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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_id	caadria2021_089
id	caadria2021_089
authors	Cristie, Verina, Ibrahim, Nazim and Joyce, Sam Conrad
year	2021
title	Capturing and Evaluating Parametric Design Exploration in a Collaborative Environment - A study case of versioning for parametric design
doi	https://doi.org/10.52842/conf.caadria.2021.2.131
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. 131-140
summary	Although parametric modelling and digital design tools have become ubiquitous in digital design, there is a limited understanding of how designers apply them in their design processes (Yu et al., 2014). This paper looks at the use of GHShot versioning tool developed by the authors (Cristie & Joyce, 2018; 2019) used to capture and track changes and progression of parametric models to understand early-stage design exploration and collaboration empirically. We introduce both development history graph-based metrics (macro-process) and parametric model and geometry change metric (micro-process) as frameworks to explore and understand the captured progression data. These metrics, applied to data collected from three cohorts of classroom collaborative design exercises, exhibited students' distinct modification patterns such as major and complex creation processes or minor parameter explorations. Finally, with the metrics' applicability as an objective language to describe the (collaborative) design process, we recommend using versioning for more data-driven insight into parametric design exploration processes.
keywords	Design exploration; parametric design; history recording; version control; collaborative design
series	CAADRIA
email
last changed	2022/06/07 07:56

_id	caadria2018_314
id	caadria2018_314
authors	Kim, Jin Sung, Song, Jae Yeol and Lee, Jin Kook
year	2018
title	Approach to the Extraction of Design Features of Interior Design Elements Using Image Recognition Technique
doi	https://doi.org/10.52842/conf.caadria.2018.2.287
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. 287-296
summary	This paper aims to propose deep learning-based approach to the auto-recognition of their design features of interior design elements using given digital images. The recently image recognition technique using convolutional neural networks has shown great success in the various field of research and industry. The open-source frameworks and pre-trained image recognition models supporting image recognition task enable us to easily retrain the models to apply them on any domain. This paper describes how to apply such techniques on interior design process and depicts some demonstration results in that approaches. Furniture that is one of the most common interior design elements has sub-feature including implicit design features, such as style, shape, function as well as explicit properties, such as component, materials, and size. This paper shows to retrain the model to extract some of the features for efficiently managing and utilizing such design information. The target element is chair and the target design features are limited to functional features, materials, seating capacity and design style. Total 3933 chair images dataset and 6 retrained image recognition models were utilized for retraining. Through the combination of those multiple models, inference demonstration also has been described.
keywords	Deep learning; Image recognition; Interior design elements; Design feature; Chair
series	CAADRIA
email
last changed	2022/06/07 07:52

_id	caadria2021_262
id	caadria2021_262
authors	Olthof, Owen, Globa, Anastasia and Stracchi, Paolo
year	2021
title	SISTEMA NERVI - Sustainable Production of Optimised Floor Slabs Through Digital Fabrication
doi	https://doi.org/10.52842/conf.caadria.2021.1.723
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. 723-732
summary	'Sistema Nervi' (the Nervi System) invented by Pier Luigi Nervi greatly economised the production of complex concrete forms optimised in both material usage and structurally. However it did not translate well into other contexts due to labour and material considerations (Leslie, 2018). This paper explores novel methodologies of producing optimised floor slabs and concrete structures, using digital fabrication techniques, focusing on both labour economisation and sustainability principles. A module from the Australia Square lobby slab has been used as the set geometry and was reproduced using differing techniques of fabrication for a comparative study. The study was conducted at scale (1:20). The viability for production at full scale (1:1) for manufacturing is discussed. The assessment criteria for the tests are divided into four categories: Cost, Time, Performance, and Sustainability. 3D printing of PLA plastic and ceramic clay extrusion printing has been used to produce removable or degradable formworks. These technologies have been selected due to their current market availability and associated costs. This study hopes to introduce improved methodologies for producing optimized concrete forms, as well as the sustainability potentials of a degradable formwork such as ceramic clay. Both systems were ultimately able to produce workable formworks for optimised shapes and showed promise for reducing labour involved as well as presenting with material sustainability for discussion.
keywords	Concrete formwork; Sustainability; Degradable formwork; Optimised concrete; Advanced fabrication
series	CAADRIA
email
last changed	2022/06/07 08:00

_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
doi	https://doi.org/10.52842/conf.caadria.2018.2.247
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
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	caadria2018_237
id	caadria2018_237
authors	Yi, Taeha, Lee, Injung, Lee, Chae-Seok, Lee, Gi Bbeum, Kim, Meereh and Lee, Ji-Hyun
year	2018
title	Interactive Data Acquisition for CBR System Based Smart Home Assistant - Utilizing Function-Behavior-Structure Framework
doi	https://doi.org/10.52842/conf.caadria.2018.2.525
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. 525-534
summary	This research aims to develop a Case-Based Reasoning (CBR) system that recommends services to users in IoT environment. To develop this system, we establish a framework that designs raw data into analyzable information using Function-Behavior-Structure properties. Also, we develop an interactive flow of data acquisition that builds up cases gradually by gathering data through conversational interactions between the system and its user. This research develop a prototype of this system based on simulated cases. Finally, the prototype of this system was evaluated by experts in the field of system design to verify how the service (solution) recommended by system is similar with them. The results of this evaluation showed an agreement of average 54%, but found that there was a big difference from the experts in the specific context. This result implies that it is necessary to improve the context awareness in the reasoning process of this system.
keywords	Case Based Reasoning; Function-Behavior-Structure framework; Service recommendation; IoT environment; Conversation
series	CAADRIA
email
last changed	2022/06/07 07:57

_id	caadria2018_126
id	caadria2018_126
authors	Khean, Nariddh, Kim, Lucas, Martinez, Jorge, Doherty, Ben, Fabbri, Alessandra, Gardner, Nicole and Haeusler, M. Hank
year	2018
title	The Introspection of Deep Neural Networks - Towards Illuminating the Black Box - Training Architects Machine Learning via Grasshopper Definitions
doi	https://doi.org/10.52842/conf.caadria.2018.2.237
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. 237-246
summary	Machine learning is yet to make a significant impact in the field of architecture and design. However, with the combination of artificial neural networks, a biologically inspired machine learning paradigm, and deep learning, a hierarchical subsystem of machine learning, the predictive capabilities of machine learning processes could prove a valuable tool for designers. Yet, the inherent knowledge gap between the fields of architecture and computer science has meant the complexity of machine learning, and thus its potential value and applications in the design of the built environment remain little understood. To bridge this knowledge gap, this paper describes the development of a learning tool directed at architects and designers to better understand the inner workings of machine learning. Within the parametric modelling environment of Grasshopper, this research develops a framework to express the mathematic and programmatic operations of neural networks in a visual scripting language. This offers a way to segment and parametrise each neural network operation into a basic expression. Unpacking the complexities of machine learning in an intermediary software environment such as Grasshopper intends to foster the broader adoption of artificial intelligence in architecture.
keywords	machine learning; neural network; action research; supervised learning; education
series	CAADRIA
email
last changed	2022/06/07 07:52

_id	caadria2018_297
id	caadria2018_297
authors	Kim, Eonyong
year	2018
title	Field Survey System for Facility Management Using BIM Model - IoT Management for Facility Management
doi	https://doi.org/10.52842/conf.caadria.2018.2.535
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. 535-544
summary	Combining IoT technology with the BIM paradigm can enhance the data collection that BIM strives for by enabling real-time monitoring of building conditions. This data collection can be used very effectively for managing facilities. However, many IoT devices must be installed in buildings to achieve such results and therefore, a management system is required. The purpose of this study is to suggest an IoT management system that uses the drawing information extracted from a BIM model to allow effective management from initial installation of IoT devices to maintenance. In the pursuit of this purpose, a converter and an IoT device which developed in the research is used. The converter extracts space information and 2D floor drawing from BIM model and the IoT device is developed based on ESP 8266 chip which consist of one computer and WIFI module. To store the data which collected by the IoT devices, IoT service of AWS(Amazon Web Service) is used.
keywords	Facility Management; IoT; Management System; BIM
series	CAADRIA
email
last changed	2022/06/07 07:52

_id	ecaade2018_258
id	ecaade2018_258
authors	Kim, Jingoog, Maher, Mary Lou, Gero, John and Sauda, Eric
year	2018
title	Metaphor - A tool for designing the next generation of human-building interaction
doi	https://doi.org/10.52842/conf.ecaade.2018.2.149
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. 149-158
summary	Well known metaphors play an explanatory role in human-computer interaction (HCI) and support users in understanding an unfamiliar object with references to a familiar object, for example the desktop metaphor. Metaphors can also support designers in forming and exploring new concepts during the process of designing. We present metaphors that establish user expectations and provide guidance for new design concepts while integrating interactive technology in buildings to enable human-building interaction (HBI). HBI is a research area that studies how HCI research and practice provides opportunities for interactive buildings. Interactive experiences in architecture can be characterized by three metaphorical concepts: HBI as Device (user-centered view), HBI as Robot (building-centered view), and HBI as Friend (activity centered-view). These metaphors provide a tool for architects and HBI designers to explore designs that engage occupants' existing mental models from previous HCI experiences. We expand on each metaphor using analogical reasoning to define exploratory design spaces for HBI.
keywords	Human-Building Interaction; Metaphor; Human-Computer Interaction; Interactive Architecture
series	eCAADe
email
last changed	2022/06/07 07:52

_id	ecaade2018_251
id	ecaade2018_251
authors	Park, Hyejin, Panya, David Stephen, Goo, Hyungmo, Kim, Teahoon and Seo, Jihyo
year	2018
title	BIM-based Virtual Reality and Human Behavior Simulation For Safety Design
doi	https://doi.org/10.52842/conf.ecaade.2018.2.823
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. 823-832
summary	The constant development of Building Information Modelling and Virtual reality in architecture and construction has gone beyond visualization and marketing in architecture to enhancing workflows of architects with assets such as immersion and interaction that assists Architects to make more informed decisions from design to construction. Using virtual reality complex decisions can be simulated and analyzed to produce iterations for the optimizing design. Recently, safety design to protect users from the risk of life has become an issue. BIM and VR for Safety Design is a beneficial collaboration for the designer to experience user safety in a virtual built environment immersively. There is a need for intensive experimentation and simulation into user-centered design safety due to the complexity of this part of the design process. The most unpredictable elements of user design safety is human behavior. this paper explores Human behavior using intelligent virtual agents in emergency situations, as this is when user safety is at highest risk in a built environment. In this paper, we explore the potential of a BIM based VR and human behavior simulation in relation to emergency situations.
keywords	BIM; Virtual Reality; Safety simulation; Safety design; human behavior
series	eCAADe
email
last changed	2022/06/07 08:00

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