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 628

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

_id	ijac201816407
id	ijac201816407
authors	Mahankali, Ranjeeth; Brian R. Johnson and Alex T. Anderson
year	2018
title	Deep learning in design workflows: The elusive design pixel
source	International Journal of Architectural Computing vol. 16 - no. 4, 328-340
summary	The recent wave of developments and research in the field of deep learning and artificial intelligence is causing the border between the intuitive and deterministic domains to be redrawn, especially in computer vision and natural language processing. As designers frequently invoke vision and language in the context of design, this article takes a step back to ask if deep learning’s capabilities might be applied to design workflows, especially in architecture. In addition to addressing this general question, the article discusses one of several prototypes, BIMToVec, developed to examine the use of deep learning in design. It employs techniques like those used in natural language processing to interpret building information models. The article also proposes a homogeneous data format, provisionally called a design pixel, which can store design information as spatial-semantic maps. This would make designers’ intuitive thoughts more accessible to deep learning algorithms while also allowing designers to communicate abstractly with design software.
keywords	Associative logic, creative processes, deep learning, embedding vectors, BIMToVec, homogeneous design data format, design pixel, idea persistence
series	journal
email
last changed	2019/08/07 14:04

_id	sigradi2023_375
id	sigradi2023_375
authors	Consalter Diniz, Maria Luisa, Polverini Boeing, Lais, dos Santos Carvalho, Wendel and Bertola Duarte, Rovenir
year	2023
title	Natural Language Processing, Sentiment Analysis, and Urban Studies: A Systematic Review
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. 1761–1772
summary	This paper discusses the potential of using data from social media and location data platforms to create cartographies that enhance our understanding of urban dynamics. Natural Language Processing (NLP) and sentiment analysis are highlighted as essential tools for comprehending and categorizing this data. The study conducted a systematic review of NLP and sentiment analysis applications in urban studies, covering 27 peer-reviewed journals and conference papers published between 2018 and 2023. The research classified applications into six categories: urban livability, governance and management, user and landscape perception, land use and zoning, public health, and transportation and mobility. Most studies primarily relied on data from social media platforms like Twitter and location data sources such as Google Maps and Trip Advisor. Challenges include dealing with irrelevant or misleading information in publicly available data and limited accuracy when analyzing sentiments of non-English-speaking populations.
keywords	Natural language processing, Sentiment analysis, Urban studies, Digital cartographies, Systematic review.
series	SIGraDi
email
last changed	2024/03/08 14:09

_id	ecaade2018_392
id	ecaade2018_392
authors	Gargaro, Silvia, Cigola, Michela, Gallozzi, Arturo and Fioravanti, Antonio
year	2018
title	Cultural Heritage Knowledge Context - A model based on Collaborative Cultural approach
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. 205-214
doi	https://doi.org/10.52842/conf.ecaade.2018.2.205
summary	Cultural Heritage is a wide concept. It's what remains of the past generations Cultural Heritage includes tangible culture (such as buildings, monuments, landscapes, books, works of art and artifacts), intangible culture (such as folklore, music, traditions, language and knowledge) and natural heritage (including culturally significant landscapes, and biodiversity). A good preservation, restauration and valorization of Cultural Heritage embraces tangible and intangible culture, actually not evaluated in an holistic way.Cultural Heritage is not only an historical memory of the past, but the mirror of an anthropological reality that characterizes our personal and collective identity within a cultural context. The question is: How can we take into account these thought categories? The model proposed would be an used methodology to analyze the model for data acquisition, processing, modeling and implementation of knowledge on culture and social context through ontologies. The purpose of the research is to analyze the relationship between Cultural Context and Cultural Heritage.The contribution proposes an original approach to Cultural Heritage based on a social and cultural approach, transforming the user as an actor for the acquisition of raw data and cultural knowledge, applying the model to the Archaeological Complex of Casinum, in South Latium.
keywords	Cultural Heritage; Context Knowledge; Intangible Knowledge; Ontologies; Human Behavior Constraints
series	eCAADe
email
last changed	2022/06/07 07:51

_id	ecaade2018_139
id	ecaade2018_139
authors	Cudzik, Jan and Radziszewski, Kacper
year	2018
title	Artificial Intelligence Aided Architectural Design
source	Kepczynska-Walczak, A, Bialkowski, S (eds.), Computing for a better tomorrow - Proceedings of the 36th eCAADe Conference - Volume 1, Lodz University of Technology, Lodz, Poland, 19-21 September 2018, pp. 77-84
doi	https://doi.org/10.52842/conf.ecaade.2018.1.077
summary	Tools and methods used by architects always had an impact on the way building were designed. With the change in design methods and new approaches towards creation process, they became more than ever before crucial elements of the creation process. The automation of architects work has started with computational functions that were introduced to traditional computer-aided design tools. Nowadays architects tend to use specified tools that suit their specific needs. In some cases, they use artificial intelligence. Despite many similarities, they have different advantages and disadvantages. Therefore the change in the design process is more visible and unseen before solution are brought in the discipline. The article presents methods of applying the selected artificial intelligence algorithms: swarm intelligence, neural networks and evolutionary algorithms in the architectural practice by authors. Additionally research shows the methods of analogue data input and output approaches, based on vision and robotics, which in future combined with intelligence based algorithms, might simplify architects everyday practice. Presented techniques allow new spatial solutions to emerge with relatively simple intelligent based algorithms, from which many could be only accomplished with dedicated software. Popularization of the following methods among architects, will result in more intuitive, general use design tools.
keywords	computer aideed design; artificial intelligence,; evolutionary algorithms; swarm behaviour; optimization; parametric design
series	eCAADe
email
last changed	2022/06/07 07:56

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

_id	caadria2018_083
id	caadria2018_083
authors	Luo, Dan, Wang, Jinsong and Xu, Weiguo
year	2018
title	Robotic Automatic Generation of Performance Model for Non-Uniform Linear Material via Deep Learning
source	T. Fukuda, W. Huang, P. Janssen, K. Crolla, S. Alhadidi (eds.), Learning, Adapting and Prototyping - Proceedings of the 23rd CAADRIA Conference - Volume 1, Tsinghua University, Beijing, China, 17-19 May 2018, pp. 39-48
doi	https://doi.org/10.52842/conf.caadria.2018.1.039
summary	In the following research, a systematic approach is developed to generate an experiment-based performance model that computes and customizes properties of non-uniform linear materials to accommodate the form of designated curve under bending and natural force. In this case, the test subject is an elastomer strip of non-uniform sections. A novel solution is provided to obtain sufficient training data required for deep learning with an automatic material testing mechanism combining robotic arm automation and image recognition. The collected training data are fed into a deep combination of neural networks to generate a material performance model. Unlike most traditional performance models that are only able to simulate the final form from the properties and initial conditions of the given materials, the trained neural network offers a two-way performance model that is also able to compute appropriate material properties of non-uniform materials from target curves. This network achieves complex forms with minimal and effective programmed materials with complicated nonlinear properties and behaving under natural forces.
keywords	Material performance model; Deep Learning; Robotic automation; Material computation; Neural network
series	CAADRIA
email
last changed	2022/06/07 07:59

_id	ecaade2018_335
id	ecaade2018_335
authors	Seifert, Nils and Petzold, Frank
year	2018
title	Architects & Algorithms - Developing Interactive Visualizations for Architectural Communication
source	Kepczynska-Walczak, A, Bialkowski, S (eds.), Computing for a better tomorrow - Proceedings of the 36th eCAADe Conference - Volume 1, Lodz University of Technology, Lodz, Poland, 19-21 September 2018, pp. 361-370
doi	https://doi.org/10.52842/conf.ecaade.2018.1.361
summary	The paper presents the concept and results of a seminar that addresses the intersecting fields of architecture and urbanism, data and information visualization as well as information technology. In the first part of the paper, an introduction to the seminar topic and relevance in the context of architectural education and practice is given. Subsequently, the course concept, the learning contents and the corresponding learning objectives are presented. In the second part, selected student projects are shown as exemplary course results. In the conclusion, the results of the seminar for students, teachers and research implications are discussed. The overall aim of this publication is to draw on the experience gained in this field of education to offer starting points for others in developing similar teaching concepts and support for their implementation.
keywords	Urban Planning; Programming; Information Design; Data Visualization; Smart City; Processing
series	eCAADe
email
last changed	2022/06/07 07:56

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

_id	caadria2018_303
id	caadria2018_303
authors	Song, Jae Yeol, Kim, Jin Sung, Kim, Hayan, Choi, Jungsik and Lee, Jin Kook
year	2018
title	Approach to Capturing Design Requirements from the Existing Architectural Documents Using Natural Language Processing Technique
source	T. Fukuda, W. Huang, P. Janssen, K. Crolla, S. Alhadidi (eds.), Learning, Adapting and Prototyping - Proceedings of the 23rd CAADRIA Conference - Volume 2, Tsinghua University, Beijing, China, 17-19 May 2018, pp. 247-254
doi	https://doi.org/10.52842/conf.caadria.2018.2.247
summary	This paper describes an approach to utilizing natural language processing (NLP) to capture design requirements from the natural language-based architectural documents. In various design stage of the architectural process, there are several different kinds of documents describing requirements for buildings. Capturing the design requirements from those documents is based on extracting information of objects, their properties, and relations. Until recently, interpreting and extracting that information from documents are almost done by a manual process. To intelligently automate the conventional process, the computer has to understand the semantics of natural languages. In this regards, this paper suggests an approach to utilizing NLP for semantic analysis which enables the computer to understand the semantics of the given text data. The proposed approach has following steps: 1) extract noun words which mostly represent objects and property data in Korean Building Act; 2) analyze the semantic relations between words, using NLP and deep learning; 3) Based on domain database, translate the noun words in objects and properties data and find out their relations.
keywords	NLP (Natural Language Processing); Deep learning; Design requirements; Korean Building Act; Semantic analysis
series	CAADRIA
email
last changed	2022/06/07 07:56

_id	ecaade2018_389
id	ecaade2018_389
authors	Algeciras-Rodriguez, Jose
year	2018
title	Stochastic Hybrids - From references to design options through Self-Organizing Maps methodology.
source	Kepczynska-Walczak, A, Bialkowski, S (eds.), Computing for a better tomorrow - Proceedings of the 36th eCAADe Conference - Volume 1, Lodz University of Technology, Lodz, Poland, 19-21 September 2018, pp. 119-128
doi	https://doi.org/10.52842/conf.ecaade.2018.1.119
summary	This ongoing research aims to define a general assisted design method to offer non-trivial design options, where form is produced by merging characteristics from initial reference samples collection that serves as an input set. This project explores design processes laying on the use of non-linear procedures and experiments with Self-Organizing Map (SOM), as neural networks algorithms, to generate geometries. All processes are applied to a set of models representing classic sculpture, whose characteristics are encoded by the SOM process. The result of it is a set of new geometry resembling characteristics from the original references. This method produces hybrid forms that acquire characteristics from several input references. The resulting hybrid entities are intended to be non-trivial solutions to specific design situations, so far, at the stage of this research, mainly formal requirements.
keywords	Self-Orgnizing Maps; Cognitive Space; Design Options; Form Finding; Artificial Intelligence
series	eCAADe
email
last changed	2022/06/07 07:54

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

_id	caadria2018_029
id	caadria2018_029
authors	Ayoub, Mohammed
year	2018
title	Adaptive Façades:An Evaluation of Cellular Automata Controlled Dynamic Shading System Using New Hourly-Based Metrics
source	T. Fukuda, W. Huang, P. Janssen, K. Crolla, S. Alhadidi (eds.), Learning, Adapting and Prototyping - Proceedings of the 23rd CAADRIA Conference - Volume 2, Tsinghua University, Beijing, China, 17-19 May 2018, pp. 83-92
doi	https://doi.org/10.52842/conf.caadria.2018.2.083
summary	This research explores utilizing Cellular Automata patterns as climate-adaptive dynamic shading systems to mitigate the undesirable impacts by excessive solar penetration in cooling-dominant climates. The methodological procedure is realized through two main phases. The first evaluates all 256 Elementary Cellular Automata possible rules to elect the ones with good visual and random patterns, to ensure an equitable distribution of the natural daylight in internal spaces. Based on the newly developed hourly-based metrics, simulations are conducted in the second phase to evaluate the Cellular Automata controlled dynamic shadings performance, and formalize the adaptive façade variation logic that maximizes daylighting and minimizes energy demand.
keywords	Adaptive Façade; Dynamic Shading; Cellular Automata; Hourly-Based Metric; Performance Evaluation
series	CAADRIA
email
last changed	2022/06/07 07:54

_id	ecaade2018_219
id	ecaade2018_219
authors	Bai, Nan, Ye, Wenqia, Li, Jianan, Ding, Huichao, Pienaru, Meram-Irina and Bunschoten, Raoul
year	2018
title	Customised Collaborative Urban Design - A Collective User-based Urban Information System through Gaming
source	Kepczynska-Walczak, A, Bialkowski, S (eds.), Computing for a better tomorrow - Proceedings of the 36th eCAADe Conference - Volume 1, Lodz University of Technology, Lodz, Poland, 19-21 September 2018, pp. 419-428
doi	https://doi.org/10.52842/conf.ecaade.2018.1.419
summary	As we step into a new data-based information age, it is important to get citizens involved in the whole design process. Our research tries to build up a user-based urban information system by collecting the data of neighborhood land use preference from all the residents through gaming. The result of each individual decision will be displayed in real time using Augmented Reality technology, while the collective decision dataset will be stored, analyzed and learnt by computer, forming an optimal layout that meets the highest demand of the community. A pre-experiment has been conducted in a. an abstract virtual site and b. an existing site by collecting opinions from 122 participants, which shows that the system works well as a new method for collaborative design. This system has the potential to be applied both in realistic planning processes, as a negotiation toolkit, and in virtual urban forming, in the case of computer games or space colonization.
keywords	Collaborative Design; Customization; Urban Design; Gaming; Information System
series	eCAADe
email
last changed	2022/06/07 07:54

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

_id	sigradi2018_1671
id	sigradi2018_1671
authors	Brito, Michele; de Sá, Ana Isabel; Borges, Jéssica; Rena, Natacha
year	2018
title	IndAtlas - Technopolitic platform for urban investigation
source	SIGraDi 2018 [Proceedings of the 22nd Conference of the Iberoamerican Society of Digital Graphics - ISSN: 2318-6968] Brazil, São Carlos 7 - 9 November 2018, pp. 1305-1312
summary	This article presents the project of the urban research platform IndAtlas, currently in early development stage by UFMG’s Research Group Indisciplinar. Through the association of crowdsourcing tools, a spatial database and the production of visualizations of different types, it is intended to create a Web platform for collecting, analyzing and depicting information about processes of production and transformation of urban space. It is proposed that the phenomena (themes) investigated in the platform are approached mainly from four axes: 1) spatial / territorial; 2) temporal; 3) social; 4) communicational. To do this, we try to combine online collaborative maps with the production of dynamic timelines and visualizations of networks of social actors (graphs), connected with social networks and Wiki pages. The article will address the development of Indisciplinar’s working method, which guided the proposal of the platform, as well as the functional and technical aspects to be observed for its implementation, the proposed architecture and the importance of interoperability for the project. Finally, the inquiries derived from the first test experiment of an IndAtlas test prototype will be presented. The experiment took place in a workshop belonging to the Cidade Eletrônika 2018 Festival – an arts and technology event. The workshop was offered in January of the same year, and it proposed a collaborative cartography of the Santa Tereza neighborhood, in Belo Horizonte / MG – a traditional neighborhood of great importance for historical heritage, currently subject to great real estate pressure and the focus of a series of territorial disputes.
keywords	IndAtlas, Crowdsourcing, Urban Technopolitics,, Digital Cartographies,, Spatial Data.
series	SIGRADI
email
last changed	2021/03/28 19:58

_id	caadria2018_181
id	caadria2018_181
authors	Chun, Junho, Lee, Juhun and Park, Daekwon
year	2018
title	TOPO-JOINT - Topology Optimization Framework for 3D-Printed Building Joints
source	T. Fukuda, W. Huang, P. Janssen, K. Crolla, S. Alhadidi (eds.), Learning, Adapting and Prototyping - Proceedings of the 23rd CAADRIA Conference - Volume 1, Tsinghua University, Beijing, China, 17-19 May 2018, pp. 205-214
doi	https://doi.org/10.52842/conf.caadria.2018.1.205
summary	Joints and connectors are often the most complex element in building assemblies and systems. To ensure the performance of the assemblies and systems, it is critical to optimize the geometry and configurations of the joints based on key functional requirements (e.g., stiffness and thermal exchange). The proposed research focuses on developing a multi-objective topology optimization framework that can be utilized to design highly customized joints and connections for building applications. The optimized joints that often resemble tree structures or bones are fabricated using additive manufacturing techniques. This framework is built upon the integration of high-fidelity topology optimization algorithms, additive manufacturing, computer simulations and parametric design. Case studies and numerical applications are presented to demonstrate the validity and effectiveness of the proposed optimization and additive manufacturing framework. Optimal joint designs from a variety of architectural and structural design considerations, such as stiffness, thermal exchange, and vibration are discussed to provide an insightful interpretation of these interrelationships and their impact on joint performance.
keywords	Topology optimization; parametric design; 3d printing
series	CAADRIA
email
last changed	2022/06/07 07:56

_id	ecaade2018_301
id	ecaade2018_301
authors	Cocho-Bermejo, Ana, Birgonul, Zeynep and Navarro-Mateu, Diego
year	2018
title	Adaptive & Morphogenetic City Research Laboratory
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. 659-668
doi	https://doi.org/10.52842/conf.ecaade.2018.2.659
summary	"Smart City" business model is guiding the development of future metropolises. Software industry sales to town halls for city management services efficiency improvement are, these days, a very pro?table business. Being the model decided by the industry, it can develop into a dangerous situation in which the basis of the new city design methodologies is decided by agents outside academia expertise. Drawing on complex science, social physics, urban economics, transportation theory, regional science and urban geography, the Lab is dedicated to the systematic analysis of, and theoretical speculation on, the recently coined "Science of Cities" discipline. On the research agenda there are questions arising from the synthesis of architecture, urban design, computer science and sociology. Collaboration with citizens through inclusion and empowerment, and, relationships "City-Data-Planner-Citizen" and "Citizen-Design-Science", configure Lab's methodology provoking a dynamic responsive process of design that is yet missing on the path towards the real responsive city.
keywords	Smart City; Morphogenetic Urban Design; Internet of Things; Building Information Modelling; Evolutionary Algorithms; Machine Learning & Artificial Intelligence
series	eCAADe
email
last changed	2022/06/07 07:56

_id	ecaade2018_399
id	ecaade2018_399
authors	Cutellic, Pierre
year	2018
title	UCHRON - An Event-Based Generative Design Software Implementing Fast Discriminative Cognitive Responses from Visual ERP BCI
source	Kepczynska-Walczak, A, Bialkowski, S (eds.), Computing for a better tomorrow - Proceedings of the 36th eCAADe Conference - Volume 2, Lodz University of Technology, Lodz, Poland, 19-21 September 2018, pp. 131-138
doi	https://doi.org/10.52842/conf.ecaade.2018.2.131
summary	This research aims at investigating BCI technologies in the broad scope of CAAD applications exploiting early visual cognition in computational design. More precisely, this paper will describe the investigation of key BCI and ML components for the implementation and development of a software supporting this research : Uchron. It will be organised as follows. Firstly, it will introduce the pursued interest and contribution that visual-ERP EEG based BCI application for Generative Design may provide through a synthetic review of precedents and BCI technology. Secondly, selected BCI components will be described and a methodology will be presented to provide an appropriate framework for a CAAD software approach. This section main focus is on the processing component of the BCI. It distinguishes two key aspects of discrimination and generation in its design and proposes a new model based on GAN for modulated adversarial design. Emphasis will be made on the explicit use of inference loops integrating fast human cognitive responses and its individual capitalisation through time in order to reflect towards the generation of design and architectural features.
keywords	Human Computer Interaction; Neurodesign; Generative Design; Design Computing and Cognition; Machine Learning
series	eCAADe
email
last changed	2022/06/07 07:56

_id	ecaade2018_438
id	ecaade2018_438
authors	Das, Subhajit
year	2018
title	Interactive Artificial Life Based Systems, Augmenting Design Generation and Evaluation by Embedding Expert Opinion - A Human Machine dialogue for form finding.
source	Kepczynska-Walczak, A, Bialkowski, S (eds.), Computing for a better tomorrow - Proceedings of the 36th eCAADe Conference - Volume 1, Lodz University of Technology, Lodz, Poland, 19-21 September 2018, pp. 85-94
doi	https://doi.org/10.52842/conf.ecaade.2018.1.085
summary	Evolution of natural life and subsequently selection of life forms is an interesting topic that has been explored multiple times. This area of research and its application has high relevance in evolutionary design and automated design generation. Taking inspiration from Charles Darwin's theory, all biological species were formed by the process of evolution based on natural selection of the fittest (Darwin, n.d.) this paper explains exploratory research showcasing semi-automatic design generation. This is realized by an interactive artificial selection tool, where the designer or the end user makes key decisions steering the propagation and breeding of future design artifacts. This paper, describes two prototypes and their use cases, highlighting interaction based optimal design selection. One of the prototypes explains a 2d organic shape creator using a metaball shape approach, while the other discusses a spatial layout generation technique for conceptual design.
keywords	design generation; implicit surfaces; artificial life; decision making; artificial selection; spatial layout generation
series	eCAADe
email
last changed	2022/06/07 07:55

_id	sigradi2018_1412
id	sigradi2018_1412
authors	de Oliveira Gomes, Emerson Bruno; da Silva Machado, Rodrigo Carlos; Machado Gomes, Cristiani; de Souza Xavier, Luis Gustavo
year	2018
title	The Virtual Reality as a tool to analyze modifications in the architecture of the city. Case study: the historical center of the city of Belém-Pará.
source	SIGraDi 2018 [Proceedings of the 22nd Conference of the Iberoamerican Society of Digital Graphics - ISSN: 2318-6968] Brazil, São Carlos 7 - 9 November 2018, pp. 860-865
summary	This paper presents the partial results of a research that experiments the use of Virtual Reality (VR) in the analysis of future interventions in the architecture of the city of Belém. The objective was the virtual reconstruction of part of the port area of the city, as it was about 100 years. The methods include a historical survey of the site, visits to obtain photographs and measurements, as well as the digital reconstruction of buildings (external faces only). The experiment used Sketchup software for modeling, Unity 3D for rendering and navigation, and HTC Vive glasses for immersion.
keywords	Virtual reality; Architecture; History; Engine games
series	SIGRADI
email
last changed	2021/03/28 19:58

For more results click below: