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	c71c
authors	Li, Jian Cheng
year	1996
title	Study on Computer-aided Design of Shading Device of a Building
doi	https://doi.org/10.52842/conf.caadria.1996.143
source	CAADRIA ‘96 [Proceedings of The First Conference on Computer Aided Architectural Design Research in Asia / ISBN 9627-75-703-9] Hong Kong (Hong Kong) 25-27 April 1996, pp. 143-151
summary	The design of shading device is an important aspect of architectural heat-prevent design in sub-tropical climates of China. There is a large amount of calculation how to choose suitable style and size of shading device for various window in each exposure of a building, for the aim of both sheltering from sunlight indoors and preserving proper sun-shining time in a room. The solution of the calculation for the design of shading device is presented in this paper.
series	CAADRIA
last changed	2022/06/07 07:59

_id	acadia23_v2_330
id	acadia23_v2_330
authors	Li, Jiaqi; Lin, Chen-Yang; Lai, Zhen-Zhou; Lo, Tian-Tian
year	2023
title	Revitalization of Digital Hometown of Overseas Chinese: Using Virtual Reality Interaction Technology - The Example of Jimei School Village
source	ACADIA 2023: Habits of the Anthropocene: Scarcity and Abundance in a Post-Material Economy [Volume 2: Proceedings of the 43rd Annual Conference for the Association for Computer Aided Design in Architecture (ACADIA) ISBN 979-8-9891764-0-3]. Denver. 26-28 October 2023. edited by A. Crawford, N. Diniz, R. Beckett, J. Vanucchi, M. Swackhamer 330-339.
summary	Promoting the transformation and development of overseas Chinese hometowns through the inheritance of overseas Chinese culture and the integration of culture and tourism is an important research perspective in China's rural revitalization strategy. Nowadays, the development of rural cultural tourism through various digital means has effectively promoted the economic vitality of the region. This research takes Jimei School Village as an example and uses virtual-real interactive technology [Mixed Reality (MR) and an open- source electronics platform based on easy-to-use hardware and software (Arduino)] to build a ""Phygital Game"" - a virtual-real interactive platform. First, this research uses MR technology to display the characteristic content of the hometown of overseas Chinese, expand the amount of information displayed, and immerse tourists in the realistic scene of virtual-real fusion. In terms of interactive form, through the design of physical inter- action of Arduino, visitors can participate in puzzle-solving games. This platform aims to encourage tourists to actively explore the architectural features and culture of the hometown of overseas Chinese, to provide a valuable perspective for the optimization and development of the immersive cultural tourism platform.
series	ACADIA
type	paper
email
last changed	2024/12/20 09:12

_id	caadria2024_166
id	caadria2024_166
authors	Li, Jinmin, Luo, Yilu, Lu, Shuai, Zhang, Jingyun, Wang, Jun, Guo, Rizen and Wang, ShaoMing
year	2024
title	ChatDesign: Bootstrapping Generative Floor Plan Design With Pre-trained Large Language Models
doi	https://doi.org/10.52842/conf.caadria.2024.1.099
source	Nicole Gardner, Christiane M. Herr, Likai Wang, Hirano Toshiki, Sumbul Ahmad Khan (eds.), ACCELERATED DESIGN - Proceedings of the 29th CAADRIA Conference, Singapore, 20-26 April 2024, Volume 1, pp. 99–108
summary	Large language models (LLMs) have achieved remarkable success in various domains, revolutionizing tasks such as language translation, text generation, and question-answering. However, generating floor plan designs poses a unique challenge that demands the fulfilment of intricate spatial and relational constraints. In this paper, we propose ChatDesign, an innovative approach that leverages the power of pre-trained LLMs to generate floor plan designs from natural language descriptions, while incorporating iterative modifications based on user interaction. By processing user input text through a pre-trained LLM and utilizing a decoder, we can generate regression parameters and floor plans that are precisely tailored to satisfy the specific needs of the user. Our approach incorporates an iterative refinement process, optimizing the model output by considering the input text and previous results. Throughout these interactions, we employ many strategic techniques to ensure the generated design images align precisely with the user's requirements. The proposed approach is extensively evaluated through rigorous experiments, including user studies, demonstrating its feasibility and efficacy. The empirical results consistently demonstrate the superiority of our method over existing approaches, showcasing its ability to generate floor plans that rival those created by human designer. Our code will be available at https://github.com/THU-Kingmin/ChatDesign.
keywords	floor plan generation, large language models, user interactions, automatic design, deep learning, pre-train models
series	CAADRIA
email
last changed	2024/11/17 22:05

_id	caadria2024_465
id	caadria2024_465
authors	Li, Jinze, Song, Zhehao, Wen, Jian, Cai, Chenyi and Tang, Peng
year	2024
title	Exploring Nonlinear Relationship Between Built Environment and Street Vitality Using Machine Learning: A Case Study of Ding Shu, China
doi	https://doi.org/10.52842/conf.caadria.2024.2.375
source	Nicole Gardner, Christiane M. Herr, Likai Wang, Hirano Toshiki, Sumbul Ahmad Khan (eds.), ACCELERATED DESIGN - Proceedings of the 29th CAADRIA Conference, Singapore, 20-26 April 2024, Volume 2, pp. 375–384
summary	Urban vitality serves as the linchpin for sustainable urban development. Being the most extensively utilized public space within cities, augmenting street vitality bears paramount importance in accelerating design in human-centric habitats. This study employs spatial analysis and machine learning methods to explore the potential nonlinear relationships and local threshold effects between the built environment (BE) and street vitality based on multi-source data. This investigation provides support for the quantitative assessment and optimization of street vitality. Initially, using collected street view images, street spatial elements are extracted through deep learning algorithms. Subsequently, integrating multiple data sources, machine learning methods are employed to quantify the impact and interactions of the built environment on street vitality. Illustrated with the case of Dingshu, the feasibility of this process is demonstrated. By examining the correlation and underlying mechanisms between the built environment and street vitality, this study aids decision-makers in leveraging technological means to expedite design processes and create human-centric cities.
keywords	Nonlinear Relationship, Built Environment, Street Vitality, GBDT-SHAP, Interaction Effect
series	CAADRIA
email
last changed	2024/11/17 22:05

_id	caadria2024_88
id	caadria2024_88
authors	Li, Jiongye and Stouffs, Rudi
year	2024
title	Convolutional Neural Network-Based Predictions of Potential Flash Flood Hotspots in Singapore: Insights and Strategic Interventions
doi	https://doi.org/10.52842/conf.caadria.2024.2.069
source	Nicole Gardner, Christiane M. Herr, Likai Wang, Hirano Toshiki, Sumbul Ahmad Khan (eds.), ACCELERATED DESIGN - Proceedings of the 29th CAADRIA Conference, Singapore, 20-26 April 2024, Volume 2, pp. 69–78
summary	Amid increasing urbanization, changing climate, and limited stormwater infrastructure, urban flooding is a global issue, and Singapore is no exception. Traditional identification of flood-prone areas in Singapore has relied on historical flash flood data. However, by applying the booming influx of big data across various domains, including geography, weather, and DEM data, and using the deep learning model, Convolutional Neural Network (CNN), this research proposes a method that can accurately and effectively predict flash flood spots in an urban environment. Specifically, datasets including elevation, slope, aspect, rainfall, canals, drainage, and land use are fed into the CNN model to predict the locations of flash floods. The model, with a testing accuracy of 0.962, generates a comprehensive flash flood assessment map identifying high-risk areas in Singapore. Contrary to the current flood-prone area identification, which classifies only 0.79% of the country as susceptible to flash floods based on historical events, our CNN model-based assessment indicates that 11.4% of the country is at high risk. These newly identified zones are predominantly located along the coastline and in low-lying watershed outlets. Additionally, we propose corresponding stormwater infrastructure enhancements to mitigate flash flooding in these locations.
keywords	flash floods, flood prediction, convolutional neural network, geospatial data, flash flood assessment map, stormwater management measures
series	CAADRIA
email
last changed	2024/11/17 22:05

_id	caadria2024_87
id	caadria2024_87
authors	Li, Jiongye and Stouffs, Rudi
year	2024
title	Distribution of Carbon Storage and Potential Strategies to Enhance Carbon Sequestration Capacity in Singapore: A Study Based on Machine Learning Simulation and Geospatial Analysis
doi	https://doi.org/10.52842/conf.caadria.2024.2.089
source	Nicole Gardner, Christiane M. Herr, Likai Wang, Hirano Toshiki, Sumbul Ahmad Khan (eds.), ACCELERATED DESIGN - Proceedings of the 29th CAADRIA Conference, Singapore, 20-26 April 2024, Volume 2, pp. 89–98
summary	The expansion of urbanization leads to significant changes in land use, consequently affecting carbon storage. This research aims to investigate the carbon loss due to land use alterations and proposes strategies for mitigation. Utilizing existing land use data from 2017 and 2022, along with simulated data for 2025 generated by an ANN model and Cellular Automata, we identified changes in land use. These changes were then correlated with variations in carbon storage, both gains and losses. Our findings reveal a significant loss of 36,859 metric tons of carbon storage from 2017 to 2022. The projection for 2025 estimates a further reduction, reaching a total loss of 83,409 metric tons. By employing the LISA method, we identified that low-carbon storage zones are concentrated in the southeast region of the research site. By overlaying these zones with areas of carbon storage loss, we pinpointed regions severely affected by carbon depletion. Consequently, we propose that mitigation strategies should be imperatively implemented in these identified areas to counteract the trend of carbon storage loss. This approach offers urban planners a solution to identify areas experiencing carbon storage decline. Moreover, our research methodology provides a novel framework for scholars studying similar carbon issues.
keywords	land use and land cover (LULC) changes, simulated LULC, machine learning model, carbon storage changes, GIS
series	CAADRIA
email
last changed	2024/11/17 22:05

_id	caadria2023_347
id	caadria2023_347
authors	Li, Keke, Wu, Hao, Ding, Xiangwen, Li, Haowei and Yuan, Philip F.
year	2023
title	Bespoke 3D Printed Chair: Research on the Digital Design and Fabrication Method of Multi-Body Pose Fusion
doi	https://doi.org/10.52842/conf.caadria.2023.1.169
source	Immanuel Koh, Dagmar Reinhardt, Mohammed Makki, Mona Khakhar, Nic Bao (eds.), HUMAN-CENTRIC - Proceedings of the 28th CAADRIA Conference, Ahmedabad, 18-24 March 2023, pp. 169–178
summary	Customization has become a vital part of the post-industrial production model. Traditional production methods struggle with the challenge of collecting large amounts of data and the high costs of customization. With advancements in big data and deep learning algorithms, it is now possible to reduce the difficulty and cost of data collection, resulting in more accurate individual customization. This paper presents a proposed workflow for customizing multi-position seating for individuals. Using deep learning algorithms such as OpenPose and parametric design platforms such as Grasshopper, the workflow transforms user-generated photos of the body into a seating model that fits corresponding positions. This process combines deep learning algorithms, simplifies the data collection and processing process, and provides an interface for user interaction on the Grasshopper platform. The workflow provides a comprehensive example of data-driven customization in the context of big data. It explores the potential of a new paradigm in digital design where data is the primary driving force.
keywords	Customization, Posture recognition, Multi-platform collaboration, Deep Learning, Workflow
series	CAADRIA
email
last changed	2023/06/15 23:14

_id	acadia23_v3_241
id	acadia23_v3_241
authors	Li, Leyuan
year	2023
title	Wall-Table-Bed
source	ACADIA 2023: Habits of the Anthropocene: Scarcity and Abundance in a Post-Material Economy [Volume 3: Proceedings of the 43rd Annual Conference for the Association for Computer Aided Design in Architecture (ACADIA) ISBN 979-8-9891764-1-0]. Denver. 26-28 October 2023. edited by A. Crawford, N. Diniz, R. Beckett, J. Vanucchi, M. Swackhamer 24-32.
summary	“Wall-Table-Bed” is an exhibition installation devised for this year’s ACADIA conference (Figure 1). It comprises nine movable and operable panels that create a malleable exhibition venue to showcase thirty-two posters selected through a rigorous peer-reviewed process. It also functions as a temporal device of enclosure, constructing a series of threshold conditions to engage events and activities at divergent scales and locations. The exhibition was first housed at the Jake Jabs Center during the conference and then relocated to outdoor and indoor public spaces in Denver to further its engagement with students and community stakeholders.
series	ACADIA
email
last changed	2024/04/17 14:00

_id	acadia20_170
id	acadia20_170
authors	Li, Peiwen; Zhu, Wenbo
year	2020
title	Clustering and Morphological Analysis of Campus Context
doi	https://doi.org/10.52842/conf.acadia.2020.2.170
source	ACADIA 2020: Distributed Proximities / Volume I: Technical Papers [Proceedings of the 40th Annual Conference of the Association of Computer Aided Design in Architecture (ACADIA) ISBN 978-0-578-95213-0]. Online and Global. 24-30 October 2020. edited by B. Slocum, V. Ago, S. Doyle, A. Marcus, M. Yablonina, and M. del Campo. 170-177.
summary	“Figure-ground” is an indispensable and significant part of urban design and urban morphological research, especially for the study of the university, which exists as a unique product of the city development and also develops with the city. In the past few decades, methods adapted by scholars of analyzing the figure-ground relationship of university campuses have gradually turned from qualitative to quantitative. And with the widespread application of AI technology in various disciplines, emerging research tools such as machine learning/deep learning have also been used in the study of urban morphology. On this basis, this paper reports on a potential application of deep clustering and big-data methods for campus morphological analysis. It documents a new framework for compressing the customized diagrammatic images containing a campus and its surrounding city context into integrated feature vectors via a convolutional autoencoder model, and using the compressed feature vectors for clustering and quantitative analysis of campus morphology.
series	ACADIA
type	paper
email
last changed	2023/10/22 12:06

_id	ecaade2017_129
id	ecaade2017_129
authors	Li, Qinying and Teng, Teng
year	2017
title	Integrated Adaptive and Tangible Architecture Design Tool
doi	https://doi.org/10.52842/conf.ecaade.2017.1.619
source	Fioravanti, A, Cursi, S, Elahmar, S, Gargaro, S, Loffreda, G, Novembri, G, Trento, A (eds.), ShoCK! - Sharing Computational Knowledge! - Proceedings of the 35th eCAADe Conference - Volume 1, Sapienza University of Rome, Rome, Italy, 20-22 September 2017, pp. 619-628
summary	In this paper, we identified two majority issues of current CAAD development situating from the standpoint of CAAD history and the nature of design. On one hand, current CAAD tools are not adaptive enough for early design stage, since most of CAAD tools are designed to be mathematical correct. as we conducted a detailed survey of CAAD development history, we find out that most of the techniques of Computer-Aided Design applied into architecture are always adopted from engineering track. On other hand, the interaction between Architects/Designer and CAAD tools needs to be enhanced. Design objects are operated by 2d based tools such as keyboard, mouse as well as monitors which are less capable of comprehensively representing physical 3D building objects. In addition, we proposed a working in progress potential solution with HCI approaches to fix these issues. We summarize that , the prototype proved that architects and designers could benefit from utilizing adaptive and tangible design tools, especially during massing studies in the early phases of architectural design.
keywords	CAAD development,; Human Computer Interaction; Tangible User Interfaces; Design Tool development; Design Process
series	eCAADe
email
last changed	2022/06/07 07:59

_id	caadria2023_238
id	caadria2023_238
authors	Li, Shuyang, Sun, Chengyu and Zou, Mingyan
year	2023
title	Indispensable Effects of Surrounding Avatars in VR-based Wayfinding Experiments
doi	https://doi.org/10.52842/conf.caadria.2023.2.431
source	Immanuel Koh, Dagmar Reinhardt, Mohammed Makki, Mona Khakhar, Nic Bao (eds.), HUMAN-CENTRIC - Proceedings of the 28th CAADRIA Conference, Ahmedabad, 18-24 March 2023, pp. 431–440
summary	Virtual reality technologies facilitate the presentation of the indoor and outdoor environment, enabling researchers to conduct environmental behaviour experiments and evidence-based design research with great feasibility. However, most previous environmental behaviour research based on VR technologies did not consider the surrounding crowd, especially wayfinding-related research. Thus, from a human-centric perspective, the credibility of these studies will be greatly argued. Are the avatars indispensable in the virtual environment? To answer this question, we designed a comparative test including three scenarios: the virtual environment without avatars, data-driven avatars in the virtual environment, and agent-based avatars in the virtual environment. Taking the Satellite Terminal of Shanghai Pudong International Airport as a study case, we developed an online VR wayfinding experiment platform. 435 participants were invited to this experiment, their wayfinding performance will be recorded and then analysed and visualisation. The results demonstrate that the presence or absence of avatars significantly impacts the participants' decision-making time in virtual environments. Besides, the distribution and movement of avatars may affect the participants' wayfinding behaviour. This study highlights the importance of avatars in VR-based experiments and validates the feasibility of data-driven avatars replicating real-world crowds.
keywords	Metaverse, Virtual Reality, Avatars, Online Experiment, Wayfinding, Transportation Building
series	CAADRIA
email
last changed	2023/06/15 23:14

_id	85db
authors	Li, Siu Pan Thomas and Will, Barry F.
year	1997
title	A Computer Based Evaluation Tool for the Visual Aspects in Window Design
doi	https://doi.org/10.52842/conf.caadria.1997.247
source	CAADRIA ‘97 [Proceedings of the Second Conference on Computer Aided Architectural Design Research in Asia / ISBN 957-575-057-8] Taiwan 17-19 April 1997, pp. 247-256
summary	Windows in buildings must respond to five major issues – daylight, sunshine, view, ventilation and sound. Each of these processes in its own way can be critical to the synthesis of a successful architectural design. All factors except view are engineering criteria that can be evaluated by some mathematical formulae provided there is sufficient information for the calculations. In contrast view” being a qualitative entity has difficulty in being measured by using conventional mathematical tools but it is probably the major factor that leads to the satisfaction and comfort of the users inside the building enclosure. This paper introduces a new approach in analyzing views by the use of computers. One of the advantages of this analysis process is that the psychological aspects are less biased in the end product. This paper explains the methodologies, theories and principles underlying these modeling and analyzing tools.
series	CAADRIA
email
last changed	2022/06/07 07:59

_id	acadia23_v1_48
id	acadia23_v1_48
authors	Li, Tianying; Zhang, Haotian
year	2023
title	Flooded House: A Disruptive Comfort Zone
source	ACADIA 2023: Habits of the Anthropocene: Scarcity and Abundance in a Post-Material Economy [Volume 1: Projects Catalog of the 43rd Annual Conference of the Association of Computer Aided Design in Architecture (ACADIA) ISBN 979-8-9860805-8-1]. Denver. 26-28 October 2023. edited by A. Crawford, N. Diniz, R. Beckett, J. Vanucchi, M. Swackhamer 48-55.
summary	“Flooded House” questions the concept of hygiene of the domestic space from a post-human perspective assisted by an experimental modeling process specifying ready-made plastic products. Against the threat of water, the nemesis of indoor space, modern architecture shields it as a submarine to retain the interior bubble of the comfort zone. The “Flooded House” is instead an aquarium. While a modern home strenuously excludes nature to retain the climatic management inside the bubble, the installation, “Flooded House,” presents faithfully the precarious condition of architecture by stripping bare the wall surfaces and exposing the plastic organs in architecture, an ad hoc assembly undergoing the crisis of water.
series	ACADIA
type	project
email
last changed	2024/04/17 13:58

_id	caadria2023_80
id	caadria2023_80
authors	Li, Weiqiong, Lo, Tiantian and Guo, Xiangmin
year	2023
title	Exploring the Application of the Digital Gamification Mechanisms to the Experience of Physical Architectural Exhibitions
doi	https://doi.org/10.52842/conf.caadria.2023.1.717
source	Immanuel Koh, Dagmar Reinhardt, Mohammed Makki, Mona Khakhar, Nic Bao (eds.), HUMAN-CENTRIC - Proceedings of the 28th CAADRIA Conference, Ahmedabad, 18-24 March 2023, pp. 717–726
summary	This study aims to respond to the 'human-centred' theme of digital heritage and visualisation by exploring a new approach to applying gamification mechanisms to design physical architectural exhibitions. This paper analyses the current exhibition's gamification design in three parts-core drivers, defining characteristics and development models. Then constructs a design model for "digital gamification". The history museum of Harbin Institute of Technology (Shenzhen) is selected as an example to conduct an empirical investigation. Finally, future experiments are proposed to evaluate the design process's effects on improving the platform's design. It is expected that the demonstration of this study will enrich the exploration of the application of the emerging design method of digital gamification mechanism in exhibition design. On the one hand, it attempts to construct the relationship between the influence of digital gamification mechanisms on the tangible and intangible information in the audience's cognitive space, thus providing new ideas for designing cultural experiences in future exhibition spaces. On the other hand, it gives new vitality to the exhibition design and enhances the audience's motivation to interact, which helps to expand cultural communication's influence.
keywords	Exhibition space, Experiential mechanism, Digital interaction, Gamification, Extended reality
series	CAADRIA
email
last changed	2023/06/15 23:14

_id	ecaade2024_360
id	ecaade2024_360
authors	Li, Wen-Ting; Fang, Han; Mak, Michele W. T.; Iuorio, Ornella
year	2024
title	Impacts of Human Energy-Related Behaviours on the Energy Efficiency of Adaptive Building Façade: A Review
doi	https://doi.org/10.52842/conf.ecaade.2024.2.557
source	Kontovourkis, O, Phocas, MC and Wurzer, G (eds.), Data-Driven Intelligence - Proceedings of the 42nd Conference on Education and Research in Computer Aided Architectural Design in Europe (eCAADe 2024), Nicosia, 11-13 September 2024, Volume 2, pp. 557–566
summary	Amid growing imperatives for heightened building energy efficiency and occupant comfort, adaptive façades have garnered significant attention and research efforts aimed at refining their structure and techniques to achieve energy savings. However, studies frequently overlook the consideration of human factors that impact the energy performance of adaptive façades, with limited discussions on potential solutions. In this review study, an investigation is undertaken to firstly delineate the challenges posed by occupant disruptive behaviour to the expectation of adaptive façade operations. Secondly, this study focuses on reviewing gamification design and implementation techniques aimed at enhancing operational efficiency and fostering increased user engagement. Findings from this review indicate that occupant-oriented adaptivity is crucial for the effective operation of adaptive façades, underscoring the importance of incorporating occupant-empowered control when automation systems are involved. Furthermore, the review highlights the necessity for gamification implementation methods to align with the unique characteristics of the building type and its occupants. Particularly, achieving a balance between extrinsic and intrinsic motivation appears as crucial. This study serves as a foundational resource for researchers and practitioners seeking to leverage the gamification for enhancing data communication and collection by promoting users’ engagement and positive behavioural change within the context of building adaptive façades - users interaction.
keywords	adaptive façade, building energy efficiency, human factors, occupant energy behaviour, gamification
series	eCAADe
email
last changed	2024/11/17 22:05

_id	ecaade2024_80
id	ecaade2024_80
authors	Li, Wenpei; Wu, Jiaqian; M. Herr, Christiane; Stouffs, Rudi
year	2024
title	Enhancing Lexicon Based Evaluation of Urban Green Space Characteristics and Perceptions with a Large Language Model
doi	https://doi.org/10.52842/conf.ecaade.2024.2.059
source	Kontovourkis, O, Phocas, MC and Wurzer, G (eds.), Data-Driven Intelligence - Proceedings of the 42nd Conference on Education and Research in Computer Aided Architectural Design in Europe (eCAADe 2024), Nicosia, 11-13 September 2024, Volume 2, pp. 59–68
summary	Evaluating Urban green space Characteristics and Human Perceptions (UCHP) is crucial for landscape design and management due to their impact on public health. Online park reviews provide valuable insights into human-environment interactions, enabling the large-scale evaluation of UCHP. However, existing approaches to classify online park reviews commonly ignore text context, leading to low precision of UCHP quantification and supervised approaches are rarely applied due to huge cost. To improve the precision and effectiveness of UCHP quantification, we propose a novel workflow comprising five stages: custom lexicon creation, design of labels for a Large Language Model (LLM), sentence classification using lexicon and LLM, and performance evaluation using a manually annotated dataset and four metrics: precision, recall, accuracy, and F1 score. To examine the performance of the LLM, we compared the classification of 15 UCHP using LLM, lexicon, and lexicon+LLM. The analysis involved utilizing online park review sentences from Google Map and TripAdvisor using the proposed workflow. The higher precision, accuracy and F1 score demonstrate that combination of lexicon and LLM yields the highest performance, followed by using only lexicon and then solely LLM. This performance evaluation demonstrates the validity of the proposed LLM-aided workflow, providing a practical, reliable, and efficient alternative to the lower performance of unsupervised methods, or costly supervised classification methods. We discuss the limitations of lexicon+LLM and outline new opportunities for LLM application in landscape studies.
keywords	urban green space, characteristics and human perceptions, large language model, evaluation
series	eCAADe
email
last changed	2024/11/17 22:05

_id	caadria2024_273
id	caadria2024_273
authors	Li, Xiaoqian, Han, Zhen, Liu, Gang and Stouffs, Rudi
year	2024
title	A Rapid Prediction Model for View-Based Glare Performance With Multimodal Generative Adversarial Networks
doi	https://doi.org/10.52842/conf.caadria.2024.1.029
source	Nicole Gardner, Christiane M. Herr, Likai Wang, Hirano Toshiki, Sumbul Ahmad Khan (eds.), ACCELERATED DESIGN - Proceedings of the 29th CAADRIA Conference, Singapore, 20-26 April 2024, Volume 1, pp. 29–38
summary	Machine learning-based glare prediction has greatly improved the efficiency of performance feedback. However, its limited generalizability and the absence of intuitive predictive indicators have constrained its practical application. In response, this study proposes a prediction model for luminance distribution images based on the multimodal learning approach. This model focuses on objects within the field of view, integrating spatial and material features through images. It also employs semantic feature mapping and multimodal data integration to flexibly represent building information, removing limitations on model validity imposed by changes in design scenarios. Additionally, the study proposes a multimodal Generative Adversarial Network tailored for the multimodal inputs. This network is equipped with unique feature fusion and reinforcement blocks, along with advanced up-sampling techniques, to efficiently distill and extract pertinent information from the inputs. The model's efficacy is verified by cases focusing on residential building luminance distribution, with a 97% improvement in computational speed compared to simulation methods. Offering both speed and accuracy, this model provides designers with a rapid, flexible, and intuitive supporting approach for daylight performance optimization design, particularly beneficial in the early design stage.
keywords	Glare Prediction, Prediction Model, Multimodal Model, Generative Adversarial Networks
series	CAADRIA
email
last changed	2024/11/17 22:05

_id	caadria2020_260
id	caadria2020_260
authors	LI, Yan, DU, Hongwu and WANG, Qing
year	2020
title	The Association Study Between Residential Building Interface and Perceived Density based on VR Technology - Taking 2 Enclosed Residential Districts of Guangzhou as Examples
doi	https://doi.org/10.52842/conf.caadria.2020.1.711
source	D. Holzer, W. Nakapan, A. Globa, I. Koh (eds.), RE: Anthropocene, Design in the Age of Humans - Proceedings of the 25th CAADRIA Conference - Volume 1, Chulalongkorn University, Bangkok, Thailand, 5-6 August 2020, pp. 711-720
summary	As urban development enters the stock increment era , the demand of environmental quality in urban residential districts gradually improves, making the construction of livable residential environment an important direction of urban development. The improvement of livable environment is the inevitable result of this process and perceived density is an indispensable and important part. Among the statistical methods, preference study is the most commonly one to explore the subjective factors affecting preference. The experience of immersive virtual environment can provide a more appropriate analytical method better for traditional image selection. Different permeability of architectural interface has significant influences on the perception of space comfortability, crowding and fascination. In this paper, two existing enclosed residential districts are selected for case study. The factors closely related to perceived density, such as solid Wall, grille, glass, open space, greening, etc, are selected by using immersive virtual technology. Through the interviewees' evaluations of perceived density of the virtual environment, the relationship between building interface and the perceived density of the residential area will be established.
keywords	Spatial Perceived Density; Virtual Reality Technology; Enclosed Residential District; Housing Interface; Association Study
series	CAADRIA
email
last changed	2022/06/07 07:51

_id	ecaade2024_210
id	ecaade2024_210
authors	Li, Yangzhi; Fingrut, Adam; Altun, Sevgi
year	2024
title	Embedding Systems Platform Arduino and Robotics into Architectural Education: A project-based approach combining computational design and digital fabrication
doi	https://doi.org/10.52842/conf.ecaade.2024.2.685
source	Kontovourkis, O, Phocas, MC and Wurzer, G (eds.), Data-Driven Intelligence - Proceedings of the 42nd Conference on Education and Research in Computer Aided Architectural Design in Europe (eCAADe 2024), Nicosia, 11-13 September 2024, Volume 2, pp. 685–694
summary	This paper investigates integrating robotic fabrication technologies within architectural pedagogy, aiming to develop effective teaching strategy tailored for a diverse group of students, including postgraduate and undergraduate students. Robotics is an essential technology in Industry 4.0, providing a wide range of capabilities in the manufacturing field. The rapid advancement of robotic arms in various industries has opened new possibilities for architectural education. Many architecture schools worldwide have established experimental laboratories equipped with robotic arms, creating opportunities for students to explore beyond the traditional scope of CNC manufacturing. However, professional courses on integrating robotic construction technologies into architectural education are scarce. This research aims to explore using robots as an open interface for problem-solving, geometry exploration, and programming in architectural education, catering to the students' diverse backgrounds and skill levels. By utilizing robotic construction technologies, students can engage in hands-on experimentation, fostering the adoption of digital fabrication techniques.
keywords	Architectural education, Digital Fabrication, Parametric design, Robotic fabrication, Hands-on experimentation
series	eCAADe
email
last changed	2024/11/17 22:05

_id	cf2009_501
id	cf2009_501
authors	Li, Yongzhi; Lertlakkhanakul, Jumphon; Lee, Seongki and Choi, Jinwon
year	2009
title	Design with space syntax analysis based on building information model: Towards an interactive application of building information model in early design process
source	T. Tidafi and T. Dorta (eds) Joining Languages, Cultures and Visions: CAADFutures 2009, PUM, 2009, pp. 501- 514
summary	This paper introduces a new framework to enable user-friendly space syntax analysis during the initial design stage. It assists designers, without in-depth knowledge on space syntax, to evaluate and compare design outcomes rapidly. The framework is realized by integration between space syntax and building information model in which space topology is autonomously retrieved. A BIM modeler so called ‘ArchiSpace’ has been developed to demonstrate the applicability of the framework to design practice. Our experiment shows that designers can use the modeler to analyze their design alternatives instantly at any moment during the initial design stage. Therefore, users can generate and evaluate their design alternatives simultaneously without distraction and tedious work on the space syntax analysis in detail.
keywords	Space syntax, building information modeling, evidence based design, space topology
series	CAAD Futures
email
last changed	2009/06/08 20:53

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