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 644

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

_id	acadia20_74
id	acadia20_74
authors	Bucklin, Oliver; Born, Larissa; Körner, Axel; Suzuki, Seiichi; Vasey, Lauren; T. Gresser, Götz; Knippers, Jan; Menges,
year	2020
title	Embedded Sensing and Control
doi	https://doi.org/10.52842/conf.acadia.2020.1.074
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. 74-83.
summary	This paper investigates an interactive and adaptive control system for kinetic architectural applications with a distributed sensing and actuation network to control modular fiber-reinforced composite components. The aim of the project was to control the actuation of a foldable lightweight structure to generate programmatic changes. A server parses input commands and geometric feedback from embedded sensors and online data to drive physical actuation and generate a digital twin for real-time monitoring. Physical components are origami-like folding plates of glass and carbon-fiber-reinforced plastic, developed in parallel research. Accelerometer data is analyzed to determine component geometry. A component controller drives actuators to maintain or move towards desired positions. Touch sensors embedded within the material allow direct control, and an online user interface provides high-level kinematic goals to the system. A hierarchical control system parses various inputs and determines actuation based on safety protocols and prioritization algorithms. Development includes hardware and software to enable modular expansion. This research demonstrates strategies for embedded networks in interactive kinematic structures and opens the door for deeper investigations such as artificial intelligence in control algorithms, material computation, as well as real-time modeling and simulation of structural systems.
series	ACADIA
type	paper
email
last changed	2023/10/22 12:06

_id	acadia20_406
id	acadia20_406
authors	Duong, Eric; Vercoe, Garrett; Baharlou, Ehsan
year	2020
title	Engelbart
doi	https://doi.org/10.52842/conf.acadia.2020.1.406
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. 406-415.
summary	The internet has long been viewed as a cyberspace of free and collective information, allowing for an increase in the diversity of ideas and viewpoints available to the general public. However, critics argue that the emergence of personalization algorithms on social media and other internet platforms instead reduces information diversity by forming “filter bubbles"" of viewpoints similar to the user’s own. The adoption of these personalization algorithms is due in part to advancements in natural language processing, which allow for textual analysis at unprecedented scales. This paper aims to utilize natural language processing and architectural spatial principles to present social media from a collective viewpoint rather than a personalized one. To accomplish this, the paper introduces Engelbart, a data-driven agent-based system, where real-time Twitter conversations are visualized within a two-dimensional environment. This environment is interacted with by the artificial intelligence (AI) agent, Engelbart, which summarizes crowdsourced thoughts and feelings about current trending topics. The functionality of this web application comes from the natural language processing of thousands of tweets per minute throughout several layers of operations, including sentiment analysis and word embeddings. Presented as an understandable interface, it incorporates the values of cybernetics, cyberspace, agent-based modeling, and data ethics to show the potential for social media to become a more transparent space for collective discussion.
series	ACADIA
type	paper
email
last changed	2023/10/22 12:06

_id	caadria2020_423
id	caadria2020_423
authors	Erhan, Halil, Zarei, Maryam, Abuzuraiq, Ahmed M., Haas, Alyssa, Alsalman, Osama and Woodbury, Robert
year	2020
title	FlowUI: Combining Directly-Interactive Design Modeling with Design Analytics
doi	https://doi.org/10.52842/conf.caadria.2020.1.475
source	D. Holzer, W. Nakapan, A. Globa, I. Koh (eds.), RE: Anthropocene, Design in the Age of Humans - Proceedings of the 25th CAADRIA Conference - Volume 1, Chulalongkorn University, Bangkok, Thailand, 5-6 August 2020, pp. 475-484
summary	In a systems building experiment, we explored how directly manipulating non-parametric geometries can be used together with a real-time parametric performance analytics for informed design decision-making in the early phases of design. This combination gives rise to a design process where considerations that would traditionally take place in the late phases of design can become part of the early phases. The paper presents FlowUI, a prototype tool for performance-driven design that is developed in a collaboration with our industry partner as part of our design analytics research program. The tool works with and responds to changes in the design modeling environment, processes the design data and presents the results in design (data) analytics interfaces. We discuss the system's design intent and its overall architecture, followed by a set of suggestions on the comparative analysis of design solutions and design reports generation as integral parts of design exploration tasks.
keywords	Non-Parametric Modeling; Performance-Driven Design; Design Analytics; Information Visualization
series	CAADRIA
email
last changed	2022/06/07 07:55

