Cumincad : CUMINCAD Papers : Search Results

CumInCAD is a Cumulative Index about publications in Computer Aided Architectural Design
supported by the sibling associations ACADIA, CAADRIA, eCAADe, SIGraDi, ASCAAD and CAAD futures

PDF papers
References

Hits 1 to 20 of 512

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

_id	acadia17_426
id	acadia17_426
authors	Moorman, Andrew
year	2017
title	Pattern Making and Learning: Non-Routine Practices in Generative Design
source	ACADIA 2017: DISCIPLINES & DISRUPTION [Proceedings of the 37th Annual Conference of the Association for Computer Aided Design in Architecture (ACADIA) ISBN 978-0-692-96506-1] Cambridge, MA 2-4 November, 2017), pp. 426- 435
doi	https://doi.org/10.52842/conf.acadia.2017.426
summary	We now witness an upsurge in mainstream generative design tools fortified by simulation that speed up the concealed linear synthesis of optimized design alternatives. In pursuit of optimality, these tools saturate local machines or cloud servers with analysis and design iteration data, only to discard it once the procedure has concluded. Largely absent, however, are tools for an active, adaptive relationship with design exploration and the reuse of corresponding design data and metadata. In Pattern Making and Pattern Learning, we propose that these characteristics are mutually beneficial. This paper presents a series of revisions to the optimization framework for routine design synthesis that examine a potential symbiosis between the production of large datasets (big data) and non-routine practices of making in design. Our engagement with iterative design exercises is twofold: as a supply of computer-generated design information to foster user intuition and explore the design space on non-objective terms, and as a supply of human-generated design information to learn artifacts of user preference in the interest of design software personalization. These concepts are applied to the generation of functionally graded patterning in chair design, combining methods of physical production with programmable sheet material behavior through a custom interactive synthesis framework.
keywords	design methods; information processing; ai & machine learning; simulation & optimization; generative system
series	ACADIA
email
last changed	2022/06/07 07:58

_id	ijac201715106
id	ijac201715106
authors	Cardoso Llach, Daniel; Ardavan Bidgoli and Shokofeh Darbari
year	2017
title	Assisted automation: Three learning experiences in architectural robotics
source	International Journal of Architectural Computing vol. 15 - no. 1, 87-102
summary	Fueled by long-standing dreams of both material efficiency and aesthetic liberation, robots have become part of mainstream architectural discourses, raising the question: How may we nurture an ethos of visual, tactile, and spatial exploration in technologies that epitomize the legacies of industrial automation—for example, the pursuit of managerial efficiency, control, and an ever-finer subdivision of labor? Reviewing and extending a growing body of research on architectural robotics pedagogy, and bridging a constructionist tradition of design education with recent studies of science and technology, this article offers both a conceptual framework and concrete strategies to incorporate robots into architectural design education in ways that foster a spirit of exploration and discovery, which is key to learning creative design. Through reflective accounts of three learning experiences, we introduce the notions “assisted automation” and “robotic embodiment” as devices to enrich current approaches to robot–human design, highlighting situated and embodied aspects of designing with robotic machines.
keywords	Design education, architectural robotics, computational design, robot–human collaboration, studies of science and technology
series	other
type	normal paper
email
last changed	2019/08/02 08:28

_id	acadia17_92
id	acadia17_92
authors	Anzalone, Phillip; Bayard, Stephanie; Steenblik, Ralph S.
year	2017
title	Rapidly Deployed and Assembled Tensegrity System: An Augmented Design Approach
source	ACADIA 2017: DISCIPLINES & DISRUPTION [Proceedings of the 37th Annual Conference of the Association for Computer Aided Design in Architecture (ACADIA) ISBN 978-0-692-96506-1] Cambridge, MA 2-4 November, 2017), pp. 92-101
doi	https://doi.org/10.52842/conf.acadia.2017.092
summary	The Rapidly Deployable and Assembled Tensegrity (RDAT) project enables the efficient automated design and deployment of differential-geometry tensegrity structures through computation-driven design-to-installation workflow. RDAT employs the integration of parametric and solid-modeling methods with production by streamlining computer numerically controlled manufacturing through novel detailing and production techniques to develop an efficient manufacturing and assembly system. The RDAT project emerges from the Authors' research in academia and professional practice focusing on computationally produced full-scale performative building systems and their innovative uses in the building and construction industry.
keywords	design methods; information processing; AI; machine learning; form finding; VR; AR; mixed reality
series	ACADIA
email
last changed	2022/06/07 07:54

_id	caadria2017_070
id	caadria2017_070
authors	Chen, Nai Chun, Xie, Jenny, Tinn, Phil, Alonso, Luis, Nagakura, Takehiko and Larson, Kent
year	2017
title	Data Mining Tourism Patterns - Call Detail Records as Complementary Tools for Urban Decision Making
source	P. Janssen, P. Loh, A. Raonic, M. A. Schnabel (eds.), Protocols, Flows, and Glitches - Proceedings of the 22nd CAADRIA Conference, Xi'an Jiaotong-Liverpool University, Suzhou, China, 5-8 April 2017, pp. 685-694
doi	https://doi.org/10.52842/conf.caadria.2017.685
summary	In this study we show how Call Detail Record (CDR) can be used to better understand the travel patterns of visitors. We show how Origin-Destination (OD) Interactive Maps can provide transportation information through CDR. We then use aggregation of CDR to show the differences between the travel patterns of visitors from different countries and of different lengths of stay. We also show that visitors move differently during event periods and non-event periods, reflecting the importance of real-time data available by CDR. From CDR, we can gain more detailed and complete information about how tourists move compared to traditional surveys, which can be used to aid smarter transportation systems and urban resource planning.
keywords	Machine Learning; Call Detail Record; Original-Destination Matrix; Urban Design Tool
series	CAADRIA
email
last changed	2022/06/07 07:55

_id	acadia17_284
id	acadia17_284
authors	Hu, Zhengrong; Park, Ju Hong
year	2017
title	HalO [Indoor Positioning Mobile Platform]: A Data-Driven, Indoor-Positioning System With Bluetooth Low Energy Technology To Datafy Indoor Circulation And Classify Social Gathering Patterns For Assisting Post Occupancy Evaluation
source	ACADIA 2017: DISCIPLINES & DISRUPTION [Proceedings of the 37th Annual Conference of the Association for Computer Aided Design in Architecture (ACADIA) ISBN 978-0-692-96506-1] Cambridge, MA 2-4 November, 2017), pp. 284-291
doi	https://doi.org/10.52842/conf.acadia.2017.284
summary	Post-Occupancy Evaluation (POE) as an integrated field between architecture and sociology has created practical guidelines for evaluating indoor human behavior within a built environment. This research builds on recent attempts to integrate datafication and machine learning into POE practices that may one day assist Building Information Modeling (BIM) and multi-agent modeling. This research is based on two premises: 1) that the proliferation of Bluetooth Low Energy (BLE) technology allows us to collect a building user’s data cost-effectively and 2) that the growing application of machine learning algorithms allows us to process, analyze and synthesize data efficiently. This study illustrates that the mobile platform HalO can serve as a generic tool for datafication and automation of data analysis of the movement of a building user. In this research, the iOS mobile application HalO, combined with BLE beacons enable building providers (architects, developers, engineers and facility managers etc.) to collect the user’s indoor location data. Triangulation was used to pinpoint the user’s indoor positions, and k-means clustering was applied to classify users into different gathering groups. Through four research procedures—Design Intention Analysis, Data Collection, Data Storage and Data Analysis—the visualized and classified data helps building providers to better evaluate building performance, optimize building operations and improve the accuracy of simulations.
keywords	design methods; information processing; data mining; IoT; AI; machine learning
series	ACADIA
email
last changed	2022/06/07 07:49

_id	caadria2023_362
id	caadria2023_362
authors	Luo, Jiaxiang, Mastrokalou, Efthymia, Aldabous, Rahaf, Aldaboos, Sarah and Lopez Rodriguez, Alvaro
year	2023
title	Fabrication of Complex Clay Structures Through an Augmented Reality Assisted Platform
source	Immanuel Koh, Dagmar Reinhardt, Mohammed Makki, Mona Khakhar, Nic Bao (eds.), HUMAN-CENTRIC - Proceedings of the 28th CAADRIA Conference, Ahmedabad, 18-24 March 2023, pp. 413–422
doi	https://doi.org/10.52842/conf.caadria.2023.1.413
summary	The relationship between clay manufacturing and architectural design has a long trajectory that has been explored since the early 2000s. From a 3D printing or assembly perspective, using clay in combination with automated processes in architecture to achieve computational design solutions is well established. (Yuan, Leach & Menges, 2018). Craft-based clay art, however, still lacks effective computational design integration. With the improvement of Augmented Reality (AR) technologies (Driscoll et al., 2017) and the appearance of digital platforms, new opportunities to integrate clay manufacturing and computational design have emerged. The concept of digitally transferring crafting skills, using holographic guidance and machine learning, could make clay crafting accessible to more workers while creating the potential to share and exchange digital designs via an open-source manufacturing platform. In this context, this research project explores the potential of integrating computational design and clay crafting using AR. Moreover, it introduces a platform that enables AR guidance and the digital transfer of fabrication skills, allowing even amateur users with no prior making experience to produce complex clay components.
keywords	Computer vision, Distributed manufacturing, Augmented craftsmanship, Augmented reality, Real-time modification, Hololens
series	CAADRIA
email
last changed	2023/06/15 23:14

_id	ijac201715105
id	ijac201715105
authors	Nahmad Vazque, Alicia and Wassim Jabi
year	2017
title	Investigations in robotic-assisted design: Strategies for symbiotic agencies in material-directed generative design processes
source	International Journal of Architectural Computing vol. 15 - no. 1, 70-86
summary	The research described in this article utilises a phase-changing material, three-dimensional scanning technologies and a six-axis industrial robotic arms as vehicles to enable a novel framework where robotic technology is utilised as an ‘amplifier’ of the design process to realise geometries that derive from both constructive visions and architectural visions through iterative feedback loops between them. The robot in this scenario is not a fabrication tool but the enabler of an environment where the material, robotic and human agencies interact. This article describes the exploratory research for the development of a dialogic design process, sets the framework for its implementation, carries out an evaluation based on designer use and concludes with a set of observations. One of the main findings of this article is that a deeper collaboration that acknowledges the potential of these tools, in a learning-by-design method, can lead to new choreographies for architectural design and fabrication.
keywords	Robotic fabrication, human-machine networks, digital design, agency
series	other
type	normal paper
email
last changed	2019/08/02 08:28

_id	ecaade2017_271
id	ecaade2017_271
authors	Narahara, Taro
year	2017
title	Collective Construction Modeling and Machine Learning: Potential for Architectural Design
source	Fioravanti, A, Cursi, S, Elahmar, S, Gargaro, S, Loffreda, G, Novembri, G, Trento, A (eds.), ShoCK! - Sharing Computational Knowledge! - Proceedings of the 35th eCAADe Conference - Volume 2, Sapienza University of Rome, Rome, Italy, 20-22 September 2017, pp. 341-348
doi	https://doi.org/10.52842/conf.ecaade.2017.2.341
summary	Recently, there are significant developments in artificial intelligence using advanced machine learning algorithms such as deep neural networks. These new methods can defeat human expert players in strategy-based board games such as Go and video games such as Breakout. This paper suggests a way to incorporate such advanced computing methods into architectural design through introducing a simple conceptual design project inspired by computational interpretations of wasps' collective constructions. At this stage, the paper's intent is not to introduce a practical and fully finished tool directly useful for architectural design. Instead, the paper proposes an example of a program that can potentially become a conceptual framework for incorporating such advanced methods into architectural design.
keywords	Design tools; Stigmergy; Machine learning
series	eCAADe
email
last changed	2022/06/07 07:58

_id	acadia23_v1_242
id	acadia23_v1_242
authors	Noel, Vernelle A.
year	2023
title	Carnival + AI: Heritage, Immersive virtual spaces, and Machine Learning
source	ACADIA 2023: Habits of the Anthropocene: Scarcity and Abundance in a Post-Material Economy [Volume 1: Projects Catalog of the 43rd Annual Conference of the Association of Computer Aided Design in Architecture (ACADIA) ISBN 979-8-9860805-8-1]. Denver. 26-28 October 2023. edited by A. Crawford, N. Diniz, R. Beckett, J. Vanucchi, M. Swackhamer 242-245.
summary	Built on a Situated Computations framework, this project explores preservation, reconfiguration, and presentation of heritage through immersive virtual experiences, and machine learning for new understandings and possibilities (Noel 2020; 2017; Leach and Campo 2022; Leach 2021). Using the Trinidad and Tobago Carnival - hereinafter referred to as Carnival - as a case study, Carnival + AI is a series of immersive experiences in design, culture, and artificial intelligence (AI). These virtual spaces create new digital modes of engaging with cultural heritage and reimagined designs of traditional sculptures in the Carnival (Noel 2021). The project includes three virtual events that draw on real events in the Carnival: (1) the Virtual Gallery, which builds on dancing sculptures in the Carnival and showcases AI-generated designs; (2) Virtual J’ouvert built on J’ouvert in Carnival with AI-generated J’ouvert characters specific; and (3) Virtual Mas which builds on the masquerade.
series	ACADIA
type	project
email
last changed	2024/04/17 13:58

_id	ecaade2017_220
id	ecaade2017_220
authors	Quartara, Andrea and Figliola, Angelo
year	2017
title	Tangible Computing - Manufacturing of Intertwined Logics
source	Fioravanti, A, Cursi, S, Elahmar, S, Gargaro, S, Loffreda, G, Novembri, G, Trento, A (eds.), ShoCK! - Sharing Computational Knowledge! - Proceedings of the 35th eCAADe Conference - Volume 2, Sapienza University of Rome, Rome, Italy, 20-22 September 2017, pp. 115-122
doi	https://doi.org/10.52842/conf.ecaade.2017.2.115
summary	This paper explores the process of digital materialization through robotic fabrication techniques by presenting three wooden projects. The analysis of the case studies is oriented to underline the impact that computation had on architectural construction due to its methodological and instrumental innovations over the last decades. The absorption of computing and digital fabrication logics within the discipline is explored from either an architectural point of view and from the improvements related to automation of the constructive process. On the one hand the case studies are caught because of the desire to expand material complexity and, on the other hand because of the integration with other technological systems. The narrative allows gathering pros and cons in three different investigative macro areas: material culture, methodological oversights, and operative setbacks coming from digital machine and communicational constraints. This analytical investigation helps the definition of a new pathway for future researches, looking forward the assimilation of digital materiality learning in building construction.
keywords	computational design; file-to-factory; large-scale robotic woodworking; new production methods
series	eCAADe
email
last changed	2022/06/07 08:00

_id	acadia17_552
id	acadia17_552
authors	Sjoberg, Christian; Beorkrem, Christopher; Ellinger, Jefferson
year	2017
title	Emergent Syntax: Machine Learning for the Curation of Design Solution Space
source	ACADIA 2017: DISCIPLINES & DISRUPTION [Proceedings of the 37th Annual Conference of the Association for Computer Aided Design in Architecture (ACADIA) ISBN 978-0-692-96506-1] Cambridge, MA 2-4 November, 2017), pp. 552- 561
doi	https://doi.org/10.52842/conf.acadia.2017.552
summary	The expanding role of computational models in the process of design is producing exponential growth in parameter spaces. As designers, we must create and implement new methods for searching these parameter spaces, considering not only quantitative optimization metrics but also qualitative features. This paper proposes a methodology that leverages the pattern modeling properties of artificial neural networks to capture designers' inexplicit selection criteria and create user-selection-based fitness functions for a genetic solver. Through emulation of learned selection patterns, fitness functions based on trained networks provide a method for qualitative evaluation of designs in the context of a given population. The application of genetic solvers for the generation of new populations based on the trained network selections creates emergent high-density clusters in the parameter space, allowing for the identification of solutions that satisfy the designer’s inexplicit criteria. The results of an initial user study show that even with small numbers of training objects, a search tool with this configuration can begin to emulate the design criteria of the user who trained it.
keywords	design methods; information processing; AI; machine learning; generative system
series	ACADIA
email
last changed	2022/06/07 07:56

_id	ecaade2023_259
id	ecaade2023_259
authors	Sonne-Frederiksen, Povl Filip, Larsen, Niels Martin and Buthke, Jan
year	2023
title	Point Cloud Segmentation for Building Reuse - Construction of digital twins in early phase building reuse projects
source	Dokonal, W, Hirschberg, U and Wurzer, G (eds.), Digital Design Reconsidered - Proceedings of the 41st Conference on Education and Research in Computer Aided Architectural Design in Europe (eCAADe 2023) - Volume 2, Graz, 20-22 September 2023, pp. 327–336
doi	https://doi.org/10.52842/conf.ecaade.2023.2.327
summary	Point cloud processing has come a long way in the past years. Advances in computer vision (CV) and machine learning (ML) have enabled its automated recognition and processing. However, few of those developments have made it through to the Architecture, Engineering and Construction (AEC) industry. Here, optimizing those workflows can reduce time spent on early-phase projects, which otherwise could be spent on developing innovative design solutions. Simplifying the processing of building point cloud scans makes it more accessible and therefore, usable for design, planning and decision-making. Furthermore, automated processing can also ensure that point clouds are processed consistently and accurately, reducing the potential for human error. This work is part of a larger effort to optimize early-phase design processes to promote the reuse of vacant buildings. It focuses on technical solutions to automate the reconstruction of point clouds into a digital twin as a simplified solid 3D element model. In this paper, various ML approaches, among others KPConv Thomas et al. (2019), ShapeConv Cao et al. (2021) and Mask-RCNN He et al. (2017), are compared in their ability to apply semantic as well as instance segmentation to point clouds. Further it relies on the S3DIS Armeni et al. (2017), NYU v2 Silberman et al. (2012) and Matterport Ramakrishnan et al. (2021) data sets for training. Here, the authors aim to establish a workflow that reduces the effort for users to process their point clouds and obtain object-based models. The findings of this research show that although pure point cloud-based ML models enable a greater degree of flexibility, they incur a high computational cost. We found, that using RGB-D images for classifications and segmentation simplifies the complexity of the ML model but leads to additional requirements for the data set. These can be mitigated in the initial process of capturing the building or by extracting the depth data from the point cloud.
keywords	Point Clouds, Machine Learning, Segmentation, Reuse, Digital Twins
series	eCAADe
email
last changed	2023/12/10 10:49

_id	ecaade2017_028
id	ecaade2017_028
authors	Elsayed, Kareem, Fioravanti, Antonio and Squasi, Francesco
year	2017
title	Low-Cost Housing - Testing snap-fit joints in agricultural residue panels
source	Fioravanti, A, Cursi, S, Elahmar, S, Gargaro, S, Loffreda, G, Novembri, G, Trento, A (eds.), ShoCK! - Sharing Computational Knowledge! - Proceedings of the 35th eCAADe Conference - Volume 2, Sapienza University of Rome, Rome, Italy, 20-22 September 2017, pp. 167-174
doi	https://doi.org/10.52842/conf.ecaade.2017.2.167
summary	Within the field of digitally fabricated housing, the paper outlines a theoretical model for a housing system that combines complete off-site prefabrication with parametric assemblies. The paper then presents some insights on the application of snap-fit joints to the wall assemblies entirely fabricated using agricultural residue panels. Mechanical characterization of the material was performed through axial tension, compression and 4-point bending tests. Guidelines of plastics snap-fit design were applied to the joint design within the elastic limits of the material. Three different full scale wall typology prototypes were built using this jointing technique. The results show that while snap-fits can be a promising solution encouraging self-build in low-cost housing, the brittle nature of the specific agricultural residue panel material necessitates further joint enhancements.
keywords	Digital fabrication; Low-cost housing; Agricultural residues; Structural testing
series	eCAADe
email
last changed	2022/06/07 07:55

_id	ecaade2017_157
id	ecaade2017_157
authors	Date, Kartikeya, Schaumann, Davide and Kalay, Yehuda E.
year	2017
title	A Parametric Approach To Simulating Use-Patterns in Buildings - The Case Of Movement
source	Fioravanti, A, Cursi, S, Elahmar, S, Gargaro, S, Loffreda, G, Novembri, G, Trento, A (eds.), ShoCK! - Sharing Computational Knowledge! - Proceedings of the 35th eCAADe Conference - Volume 2, Sapienza University of Rome, Rome, Italy, 20-22 September 2017, pp. 503-510
doi	https://doi.org/10.52842/conf.ecaade.2017.2.503
summary	We describe one of the three core use-pattern building blocks of a parametric approach to simulating use-patterns in buildings. Use-patterns are modeled as events which use specified descriptions of spaces, actors and activities which constitute them. The simulation system relies on three fundamental patterns of use - move, meet and do. The move pattern is considered in detail in this paper with specific reference to what we term the partial knowledge issue. Modeling decision making about how to move through the space (what path to take) depends on modeling the actor's partial access to knowledge. Visibility is used as an example of partial knowledge. The parametric approach described in the paper enables the clear separation of syntactical and semantic conditions which inform decisions and the coordination of decisions made by agents in a simulation of use-patterns. This approach contributes to extending the analytical capability of Building Information Models from the point of view of evaluating how a proposed building design may be used, given complex, interrelated patterns of use.
keywords	Agent-Based Systems, Simulation, Use-Patterns, Design Tools
series	eCAADe
email
last changed	2022/06/07 07:55

_id	cf2017_249
id	cf2017_249
authors	Agirbas, Asli
year	2017
title	Teaching Design by Coding in Architecture Undergraduate Education: A Case Study with Islamic Patterns
source	Gülen Çagdas, Mine Özkar, Leman F. Gül and Ethem Gürer (Eds.) Future Trajectories of Computation in Design [17th International Conference, CAAD Futures 2017, Proceedings / ISBN 978-975-561-482-3] Istanbul, Turkey, July 12-14, 2017, pp. 249-258.
summary	Computer-aided design has found its role in the undergraduate education of architects, and presently design by coding is also gradually finding further prominence in accord with the increasing demand by students who wish to learn more about this topic. This subject is included in an integrated manner in some studio courses on architecture design in some schools, or it is taught separately in elsewhere. In terms of the separate course on coding, the principal difficulty is that actual applications of the method can rarely be included due to time limitations and the fact that it is conducted separately from the studio course on architecture. However, within the framework of the architectural education, in order to learn about the coding it is necessary to consider it along with the design process, and this versatile thinking can only be achieved by the application of the design. In this study, an elective undergraduate course is considered in the context of design and to yield a versatile thinking strategy while learning the language of visual programming. The course progressed under the theoretical framework of shape grammar from the design stage through to the digital fabrication process, and the experimental studies were carried out on the selected topic of Islamic pattern. A method was proposed to improve the productivity of such courses, and an evaluation of the results is presented.
keywords	Islamic Patterns, Shape Grammars, Architectural Education, Parametric Design, CAAD.
series	CAAD Futures
email
last changed	2017/12/01 14:38

_id	acadia17_164
id	acadia17_164
authors	Brugnaro, Giulio; Hanna, Sean
year	2017
title	Adaptive Robotic Training Methods for Subtractive Manufacturing
source	ACADIA 2017: DISCIPLINES & DISRUPTION [Proceedings of the 37th Annual Conference of the Association for Computer Aided Design in Architecture (ACADIA) ISBN 978-0-692-96506-1] Cambridge, MA 2-4 November, 2017), pp. 164-169
doi	https://doi.org/10.52842/conf.acadia.2017.164
summary	This paper presents the initial developments of a method to train an adaptive robotic system for subtractive manufacturing with timber, based on sensor feedback, machine-learning procedures and material explorations. The methods were evaluated in a series of tests where the trained networks were successfully used to predict fabrication parameters for simple cutting operations with chisels and gouges. The results suggest potential benefits for non-standard fabrication methods and a more effective use of material affordances.
keywords	design methods; information processing; construction; robotics; ai & machine learning; digital craft; manual craft
series	ACADIA
email
last changed	2022/06/07 07:52

_id	acadia17_238
id	acadia17_238
authors	El-Zanfaly, Dina
year	2017
title	A Multisensory Computational Model for Human-Machine Making and Learning
source	ACADIA 2017: DISCIPLINES & DISRUPTION [Proceedings of the 37th Annual Conference of the Association for Computer Aided Design in Architecture (ACADIA) ISBN 978-0-692-96506-1] Cambridge, MA 2-4 November, 2017), pp. 238-247
doi	https://doi.org/10.52842/conf.acadia.2017.238
summary	Despite the advancement of digital design and fabrication technologies, design practices still follow Alberti’s hylomorphic model of separating the design phase from the construction phase. This separation hinders creativity and flexibility in reacting to surprises that may arise during the construction phase. These surprises often come as a result of a mismatch between the sophistication allowed by the digital technologies and the designer’s experience using them. These technologies and expertise depend on one human sense, vision, ignoring other senses that could be shaped and used in design and learning. Moreover, pedagogical approaches in the design studio have not yet fully integrated digital technologies as design companions; rather, they have been used primarily as tools for representation and materialization. This research introduces a multisensory computational model for human-machine making and learning. The model is based on a recursive process of embodied, situated, multisensory interaction between the learner, the machines and the thing-in-the-making. This approach depends heavily on computational making, abstracting, and describing the making process. To demonstrate its effectiveness, I present a case study from a course I taught at MIT in which students built full-scale, lightweight structures with embedded electronics. This model creates a loop between design and construction that develops students’ sensory experience and spatial reasoning skills while at the same time enabling them to use digital technologies as design companions. The paper shows that making can be used to teach design while enabling the students to make judgments on their own and to improvise.
keywords	education, society & culture; fabrication
series	ACADIA
email
last changed	2022/06/07 07:55

_id	cf2017_533
id	cf2017_533
authors	El-Zanfaly, Dina; Abdelmohsen, Sherif
year	2017
title	Imitation in Action: A Pedagogical Approach for Making Kinetic Structures
source	Gülen Çagdas, Mine Özkar, Leman F. Gül and Ethem Gürer (Eds.) Future Trajectories of Computation in Design [17th International Conference, CAAD Futures 2017, Proceedings / ISBN 978-975-561-482-3] Istanbul, Turkey, July 12-14, 2017, pp. 533-545.
summary	One of the problems in teaching students how to design kinetic architecture is the difficulty of helping them grasp concepts like motion, physical computing and fabrication, concepts not generally dealt with in conventional architectural projects. In this paper, we introduce a pedagogical method for better utilizing prototyping and explore the role prototyping plays in learning and conceptualizing design ideas. Our method is based on building the learner’s sensory experience through iteration and focusing on the process as well as the product. Specifically, our research attempts to address the following questions: How can architecture students anticipate and feel motion while they design kinetic prototypes? How do their prototypes enable them to explore design ideas? As a case study, we applied our methodology in an 8-week workshop in a fabrication laboratory in Cairo, Egypt. The workshop was open to young architects and students who had completed at least four semesters of study at the university. We describe the pedagogical approach we developed to build the sensory experience of making motion, and demonstrate the basic setting and stages of the workshop. We show how a cyclical learning process, based on perception and action -- copying and iteration -- contributed to the students’ learning experience and enabled them to create and improvise on their own.
keywords	Kinetic Architecture, Digital Fabrication, Sensory Experience, Computational Making, Imitation
series	CAAD Futures
email
last changed	2017/12/01 14:38

_id	ecaade2018_243
id	ecaade2018_243
authors	Gardner, Nicole
year	2018
title	Architecture-Human-Machine (re)configurations - Examining computational design in practice
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. 139-148
doi	https://doi.org/10.52842/conf.ecaade.2018.2.139
summary	This paper outlines a research project that explores the participation in, and perception of, advanced technologies in architectural professional practice through a sociotechnical lens and presents empirical research findings from an online survey distributed to employees in five large-scale architectural practices in Sydney, Australia. This argues that while the computational design paradigm might be well accepted, understood, and documented in academic research contexts, the extent and ways that computational design thinking and methods are put-into-practice has to date been less explored. In engineering and construction, technology adoption studies since the mid 1990s have measured information technology (IT) use (Howard et al. 1998; Samuelson and Björk 2013). In architecture, research has also focused on quantifying IT use (Cichocka 2017), as well as the examination of specific practices such as building information modelling (BIM) (Cardoso Llach 2017; Herr and Fischer 2017; Son et al. 2015). With the notable exceptions of Daniel Cardoso Llach (2015; 2017) and Yanni Loukissas (2012), few scholars have explored advanced technologies in architectural practice from a sociotechnical perspective. This paper argues that a sociotechnical lens can net valuable insights into advanced technology engagement to inform pedagogical approaches in architectural education as well as strategies for continuing professional development.
keywords	Computational design; Sociotechnical system; Technology adoption
series	eCAADe
email
last changed	2022/06/07 07:51

_id	caadria2019_626
id	caadria2019_626
authors	Hahm, Soomeen, Maciel, Abel, Sumitiomo, Eri and Lopez Rodriguez, Alvaro
year	2019
title	FlowMorph - Exploring the human-material interaction in digitally augmented craftsmanship
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. 553-562
doi	https://doi.org/10.52842/conf.caadria.2019.1.553
summary	It has been proposed that, after the internet age, we are now entering a new era of the '/Augmented Age/' (King, 2016). Physician Michio Kaku imagined the future of architects will be relying heavily on Augmented Reality technology (Kaku, 2015). Augmented reality technology is not a new technology and has been evolving rapidly. In the last three years, the technology has been applied in mainstream consumer devices (Coppens, 2017). This opened up possibilities in every aspect of our daily lives and it is expected that this will have a great impact on every field of consumer's technology in near future, including design and fabrication. What is the future of design and making? What kind of new digital fabrication paradigm will emerge from inevitable technological development? What kind of impact will this have on the built environment and industry? FlowMorph is a research project developed in the Bartlett School of Architecture, B-Pro AD with the collaboration of the authors and students as a 12 month MArch programme, we developed a unique design project trying to answer these questions which will be introduced in this paper.
keywords	Augmented Reality, Mixed Reality, Virtual Reality, Design Augmentation, Digital Fabrication, Cognition models, Conceptual Designing, Design Process, Design by Making, Generative Design, Computational Design, Human-Machine Collaboration, Human-Computer Collaboration, Human intuition in digital fabrication
series	CAADRIA
email
last changed	2022/06/07 07:51

For more results click below: