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 606

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

_id	ascaad2021_022
id	ascaad2021_022
authors	Baºarir, Lale; Kutluhan Erol
year	2021
title	Briefing AI: From Architectural Design Brief Texts to Architectural Design Sketches
source	Abdelmohsen, S, El-Khouly, T, Mallasi, Z and Bennadji, A (eds.), Architecture in the Age of Disruptive Technologies: Transformations and Challenges [9th ASCAAD Conference Proceedings ISBN 978-1-907349-20-1] Cairo (Egypt) [Virtual Conference] 2-4 March 2021, pp. 23-31
summary	The main focus of this research is to uncover the underlying intuitive knowledge of architecture with the help of machine learning models. To achieve this, a generic architectural design process is considered and divided into iterative portions based on their output for each phase. This study looks into the initial portion of the architectural design process called “Briefing”. The authors search for the intuition that exists within the design process and how it can be learned by artificial intelligence (AI) that is currently gained through master-apprentice relationship and experience that builds up this knowledge. In this study, a way to enable users to attain an architectural design sketch while defining an architectural design problem with text is explored. This on-going research decomposes the components of the briefing and preliminary design sketching processes. Therefore the domain knowledge at each phase is considered for translating to constraints via natural language processing (NLP) and machine learning (ML) models such as Generative Adversarial Networks (GANs).
series	ASCAAD
type	normal paper
email
last changed	2021/08/09 13:11

_id	ascaad2021_074
id	ascaad2021_074
authors	Belkaid, Alia; Abdelkader Ben Saci, Ines Hassoumi
year	2021
title	Human-Computer Interaction for Urban Rules Optimization
source	Abdelmohsen, S, El-Khouly, T, Mallasi, Z and Bennadji, A (eds.), Architecture in the Age of Disruptive Technologies: Transformations and Challenges [9th ASCAAD Conference Proceedings ISBN 978-1-907349-20-1] Cairo (Egypt) [Virtual Conference] 2-4 March 2021, pp. 603-613
summary	Faced with the complexity of manual and intuitive management of urban rules in architectural and urban design, this paper offers a collaborative and digital human-computer approach. It aims to have an Authorized Bounding Volume (ABV) which uses the best target values of urban rules. It is a distributed constraint optimization problem. The ABV Generative Model uses multi-agent systems. It offers an intelligent system of urban morphology able to transform the urban rules, on a given plot, into a morphological delimitation permitted by the planning regulations of a city. The overall functioning of this system is based on two approaches: construction and supervision. The first is conducted entirely by the machine and the second requires the intervention of the designer to collaborate with the machine. The morphological translation of urban rules is sometimes contradictory and may require additional external relevance to urban rules. Designer arbitration assists the artificial intelligence in accomplishing this task and solving the problem. The Human-Computer collaboration is achieved at the appropriate time and relies on the degree of constraint satisfaction with fitness function. The resolution of the distributed constraint optimization problem is not limited to an automatic generation of urban rules, but involves also the production of multiple optimal-ABV conditioned both by urban constraints as well as relevance, chosen by the designer.
series	ASCAAD
email
last changed	2021/08/09 13:13

_id	caadria2021_389
id	caadria2021_389
authors	del Campo, Matias
year	2021
title	Architecture,Language and AI - Language,Attentional Generative Adversarial Networks (AttnGAN) and Architecture Design
doi	https://doi.org/10.52842/conf.caadria.2021.1.211
source	A. Globa, J. van Ameijde, A. Fingrut, N. Kim, T.T.S. Lo (eds.), PROJECTIONS - Proceedings of the 26th CAADRIA Conference - Volume 1, The Chinese University of Hong Kong and Online, Hong Kong, 29 March - 1 April 2021, pp. 211-220
summary	The motivation to explore Attentional Generative Adversarial Networks (AttnGAN) as a design technique in architecture can be found in the desire to interrogate an alternative design methodology that does not rely on images as starting point for architecture design, but language. Traditionally architecture design relies on visual language to initiate a design process, wither this be a napkin sketch or a quick doodle in a 3D modeling environment. AttnGAN explores the information space present in programmatic needs, expressed in written form, and transforms them into a visual output. The key results of this research are shown in this paper with a proof-of-concept project: the competition entry for the 24 Highschool in Shenzhen, China. This award-winning project demonstrated the ability of GraphCNN to serve as a successful design methodology for a complex architecture program. In the area of Neural Architecture, this technique allows to interrogate shape through language. An alternative design method that creates its own unique sensibility.
keywords	Artificial Intelligence; Machine Learning; Artificial Neural Networks; Semiotics; Design Methodology
series	CAADRIA
email
last changed	2022/06/07 07:55

_id	ijac202119106
id	ijac202119106
authors	Del Campo, Matias; Alexandra Carlson, and Sandra Manninger
year	2021
title	Towards Hallucinating Machines - Designing with Computational Vision
source	International Journal of Architectural Computing 2021, Vol. 19 - no. 1, 88–103
summary	There are particular similarities in how machines learn about the nature of their environment, and how humans learn to process visual stimuli. Machine Learning (ML), more specifically Deep Neural network algorithms rely on expansive image databases and various training methods (supervised, unsupervised) to “make sense” out of the content of an image. Take for example how students of architecture learn to differentiate various architectural styles. Whether this be to differentiate between Gothic, Baroque or Modern Architecture, students are exposed to hundreds, or even thousands of images of the respective styles, while being trained by faculty to be able to differentiate between those styles. A reversal of the process, striving to produce imagery, instead of reading it and understanding its content, allows machine vision techniques to be utilized as a design methodology that profoundly interrogates aspects of agency and authorship in the presence of Artificial Intelligence in architecture design. This notion forms part of a larger conversation on the nature of human ingenuity operating within a posthuman design ecology. The inherent ability of Neural Networks to process large databases opens up the opportunity to sift through the enormous repositories of imagery generated by the architecture discipline through the ages in order to find novel and bespoke solutions to architectural problems. This article strives to demystify the romantic idea of individual artistic design choices in architecture by providing a glimpse under the hood of the inner workings of Neural Network processes, and thus the extent of their ability to inform architectural design.The approach takes cues from the language and methods employed by experts in Deep Learning such as Hallucinations, Dreaming, Style Transfer and Vision. The presented approach is the base for an in-depth exploration of its meaning as a cultural technique within the discipline. Culture in the extent of this article pertains to ideas such as the differentiation between symbolic and material cultures, in which symbols are defined as the common denominator of a specific group of people.1 The understanding and exchange of symbolic values is inherently connected to language and code, which ultimately form the ingrained texture of any form of coded environment, including the coded structure of Neural Networks.A first proof of concept project was devised by the authors in the form of the Robot Garden. What makes the Robot Garden a distinctively novel project is the motion from a purely two dimensional approach to designing with the aid of Neural Networks, to the exploration of 2D to 3D Neural Style Transfer methods in the design process.
keywords	Artificial intelligence, design agency, neural networks, machine learning, machine vision
series	journal
email
last changed	2021/06/03 23:29

_id	ijac202119404
id	ijac202119404
authors	Ghandi, Mona; Blaisdell, Marcus; Ismail, Mohamed
year	2021
title	Embodied empathy: Using affective computing to incarnate human emotion and cognition in architecture
source	International Journal of Architectural Computing 2021, Vol. 19 - no. 4, 532–552
summary	This research aims to develop a cyber-physical adaptive architectural space capable of real-time responses topeople’s emotions, based on biological and neurological data. To achieve this goal, we integrated artificialintelligence (AI), wearable technology, sensory environments, and adaptive architecture to create anemotional bond between a space and its occupants and encourage affective emotional interactions betweenthe two. The project’s objectives were to (1) measure and analyze biological and neurological data to detectemotions, (2) map and illustrate that emotional data, and (3) link occupants’emotions and cognition to a builtenvironment through a real-time emotive feedback loop. Using an interactive installation as a case study, thiswork examines the cognition-emotion-space interaction through changes in volume, color, and light as ameans of emotional expression. It contributes to the current theory and practice of cyber-physical design andthe role AI plays, as well as the interaction of technology and empathy.
keywords	Places and awareness, artificial intelligence and machine learning in design, intelligent responsive spaces,affective computing in architecture, cognition-emotion-space interaction, embodied empathy, neuromorphicdesign, cyber-physical neurospaces
series	journal
email
last changed	2024/04/17 14:29

_id	acadia21_100
id	acadia21_100
authors	Ghandi, Mona; Ismail, Mohamed; Blaisdell, Marcus
year	2021
title	Parasympathy
doi	https://doi.org/10.52842/conf.acadia.2021.100
source	ACADIA 2021: Realignments: Toward Critical Computation [Proceedings of the 41st Annual Conference of the Association of Computer Aided Design in Architecture (ACADIA) ISBN 979-8-986-08056-7]. Online and Global. 3-6 November 2021. edited by B. Bogosian, K. Dörfler, B. Farahi, J. Garcia del Castillo y López, J. Grant, V. Noel, S. Parascho, and J. Scott. 100-109.
summary	Parasympathy is an interactive spatial experience operating as an extension of visitors’ minds. By integrating Artificial Intelligence (AI), wearable technologies, affective computing (Picard 1995; Picard 2003), and neuroscience, this project blurs the lines between the physical, digital, and biological spheres and empowers users’ brains to solicit positive changes from their spaces based on their real-time biophysical reactions and emotions. The objective is to deploy these technologies in support of the wellbeing of the community especially when related to social matters such as inclusion and social justice in our built environment. Consequently, this project places the users’ emotions at the very center of its space by performing real-time responses to the emotional state of the individuals within the space.
series	ACADIA
type	project
email
last changed	2023/10/22 12:06

_id	caadria2023_446
id	caadria2023_446
authors	Guida, George
year	2023
title	Multimodal Architecture: Applications of Language in a Machine Learning Aided Design Process
doi	https://doi.org/10.52842/conf.caadria.2023.2.561
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. 561–570
summary	Recent advances in Natural Language Processing (NLP) and Diffusion Models (DMs) are leading to a significant change in the way architecture is conceived. With capabilities that surpass those of current generative models, it is now possible to produce an unlimited number of high-quality images (Dhariwal and Nichol 2021). This opens up new opportunities for using synthetic images and marks a new phase in the creation of multimodal 3D forms, central to architectural concept design stages. Presented here are three methodologies of generation of meaningful 2D and 3D designs, merging text-to-image diffusion models Stable Diffusion, and DALL-E 2 with computational methods. These allow designers to intuitively navigate through a multimodal feedback loop of information originating from language and aided by artificial intelligence tools. This paper contributes to our understanding of machine-augmented design processes and the importance of intuitive user interfaces (UI) in enabling new dialogues between humans and machines. Through the creation of a prototype of an accessible UI, this exchange of information can empower designers, build trust in these tools, and increase control over the design process.
keywords	Machine Learning, Diffusion Models, Concept Design, Semantics, User Interface, Design Agency
series	CAADRIA
email
last changed	2023/06/15 23:14

_id	ecaade2021_158
id	ecaade2021_158
authors	Joyce, Sam Conrad and Nazim, Ibrahim
year	2021
title	Limits to Applied ML in Planning and Architecture - Understanding and defining extents and capabilities
doi	https://doi.org/10.52842/conf.ecaade.2021.1.243
source	Stojakovic, V and Tepavcevic, B (eds.), Towards a new, configurable architecture - Proceedings of the 39th eCAADe Conference - Volume 1, University of Novi Sad, Novi Sad, Serbia, 8-10 September 2021, pp. 243-252
summary	There has been an exponential increase in Machine Learning (ML) research in design. Specifically, with Deep Learning becoming more accessible, frameworks like Generative Adversarial Networks (GANs), which are able to synthesise novel images are being used in the classification and generation of designs in architecture. While much of these explorations successfully demonstrate the 'magic' and potential of these techniques, their limits remain unclear, with only a few, but crucial, discussions on underlying fundamental limits and sensitivities of ML. This is a gap in our understanding of these tools especially within the complex context of planning and architecture. This paper seeks to discuss what limits ML in design as it exists today, by examining the state-of-the-art and mechanics of ML models relevant to design tasks. Aiming to help researchers to focus on productive uses of ML and avoid areas of over-promise.
keywords	Machine Learning; Artificial Intelligence; Creativity
series	eCAADe
email
last changed	2022/06/07 07:52

_id	sigradi2021_200
id	sigradi2021_200
authors	Karabagli, Kaan, Koc, Mustafa, Basu, Prithwish and As, Imdat
year	2021
title	A Machine Learning Approach to Translate Graph Representations into Conceptual Massing Models
source	Gomez, P and Braida, F (eds.), Designing Possibilities - Proceedings of the XXV International Conference of the Ibero-American Society of Digital Graphics (SIGraDi 2021), Online, 8 - 12 November 2021, pp. 191–202
summary	Machine learning (ML) has popular applications in domains involving image, video, text and voice. However, in architecture, image-based ML systems face challenges capturing the complexity of three-dimensional space. In this paper, we leverage a graph-based ML system that can capture the inherent topology of architectural conceptual designs and identify high-performing latent patterns within such designs. In particular, our goal is to translate architectural graph data into three-dimensional massing models. We are building on our prior ML work, where we, a. discovered latent topological features, b. composed building blocks into new designs, c. evaluated their feasibility, and d. explored Generative Adversarial (Neural) Networks (GAN)-generated design variations. We trained the ML system with architectural design data that we gathered from an online architectural design competition platform, translated them into machine-readable graph representations, and identified their essential subgraphs to develop novel compositions. In this paper, we explore how these novel designs (outputted in graph form), can be translated into three-dimensional architectural form. We present an ML approach to turn graph representations into functional volumetric massing models. The ultimate goal of the study is to develop an end-to-end pipeline to generate architectural design - from a graph representation to a fully developed conceptual proxy of a designed product. The research question is promising in automating conceptual design, and we believe the outcome can be relevant to other design disciplines as well.
keywords	Architectural design, machine learning, conceptual design, deep learning, artificial intelligence
series	SIGraDi
email
last changed	2022/05/23 12:10

_id	acadia21_572
id	acadia21_572
authors	Rodrigues, Ricardo Cesar; Alzate-Martinez, Fábio A.; Escobar, Daniel; Mistry, Mayur
year	2021
title	Rendering Conceptual Design Ideas with Artificial Intelligence
doi	https://doi.org/10.52842/conf.acadia.2021.572
source	ACADIA 2021: Realignments: Toward Critical Computation [Proceedings of the 41st Annual Conference of the Association of Computer Aided Design in Architecture (ACADIA) ISBN 979-8-986-08056-7]. Online and Global. 3-6 November 2021. edited by S. Parascho, J. Scott, and K. Dörfler. 572-575.
summary	This paper documents a data-driven approach to a conceptual rendering workflow with Artificial Intelligence (AI) models. This work originates from the workshop ‘Intro to AI for Architectural Design Explorations’ lectured by the authors Mayur Mistry and Daniel Escobar, during the event ‘Inclusive FUTURES 2021’ at the Digital Futures platform. The observations reflect about the applicability of machine-augmented conceptual design. As a common practice in the fi eld, architects start designing their buildings by sketching their ideas, this is a process that attempts to translate a concept into a spatial and aesthetic solution. Nevertheless, the design process is an iterative and time-consuming task. For this reason, we must experiment new methods that can potentially enhance architectural practice.
series	ACADIA
type	field note
email
last changed	2023/10/22 12:06

_id	ecaade2021_237
id	ecaade2021_237
authors	Sönmez, Ayça and Gönenç Sorguç, Arzu
year	2021
title	Computer-Aided Fabrication Technologies as Computational Design Mediators
doi	https://doi.org/10.52842/conf.ecaade.2021.1.465
source	Stojakovic, V and Tepavcevic, B (eds.), Towards a new, configurable architecture - Proceedings of the 39th eCAADe Conference - Volume 1, University of Novi Sad, Novi Sad, Serbia, 8-10 September 2021, pp. 465-474
summary	The developments in recent technologies through Industry 4.0 lead to the integration of digital design and manufacturing processes. Albeit manufacturing continues to increase its importance as design input, it is generally considered at the last stages of the design process. This misconception results in a gap between digital design and fabrication, leading to differences between the initial design and the fabricated outcome in the context of architectural tectonics. Here, we present an artificial intelligence (AI)-based approach that aims to provide a basis to bridge the gap between computation and fabrication. We considered a case study of a 3D model in two stages. In the first stage, an intuitive and top-down design process is adopted, and in the second stage, an AI-based exploration is conducted with three cases derived from the same 3D model. The outcomes of the two stages provided a dataset including different design parameters to be used in a decision tree classifier algorithm which selects the manufacturing method for a given 3D model. Our results show that generative design simulations based on manufacturing constraints can provide a significant variety of manufacturable design alternatives, and minimizes the difference between design alternatives. Using our proposed approach, the time spent in form-finding and fabrication can be reduced significantly. Additionally, the implementation of decision tree classifier learning algorithm shows that AI can serve designers to make accurate predictions for manufacturing method.
keywords	Generative Design; Computer-Aided Fabrication; Arcihtecture 4.0; Artificial Intelligence; Digital Tectonics
series	eCAADe
email
last changed	2022/06/07 07:56

_id	cdrf2021_117
id	cdrf2021_117
authors	Z. Feng, P. Gu, M. Zheng, X Yan, and D. W. Bao
year	2021
title	Environmental Data-Driven Performance-Based Topological Optimisation for Morphology Evolution of Artificial Taihu Stone
doi	https://doi.org/https://doi.org/10.1007/978-981-16-5983-6_11
source	Proceedings of the 2021 DigitalFUTURES The 3rd International Conference on Computational Design and Robotic Fabrication (CDRF 2021)
summary	Taihu stone is the most famous one among the top four stones in China. It is formed by the water’s erosion in Taihu Lake for hundreds or even thousands of years. It has become a common ornamental stone in classical Chinese gardens because of its porous and intricate forms. At the same time, it has become a cultural symbol through thousands of years of history in China; later, people researched its spatial aesthetics; there are also some studies on its structural properties. For example, it has been found that the opening of Taihu stone caves has a steady-state effect which people develop its value in the theory of Poros City, Porosity in Architecture and some cultural symbols based on the original ornamental value of Taihu stone. This paper introduces a hybrid generative design method that integrates the Computational Fluid Dynamics (CFD) and Bi-directional Evolutionary Structural Optimization (BESO) techniques. Computational Fluid Dynamics (CFD) simulation enables architects and engineers to predict and optimise the performance of buildings and environment in the early stage of the design and topology optimisation techniques BESO has been widely used in structural design to evolve a structure from the full design domain towards an optimum by gradually removing inefficient material and adding materials simultaneously. This research aims to design the artificial Taihu stone based on the environmental data-driven performance feedback using the topological optimisation method. As traditional and historical ornament craftwork in China, the new artificial Taihu stone stimulates thinking about the new value and unique significance of the cultural symbol of Taihu stone in modern society. It proposes possibilities and reflections on exploring the related fields of Porosity in Architecture and Poros City from the perspective of structure.
series	cdrf
email
last changed	2022/09/29 07:53

_id	sigradi2021_234
id	sigradi2021_234
authors	Al Nouri, Mhd Ziwar, Baghdadi, Bilal and Khateeb, Nairooz
year	2021
title	Re-coding Post-War Syria: The Role of Data Collection & Objective Investigations in PostWar Smart City
source	Gomez, P and Braida, F (eds.), Designing Possibilities - Proceedings of the XXV International Conference of the Ibero-American Society of Digital Graphics (SIGraDi 2021), Online, 8 - 12 November 2021, pp. 127–145
summary	Re-coding post-war Syria is an ongoing research and data platform, focused on innovation and collecting comprehensive, infrastructural and socioeconomic analytics, synchronization data, by using AI driven to give a more transparent image of innovating a new methodology to regenerate the future of post-war smart cities into advanced and sustainable urban environments in a smarter way (Fig. 1). The pressure to achieve a rapid Post-war smart city without clear strategy and comprehensive analysis of all aspects will cause a particularly catastrophic collapse in the interconnected social structure, services, education and health care system, leaving a long-term impact on the society. This paper presents the current status of the Research & Documentation methodology in the Data Collection phase by the objective investigations conducted through a series of local and international workshops species developed in this research called “Re-Coding“, offering consequent direct ground surveys, statistics and documentation study of the targeted areas, merging professionalism and youth power with local community to detect an open source data used as a tool to re-generate a precarious area towards a new methodology.
keywords	Post-War Smart cities, Collecting Data, Local community, Objective Investigations, Artificial intelligence
series	SIGraDi
email
last changed	2022/05/23 12:10

_id	sigradi2021_304
id	sigradi2021_304
authors	Andia, Alfredo
year	2021
title	Synthetic Biology Imaginations for the Biscayne Bay, Florida
source	Gomez, P and Braida, F (eds.), Designing Possibilities - Proceedings of the XXV International Conference of the Ibero-American Society of Digital Graphics (SIGraDi 2021), Online, 8 - 12 November 2021, pp. 1487–1497
summary	This project attempts to reimagine Miami and coastal communities with the advent of climate change and the rise of biotechnology. We develop a speculative vision/plan for the Biscayne Bay estuary that envisions infrastructures that grow by themselves using synthetic biology. In this paper, we elaborate on how Synthetic Biology has evolved to become the fastest growing technology in human history, its potential in the development of large-scale infrastructures, and its impact on the future imaginations of Architecture.
keywords	Automated Workflows, Synthetic Biology, Artificial Intelligence, Architecture, Sea-level Rise
series	SIGraDi
email
last changed	2022/05/23 12:11

_id	cdrf2021_231
id	cdrf2021_231
authors	Andrea Macruz, Ernesto Bueno, Gustavo G. Palma, Jaime Vega, Ricardo A. Palmieri, and Tan Chen Wu
year	2021
title	Measuring Human Perception of Biophilically-Driven Design with Facial Micro-expressions Analysis and EEG Biosensor
doi	https://doi.org/https://doi.org/10.1007/978-981-16-5983-6_22
source	Proceedings of the 2021 DigitalFUTURES The 3rd International Conference on Computational Design and Robotic Fabrication (CDRF 2021)
summary	This paper investigates the role technology and neuroscience play in aiding the design process and making meaningful connections between people and nature. Using two workshops as a vehicle, the team introduced advanced technologies and Quantified Self practices that allowed people to use neural data and pattern recognition as feedback for the design process. The objective is to find clues to natural elements of human perception that can inform the design to meet goals for well-being. A pattern network of geometric shapes that achieve a higher level of monitored meditation levels and point toward a positive emotional valence is proposed. By referencing biological forms found in nature, the workshops utilized an algorithmic process that explored how nature can influence architecture. To measure the impact, the team used FaceOSC for capture and an Artificial Neural Network for micro-expression recognition, and a MindWave sensor manufactured by NeuroSky, which documented the human response further. The methodology allowed us to establish a boundary logic, ranking geometric shapes that suggested positive emotions and a higher level of monitored meditation levels. The results pointed us to a deeper level of understanding relative to geometric shapes in design. They indicate a new way to predict how well-being factors can clarify and rationalize a more intuitive design process inspired by nature.
series	cdrf
email
last changed	2022/09/29 07:53

_id	ecaade2021_203
id	ecaade2021_203
authors	Arora, Hardik, Bielski, Jessica, Eisenstadt, Viktor, Langenhan, Christoph, Ziegler, Christoph, Althoff, Klaus-Dieter and Dengel, Andreas
year	2021
title	Consistency Checker - An automatic constraint-based evaluator for housing spatial configurations
doi	https://doi.org/10.52842/conf.ecaade.2021.2.351
source	Stojakovic, V and Tepavcevic, B (eds.), Towards a new, configurable architecture - Proceedings of the 39th eCAADe Conference - Volume 2, University of Novi Sad, Novi Sad, Serbia, 8-10 September 2021, pp. 351-358
summary	The gradual rise of artificial intelligence (AI) and its increasing visibility among many research disciplines affected Computer-Aided Architectural Design (CAAD). Architectural deep learning (DL) approaches are being developed and published on a regular basis, such as retrieval (Sharma et al. 2017) or design style manipulation (Newton 2019; Silvestre et al. 2016). However, there seems to be no method to evaluate highly constrained spatial configurations for specific architectural domains (such as housing or office buildings) based on basic architectural principles and everyday practices. This paper introduces an automatic constraint-based consistency checker to evaluate the coherency of semantic spatial configurations of housing construction using a small set of design principles to evaluate our DL approaches. The consistency checker informs about the overall performance of a spatial configuration followed by whether it is open/closed and the constraints it didn't satisfy. This paper deals with the relation of spaces processed as mathematically formalized graphs contrary to existing model checking software like Solibri.
keywords	model checking, building information modeling, deep learning, data quality
series	eCAADe
email
last changed	2022/06/07 07:54

_id	ecaade2021_263
id	ecaade2021_263
authors	Azadi, Shervin and Nourian, Pirouz
year	2021
title	GoDesign - A modular generative design framework for mass-customization and optimization in architectural design
doi	https://doi.org/10.52842/conf.ecaade.2021.1.285
source	Stojakovic, V and Tepavcevic, B (eds.), Towards a new, configurable architecture - Proceedings of the 39th eCAADe Conference - Volume 1, University of Novi Sad, Novi Sad, Serbia, 8-10 September 2021, pp. 285-294
summary	We present a modular generative design framework for design processes in the built environment that provides for the unification of participatory design and optimization to achieve mass-customization and evidence-based design. The paper articulates this framework mathematically as three meta procedures framing the typical design problems as multi-dimensional, multi-criteria, multi-actor, and multi-value decision-making problems: 1) space-planning, 2) configuring, and 3) shaping; structured as to the abstraction hierarchy of the chain of decisions in design processes. These formulations allow for applying various problem-solving approaches ranging from mathematical derivation & artificial intelligence to gamified play & score mechanisms and grammatical exploration. The paper presents a general schema of the framework; elaborates on the mathematical formulation of its meta procedures; presents a spectrum of approaches for navigating solution spaces; discusses the specifics of spatial simulations for ex-ante evaluation of design alternatives. The ultimate contribution of this paper is laying the foundation of comprehensive Spatial Decision Support Systems (SDSS) for built environment design processes.
keywords	Generative Design; Spatial Configuration; Serious Gaming; Mass Customization; Decision Problems
series	eCAADe
email
last changed	2022/06/07 07:54

_id	caadria2021_146
id	caadria2021_146
authors	Calixto, Victor, Canuto, Robson, Noronha, Marcela, Afrooz, Aida, Gu, Ning and Celani, Gabriela
year	2021
title	A layered approach for the data-driven design of smart cities
doi	https://doi.org/10.52842/conf.caadria.2021.2.739
source	A. Globa, J. van Ameijde, A. Fingrut, N. Kim, T.T.S. Lo (eds.), PROJECTIONS - Proceedings of the 26th CAADRIA Conference - Volume 2, The Chinese University of Hong Kong and Online, Hong Kong, 29 March - 1 April 2021, pp. 739-748
summary	Current approaches to smart cities have focused on implementing technologies to harvest and analyse data through sensors and artificial intelligence to improve urban performance from the top-down. However, cities are complex systems of interconnected layers that change at different speeds. More persistent layers, like networks and occupation, must have smartness embedded in them through smarter design processes. In recent years, there has been an increase in digital tools for urban design, applying computational design methods and data analytics strategies, enabling collaborative and evidence-based approaches that support sustainable urban design. A critical evaluation of their potential to inform design is necessary to aid practitioners to choose and adopt these novel strategies and tools in practice. This paper presents a critical review of selected data-driven design cloud platforms, focusing on data-driven urban design approaches that can enable the use of ICTs to steer cities into a smarter future from the bottom-up.
keywords	Smart Cities; Data-Driven Urban Design; Computational Design
series	CAADRIA
email
last changed	2022/06/07 07:54

_id	sigradi2023_16
id	sigradi2023_16
authors	Carline Andrade Bastos, Bruno, Pereira Barcelos Ribeiro, Letícia, Celeste Santana Cunha, Aura, Monteiro Xavier de Lima, Mariana and Ribeiro Cardoso, Daniel
year	2023
title	Artificial Intelligence Applied to Ideation in Design
source	García Amen, F, Goni Fitipaldo, A L and Armagno Gentile, Á (eds.), Accelerated Landscapes - Proceedings of the XXVII International Conference of the Ibero-American Society of Digital Graphics (SIGraDi 2023), Punta del Este, Maldonado, Uruguay, 29 November - 1 December 2023, pp. 1325–1336
summary	This paper is based on two main concepts: Concept Design and Artificial Intelligence (A.I.). According to Leach (2021), people are surrounded by A.I. in various aspects of daily life. This circumstance highlights the importance of creative professionals to interpret A.I. as a Design tool. The objective of this paper is to evaluate how A.I. can be used in early stages of the ideation process for the development of an artifact. The methodological framework is exploratory-descriptive and was developed through a case study. The practical contribution is to exemplify the simultaneous use of AI and Design tools in a simulation of the creative phase of a furniture project, this result was diagrammed to represent a systematization of where each tool fits into the creative process. The theoretical contribution is to add to the debate around this subject.
keywords	Artificial intelligence, Concept Design, Creative processes, Design Methods, Ideation
series	SIGraDi
email
last changed	2024/03/08 14:08

_id	ecaade2022_249
id	ecaade2022_249
authors	Carrasco Hortal, Jose, Hernandez Carretero, Sergi, Abellan Alarcon, Antonio and Bermejo Pascual, Jorge
year	2022
title	Algae, Gobiidae Fish and Insects that inspire Coastal Custodian Entities - Digital models for a real-virtual space using TouchDesigner
doi	https://doi.org/10.52842/conf.ecaade.2022.1.361
source	Pak, B, Wurzer, G and Stouffs, R (eds.), Co-creating the Future: Inclusion in and through Design - Proceedings of the 40th Conference on Education and Research in Computer Aided Architectural Design in Europe (eCAADe 2022) - Volume 1, Ghent, 13-16 September 2022, pp. 361–370
summary	At the beginning of the twenty-first century, a discipline at the intersection of digital art and science explores how natural and artificial species are affected, coexist, and feed back to humans based on multi-scalar hybrid models. They embody types of surveillance entities or non-human custodians, and serve as inspiration for another generation of designs produced ten years later, the case studies that are presented here. This paper explains the design and parametric fundamentals of a digital architecture installation at the University of Alicante (Spain 2021) using CNC models and the TouchDesigner programming environment. The installation contains a clan of technological-virtual hybrid species, non-human custodians, which: (a) strengthen the Proposal’s discourse on the recognition of legal identity of the Mar Menor lagoon (Southeast Spain); (b) incorporate reactive designs; (c) help raise awareness of the effect of human actions on the lagoon’s ecology and nearby streams. The viewpoint is not anthropocentric, because it adopts the perspective of the foraging fish species or the oxygen-seeking algae species, among others, in order to reveal the deterioration processes. In most cases, the result is a sort of synaesthetic conversation that interweaves light, sound, movement and data.
keywords	Human-Machine Interaction, TouchDesigner, Non-Human Custodian, Responsive Interface, Ethnography of Things
series	eCAADe
email
last changed	2024/04/22 07:10

For more results click below: