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	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_085
id	caadria2018_085
authors	Chung, Chia-Chun and Jeng, Tay-Sheng
year	2018
title	Information Extraction Methodology by Web Scraping for Smart Cities - Using Machine Learning to Train Air Quality Monitor for Smart Cities
doi	https://doi.org/10.52842/conf.caadria.2018.2.515
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. 515-524
summary	This paper presents an opportunistic sensing system for air quality monitoring to forecast the implicit factors of air pollution. Opportunistic sensing is performed by web scraping in the social network service to extract information. The data source for the air quality analysis combines two types of information: explicit and implicit information. The objective is to develop the information extraction methodology by web scraping for smart cities. The application development methodology has potential for solving real-world problems such as air pollution by data comparison between social activity observing and data collecting in sensor network.
keywords	smart city; open data; web scraping; social media; machine learning
series	CAADRIA
email
last changed	2022/06/07 07:56

_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	caadria2018_122
id	caadria2018_122
authors	Leung, Emily, Asher, Rob, Butler, Andrew, Doherty, Ben, Fabbri, Alessandra, Gardner, Nicole and Haeusler, M. Hank
year	2018
title	Redback BIM - Developing 'De-Localised' Open-Source Architecture-Centric Tools
doi	https://doi.org/10.52842/conf.caadria.2018.2.021
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. 21-30
summary	Emerging technologies that use data have contributed to the success of communication all over the world. Social media and gaming industries have already taken advantage of the web to provide synchronous communication and updated information. Conversely, existing methods of communication within the AEC industry require multiple platforms, such as emails and file sharing services in conjunction with 3D Modelling software, to inform changes made by stakeholders, resulting in file duplication and limited accessibility to the latest version, while augmenting existing practice's inefficiency. As communication is critical to the success of a project and should be enhanced, Redback BIM promises to establish a workflow for a dynamic platform, while achieving similar results to that of a 3D modelling program hosted on the web. Using existing open-source web development software, multiple users will be able to collaboratively organise and synchronise changes made to the design scheme in real-time. Features such as this would enable more fluid communication between multiple stakeholders within the life of a project.
keywords	De-localised Workspaces; Web-based Software Platforms; Data; Open-source; Collaboration
series	CAADRIA
email
last changed	2022/06/07 07:52

_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
doi	https://doi.org/10.52842/conf.acadia.2018.176
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
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_w11
id	ecaade2018_w11
authors	Kunze, Antje, Marz, Michael and Wyka, Edyta
year	2018
title	Smart Communities - Unleashing the Potential of Data for Smart Communities
doi	https://doi.org/10.52842/conf.ecaade.2018.1.069
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. 69-70
summary	Are you excited about data, mapping and analytics and want to learn new skills? Then you'll love our hands-on workshop on how to collect and blend open and premium data with the cities' everyday planning and management tasks, analyze urban environments, and deliver the results in stunning 2D and 3D web mapping apps.
keywords	smart city; GIS; data visualisation; data driven design
series	eCAADe
email
last changed	2022/06/07 07:52

_id	ecaade2018_415
id	ecaade2018_415
authors	Shah, Anand and Sousa, José Pedro
year	2018
title	A Robotically Fabricated Connection System as a Possible Solution for a Free-form "ROBO-WEB" Gridshell which Takes Inspirations from English Fan Vaulted Cathedrals
doi	https://doi.org/10.52842/conf.ecaade.2018.1.821
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. 821-826
summary	Gridshell is a unique category of shell structures, which, by departing from a double-curved resistant form, concentrates the forces in its lattice members. Majority of the gridshell structures use quadrangular or triangular grid patterns because they can easily mesh and it is less complicated to resolve its details. This research project provides a unique robotically fabricated joinery system for free-form gridshells. The research project attempts to increase the versatility in terms of design and feasibility in terms of construction for future gridshell structures. It tries to merge the extremely efficient historical design principles with the new age design and construction methods. The lattice grid for the Robo-Web gridshell takes inspiration from the ribs of the English fan vaulted cathedrals. Based on the experiences gained through the research project the research concludes with a critical discussion of the practical applications and future scope of the free-form lattice grid and robotically fabricated joinery system.
keywords	Gridshell; Robotics; Free-form; Fan-vaults
series	eCAADe
email
last changed	2022/06/07 07:59

_id	ecaade2018_164
id	ecaade2018_164
authors	Chang, Mei-Chih, Buš, Peter, Tartar, Ayça, Chirkin, Artem and Schmitt, Gerhard
year	2018
title	Big-Data Informed Citizen Participatory Urban Identity Design
doi	https://doi.org/10.52842/conf.ecaade.2018.2.669
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. 669-678
summary	The identity of an urban environment is important because it contributes to self-identity, a sense of community, and a sense of place. However, under present-day conditions, the identities of expanding cities are rapidly deteriorating and vanishing, especially in the case of Asian cities. Therefore, cities need to build their urban identity, which includes the past and points to the future. At the same time, cities need to add new features to improve their livability, sustainability, and resilience. In this paper, using data mining technologies for various types of geo-referenced big data and combine them with the space syntax analysis for observing and learning about the socioeconomic behavior and the quality of space. The observed and learned features are identified as the urban identity. The numeric features obtained from data mining are transformed into catalogued levels for designers to understand, which will allow them to propose proper designs that will complement or improve the local traditional features. A workshop in Taiwan, which focuses on a traditional area, demonstrates the result of the proposed methodology and how to transform a traditional area into a livable area. At the same time, we introduce a website platform, Quick Urban Analysis Kit (qua-kit), as a tool for citizens to participate in designs. After the workshop, citizens can view, comment, and vote on different design proposals to provide city authorities and stakeholders with their ideas in a more convenient and responsive way. Therefore, the citizens may deliver their opinions, knowledge, and suggestions for improvements to the investigated neighborhood from their own design perspective.
keywords	Urban identity; unsupervised machine learning; Principal Component Analysis (PCA); citizen participated design; space syntax
series	eCAADe
email
last changed	2022/06/07 07:56

_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	ecaade2018_139
id	ecaade2018_139
authors	Cudzik, Jan and Radziszewski, Kacper
year	2018
title	Artificial Intelligence Aided Architectural Design
doi	https://doi.org/10.52842/conf.ecaade.2018.1.077
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
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_336
id	acadia18_336
authors	Forren, James; Nicholas, Claire
year	2018
title	Lap, Twist, Knot. Intentionality in digital-analogue making environments
doi	https://doi.org/10.52842/conf.acadia.2018.336
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. 336-341
summary	This paper discusses a theoretical approach and method of making in computational design and construction. The project examines digital and analogue building practices through a social anthropological and STS lens to better understand the use of technology in complex making environments. We position this with respect to contemporary investigations of materials in architecture which use physical and virtual prototyping and collaborative building. Our investigation extends this work by parsing complex making through ethnographic analysis. In doing so we seek to recalibrate computational design methods which privilege rote execution of digital form. This inquiry challenges ideas of agency and intention as ‘enabled’ by new technologies or materials. Rather, we investigate the troubling (as well as extension) of explicit designer intentions by the tacit intentions of technologies. Our approach is a trans-disciplinary investigation synthesizing architectural making and ethnographic analysis. We draw on humanistic and social science theories which examine activities of human-technology exchange and architectural practices of algorithmic design and fabrication. We investigate experimental design processes through prototyping architectural components and assemblies. These activities are examined by collecting data on human-technology interactions through field notes, journals, sketches, and video recordings. Our goal is to foster (and acknowledge) more complex, socially constructed methods of design and fabrication. This work in progress, using a cement composite fabric, is a preliminary study for a larger project looking at complex making in coordination with public engagement.
keywords	work in progress, illusory dichotomies, design theory & history, materials/adaptive systems, collaboration, hybrid practices
series	ACADIA
type	paper
email
last changed	2022/06/07 07:51

_id	ecaade2018_257
id	ecaade2018_257
authors	Guo, Zhe, Yin, Hao and Yuan, Philip F.
year	2018
title	Spatial Redesign Method Based on Behavior Data Visualization System - UWB interior positioning technology based office space redesign method research
doi	https://doi.org/10.52842/conf.ecaade.2018.2.577
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. 577-584
summary	There is a typical symbiotic relationship between behavior and space. Design and evaluation of space are also inseparable from people's behavioral needs. Therefore, the study of behavior patterns can be regarded as the process of exploring the relationship between human and space. Traditional behavioral research lacks precise micro-individual data and analytical tools to express complex environments, and is more inclined to macro and qualitative static analysis. With the maturity of indoor positioning technology, the use of big data as a medium to quantitatively study the laws of behavior has gradually penetrated into the micro-level of indoor space. This paper begins with a brief introduction of the behavioral performance research process in history. The paper then describes the method that constructs the observation, quantification and visualization process of behavior data by using UWB positioning technology and visualization implementation system through an on-site experiment of office space. The last part of this paper discusses the establishment of spatial redesign method by mining the behavior data, and translating the results into spatial attributes.
keywords	behavior data visualization; UWB interior positioning technology; data mining; spatial redesign method
series	eCAADe
email
last changed	2022/06/07 07:50

_id	acadia18_156
id	acadia18_156
authors	Huang, Weixin; Zheng, Hao
year	2018
title	Architectural Drawings Recognition and Generation through Machine Learning
doi	https://doi.org/10.52842/conf.acadia.2018.156
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
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	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
doi	https://doi.org/10.52842/conf.acadia.2018.166
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
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	sigradi2018_1237
id	sigradi2018_1237
authors	Nestler, Gerald
year	2018
title	Aesthetics of Resolution. A postdisciplinary approach to countering the technocapitalist black box
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. 1187-1197
summary	Visibility and knowledge are based on access to information. We usually consider this as either a question of collecting new or examining existing data. However, the term -black box society? (Pasquale) points to a situation in which data are deliberately concealed, enabling complex processes of technocapitalist exploitation. Manufacturing information asymmetry and noise have become effective tools to gain competitive advantage across all levels of life. This text argues that adverse technopolitical schemes can be addressed with an aesthetics of resolution and with the figure of the renegade, an expert who makes the black box speak from inside.
keywords	Aesthetics; Black box automation; Big data; Finance; Information asymmetry; Resolution; Renegade
series	SIGRADI
email
last changed	2021/03/28 19:59

_id	caadria2018_115
id	caadria2018_115
authors	Przybylski, Maya
year	2018
title	A Framework to Establish Data Quality for Software Embedded Design
doi	https://doi.org/10.52842/conf.caadria.2018.2.267
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. 267-276
summary	This paper focuses on the discovery and articulation of methods for expanding the degree to which designers relate to the data used in their computationally-oriented projects from a sociocultural and ethical perspective. It supports the early development of methods directed at achieving a more complete engagement with the computational components embedded within software embedded design work.
keywords	Computational Design; Ethics; Software Embedded Design; Design Methods; Information Processing
series	CAADRIA
email
last changed	2022/06/07 08:00

_id	ecaade2023_10
id	ecaade2023_10
authors	Sepúlveda, Abel, Eslamirad, Nasim and De Luca, Francesco
year	2023
title	Machine Learning Approach versus Prediction Formulas to Design Healthy Dwellings in a Cold Climate
doi	https://doi.org/10.52842/conf.ecaade.2023.2.359
source	Dokonal, W, Hirschberg, U and Wurzer, G (eds.), Digital Design Reconsidered - Proceedings of the 41st Conference on Education and Research in Computer Aided Architectural Design in Europe (eCAADe 2023) - Volume 2, Graz, 20-22 September 2023, pp. 359–368
summary	This paper presents a study about the prediction accuracy of daylight provision and overheating levels in dwellings when considering different methods (machine learning vs prediction formulas), training, and validation data sets. An existing high-rise building located in Tallinn, Estonia was considered to compare the best ML predictive method with novel prediction formulas. The quantification of daylight provision was conducted according to the European daylight standard EN 17037:2018 (based on minimum Daylight Factor (minDF)) and overheating level in terms of the degree-hour (DH) metric included in local regulations. The features included in the dataset are the minDF and DH values related to different combinations of design parameters: window-to-floor ratio, level of obstruction, g-value, and visible transmittance of the glazing system. Different training and validation data sets were obtained from a main data set of 5120 minDF values and 40960 DH values obtained through simulation with Radiance and EnergyPlus, respectively. For each combination of training and validation dataset, the accuracy of the ML model was quantified and compared with the accuracy of the prediction formulas. According to our results, the ML model could provide more accurate minDF/DH predictions than by using the prediction formulas for the same design parameters. However, the amount of room combinations needed to train the machine-learning model is larger than for the calibration of the prediction formulas. The paper discuss in detail the method to use in practice, depending on time and accuracy concerns.
keywords	Optimization, Daylight, Thermal Comfort, Overheating, Machine Learning, Predictive Model, Dwellings, Cold Climates
series	eCAADe
email
last changed	2023/12/10 10:49

_id	sigradi2018_1867
id	sigradi2018_1867
authors	Alawadhi, Mohammad; Yan, Wei
year	2018
title	Geometry from 3D Photogrammetry for Building Energy Modeling
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. 631-637
summary	Building energy modeling requires skilled labor, and there is a need to make environmental assessments of buildings more efficient and accessible for architects. A building energy model is based on collecting data from the real, physical world and representing them as a digital model. Recent digital photogrammetry tools can reconstruct real-world geometry by transforming photographs into 3D models automatically. However, there is a lack of accessible workflows that utilize this technology for building energy modeling and simulations. This paper presents a novel methodology to generate a building energy model from a photogrammetry-based 3D model using available tools and computer algorithms.
keywords	3D scanning; Building energy modeling; Building energy simulation; Digital photogrammetry; Photo-to-BEM
series	SIGRADI
email
last changed	2021/03/28 19:58

_id	caadria2018_056
id	caadria2018_056
authors	Chirkin, Artem, Pishniy, Maxim and Sender, Arina
year	2018
title	Generilized Visibility-Based Design Evaluation Using GPU
doi	https://doi.org/10.52842/conf.caadria.2018.2.483
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. 483-492
summary	Visibility plays an important role in perception and use of an urban design, and thus often becomes a target of design analysis. This work presents a fast method of evaluating various visibility-based design characteristics, such as isovists or insolation exploiting the GPU rendering pipeline and compute shaders. The proposed method employs a two-stage algorithm on each point of interest. First, it projects the visible space around a vantage point onto an equirectangular map. Second, it folds the map using a flexibly defined function into a single value that is associated with the vantage point. Being executed on a grid of points in a 3D scene, it can be visualized as a heat map or utilized by another algorithm for further design analysis. The developed system provides nearly real-time analysis tools for an early-stage design process to a broad audience via web services.
keywords	design analysis; design evaluation; GPU; isovist; insolation
series	CAADRIA
email
last changed	2022/06/07 07:55

_id	ecaade2018_121
id	ecaade2018_121
authors	Dimopoulos, Georgios
year	2018
title	Museum and Cultural Heritage in the World of Digital Technology
doi	https://doi.org/10.52842/conf.ecaade.2018.2.199
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. 199-204
summary	Museum as a cultural epiphenomenon reflects all changes occurring in cultural, political, economic and technological fields. Nowadays, as new technologies bring upon significant changes in the way we perceive space and time and open up new ways in understanding the world and all things, the museum is perceived as a network of potential things, a kind of web intersection that connects objective with digital reality. New technologies within the museum's space form a new relationship between the public and the cultural heritage objects, and offers new approach perspectives by reinforcing revisionist trends as far as the role and importance of the museum.
keywords	metanarratives; digital museum; visual reality
series	eCAADe
email
last changed	2022/06/07 07:55

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