_id	acadia20_698
id	acadia20_698
authors	Kimm, Geoff; Burry, Mark
year	2020
title	Steering into the Skid
doi	https://doi.org/10.52842/conf.acadia.2020.1.698
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. 698-707.
summary	What if any perceived risks of lost authorship and artistic control posed by a wholesale embrace of artificial intelligence by the architectural profession were instead opportunities? AI’s potential to automate design has been pursued for over 50 years, yet aspirations of early researchers are not fully realized. Nonetheless, AI’s advances continue to be rapid; it is an increasingly viable adjunct to architectural practice, and there are fundamental reasons for why the perceived “risks” of AI cannot be dismissed lightly. Architects’ professional role at the intersection of social issues and technology, however, may allow them to avoid the obsolescence faced by other roles. To do this, we propose architects responsively arbitrage an ever-changing gap between maturing AI and mutable social expectations— arbitrage in the sense of seeking to exercise individual judgment to negotiate between diverse considerations and capacities for mutual advantage. Rather than feel threatened, evolving architectural practice can augment an expanded design process to generate and embed new subtleties and expectations that society may judge contemporary AI alone as being unable to achieve. Although there can be no road map to the future of AI in architecture, historical misevaluations of machines and our own human capabilities inhibit the intertwined, synergistic, and symbiotic union with AI needed to avoid a zero-sum confrontation. To act myopically, defensively, or not at all risks straitjacketing future definitions of what it means to be an architect, designer, or even a professionally unaligned creative and productive human being.
series	ACADIA
type	paper
email
last changed	2023/10/22 12:06

_id	artificial_intellicence2019_15
id	artificial_intellicence2019_15
authors	Antoine Picon
year	2020
title	What About Humans? Artificial Intelligence in Architecture
doi	https://doi.org/https://doi.org/10.1007/978-981-15-6568-7_2
source	Architectural Intelligence Selected Papers from the 1st International Conference on Computational Design and Robotic Fabrication (CDRF 2019)
summary	Artificial intelligence is about to reshape the architectural discipline. After discussing the relations between artificial intelligence and the broader question of automation in architecture, this article focuses on the future of the interaction between humans and intelligent machines. The way machines will understand architecture may be very different from the reading of humans. Since the Renaissance, the architectural discipline has defined itself as a conversation between different stakeholders, the designer, but also the clients and the artisans in charge of the realization of projects. How can this conversation be adapted to the rise of intelligent machines? Such a question is not only a matter of design effectiveness. It is inseparable from expressive and artistic issues. Just like the fascination of modernist architecture for industrialization was intimately linked to the quest for a new poetics of the discipline, our contemporary interest for artificial intelligence has to do with questions regarding the creative core of the architectural discipline.
series	Architectural Intelligence
email
last changed	2022/09/29 07:28

_id	caadria2020_412
id	caadria2020_412
authors	Capunaman, Ozguc Bertug
year	2020
title	CAM as a Tool for Creative Expression - Informing Digital Fabrication through Human Interaction
doi	https://doi.org/10.52842/conf.caadria.2020.1.243
source	D. Holzer, W. Nakapan, A. Globa, I. Koh (eds.), RE: Anthropocene, Design in the Age of Humans - Proceedings of the 25th CAADRIA Conference - Volume 1, Chulalongkorn University, Bangkok, Thailand, 5-6 August 2020, pp. 243-252
summary	Contemporary digital design and fabrication tools often present deterministic and pre-programmed workflows. This limits the potential for developing a deeper understanding of materials within the process. This paper presents an interactive and adaptive design-fabrication workflow where the user can actively take turns in the fabrication process. The proposed experimental setup utilizes paste extrusion additive manufacturing in tandem with real-time control of an industrial robotic arm. By incorporating a computer-vision based feedback loop, it captures momentary changes in the fabricated artifact introduced by the users to inform the digital representation. Using the updated digital representation, the proposed system can offer simple design hypotheses for the user to evaluate and adapt future toolpaths accordingly. This paper presents the development of the experimental setup and delineates critical concepts and their motivation.
keywords	Computer-Aided Design (CAD) and Manufacturing (CAM); Human Computer Interaction; 3D Printing; Interactive Digital Fabrication; Robotic Fabrication
series	CAADRIA
email
last changed	2022/06/07 07:54

