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	caadria2022_458
id	caadria2022_458
authors	Gong, Pixin, Huang, Xiaoran, Huang, Chenyu and White, Marcus
year	2022
title	Machine Learning-Based Walkability Modeling in Urban Life Circle
doi	https://doi.org/10.52842/conf.caadria.2022.1.645
source	Jeroen van Ameijde, Nicole Gardner, Kyung Hoon Hyun, Dan Luo, Urvi Sheth (eds.), POST-CARBON - Proceedings of the 27th CAADRIA Conference, Sydney, 9-15 April 2022, pp. 645-654
summary	With China's fast urbanization, the study of the walkability of residents' life circles has become critical to improve people's quality of life. Traditional walkability calculations are based on Lawrence Frank's theory. However, the weighted calculation method cannot be adapted to ever-changing and complicated scenarios as the scope and topic of research transforming. This study investigated walkability at the community level by combining machine learning techniques with multi-source data. Feature indicators affecting walkability were estimated from multi-source data. Machine learning was used to refine the weighting calculation under the previous indicator framework. We compared the performance of 20 regression models from 6 different machine learning algorithms for estimating the walkability of 14578 communities in downtown Shanghai. It is concluded that the Bagged Tree Model (R2=0.86, RMSE=0.36862) achieves the best performance, which is used to revise the initial walkability index values. The workflow proposed in this paper allows for rapid application of expert empirical consensus to comprehensive urban design and detailed urban governance in the future.
keywords	Life Circle, Walkability Indicator, Multi-source Data, Machine Learning, Refined Urban Design, SDG 3, SDG 10, SDG 11
series	CAADRIA
email
last changed	2022/07/22 07:34

_id	sigradi2022_85
id	sigradi2022_85
authors	Mariano, Pedro Oscar Pizzetti; Sansao, Marcos Marciel; Vaz, Carlos Eduardo Verzola
year	2022
title	Parametric modeling applied to landscape design: simulation as a tool for defining tree stratum
source	Herrera, PC, Dreifuss-Serrano, C, Gómez, P, Arris-Calderon, LF, Critical Appropriations - Proceedings of the XXVI Conference of the Iberoamerican Society of Digital Graphics (SIGraDi 2022), Universidad Peruana de Ciencias Aplicadas, Lima, 7-11 November 2022 , pp. 225–236
summary	This experiment demonstrated how the use of a process aided with computational tools, similar to the multi-criteria performative model, contributes to the learning of architecture and urbanism students in the development of designing urban and landscape projects. The study seeks to bring students closer to multi-criteria analysis in project training activities. The method used is guided by a case study that allows simulated data referring to radiation, visual permeability, and percentage of visible sky. The results were collected through the analyzes and comparisons found in the final project of the discipline, verified through the observation of the design decisions based on the simulations. This allowed us to identify the potentialities of the process in the understanding of the students in using different criteria in the initial launch of the architectural project and also to recognize the points and negatives of the use of the process.
keywords	Parametric Analysis, Simulation, Multicriteria Analysis, Landscape Design
series	SIGraDi
email
last changed	2023/05/16 16:55

_id	caadria2022_471
id	caadria2022_471
authors	Kim, Taehoon, Hong, Soonmin, Panya, David Stephen, Gu, Hyeongmo, Park, Hyejin, Won, Junghye and Choo, Seungyeon
year	2022
title	Development of Technology for Automatic Extraction of Architectural Plan Wall Lines for Concrete Waste Prediction Using Point Cloud
doi	https://doi.org/10.52842/conf.caadria.2022.2.597
source	Jeroen van Ameijde, Nicole Gardner, Kyung Hoon Hyun, Dan Luo, Urvi Sheth (eds.), POST-CARBON - Proceedings of the 27th CAADRIA Conference, Sydney, 9-15 April 2022, pp. 597-606
summary	Recently, as more and more projects on residential environment improvement in cities are actively carried out, the cases of demolishing or remodelling buildings has been increasing. Most of the target buildings for such projects are made of concrete. In order to reduce energy use as well as carbon emissions, the amount of concrete used as a building material should be reduced. This is because the concrete is the largest amount of construction waste, which the exact amount of concrete needs to be predicted. The architectural drawings are essential for the estimation and demolition of building waste, but the problem is that most of the old buildings' drawings do not exist. The 3D scanning process was performed to create the plans for such old buildings instead of the conventional method that is long time-consuming and labour-intensive actual measurement. In this study, we scanned 40 old houses that were scheduled to be demolished. The result showed that the 3D scanned drawings' accuracy - 99.2% - was higher than the ones measured by the conventional way. Through the algorithm developed in this study, the various processes of demolition, drawing measurement, and discarding quantity prediction can be solved in one process, thereby reducing work efficiently. And, considering the reliability of the research results, it is possible to reduce the economic loss by predicting the exact amount of waste in advance. After that, if the algorithm, developed in this study, can be further subdivided and supplemented to identify the materials for each part of the old buildings, it will be able to propose an efficient series of processes that distinguish between recyclable materials and wastes and thereby efficiently dispose of them. 0864108000
keywords	Point Cloud, Construction Waste, Parametric Design, Algorithm, Automatic Extraction, SDG 8
series	CAADRIA
email
last changed	2022/07/22 07:34

_id	ecaade2022_290
id	ecaade2022_290
authors	Yalçinkaya, Sezgi and Çolakoglu, Meryem Birgül
year	2022
title	A Visibility Algorithm Based on Voxel Modelling Method Developed for Architectural Geometries
doi	https://doi.org/10.52842/conf.ecaade.2022.2.057
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 2, Ghent, 13-16 September 2022, pp. 57–66
summary	A visibility algorithm has been developed and practiced on the iconic towers of Istanbul from various locations with multiple observation points. This research accepts visibility as a binary subject and limited subjective perspectives. Using visibility as a design strategy is a prevalent technique for designers. Applying visibility aspects to the design is an outcome of psychological research in the 60s. Benedikt was the first person who added visibility to his architectural studies. Visibility refers to being able to see or be seen from a distance. This research accepts and practices this definition on two iconic towers of the city of Istanbul with the model MoV (Model of Visibility) developed. The implantation of the developed model is represented with the voxel modeling method. To be able to provide volumetric data, voxel-based representation was explicitly applied to the digital models of iconic towers. This representation model aimed to illustrate and quantify the visible and non-visible areas according to the location of the observation point’s visibility range.
keywords	Visibility, Isovist, Algorithym, Iconic Structures, Visibility Values, Developed Algorithm
series	eCAADe
email
last changed	2024/04/22 07:10

_id	ijac202220310
id	ijac202220310
authors	Castro Henriques, Goncalo; Pedro Maciel Xavier; Victor de Luca Silva; Luca Rédua Bispo; Joao Victor Fraga
year	2022
title	Computation for Architecture, hybrid visual and textual language: Research developments and considerations about the implementation of structural imperative and object-oriented paradigms
source	International Journal of Architectural Computing 2022, Vol. 20 - no. 3, pp. 673–687
summary	In the fourth industrial revolution, programming promises to be a fundamental subject like mathematics, science, languages or the arts. Architects design more than buildings developing innovative methods and they are among the pioneers in visual programming development. However, after more than 10 years of visual programming in architecture, despite the fast-learning curve, visual programming presents considerable limitations to solve complex problems. To overcome limitations, the authors propose to associate the advantages of visual and textual languages in Python. The article addresses an ongoing research study to implement Computational Methods in Architectural Education. The authors began by describing the general goal of this project, and of this article in particular. This article focuses on the implementation of two disciplines ‘Computation for Architecture in Python’ I and II. The first discipline uses programming based on the construction of functions in the imperative language, implemented in the text editor, in visual programming, using Grasshopper methods. The second discipline, which is under development, intends to teach object-oriented programming. The results of the first discipline are encouraging; despite reported difficulties in programming fundamentals, such as lists, loops and recursion. The development of the second discipline, in object-oriented programming, deals with the concepts of classes and objects, and more abstract principles such abstraction, inheritance, polymorphism or encapsulation. This paradigm allows building robust programs, but requires a more in-depth syntax. The article reports this ongoing research on this new paradigm of object-oriented language, expanding the application of a hybrid visual-textual language in Architecture
keywords	computation, textual programming, visual programming, imperative programming, object oriented programming
series	journal
last changed	2024/04/17 14:30

_id	ecaade2022_125
id	ecaade2022_125
authors	Chen, Emily, Lu, Glenn, Barnik, Lyric and Correa, David
year	2022
title	Fast and Reversible Bistable Hygroscopic Actuators for Architectural Applications Based on Plant Movement Strategies
doi	https://doi.org/10.52842/conf.ecaade.2022.1.261
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. 261–270
summary	Plant movement is of great inspiration for the development of actuators in architectural applications. Since plants lack muscles, they have developed unique hygroscopic mechanisms that use specialized tissue to generate movement in response to stimuli such as touch, light, temperature, or gravity. Most research in architecture has been focused on the stress-induced bending that can be achieved with a bilayer structure – particularly using wood composites and bi-metals. The speed of these mechanisms is mostly limited by the rules of bilayers, as described by Timoshenko, and the speed of moisture/heat diffusion. This paper presents methods to use bistable mechanisms, and their elastic instability, to enable rapid movements of “snap-through” buckling that can greatly improve the speed of transformation. The research covers biomimetic studies on the Mimosa pudica, Oxalis triangularis, and the Maranta leuconeura to develop hygroscopic mechanisms whose kinematic actuation can be amplified through the integration of a bi- stable system. The presented mechanisms make it possible to significantly increase the speed of response of the hygroscopically driven mechanism while maintaining the ability to operate over several reversible cycles. Calibration of the mechanism to specific relative humidity conditions is presented together with some initial prototypes with the potential for manual override strategies. It is the aim of this combined approach that the actuation mechanisms are better able to match users’ expectations of fast shape-change actuation in relation to environmental changes.
keywords	Stimulus-Responsive, Biomimetics, Hygroscopic, Elastic Instability, Actuators
series	eCAADe
email
last changed	2024/04/22 07:10

_id	caadria2022_405
id	caadria2022_405
authors	Onishi, Ryo, Fukuda, Tomohiro and Yabuki, Nobuyoshi
year	2022
title	A Remote Sharing Method of 3D Physical Objects Using Instance-Segmented Real-Time 3D Point Cloud for Design Meeting
doi	https://doi.org/10.52842/conf.caadria.2022.2.395
source	Jeroen van Ameijde, Nicole Gardner, Kyung Hoon Hyun, Dan Luo, Urvi Sheth (eds.), POST-CARBON - Proceedings of the 27th CAADRIA Conference, Sydney, 9-15 April 2022, pp. 395-404
summary	In the field of architecture and urban design, physical models are used in design meetings. Furthermore, teleconferencing via the internet has begun to be widely used in society due to COVID-19 and in preparation for disasters. Although conventional web conferencing can share only 2D information through screens, it is expected that interactive screen sharing of physical objects will enable smoother remote conferencing. A system that can manipulate point clouds in clusters by dividing real-time point clouds captured from 3D real objects by distance has been reported as a way to share physical objects. However, because the point clouds are divided by distance between the two clusters when the point clouds get closer than some threshold, they become treated as a single object. In this study, we aim to develop a system that uses instance segmentation to divide point clouds by region rather than by distance between objects. This system is expected to contribute to the realisation of better architectural and urban design processes without any misunderstandings among the parties involved and to the reduction of unnecessary energy consumption due to travel for face-to-face meetings.
keywords	remote meeting, fast point cloud, instance segmentation, three-dimensional remote sharing, mixed reality, SDG 11, SDG 13
series	CAADRIA
email
last changed	2022/07/22 07:34

_id	sigradi2022_146
id	sigradi2022_146
authors	Pazeti, Gabriel; Tanoue Vizioli, Simone Helena; Ippolito, Alfonso
year	2022
title	Mapping of cultural heritage: the Palacete Bento Carlos, Sao Carlos - SP.
source	Herrera, PC, Dreifuss-Serrano, C, Gómez, P, Arris-Calderon, LF, Critical Appropriations - Proceedings of the XXVI Conference of the Iberoamerican Society of Digital Graphics (SIGraDi 2022), Universidad Peruana de Ciencias Aplicadas, Lima, 7-11 November 2022 , pp. 895–907
summary	Documenting a historical heritage is always a complex process, especially in terms of data acquisition. However, the new technologies, in particular the scanning techniques with laser scanner and photogrammetry, allow a fast data acquisition. This research aims to carry out a scientifically based documentation of the Palacete Bento Carlos (1890), an example of the eclectic architecture of the interior of Sao Paulo, by applying a heritage documentation protocol as a way of standardizing the process and 3D mapping results, allowing access to information by different audiences.
keywords	Digital Heritage, Laser Scanner, Protocol, Photogrammetry, Cloud Point
series	SIGraDi
email
last changed	2023/05/16 16:57

_id	caadria2022_277
id	caadria2022_277
authors	Akbar, Zuardin, Wood, Dylan, Kiesewetter, Laura, Menges, Achim and Wortmann, Thomas
year	2022
title	A Data-Driven Workflow for Modelling Self-Shaping Wood Bilayer, Utilizing Natural Material Variations with Machine Vision and Machine Learning
doi	https://doi.org/10.52842/conf.caadria.2022.1.393
source	Jeroen van Ameijde, Nicole Gardner, Kyung Hoon Hyun, Dan Luo, Urvi Sheth (eds.), POST-CARBON - Proceedings of the 27th CAADRIA Conference, Sydney, 9-15 April 2022, pp. 393-402
summary	This paper develops a workflow to train machine learning (ML) models with a small dataset from physical samples to predict the curvatures of self-shaping wood bilayers based on local variations in the grain. In contrast to state-of-the-art predictive models, specifically 1.) a 2D Timoshenko model and 2.) a 3D numerical model with a rheological model, our method accounts for natural and unavoidable material variations. In this paper, we only focus on local grain variations as the main driver for curvatures in small-scale material samples. We extracted a feature matrix from grain images of active and passive layers as a Grey Level Co-Occurrence Matrix and used it as the input for our ML models. We also analysed the impact of grain variations on the feature matrix. We trained and tested several tree-based regression models with different features. The models achieved very accurate predictions for curvatures in each sample (R;0.9) and extend the range of parameters that is incalculable by a Timoshenko model. This research contributes to the material-efficient design of weather-responsive shape-changing wood structures by further leveraging the use of natural material features and explainable data-driven modelling and extends the topic in ML for material behaviour-driven design among the CAADRIA community.
keywords	data-driven model, machine learning, material programming, smart material, timber structure, SDG 12
series	CAADRIA
email
last changed	2022/07/22 07:34

_id	caadria2022_361
id	caadria2022_361
authors	Lok, Leslie and Bae, Jiyoon
year	2022
title	Timber De-Standardized 2.0 : Mixed Reality Visualizations and User Interface for Processing Irregular Timber
doi	https://doi.org/10.52842/conf.caadria.2022.2.121
source	Jeroen van Ameijde, Nicole Gardner, Kyung Hoon Hyun, Dan Luo, Urvi Sheth (eds.), POST-CARBON - Proceedings of the 27th CAADRIA Conference, Sydney, 9-15 April 2022, pp. 121-130
summary	Timber De-Standardized 2.0†is a mixed reality (MR) user interface (UI) that utilizes timber waste produced by manufacturing dimensional lumber, suggesting an expanded notion for "material usability‚ in timber construction. The expanded notion of designing with discarded logs not only requires new tools and technologies for cataloguing, structuring, and fabricating. It also relies on new methods and platforms for the visualization and design of these structures. As a†MR†UI,†Timber De-Standardized†enables professionals and non-professionals alike to seamlessly design with irregular logs and to create viable structural systems using an intuitive†MR†environment. In order to develop a†MR†environment with this level of competency, the research aims to finesse the visualization techniques in the immersive full-scale†3D†environment and to minimize the use of alternative 2D UI(s). The research methodology†focuses on†(1) cataloguing and extracting basic properties of various tree logs, (2)†refining mesh visualization for better user interaction, and†(3)†developing†the†MR†UI to increase user design agency with custom menu lists and operations.†This methodology will extend the usability of†MR†UI protocols to a broader audience while democratizing design and enabling the user as co-creator.
keywords	Irregular Tree Logs, Wood Construction, Augmented and Mixed Realities, Mixed Reality User Interface, Co-Creative Design, Digital representation and visualization, SDG 9, SDG 12, SDG 13
series	CAADRIA
email
last changed	2022/07/22 07:34

_id	caadria2022_153
id	caadria2022_153
authors	Cheng, Cesar, Li, Yuke, Deshpande, Rutvik, Antonio, Rishan, Chavan, Tejas, Nisztuk, Maciej, Subramanian, Ramanathan, Weijenberg, Camiel and Patel, Sayjel Vijay
year	2022
title	Realtime Urban Insights for Bottom-up 15-minute City Design
doi	https://doi.org/10.52842/conf.caadria.2022.1.435
source	Jeroen van Ameijde, Nicole Gardner, Kyung Hoon Hyun, Dan Luo, Urvi Sheth (eds.), POST-CARBON - Proceedings of the 27th CAADRIA Conference, Sydney, 9-15 April 2022, pp. 435-444
summary	This paper introduces a real-time neighbour scoring system, using data collected from various web-based APIs, to facilitate "15-minute city‚ designs. The system extends on the current state of the art in three ways; first, it incorporates a multi-source urban API, to automate the extraction of location-based information from online sources; second, it provides a quantitative method to calculate and index "15-minute city‚ performance; and third, it provides a web-based application, to allow real-time feedback of neighbourhood design performance complementing the design refinements at a building and tenancy level. In addition to discussing its theoretical basis, and technical implementation, this paper provides a case study to demonstrate how the neighbourhood scoring system is incorporated into the design of a hypothetical mixed-use urban development.
keywords	Industry Innovation and Infrastructure, Sustainable Cities and Communities, Urban Walkability, Urban Accessibility, 15-minute City, Spatial Analysis, SDG 9, SDG 11
series	CAADRIA
email
last changed	2022/07/22 07:34

_id	caadria2022_231
id	caadria2022_231
authors	Kim, Frederick Chando and Huang, Jeffrey
year	2022
title	Deep Architectural Archiving (DAA), Towards a Machine Understanding of Architectural Form
doi	https://doi.org/10.52842/conf.caadria.2022.1.727
source	Jeroen van Ameijde, Nicole Gardner, Kyung Hoon Hyun, Dan Luo, Urvi Sheth (eds.), POST-CARBON - Proceedings of the 27th CAADRIA Conference, Sydney, 9-15 April 2022, pp. 727-736
summary	With the ‚digital turn‚, machines now have the intrinsic capacity to learn from big data in order to understand the intricacies of architectural form. This paper explores the research question: how can architectural form become machine computable? The research objective is to develop "Deep Architectural Archiving‚ (DAA), a new method devised to address this question. DAA consists of the combination of four distinct steps: (1) Data mining, (2) 3D Point cloud extraction, (3) Deep form learning, as well as (4) Form mapping and clustering. The paper discusses the DAA method using an extensive dataset of architecture competitions in Switzerland (with over 360+ architectural projects) as a case study resource. Machines learn the particularities of forms using 'architectural' point clouds as an opportune machine-learnable format. The result of this procedure is a multidimensional, spatialized, and machine-enabled clustering of forms that allows for the visualization of comparative relationships among form-correlated datasets that exceeds what the human eye can generally perceive. Such work is necessary to create a dedicated digital archive for enhancing the formal knowledge of architecture and enabling a better understanding of innovation, both of which provide architects a basis for developing effective architectural form in a post-carbon world.
keywords	artificial intelligence, deep learning, architectural form, architectural competitions, architectural archive, 3D dataset, SDG 11
series	CAADRIA
email
last changed	2022/07/22 07:34

_id	cdrf2022_408
id	cdrf2022_408
authors	Marcus Farr
year	2022
title	Bio-digital Sand Logics: Dune Sand Material and Computational Design
doi	https://doi.org/https://doi.org/10.1007/978-981-19-8637-6_35
source	Proceedings of the 2022 DigitalFUTURES The 4st International Conference on Computational Design and Robotic Fabrication (CDRF 2022)
summary	This paper discusses the creation of a new sand-based material, performative testing, and the computational logic involved in the design of a prototypical architectural system. Dune sand is known to be an unstable material compared to river or marine sand and as a result it is not normally used for construction. Because of this, desert regions have grown a reliance upon imported materials creating massive sustainability issues due to large scale global shipping, importation and resource extraction. This research indicates there is a viable opportunity to leverage dune sand as an ongoing line of inquiry for material science and design in local desert regions. It establishes that there is very little architectural research being done in this particular area. The methodology begins with experiments in bio-material using dune sand as a compound, and then establishes a construction system based upon a manifold of experiments. Along with material investigations, the process uses a Scientific Testing Method (STM) and Hypothesis in Action (HIA) as part of the testing methodology.
series	cdrf
email
last changed	2024/05/29 14:03

_id	ecaade2022_264
id	ecaade2022_264
authors	Sanatani, Rohit Priyadarshi
year	2022
title	Democratizing Urban Data - A smartphone-based framework for rapid cataloging of geolocated street-level imagery and visual content analysis
doi	https://doi.org/10.52842/conf.ecaade.2022.1.511
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. 511–516
summary	The commercial availability of high-resolution street view imagery, most notably Google Street View, has led to its widespread use in urban analytics research over the past couple of years. Recent developments in computer vision, most notably semantic segmentation and object detection, have made it possible to extract and map the visual features of streetscapes (such as buildings, automobiles, green cover, pedestrians etc.) using geo-located street level photographs. However, the absence of such detailed imagery in many parts of the world stands as a significant deterrent to these research methodologies. A majority of countries in Africa, the Middle East, as well as some parts of Asia currently have limited coverage by street view image providers. The cost component and equipment involved in manual data collection stands as a barrier to accessible urban visual data. This paper demonstrates a quick and inexpensive smartphone-based framework for rapid and inexpensive collection and cataloging of geolocated street-level imagery. The user walks/drives down the streets to be mapped with a smartphone, as a first-person egocentric hyper-lapse video is recorded with a fixed frame interval, along with location information for the path taken. The video frames are then automatically extracted, geo-referenced and stored in a readily retrievable format. This data can then easily be used for urban feature extraction through computer vision workflows. For demonstration, imagery has been cataloged for a ~1.5 sq.km urban area in New Delhi, and then processed through a semantic segmentation workflow for visual feature mapping. It is hoped that this framework plays a role in democratizing access to street level data for students and researchers regardless of national boundaries.
keywords	Street View Imagery, Democratizing Data, Hyperlapse Photography, Smartphone, Urban Analytics
series	eCAADe
email
last changed	2024/04/22 07:10

_id	ecaade2022_158
id	ecaade2022_158
authors	Zhao, Xingjian, Wang, Tsung-Hsien and Peng, Chengzhi
year	2022
title	Automatic Room Type Classification using Machine Learning for Two-Dimensional Residential Building Plans
doi	https://doi.org/10.52842/conf.ecaade.2022.2.593
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 2, Ghent, 13-16 September 2022, pp. 593–600
summary	Building plan semantic retrieval is of interest in every stage of construction and facility management processes. A conceptual design model with a space layout can be used for the early building evaluation, such as functional spatial validation, circulation and security checking, cost estimation, and preliminary energy consumption simulation. With the development of information technology, existing machine learning methods applied to semantic segmentation of building plan images have successfully identified building elements such as doors, windows, and walls. However, for the higher level of room type/function recognition, the prediction accuracy is low when building plans do not contain sufficient details such as furniture. In this paper, we present a workflow and a predictive model for residential room type classification. Given a building plan image, the building elements are first identified, followed by room feature extraction by connectivity and morphological characterization using a rule-based algorithm. The Multi-Layer Perceptron (MLP) is trained with the feature set and then predicts the room type of test samples. We collected 1,586 residential room samples from 165 building layout plans and categorized rooms into nine types. Finally, our current model can achieve a classification accuracy of 0.82.
keywords	Floor Plan Semantic Retrieval, Room Type Classification, Machine Learning
series	eCAADe
email
last changed	2024/04/22 07:10

_id	architectural_intelligence2022_8
id	architectural_intelligence2022_8
authors	Manning He, Huiwang Pen, Meixiang Li, Yu Huang, Da Yan, Siwei Lou & Liwei Wen
year	2022
title	Investigation on typical occupant behavior in air-conditioned office buildings for South China’s Pearl River Delta
doi	https://doi.org/https://doi.org/10.1007/s44223-022-00005-w
source	Architectural Intelligence Journal
summary	The excessive simplification of occupant behavior is considered as the most important factor that affects the uncertainty of building performance simulation, thus affects the reliability and generalizability of simulation-based design and forecast. In this paper, occupant behavior in air-conditioned office buildings of the Pearl River Delta (PRD) region was investigated and defined. Copies of 873 questionnaires about the occupant behavior in air-conditioned office buildings in the PRD region were collected to study the relationship between indoor environment quality and adaptive behaviors. Eight typical office occupant schedules were defined via K-means clustering method. A probability prediction model of cooling temperature set-point was established by using the Ordinal Logistic Regression method. According to the different control modes of air conditioning, window, blind and lighting equipment, four types of typical behavior patterns were proposed using the K-prototype clustering method, which could be developed into 20 typical occupant behavior styles of office buildings in the PRD region.
series	Architectural Intelligence
email
last changed	2025/01/09 15:00

_id	caadria2022_74
id	caadria2022_74
authors	Mazza, Domenico, Kocaturk, Tuba and Kaljevic, Sofija
year	2022
title	Geelong Digital Outdoor Museum (GDOM) - Photogrammetry as the Surface for a Portable Museum
doi	https://doi.org/10.52842/conf.caadria.2022.1.677
source	Jeroen van Ameijde, Nicole Gardner, Kyung Hoon Hyun, Dan Luo, Urvi Sheth (eds.), POST-CARBON - Proceedings of the 27th CAADRIA Conference, Sydney, 9-15 April 2022, pp. 677-686
summary	This paper presents the development and evaluation of the Geelong Digital Outdoor Museum (GDOM) prototype accessible at https://gdom.mindlab.cloud. GDOM is a portable museum‚our novel adaptation of the distributed museum model (Stuedahl & Lowe, 2013) which uses mobile devices to present museum collections attached to physical sites. Our prototype defines a way for intangible heritage associated with tangible landscapes to be accessible via personal digital devices using 360 3D scanned digital replicas of physical landscapes (photogrammetric digital models). Our work aligns with efforts set out in the UN Sustainable Development Goal 11 (SDG 11) to safeguard cultural and natural heritage, by openly disseminating the heritage of physical sites seamlessly through the landscape. Using a research by design methodology we delivered our prototype as a modular web-based platform that leveraged the Matterport digital model platform. We qualitatively evaluated the prototype's usability and future development opportunities with 32 front-end users and 13 potential stakeholders. We received a wide gamut of responses that included: users feeling empowered by the greater accessibility, users finding a welcome common ground with comparable physical experiences, and users and potential stakeholders seeing the potential to re-create physical world experiences with modifications to the digital model along with on-site activation. Our potential stakeholders suggested ways in which GDOM could be integrated into the arts, education, and tourism to widen its utility and applicability. In future we see design potential in breaking out of the static presentation of the digital model and expanding our portable museum experience to work on-site as a complement to the remote experience. However, we recognise the way in which on-site activation integrate into users' typical activities can be tangential (McGookin et al., 2019) and this would necessitate further investigation into how to best integrate the experience on-site.
keywords	Cultural Heritage, Intangible Heritage, Digital Heritage, Web Platform, 3D Scanning, Photogrammetry, Digital model, Portable Museum, Distributed Museum, SDG 11
series	CAADRIA
email
last changed	2022/07/22 07:34

_id	caadria2022_204
id	caadria2022_204
authors	Narahara, Taro
year	2022
title	Kurashiki Viewer: Qualitative Evaluations of Architectural Spaces inside Virtual Reality
doi	https://doi.org/10.52842/conf.caadria.2022.1.011
source	Jeroen van Ameijde, Nicole Gardner, Kyung Hoon Hyun, Dan Luo, Urvi Sheth (eds.), POST-CARBON - Proceedings of the 27th CAADRIA Conference, Sydney, 9-15 April 2022, pp. 11-18
summary	This paper discusses how virtual reality (VR) environments can be employed as a data collection tool beyond visualization and representation tools through a simple experiment in a VR space and speculates about its potential applications. Using a VR model that runs on a web browser based on an existing historic town in Japan called Kurashiki, the experiment asked 30 recruited participants to freely walk around and leave ratings on a 5-point scale on any buildings or objects appealing to them. The proposed system in this paper can display points of interest of multiple participants using heatmaps superimposed on a map that can help users visually understand statistical preferences among them. The project's goal is to provide a quantitative means for qualitative values of architectural and urban spaces, making such data more shareable. We intended to show that such a platform could help multiple stakeholders reach better consensuses and possibly collect training datasets for machine learning models that could extract features related to the attractiveness in architecture and urban spaces.
keywords	Virtual reality, subjective evaluation, crowdsourcing, SDG 10, SDG 11.
series	CAADRIA
email
last changed	2022/07/22 07:34

_id	ascaad2022_099
id	ascaad2022_099
authors	Sencan, Inanc
year	2022
title	Progeny: A Grasshopper Plug-in that Augments Cellular Automata Algorithms for 3D Form Explorations
source	Hybrid Spaces of the Metaverse - Architecture in the Age of the Metaverse: Opportunities and Potentials [10th ASCAAD Conference Proceedings] Debbieh (Lebanon) [Virtual Conference] 12-13 October 2022, pp. 377-391
summary	Cellular automata (CA) is a well-known computation method introduced by John von Neumann and Stanislaw Ulam in the 1940s. Since then, it has been studied in various fields such as computer science, biology, physics, chemistry, and art. The Classic CA algorithm is a calculation of a grid of cells' binary states based on neighboring cells and a set of rules. With the variation of these parameters, the CA algorithm has evolved into alternative versions such as 3D CA, Multiple neighborhood CA, Multiple rules CA, and Stochastic CA (Url-1). As a rule-based generative algorithm, CA has been used as a bottom-up design approach in the architectural design process in the search for form (Frazer,1995; Dinçer et al., 2014), in simulating the displacement of individuals in space, and in revealing complex relations at the urban scale (Güzelci, 2013). There are implementations of CA tools in 3D design software for designers as additional scripts or plug-ins. However, these often have limited ability to create customized CA algorithms by the designer. This study aims to create a customizable framework for 3D CA algorithms to be used in 3D form explorations by designers. Grasshopper3D, which is a visual scripting environment in Rhinoceros 3D, is used to implement the framework. The main difference between this work and the current Grasshopper3D plug-ins for CA simulation is the customizability and the real-time control of the framework. The parameters that allow the CA algorithm to be customized are; the initial state of the 3D grid, neighborhood conditions, cell states and rules. CA algorithms are created for each customizable parameter using the framework. Those algorithms are evaluated based on the ability to generate form. A voxel-based approach is used to generate geometry from the points created by the 3D cellular automata. In future, forms generated using this framework can be used as a form generating tool for digital environments.
series	ASCAAD
email
last changed	2024/02/16 13:38

_id	cdrf2022_78
id	cdrf2022_78
authors	Sharif Anouar, Adam Anouar, and Ayoub Lharchi
title	Heritage Information Modeling: The Case of Chellah’s Gate
doi	https://doi.org/https://doi.org/10.1007/978-981-19-8637-6_7
source	Proceedings of the 2022 DigitalFUTURES The 4st International Conference on Computational Design and Robotic Fabrication (CDRF 2022)
summary	This paper aims to propose an integrated workflow for the digitization of the built cultural heritage. To this end, we leverage the power of computational tools and the relevancy of Building Information Modeling (BIM) process to overcome the limitations and challenges faced by Scan-to-BIM. We describe the automatic generation of an as-built BIM model of a heritage building in a three-step procedure. Firstly, we outline the data acquisition method of the point cloud. Secondly, we describe the automatic processing and segmentation of the point cloud according to architectural elements using Machine Learning. Then, we tested and compared various meshing algorithms and utilized a combination depending on the desired level of details. Lastly, the resulting geometry is converted into a BIM object that will be subsequently semantically labeled. We used a UNESCO world heritage in Morocco—Chellah, as a case study to test the robustness of our protocol.
email
last changed	2024/05/29 14:02

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