.org/10.52842/conf.caadria.2018.1.081
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. 81-90
summary	The analysis of make-belief drawings and models of Sci-Fi spaceships and architecture, leaves architects usually in absence of interior, material or program information. The spatial depth of sci-fi digital or physical models is virtually non-existent and unresolved. This discrepancy within sci-fi scenarios inspired the development of an integrated teaching methodology within design studios, with the academic objective to utilize computational methods for analysis, reproduction and eventually composition, while assessing its capacity to achieve a successful assimilation of design computation in the curriculum. The Spaceship Architecture Design Studio at University of Innsbruck's Institute for Experimental Architecture.hochbau follows a procedural approach in which the design objective is not predefined. Yet, it aims to be 'outside of this world' as a sci-fi architectural quality-enriched result of our reality, via a design oriented course with immersive computational strategies.
keywords	pedagogy; computation; sci-fi; academia; teaching
series	CAADRIA
email
last changed	2022/06/07 07:50

_id	ecaade2018_176
id	ecaade2018_176
authors	Fisher-Gewirtzman, Dafna and Polak, Nir
year	2018
title	Integrating Crowdsourcing & Gamification in an Automatic Architectural Synthesis Process
doi	https://doi.org/10.52842/conf.ecaade.2018.1.439
source	Kepczynska-Walczak, A, Bialkowski, S (eds.), Computing for a better tomorrow - Proceedings of the 36th eCAADe Conference - Volume 1, Lodz University of Technology, Lodz, Poland, 19-21 September 2018, pp. 439-444
summary	This work covers the methodological approach that is used to gather information from the wisdom of crowd, to be utilized in a machine learning process for the automatic generation of minimal apartment units. The flexibility in the synthesis process enables the generation of apartment units that seem to be random and some are unsuitable for dwelling. Thus, the synthesis process is required to classify units based on their suitability. The classification is deduced from opinions of human participants on previously generated units. As the definition of "suitability" may be subjective, this work offers a crowdsourcing method in order to reach a large number of participants, that as a whole would allow to produce an objective classification. Gaming elements have been adopted to make the crowdsourcing process more intuitive and inviting for external participants.
keywords	crowdsourcing and gamification; urban density; optimization; automated architecture synthesis; minimum apartments; visual openness
series	eCAADe
email
last changed	2022/06/07 07:51

_id	caadria2018_280
id	caadria2018_280
authors	Hanaoka, Ikuya, Tanaka, Seigo, Lee, Alric and Hotta, Kensuke
year	2018
title	Sight Depth Illusion with Perforated Plane - Evaluate in Mixed Reality with Head Mounted Display
doi	https://doi.org/10.52842/conf.caadria.2018.1.411
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. 411-420
summary	This paper examines the existence of a visual illusion with depth of sight involving a perforated panel layered above another plane, evaluates the illusion's properties with virtual projection on a see-through, head-mounted display, and illustrates the relation between the veridical and perceived distances through a mathematical expression. The result would be indicative to egocentric spatial analysis research, and reveal potentials as a reference point for a new architectural design tool.
keywords	Sight Depth; Kansei Engeneering; Mixed Reality
series	CAADRIA
email
last changed	2022/06/07 07:50

_id	ecaade2018_141
id	ecaade2018_141
authors	Hermund, Anders, Klint, Lars Simon, Bundgaard, Ture Slot and Noël Meedom Meldgaard Bj?rnson-Langen, Rune
year	2018
title	The Perception of Architectural Space in Reality, in Virtual Reality, and through Plan and Section Drawings - A case study of the perception of architectural atmosphere
doi	https://doi.org/10.52842/conf.ecaade.2018.2.735
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. 735-744
summary	This paper presents the findings from a comparative study of an architectural space communicated as the space itself and its two different representations, i.e. a virtual reality model and traditional plan and section drawings. Using eye tracking technology in combination with qualitative questionnaires, a case study of an architectural space is investigated in physical reality, a virtual reality 3D BIM model, and finally through representation of the space in plan and section drawings. In this study, the virtual reality scenario seems closer to reality than the experience of the same space experienced through plan and section drawings. There is an overall higher correlation of both the conscious reflections and the less conscious behaviour between the real physical architectural space and the virtual reality space, than there is between the real space and the space communicated through plan and section drawings. We can conclude that the scenario with the best overall size estimations, compared to the actual measures, is the virtual reality scenario. The paper further discusses the future applications of virtual reality in architecture.
keywords	Architectural representation; Virtual Reality; Perception; Tradition
series	eCAADe
email
last changed	2022/06/07 07:49

_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
doi	https://doi.org/10.52842/conf.acadia.2020.1.382
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.
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	sigradi2018_1875
id	sigradi2018_1875
authors	Kalantari, Cruze-Garza; Banner, Pamela; Contreras-Vidal, Jose Luis
year	2018
title	Computationally Analyzing Biometric Data and Virtual Response Testing in Evaluating Learning Performance of Educational Setting Through
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. 390-396
summary	Due to construction costs, the human effects of innovations in architectural design can be expensive to test. Post-occupancy studies provide valuable data about what did and did not work in the past, but they cannot provide direct feedback for new ideas that have not yet been attempted. This presents designers with something of a dilemma. How can we harness the best potential of new technology and design innovation, while avoiding costly and potentially harmful mistakes? The current research use virtual immersion and biometric data to provide a new form of extremely rigorous human-response testing prior to construction. The researchers’ hypothesis was that virtual test runs can help designers to identify potential problems and successes in their work prior to its being physically constructed. The pilot study aims to develop a digital pre-occupancy toolset to understand the impact of different interior design variables of learning environment (independent variables) on learning performance (dependent variable). This project provides a practical toolset to test the potential human impacts of architectural design innovations. The research responds to a growing call in the field for evidence-based design and for an inexpensive means of evaluating the potential human effects of new designs. Our research will address this challenge by developing a prototype mobile brain-body imaging interface that can be used in conjunction with virtual immersion.
keywords	Signal Processing; Brain; EEG; Virtual Reality; Big Data; Learning Performance
series	SIGRADI
email
last changed	2021/03/28 19:58

_id	acadia18_118
id	acadia18_118
authors	Kalantari, Saleh; Contreras-Vidal, Jose Luis; Smith, Joshua Stanton; Cruz-Garza, Jesus; Banner, Pamela
year	2018
title	Evaluating Educational Settings through Biometric Data and Virtual Response Testing
doi	https://doi.org/10.52842/conf.acadia.2018.118
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. 118-125
summary	The physical design of the learning environment has been shown to contribute significantly to student performance and educational outcomes. However, the existing literature on this topic relies primarily on generalized observations rather than on rigorous empirical testing. Broad trends in environmental impacts have been noted, but there is a lack of detailed evidence about how specific design variables can affect learning performance. The goal of this study was to apply a new approach in examining classroom design innovations. We developed a protocol to evaluate the effectiveness of classroom designs by measuring the physical responses of study participants as they interacted with different designs using a virtual reality platform. Our hypothesis was that virtual “test runs” can help designers to identify potential problems and successes in their work prior to its being physically constructed. The results of our initial pilot study indicated that this approach could yield important results about human responses to classroom design, and that the virtual environment seemed to be a reliable testing substitute when compared against real classroom environments. In addition to leading toward practical conclusions about specific classroom design variables, this project provides a new kind of research method and toolset to test the potential human impacts of a wide variety of architectural innovations.
keywords	work in progress, signal processing, eeg, virtual reality, big data, learning performance
series	ACADIA
type	paper
email
last changed	2022/06/07 07:52

_id	ecaade2018_260
id	ecaade2018_260
authors	Kallegias, Alexandros
year	2018
title	Design by Computation - A material driven study
doi	https://doi.org/10.52842/conf.ecaade.2018.2.279
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. 279-284
summary	The paper aims to address methods of creating a system for design through material studies that are employed as feedback on a computational digital model. The case study described in this paper is the output of an exploration that has investigated physical transformation, interaction and wood materiality over the period of two weeks of the international architecture programme AA Athens Visiting School in Greece. Real-time performative form-responsive methods based on bending and stretching have been developed and simulated in an open-source programming environment. The output of the simulation has been informed by the results of material tests that took place in parallel and have served as inputs for the fine-tuning of the simulation. Final conclusions were made possible from these explorations that enabled the fabrication of a prototype using wood veneer at one-to-one scale. From a pedagogical aspect, the research main focus is to improve the quality of architectural education by learning through making. This is made possible using advanced computational techniques and coupling them with material studies towards an integrated system for architectural prototypes within a limited time frame.
keywords	materiality; computation; 1:1 scale prototyping; simulation; fabrication
series	eCAADe
email
last changed	2022/06/07 07:52

_id	ecaade2018_111
id	ecaade2018_111
authors	Khean, Nariddh, Fabbri, Alessandra and Haeusler, M. Hank
year	2018
title	Learning Machine Learning as an Architect, How to? - Presenting and evaluating a Grasshopper based platform to teach architecture students machine learning
doi	https://doi.org/10.52842/conf.ecaade.2018.1.095
source	Kepczynska-Walczak, A, Bialkowski, S (eds.), Computing for a better tomorrow - Proceedings of the 36th eCAADe Conference - Volume 1, Lodz University of Technology, Lodz, Poland, 19-21 September 2018, pp. 95-102
summary	Machine learning algorithms have become widely embedded in many aspects of modern society. They have come to enhance systems, such as individualised marketing, social media services, and search engines. However, contrasting its growing ubiquity, the architectural industry has been comparatively resistant in its adoption; objectively one of the slowest industries to integrate with machine learning. Machine learning expertise can be separate from professionals in other fields; however, this separation can be a major hinderance in architecture, where interaction between the designer and the design facilitates the production of favourable outcomes. To bridge this knowledge gap, this research suggests that the solution lies with architectural education. Through the development of a novel educative framework, the research aims to teach architecture students how to implement machine learning. Exploration of student-centred pedagogical strategies was used to inform the conceptualisation of the educative module, which was subsequently implemented into an undergraduate computational design studio, and finally evaluated on its ability to effectively teach designers machine learning. The developed educative module represents a step towards greater technological adoption in the architecture industry.
keywords	Artificial Intelligence; Machine Learning; Neural Networks; Student-Centred Learning; Educative Framework
series	eCAADe
email
last changed	2022/06/07 07:52

_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
doi	https://doi.org/10.52842/conf.acadia.2018.232
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
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	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
doi	https://doi.org/10.52842/conf.acadia.2018.166
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
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_190
id	caadria2018_190
authors	Lee, Ju Hyun, Gu, Ning, Taylor, Mark and Ostwald, Michael
year	2018
title	Rethinking and Designing the Key Behaviours of Architectural Responsiveness in the Digital Age
doi	https://doi.org/10.52842/conf.caadria.2018.1.359
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. 359-368
summary	In the late 1960s the architect Nicholas Negroponte introduced that the physical environment could exhibit reflexive and simulated behaviours, an idea that has since been widely explored. Despite of this wider interest, there is not, however, a systematic approach to understanding architectural responsiveness in the digital age. This paper aims to provide a formal way to facilitate designing smart and interactive artificiality in the built environment. This paper presents a conceptual framework, through exploratory studies on recent architecture, highlighting four key behaviours: (1) tangible interaction, (2) embodied response, (3) ambient simulation, and (4) mixed reality. In addition, two essential enablers, collectiveness and immersion, are proposed to enhance these key behaviours. This framework can be used as a tool to systematically identify and characterise the responsiveness of "responsive architecture". The creative mixtures of the key behaviours will contribute to the development of unique responsive environments.
keywords	Responsive architecture; Responsive behaviour; Interactive art; Negroponte
series	CAADRIA
email
last changed	2022/06/07 07:52

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