_id	ecaade2020_037
id	ecaade2020_037
authors	Dortheimer, Jonathan, Neuman, Eran and Milo, Tova
year	2020
title	A Novel Crowdsourcing-based Approach for Collaborative Architectural Design
doi	https://doi.org/10.52842/conf.ecaade.2020.2.155
source	Werner, L and Koering, D (eds.), Anthropologic: Architecture and Fabrication in the cognitive age - Proceedings of the 38th eCAADe Conference - Volume 2, TU Berlin, Berlin, Germany, 16-18 September 2020, pp. 155-164
summary	This paper provides an overview of "Architasker", a large-scale crowdsourcing approach, platform, and method that enables a collaborative professional architectural design process in collaboration with a community of stakeholders. The platform includes communicating complex architectural project requirements; solution space exploration using different micro-tasks like sketching, 2D and 3D CAD; design selection; and design review as an evolutionary process. The architectural crowdsourcing model underlying the platform is contextualized in the state-of-the-art research on creative crowdsourcing methods and is supported by relevant evidence from empirical experiments. Experimental results validate the effectiveness of the method to generate architectural artifacts by harnessing the skills, talents, and experience of architects and the opinions and values of the stakeholders.
keywords	Crowdsourcing; Participatory Design; Human Computation; Creative Crowdsourcing; Co-Design; Collective Intelligence
series	eCAADe
email
last changed	2022/06/07 07:55

_id	acadia20_594
id	acadia20_594
authors	Farahbakhsh, Mehdi; Kalantar, Negar; Rybkowski, Zofia
year	2020
title	Impact of Robotic 3D Printing Process Parameters on Bond Strength
doi	https://doi.org/10.52842/conf.acadia.2020.1.594
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. 594-603.
summary	Additive manufacturing (AM), also known as 3D printing, offers advantages over traditional construction technologies, increasing material efficiency, fabrication precision, and speed. However, many AM projects in academia and industrial institutions do not comply with building codes. Consequently, they are not considered safe structures for public utilization and have languished as exhibition prototypes. While three discrete scales—micro, mezzo, and macro—are investigated for AM with paste in this paper, structural integrity has been tackled on the mezzo scale to investigate the impact of process parameters on the bond strength between layers in an AM process. Real-world material deposition in a robotic-assisted AM process is subject to environmental factors such as temperature, humidity, the load of upper layers, the pressure of the nozzle on printed layers, etc. Those factors add a secondary geometric characteristic to the printed objects that was missing in the initial digital model. This paper introduces a heuristic workflow for investigating the impacts of three selective process parameters on the bond strength between layers of paste in the robotic-assisted AM of large-scale structures. The workflow includes a method for adding the secondary geometrical characteristic to the initial 3D model by employing X-ray computerized tomography (CT) scanning, digital image processing, and 3D reconstruction. Ultimately, the proposed workflow offers a pattern library that can be used by an architect or artificial intelligence (AI) algorithms in automated AM processes to create robust architectural forms.
series	ACADIA
type	paper
email
last changed	2023/10/22 12:06

_id	acadia20_182p
id	acadia20_182p
authors	Grasser, Alexander; Parger, Alexandra; Hirschberg, Urs
year	2020
title	Realtime Architecture Platform: CollabWood
source	ACADIA 2020: Distributed Proximities / Volume II: Projects [Proceedings of the 40th Annual Conference of the Association of Computer Aided Design in Architecture (ACADIA) ISBN 978-0-578-95253-6]. Online and Global. 24-30 October 2020. edited by M. Yablonina, A. Marcus, S. Doyle, M. del Campo, V. Ago, B. Slocum. 182-187
summary	This project presents a Realtime Architecture Platform applied in a telepresence design studio to design and construct the CollabWood prototype. The platform, developed by the authors, enables an open workflow to collaborate and design in unity. It provides a persistent online environment for real-time architectural production. The work method is based on the concept of collaborative objects and distributed designers. These collaborative objects are the shared content: discrete parts, prefabs, or blocks that enable interaction, communication, and collaboration between its users and owners. The distributed designers can contribute by instantiating these collaborative objects. Users placing an object react to the local neighboring conditions and therefore add their embodied design decision to the global architecture. The users get immersed in digital proximity by communicating through the integrated chat or digital calls, discussing strategies, debating design intentions, analyzing the built structure, and scanning for improvements. This pervasive collaboration lays the foundation for a democratization of the design process. As a proof of concept, this method was implemented with 20 students in a telepresence design studio. The participants embraced the real-time workflow and applied the collaborative tool throughout the semester from different locations and time zones. Using the platform to design the CollabWood prototype in real-time collaboratively was realized as a 1:1 project with local, accessible material and AR technology for assembly. The global pandemic accelerated the importance of collaboration. Realtime Architecture Platform’s response of providing an accessible common platform for real-time interaction, design, and collaboration can be regarded as a first step towards how we might work together in the future.
series	ACADIA
type	project
email
last changed	2021/10/26 08:08

_id	ecaade2020_107
id	ecaade2020_107
authors	Hashimoto, Jason and Park, Hyoung-June
year	2020
title	Dance with Shadows - Capturing tacit knowledge with smart device augmented reality (SDAR)
doi	https://doi.org/10.52842/conf.ecaade.2020.2.165
source	Werner, L and Koering, D (eds.), Anthropologic: Architecture and Fabrication in the cognitive age - Proceedings of the 38th eCAADe Conference - Volume 2, TU Berlin, Berlin, Germany, 16-18 September 2020, pp. 165-172
summary	Tacit knowledge has been notified with its involvement in the creative and innovative process of design. However, it has been an elusive subject due to its difficulty to be articulated, recorded, and communicated. Augmented Reality (AR) is introduced as an affordable, accessible, and collaborative way to revisit tacit knowledge in the design process. In this paper, a computational design approach with Smart Device Augmented Reality (SDAR) is proposed for a real-time fenestration design in a targeted room. In comparison to standard methods of showcasing daylighting metrics, the use of Smart Device Augmented Reality (SDAR) is an alternative method as it delivers a dynamic experience by combining both the real and digital environments, enabling the visualization of the design in its intended site context with real-time feedback. The implementation of the proposed approach is explained and the design process with SDAR is also demonstrated in this paper.
keywords	tacit knowledge; augmented reality; simulation; real-time feedback
series	eCAADe
email
last changed	2022/06/07 07:49

_id	ecaade2020_156
id	ecaade2020_156
authors	Hemmerling, Marco and Maris, Simon
year	2020
title	INTERCOM - A platform for collaborative design processes
doi	https://doi.org/10.52842/conf.ecaade.2020.2.173
source	Werner, L and Koering, D (eds.), Anthropologic: Architecture and Fabrication in the cognitive age - Proceedings of the 38th eCAADe Conference - Volume 2, TU Berlin, Berlin, Germany, 16-18 September 2020, pp. 173-180
summary	The INTERCOM project propounds a cloud-based collaboration platform for digital planning processes in architecture. The concept is based on an openBIM approach and ensures open access for all partners involved. At its core it provides IFC-based and model-related online tools for planning, communication and collaboration. The interaction with the model and the exchange with other project partners takes place in real-time via a model-related chat and BCF exports. In addition, the integration of e-learning modules (e.g. video tutorials, wikis, project documents) encourages problem solving through further education. Especially the integration of communication and collaboration tools is supposed to enhance the decision making throughout the design process and become a key factor for a successful and coordinated BIM process. Primarily INTERCOM has been developed as a prototype for teaching BIM in interdisciplinary teams. Subsequently, the application can also be adopted for professional practice. The paper evaluates previous experiences from BIM cloud teaching and discusses the conception and development of the proposed collaborative platform.
keywords	architecture curriculum; didactics; building information modeling (BIM); collaborative design process; common data environment (CDE)
series	eCAADe
email
last changed	2022/06/07 07:49

_id	artificial_intellicence2019_129
id	artificial_intellicence2019_129
authors	Hua Chai, Liming Zhang, and Philip F. Yuan
year	2020
title	Advanced Timber Construction Platform Multi-Robot System for Timber Structure Design and Prefabrication
doi	https://doi.org/https://doi.org/10.1007/978-981-15-6568-7_9
source	Architectural Intelligence Selected Papers from the 1st International Conference on Computational Design and Robotic Fabrication (CDRF 2023)
summary	Robotic Timber Construction has been widely researched in the last decade with remarkable advancements. While existing robotic timber construction technologies were mostly developed for specific tasks, integrated platforms aiming for industrialization has become a new trend. Through the integration of timber machining center and advanced robotics, this research tries to develop an advanced timber construction platform with multi-robot system. The Timber Construction Platform is designed as a combination of three parts: multi-robot system, sensing system, and control system. While equipped with basic functions of machining centers that allows multi-scale multifunctional timber components’ prefabrication, the platform also served as an experimental facility for innovative robotic timber construction techniques, and a service platform that integrates timber structure design and construction through real-time information collection and feedback. Thereby, this platform has the potential to be directly integrated into the timber construction industry, and contributes to a mass-customized mode of timber structures design and construction.
series	Architectural Intelligence
email
last changed	2022/09/29 07:28

_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	ecaade2020_138
id	ecaade2020_138
authors	Patel, Sayjel Vijay, Tchakerian, Raffi, Lemos Morais, Renata, Zhang, Jie and Cropper, Simon
year	2020
title	The Emoting City - Designing feeling and artificial empathy in mediated environments
doi	https://doi.org/10.52842/conf.ecaade.2020.2.261
source	Werner, L and Koering, D (eds.), Anthropologic: Architecture and Fabrication in the cognitive age - Proceedings of the 38th eCAADe Conference - Volume 2, TU Berlin, Berlin, Germany, 16-18 September 2020, pp. 261-270
summary	This paper presents a theoretical blueprint for implementing artificial empathy into the built environment. Transdisciplinary design principles have oriented the creation of a new model for autonomous environments integrating psychology, architecture, digital media, affective computing and interactive UX design. 'The Emoting City', an interactive installation presented at the 2019 Shenzhen Bi-City Biennale of Urbanism/Architecture, is presented as a first step to explore how to engage AI-driven sensing by integrating human perception, cognition and behaviour in a real-world scenario. The approach described encompasses two main elements: embedded cyberception and responsive surfaces. Its human-AI interface enables new modes of blended interaction that are conducive to self-empathy and insight. It brings forth a new proposition for the development of sensing systems that go beyond social robotics into the field of artificial empathy. The installation innovates in the design of seamless affective computing that combines 'alloplastic' and 'autoplastic' architectures. We believe that our research signals the emergence of a potential revolution in responsive environments, offering a glimpse into the possibility of designing intelligent spaces with the ability to sense, inform and respond to human emotional states in ways that promote personal, cultural and social evolution.
keywords	Artificial Intelligence; Responsive Architecture; Affective Computation; Human-AI Interfaces; Artificial Empathy
series	eCAADe
email
last changed	2022/06/07 07:59

_id	caadria2020_091
id	caadria2020_091
authors	Ren, Yue and Zheng, Hao
year	2020
title	The Spire of AI - Voxel-based 3D Neural Style Transfer
doi	https://doi.org/10.52842/conf.caadria.2020.2.619
source	D. Holzer, W. Nakapan, A. Globa, I. Koh (eds.), RE: Anthropocene, Design in the Age of Humans - Proceedings of the 25th CAADRIA Conference - Volume 2, Chulalongkorn University, Bangkok, Thailand, 5-6 August 2020, pp. 619-628
summary	In the architecture field, humans have mastered various skills for creating unique spatial experiences with unknown interplays between known contents and styles. Meanwhile, machine learning, as a popular tool for mapping different input factors and generating unpredictable outputs, links the similarity of the machine intelligence with the typical form-finding process. Style Transfer, therefore, is widely used in 2D visuals for mixing styles while inspiring the architecture field with new form-finding possibilities. Researchers have applied the algorithm in generating 2D renderings of buildings, limiting the results in 2D pixels rather than real full volume forms. Therefore, this paper aims to develop a voxel-based form generation methodology to extend the 3D architectural application of Style Transfer. Briefly, through cutting the original 3D model into multiple plans and apply them to the 2D style image, the stylized 2D results generated by Style Transfer are then abstracted and filtered as groups of pixel points in space. By adjusting the feature parameters with user customization and replacing pixel points with basic voxelization units, designers can easily recreate the original 3D geometries into different design styles, which proposes an intelligent way of finding new and inspiring 3D forms.
keywords	Form Finding; Machine Learning; Artificial Intelligence; Style Transfer
series	CAADRIA
email
last changed	2022/06/07 07:56

_id	ecaade2020_053
id	ecaade2020_053
authors	Ren, Yue, Chu, Jie and Zheng, Hao
year	2020
title	Dynamic Symbiont - An Interactive Urban Design Method Combining Swarm Intelligence and Human Decisions
doi	https://doi.org/10.52842/conf.ecaade.2020.1.383
source	Werner, L and Koering, D (eds.), Anthropologic: Architecture and Fabrication in the cognitive age - Proceedings of the 38th eCAADe Conference - Volume 1, TU Berlin, Berlin, Germany, 16-18 September 2020, pp. 383-392
summary	Can a virtual city game be built by both the public and computer-based on real-site data? In the current process of deepening global connectivity, requirements for an effective urban design are no longer limited to functions or aesthetics, but a smart, dynamic complex with multi-interactions of data, group behaviours, and physical space. This paper introduces the logic of swarm intelligence and particle system for proposing a new urban design methodology. The platforms range from simulations that quantify the impact of the disruptive interventions of city activities to communicable collaboration between different users in a UI system, which creates virtual connections between optimized urbanscape and users. In the design system, based on the context data, the computer firstly simulates and optimizes the existing 2D activity joints between the people and analyzed the current spatial connection nodes into certain design rules. Through optimal programming for spatial connection and data iterations, the activity connection structures in the second simulation are abstracted into a set of interactive 3D topographic. The final data-visualization results are presented as a co-building megacity in a virtual construction game. Users can choose the virtual building unit types and intuitively influence the future urbanscape decision through virtual construction.
keywords	Swarm Intelligence; Particle System; Digital Simulation; Human-Machine Interaction; Data Visualization
series	eCAADe
email
last changed	2022/06/07 07:56

_id	caadria2020_054
id	caadria2020_054
authors	Shen, Jiaqi, Liu, Chuan, Ren, Yue and Zheng, Hao
year	2020
title	Machine Learning Assisted Urban Filling
doi	https://doi.org/10.52842/conf.caadria.2020.2.679
source	D. Holzer, W. Nakapan, A. Globa, I. Koh (eds.), RE: Anthropocene, Design in the Age of Humans - Proceedings of the 25th CAADRIA Conference - Volume 2, Chulalongkorn University, Bangkok, Thailand, 5-6 August 2020, pp. 679-688
summary	When drawing urban scale plans, designers should always define the position and the shape of each building. This process usually costs much time in the early design stage when the condition of a city has not been finally determined. Thus the designers spend a lot of time working forward and backward drawing sketches for different characteristics of cities. Meanwhile, machine learning, as a decision-making tool, has been widely used in many fields. Generative Adversarial Network (GAN) is a model frame in machine learning, specially designed to learn and generate image data. Therefore, this research aims to apply GAN in creating urban design plans, helping designers automatically generate the predicted details of buildings configuration with a given condition of cities. Through the machine learning of image pairs, the result shows the relationship between the site conditions (roads, green lands, and rivers) and the configuration of buildings. This automatic design tool can help release the heavy load of urban designers in the early design stage, quickly providing a preview of design solutions for urban design tasks. The analysis of different machine learning models trained by the data from different cities inspires urban designers with design strategies and features in distinct conditions.
keywords	Artificial Intelligence; Urban Design; Generative Adversarial Networks; Machine Learning
series	CAADRIA
email
last changed	2022/06/07 07:56

_id	caadria2020_099
id	caadria2020_099
authors	Tu, Chun Man and Hou, June Hao
year	2020
title	After Abstraction, Before Figuration - Exploring the Potential Development of Form Re-topology and Evolution Reapplication with Three-dimensional Point Cloud Model Generation Logic.
doi	https://doi.org/10.52842/conf.caadria.2020.2.517
source	D. Holzer, W. Nakapan, A. Globa, I. Koh (eds.), RE: Anthropocene, Design in the Age of Humans - Proceedings of the 25th CAADRIA Conference - Volume 2, Chulalongkorn University, Bangkok, Thailand, 5-6 August 2020, pp. 517-526
summary	In the era of three-dimensional (3D) informatics, the 3D point cloud modeling algorithm has the potential to further develop. In this study, we attempt to eliminate the limitations of the traditional reverse modeling method and directly turn point cloud data into the material for innovative architectural design by integrating 3D point cloud modeling into the CAD/CAM platform(Rhino/Grasshopper) most widely used by parametric designers. In this way, the randomly ordered point cloud model can be regenerated and reordered according to the designer's requirements. In addition, point cloud data can be spatially segmented and morphologically evolved according to the designer's preferences to construct a 3D model with higher efficiency and more dynamic real-time adjustment compared with the triangular mesh model. Moreover, when a computer vision technique is integrated into the point cloud design process, the point cloud model can be further used to more efficiently achieve rapid visualization, artisticization, and form adjustment. Therefore, point cloud modeling can not only be applied to the spatial structure presentation of building information modeling(BIM) but also can provide further opportunities for creative architectural design.
keywords	Three-dimensional Point-cloud Model; Computer Vision; Point Set Registration; Topology Optimization; Regeneration
series	CAADRIA
email
last changed	2022/06/07 07:57

_id	ecaade2020_015
id	ecaade2020_015
authors	Yazici, Sevil
year	2020
title	A machine-learning model driven by geometry, material and structural performance data in architectural design process
doi	https://doi.org/10.52842/conf.ecaade.2020.1.411
source	Werner, L and Koering, D (eds.), Anthropologic: Architecture and Fabrication in the cognitive age - Proceedings of the 38th eCAADe Conference - Volume 1, TU Berlin, Berlin, Germany, 16-18 September 2020, pp. 411-418
summary	Artificial Intelligence (AI), based on interpretation of data, influences various professions including architectural design today. Although research on integrating conceptual design with Machine Learning (ML) algorithms as a subset of the AI has been investigated previously, there is not a framework towards integration of architectural geometry with material properties and structural performance data towards decision making in the early-design phase. Undertaking performance simulations require significant amount of computation power and time. The aim of this research is to integrate ML algorithms into design process to achieve time efficiency and improve design results. The proposed workflow consists of three stages, including generation of the parametric model; running structural performance simulations to collect the data, and operating the ML algorithms, including Artificial Neural Network (ANN), Non-Linear Regression (NLR) and Gaussian Mixture (GM) for undertaking different tasks. The results underlined that the system generates relatively fast solutions with accuracy. Additionally, ML algorithms can assist generative design processes.
keywords	Machine-learning; performance simulation; data-driven design; early-design phase
series	eCAADe
email
last changed	2022/06/07 07:57

_id	caadria2020_015
id	caadria2020_015
authors	Zheng, Hao, An, Keyao, Wei, Jingxuan and Ren, Yue
year	2020
title	Apartment Floor Plans Generation via Generative Adversarial Networks
doi	https://doi.org/10.52842/conf.caadria.2020.2.599
source	D. Holzer, W. Nakapan, A. Globa, I. Koh (eds.), RE: Anthropocene, Design in the Age of Humans - Proceedings of the 25th CAADRIA Conference - Volume 2, Chulalongkorn University, Bangkok, Thailand, 5-6 August 2020, pp. 599-608
summary	When drawing architectural plans, designers should always define every detail, so the images can contain enough information to support design. This process usually costs much time in the early design stage when the design boundary has not been finally determined. Thus the designers spend a lot of time working forward and backward drawing sketches for different site conditions. Meanwhile, Machine Learning, as a decision-making tool, has been widely used in many fields. Generative Adversarial Network (GAN) is a model frame in machine learning, specially designed to learn and generate image data. Therefore, this research aims to apply GAN in creating architectural plan drawings, helping designers automatically generate the predicted details of apartment floor plans with given boundaries. Through the machine learning of image pairs that show the boundary and the details of plan drawings, the learning program will build a model to learn the connections between two given images, and then the evaluation program will generate architectural drawings according to the inputted boundary images. This automatic design tool can help release the heavy load of architects in the early design stage, quickly providing a preview of design solutions for architectural plans.
keywords	Machine Learning; Artificial Intelligence; Architectural Design; Interior Design
series	CAADRIA
email
last changed	2022/06/07 07:57

For more results click below: