Cumincad : CUMINCAD Papers : Search Results

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

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

_id	caadria2018_016
id	caadria2018_016
authors	Zahedi, Ata and Petzold, Frank
year	2018
title	Utilization of Simulation Tools in Early Design Phases Through Adaptive Detailing Strategies
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. 11-20
doi	https://doi.org/10.52842/conf.caadria.2018.2.011
summary	Decisions taken at early stages of building design have a significant effect on the planning steps for the entire lifetime of the project as well as the performance of the building throughout its lifecycle (MacLeamy 2004). Building Information Modelling (BIM) could bring forward and enhance the planning and decision-making processes by enabling the direct reuse of data hold by the model for diverse analysis and simulation tasks (Borrmann et al. 2015). The architect today besides a couple of simplified simulation tools almost exclusively uses his know-how for evaluating and comparing design variants in the early stages of design. This paper focuses on finding new ways to facilitate the use of analytical and simulation tools during the important early phases of conceptual building design, where the models are partially incomplete. The necessary enrichment and proper detailing of the design model could be achieved by means of dialogue-based interaction concepts with analytical and simulation tools through adaptive detailing strategies. This concept is explained using an example scenario for design process. A generic description of the aimed dialog-based interface to various simulation tools will also be discussed in this paper using an example scenario.
keywords	BIM; Early Design Stages; Adaptive Detailing ; Communication Protocols; Design Variants
series	CAADRIA
email
last changed	2022/06/07 07:57

_id	caadria2018_180
id	caadria2018_180
authors	Mekawy, Mohammed and Petzold, Frank
year	2018
title	BIM-Based Model Checking in the Early Design Phases of Precast Concrete Structures
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. 71-80
doi	https://doi.org/10.52842/conf.caadria.2018.2.071
summary	Designers often carry out their work in the early design stages with disregard to prefabrication requirements, leading to poorly thought out design decisions in terms of precast concrete planning efficiency. If precast expertise could be integrated early into design schemes, this would improve design efficiency, reduce errors and misalignments, and save time at every design iteration. The objective is not to replace precast domain experts, but to help architects make better-informed design decisions. This research is part of a wider investigation that aims to develop a rule-based expert system to support an automated review of precast concrete requirements in BIM models in the early design stages, proactively providing feedback for design decision support. This specific paper summarizes the theoretical part of the research and proposes a way to formalize precast expert knowledge as rule-sets in a tabular form that can be later programmed and integrated in a BIM platform for automated checking of BIM models.
keywords	Precast Concrete; Rule-based checking; BIM-based model checking; Expert system; Decision tables
series	CAADRIA
email
last changed	2022/06/07 07:58

_id	acadia18_176
id	acadia18_176
authors	Bidgoli, Ardavan; Veloso,Pedro
year	2018
title	DeepCloud. The Application of a Data-driven, Generative Model in Design
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. 176-185
doi	https://doi.org/10.52842/conf.acadia.2018.176
summary	Generative systems have a significant potential to synthesize innovative design alternatives. Still, most of the common systems that have been adopted in design require the designer to explicitly define the specifications of the procedures and in some cases the design space. In contrast, a generative system could potentially learn both aspects through processing a database of existing solutions without the supervision of the designer. To explore this possibility, we review recent advancements of generative models in machine learning and current applications of learning techniques in design. Then, we describe the development of a data-driven generative system titled DeepCloud. It combines an autoencoder architecture for point clouds with a web-based interface and analog input devices to provide an intuitive experience for data-driven generation of design alternatives. We delineate the implementation of two prototypes of DeepCloud, their contributions, and potentials for generative design.
keywords	full paper, design tools software computing + gaming, ai & machine learning, generative design, autoencoders
series	ACADIA
type	paper
email
last changed	2022/06/07 07:52

_id	ecaade2018_315
id	ecaade2018_315
authors	Koehler, Daniel, Abo Saleh, Sheghaf, Li, Hua, Ye, Chuwei, Zhou, Yaonaijia and Navasaityte, Rasa
year	2018
title	Mereologies - Combinatorial Design and the Description of Urban Form.
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. 85-94
doi	https://doi.org/10.52842/conf.ecaade.2018.2.085
summary	This paper discusses the ability to apply machine learning to the combinatorial design-assembly at the scale of a building to urban form. Connecting the historical lines of discrete automata in computer science and formal studies in architecture this research contributes to the field of additive material assemblies, aggregative architecture and their possible upscaling to urban design. The following case studies are a preparation to apply deep-learning on the computational descriptions of urban form. Departing from the game Go as a testbed for the development of deep-learning applications, an equivalent platform can be designed for architectural assembly. By this, the form of a building is defined via the overlap between separate building parts. Building on part-relations, this research uses mereology as a term for a set of recursive assembly strategies, integrated into the design aspects of the building parts. The models developed by research by design are formally described and tested under a digital simulation environment. The shown case study shows the process of how to transform geometrical elements to architectural parts based merely on their compositional aspects either in horizontal or three-dimensional arrangements.
keywords	Urban Form; Discrete Automata ; Combinatorics; Part-Relations; Mereology; Aggregative Architecture
series	eCAADe
email
last changed	2022/06/07 07:51

_id	caadria2018_057
id	caadria2018_057
authors	Nandavar, Anirudh, Petzold, Frank, Nassif, Jimmy and Schubert, Gerhard
year	2018
title	Interactive Virtual Reality Tool for BIM Based on IFC - Development of OpenBIM and Game Engine Based Layout Planning Tool - A Novel Concept to Integrate BIM and VR with Bi-Directional Data Exchange
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. 453-462
doi	https://doi.org/10.52842/conf.caadria.2018.1.453
summary	With recent advancements in VR (Virtual Reality) technology in the past year, it has emerged as a new paradigm in visualization and immersive HMI (Human-machine Interface). On the other hand, in the past decades, BIM (Building Information Modelling) has emerged as the new standard of implementing construction projects and is quickly becoming a norm than just a co-ordination tool in the AEC industry.Visualization of the digital data in BIM plays an important role as it is the primary communication medium to the project participants, where VR can offer a new dimension of experiencing BIM and improving the collaboration of various stakeholders of a project. There are both open source and commercial solutions to extend visualization of a BIM project in VR, but so far, there are no complete solutions that offer a pure IFC format based solution, which makes the VR integration vendor neutral. This work endeavors to develop a concept for a vendor-neutral BIM-VR integration with bi-directional data exchange in order to extend VR as a collaboration tool than a mere visualization tool in the BIM ecosystem.
keywords	BIM; VR; IFC; Unity; BIM-VR integration; HMI
series	CAADRIA
email
last changed	2022/06/07 07:59

_id	ecaade2018_w12
id	ecaade2018_w12
authors	Rahbar, Morteza
year	2018
title	Application of Artificial Intelligence in Architectural Generative 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. 71-72
doi	https://doi.org/10.52842/conf.ecaade.2018.1.071
summary	In this workshop, data-driven models will be discussed and how they could change the way architects think, design and analyse. Both supervised and unsupervised learning models will be discussed and different projects will be referred as examples. Deep learning models are the third part of the workshop and more specifically, Generative Adversarial Networks will be mentioned in more detail. The GAN's open a new field of generative models in design which is based on data-driven process and we will go into detail with GANs, their branches and how we could test a sample architecture generative problem with GANs.
keywords	Artificial Intelligence; Machine Learning; Generative Design; Knowledge based Design; GAN
series	eCAADe
email
last changed	2022/06/07 08:00

_id	acadia18_146
id	acadia18_146
authors	Rossi, Gabriella; Nicholas, Paul
year	2018
title	Re/Learning the Wheel. Methods to Utilize Neural Networks as Design Tools for Doubly Curved Metal Surfaces
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. 146-155
doi	https://doi.org/10.52842/conf.acadia.2018.146
summary	This paper introduces concepts and computational methodologies for utilizing neural networks as design tools for architecture and demonstrates their application in the making of doubly curved metal surfaces using a contemporary version of the English Wheel. The research adopts an interdisciplinary approach to develop a novel method to model complex geometric features using computational models that originate from the field of computer vision. The paper contextualizes the approach with respect to the current state of the art of the usage of artificial neural networks both in architecture and beyond. It illustrates the cyber physical system that is at the core of this research, with a focus on the employed neural network–based computational method. Finally, the paper discusses the repercussions of these design tools on the contemporary design paradigm.
keywords	full paper, ai & machine learning, digital craft, robotic production, computation
series	ACADIA
type	paper
email
last changed	2022/06/07 07:56

_id	ecaaderis2023_11
id	ecaaderis2023_11
authors	Sepúlveda, Abel, Eslamirad, Nasim, Seyed Salehi, Seyed Shahabaldin, Thalfeldt, Martin and De Luca, Francesco
year	2023
title	Machine Learning-based Optimization Design Workflow based on Obstruction Angles for Building Facades
source	De Luca, F, Lykouras, I and Wurzer, G (eds.), Proceedings of the 9th eCAADe Regional International Symposium, TalTech, 15 - 16 June 2023, pp. 15–24
summary	This paper proposes a ML-based optimization design workflow based on obstruction angles for the optimization of building facades (i.e. g-value and window width). The optimization output consists of the optimal clustering of windows in order to ensure a desired level of daylight provision according to method 2 defined in the EN17307:2018 (i.e. based on Spatial Daylight Autonomy: sDA) and to not exceed a maximum level of specific cooling capacity (SCC). The independent variables or design parameters of the parametric model are: room orientation/dimensions, window dimensions, and obstruction angle (??). The ML prediction models were trained and tested with reliable simulation results using validate softwares. The total number of room combinations is 61440 for sDA and SCC simulations. The development of reliable (90% of right predictions) ML predictive models based on decision tree technique were calibrated. The optimal clustering of windows was done first by floors and secondly by the designer’s need to homogenize the external facade with similar glazing properties and window sizes, having impact on the annual heating consumption. The proposed method help designers to make accurate and faster design decisions during early design stages and renovation plans.
keywords	optimization, daylight, thermal comfort, cooling capacity, machine-learning predictive model, office buildings, cold climates
series	eCAADe
email
last changed	2024/02/05 14:28

_id	caadria2018_173
id	caadria2018_173
authors	Stouffs, Rudi
year	2018
title	A Triple Graph Grammar Approach to Mapping IFC Models into CityGML Building Models
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. 41-50
doi	https://doi.org/10.52842/conf.caadria.2018.2.041
summary	A triple graph grammar approach is adopted as a formal framework for semantic and geometric conversion of IFC models into CityGML Level of Detail 3/4 building models. The triple graph grammar approach supports a semantic mapping from IFC to CityGML, the generation of conversion routines from this mapping, and an incremental approach to achieving a "complete and near-lossless" mapping. The objective of this approach is the development of a methodology and algorithms to automate the conversion of Building Information Models into CityGML building models, capturing both geometric and semantic information as available in the BIM models, in order to create semantically enriched 3D city models that include both exterior and interior structures.
keywords	BIM; CityGML; conversion; semantic; automated
series	CAADRIA
email
last changed	2022/06/07 07:56

_id	ecaade2018_295
id	ecaade2018_295
authors	Dezen-Kempter, Eloisa, Cogima, Camila Kimi, Vieira de Paiva, Pedro Victor and Garcia de Carvalho, Marco Antonio
year	2018
title	BIM for Heritage Documentation - An ontology-based approach
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. 213-222
doi	https://doi.org/10.52842/conf.ecaade.2018.1.213
summary	In the recent decades, the high-resolution remote sensing, through 3D laser scanning and photogrammetry benefited historic buildings maintenance, conservation, and restoration works. However, the dense surface models (DSM) generated from the data capture have nonstructured features as lack of topology and semantic discretization. The process to create a semantically oriented 3D model from the DSM, using the of Building Information Model technology, is a possibility to integrate historical information about the life cycle of the building to maintain and improving architectural valued building stock to its functional level and safeguarding its outstanding historical value. Our approach relies on an ontology-based system to represent the knowledge related to the building. Our work outlines a model-driven approach based on the hybrid data acquisition, its post-processing, the identification of the building' main features for the parametric modeling, and the development of an ontological map integrated with the BIM model. The methodology proposed was applied to a large-scale industrial historical building, located in Brazil. The DSM were compared, providing a qualitative assessment of the proposed method.
keywords	Reality-based Surveying; Ontology-based System; BIM; Built heritage management
series	eCAADe
email
last changed	2022/06/07 07:55

_id	ecaade2018_265
id	ecaade2018_265
authors	Tauscher, Helga and Stouffs, Rudi
year	2018
title	An IFC-to-CityGML Triple Graph Grammar
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. 517-524
doi	https://doi.org/10.52842/conf.ecaade.2018.1.517
summary	A triple graph grammar has been adopted as a formal framework for semantic and geometric conversion of IFC models into CityGML Level of Detail (LoD) 3/4 building models. The advantages of a triple graph grammar approach are threefold: firstly, it allows for the conversion rules to be graphically defined; secondly, the generation of the conversion routines corresponding to these rules can be automated; and, thirdly, a complete mapping can be achieved in an incremental way by adding rule by rule.The objective of this work is the development of a methodology and algorithms to automate the conversion of Building Information Models into CityGML building models, capturing both geometric and semantic information as available in the BIM models, in order to create semantically enriched 3D city models that include both exterior and interior structures such as corridors, rooms, internal doors, and stairs.
keywords	BIM; CityGML; Triple Graph Grammar; conversion
series	eCAADe
email
last changed	2022/06/07 07:58

_id	ecaade2018_331
id	ecaade2018_331
authors	Trento, Armando and Fioravanti, Antonio
year	2018
title	Contextual Capabilities Meet Human Behaviour - Round the peg and square the hole
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. 613-620
doi	https://doi.org/10.52842/conf.ecaade.2018.1.613
summary	To improve environmental wellbeing and productivity, design innovation focuses on human's use-process, evolving individual space to flexible and specialized ones, according to the users' tasks - activity-based. BIM models supports sophisticated behaviours' simulation such as energy, acoustics, although it is not able to manage space use-processes. The present paper rather than a report of a case study or the presentation of a new methodology wants to contribute, together with previous works, in sketching a theroretical framework within which it is possible to compute the interaction between users and spaces (and vice versa). The quest is to reflect on possible paths for engineering knowledge and understanding, providing a BIM system the semantic information required to operate adaptively and achieve robust and innovative goal-directed behavior. Compared to current research on simulation systems, this research approach links Context, intended as spaces capabilities to Actor's Behavioural Knowledge including formalization of personality typologies and profiled behavioural patterns. By means of a classical problem solving metaphor, the "squared peg in a round hole" one, multiple categories for goal achievement are sketched, based on reciprocal Actors and Context behaviour adaptation.
keywords	Use-process Knowledge; Behavioural Knowledge; Use Simulation; Cognitive Computing
series	eCAADe
email
last changed	2022/06/07 07:57

_id	ecaade2018_193
id	ecaade2018_193
authors	Ostrowska-Wawryniuk, Karolina and Nazar, Krzysztof
year	2018
title	Generative BIM Automation Strategies for Prefabricated Multi-Family Housing 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. 247-256
doi	https://doi.org/10.52842/conf.ecaade.2018.1.247
summary	The increasing housing shortage in contemporary Poland calls for efficient ways of design and construction. In the context of time efficiency and shrinking manpower, prefabrication is considered as one of the means of introducing low and middle income housing to the market. The article presents the process of developing an experimental tool for aiding multi-family housing architectural design with the use of prefabrication. We use the potential of BIM technology as a flexible environment for comparing multiple design options and, therefore, supporting the decision-making process. The presented experiment is realized in the Autodesk Revit environment and incorporates custom generative scripts developed in Dynamo-for-Revit and Grasshopper. The prototype tool analyzes an input Revit model and simulates a prefabricated alternative based on the user-specified boundary conditions. We present our approach to the analyzing and the splitting of the input model as well as five different strategies of performing the simulation within the Revit environment.
keywords	Building Information Modeling; generative BIM; residential building design; prefabrication; design automation; Dynamo
series	eCAADe
email
last changed	2022/06/07 08:00

_id	ijac201816104
id	ijac201816104
authors	Sahbaz, Eray and Aysun Özköse
year	2018
title	Experiencing historical buildings through digital computer games
source	International Journal of Architectural Computing vol. 16 - no. 1, 22-33
summary	This study aims to demonstrate the value of experiencing historical buildings through the digital game–based learning method. A three-dimensional computer game was developed to assess the digital game–based learning method as a supportive hypermedia tool in architectural education. The computer game features interactive game missions that enable students to get a close-up experience of the buildings. As part of the study, an experiment was conducted comparing the digital game–based learning method against other traditional methods in learning about historical buildings. The results of the study show that the digital game–based learning method can serve as a support for lecturing on historical buildings to help improve students’ learning experience.
keywords	Cultural heritage, interactive learning environments, architecture, digital game–based learning, heritage conservation, hypermedia systems, heritage protection
series	journal
email
last changed	2019/08/07 14:03

_id	ecaade2018_120
id	ecaade2018_120
authors	Varinlioglu, Guzden and Turhan, Gozde Damla
year	2018
title	A Comparative Study of Formal and Informal Teaching Methods in the Digital Architectural Curricula
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. 409-416
doi	https://doi.org/10.52842/conf.ecaade.2018.1.409
summary	Design educators are rethinking design education because of the high-demand for the integration of CAD/CAM in the architectural curriculum. However, in traditional design schools with fewer digital courses and more emphasis on the studio courses, an important consideration is how these skills are introduced. With this in mind, and referring to the informal teaching setup, such as workshops and student competitions, this paper describes a study comparing two pedagogical strategies based on a workshop within the curricula and a competition as an extracurricular activity. ICMP method will be used to measure the development of participating students' abilities in analysis, synthesis, integration and critical thinking, under mentor supervision, and enable an evaluation of this approach to the integration of digital thinking, application, and informal design teaching/learning experience in architectural education.
keywords	architectural curricula; informal teaching; digital fabrication; comparative study
series	eCAADe
email
last changed	2022/06/07 07:58

_id	caadria2018_243
id	caadria2018_243
authors	Yin, Shi and Xiao, Yiqiang
year	2018
title	Research on the Impact of Traditional Urban Geometry on Outdoor Thermal Environment - Case Study of Neighbourhoods with Arcade Street in South China
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. 503-512
doi	https://doi.org/10.52842/conf.caadria.2018.2.503
summary	With the deterioration of urban environment gradually in these decades, the demand for improving the outdoor thermal environment is increasing. The traditional architecture and urban planning contain abundant climate responding strategy, while current studies about it are still insufficient. Furthermore, many researches had profound results on how different urban design parameters would impact outdoor thermal comfort, but only a few of them could achieve an effective transformation into a practical scenario. Thus, this paper attempts to present the impact of different traditional urban form, which is extracted from different neighborhoods with arcade street in south China, on the outdoor thermal environment, through field measurements and climatic simulation with Envi-met. Moreover, these different complex urban forms were transferred into a simplified form with uniform character and simulating based on the same boundary condition. Comparing the SVF (Sky View Factor) and PET (Physiological Equivalent Temperature) of each point, the organic urban form would lead better thermal environment than others on the main road. On the other hand, the SVF of a point is not the only one aspect of its PET, which related with the form of urban geometry as well.
keywords	Climate Responsive Urban Design; Traditional Arcade-Street Neighborhood; Urban Geometry; Outdoor Thermal Comfort
series	CAADRIA
email
last changed	2022/06/07 07:57

_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_176
id	ecaade2018_176
authors	Fisher-Gewirtzman, Dafna and Polak, Nir
year	2018
title	Integrating Crowdsourcing & Gamification in an Automatic Architectural Synthesis Process
source	Kepczynska-Walczak, A, Bialkowski, S (eds.), Computing for a better tomorrow - Proceedings of the 36th eCAADe Conference - Volume 1, Lodz University of Technology, Lodz, Poland, 19-21 September 2018, pp. 439-444
doi	https://doi.org/10.52842/conf.ecaade.2018.1.439
summary	This work covers the methodological approach that is used to gather information from the wisdom of crowd, to be utilized in a machine learning process for the automatic generation of minimal apartment units. The flexibility in the synthesis process enables the generation of apartment units that seem to be random and some are unsuitable for dwelling. Thus, the synthesis process is required to classify units based on their suitability. The classification is deduced from opinions of human participants on previously generated units. As the definition of "suitability" may be subjective, this work offers a crowdsourcing method in order to reach a large number of participants, that as a whole would allow to produce an objective classification. Gaming elements have been adopted to make the crowdsourcing process more intuitive and inviting for external participants.
keywords	crowdsourcing and gamification; urban density; optimization; automated architecture synthesis; minimum apartments; visual openness
series	eCAADe
email
last changed	2022/06/07 07:51

_id	acadia18_156
id	acadia18_156
authors	Huang, Weixin; Zheng, Hao
year	2018
title	Architectural Drawings Recognition and Generation through Machine Learning
source	ACADIA // 2018: Recalibration. On imprecisionand infidelity. [Proceedings of the 38th Annual Conference of the Association for Computer Aided Design in Architecture (ACADIA) ISBN 978-0-692-17729-7] Mexico City, Mexico 18-20 October, 2018, pp. 156-165
doi	https://doi.org/10.52842/conf.acadia.2018.156
summary	With the development of information technology, the ideas of programming and mass calculation were introduced into the design field, resulting in the growth of computer- aided design. With the idea of designing by data, we began to manipulate data directly, and interpret data through design works. Machine Learning as a decision making tool has been widely used in many fields. It can be used to analyze large amounts of data and predict future changes. Generative Adversarial Network (GAN) is a model framework in machine learning. It’s specially designed to learn and generate output data with similar or identical characteristics. Pix2pixHD is a modified version of GAN that learns image data in pairs and generates new images based on the input. The author applied pix2pixHD in recognizing and generating architectural drawings, marking rooms with different colors and then generating apartment plans through two convolutional neural networks. Next, in order to understand how these networks work, the author analyzed their framework, and provided an explanation of the three working principles of the networks, convolution layer, residual network layer and deconvolution layer. Lastly, in order to visualize the networks in architectural drawings, the author derived data from different layer and different training epochs, and visualized the findings as gray scale images. It was found that the features of the architectural plan drawings have been gradually learned and stored as parameters in the networks. As the networks get deeper and the training epoch increases, the features in the graph become more concise and clearer. This phenomenon may be inspiring in understanding the designing behavior of humans.
keywords	full paper, design study, generative design, ai + machine learning, ai & machine learning
series	ACADIA
type	paper
email
last changed	2022/06/07 07:49

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

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