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
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
doi	https://doi.org/10.52842/conf.caadria.1996.143
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_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
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
doi	https://doi.org/10.52842/conf.caadria.2024.2.069
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
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
doi	https://doi.org/10.52842/conf.caadria.2024.2.089
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	caadria2008_22_session3a_180
id	caadria2008_22_session3a_180
authors	Li, Li; Jingwen Gu, Jing Ma
year	2008
title	A solution of geometric security based on autoCAD
source	CAADRIA 2008 [Proceedings of the 13th International Conference on Computer Aided Architectural Design Research in Asia] Chiang Mai (Thailand) 9-12 April 2008, pp. 180-184
doi	https://doi.org/10.52842/conf.caadria.2008.180
summary	There are numerous electronic blueprints used in engineering today. The geometric security of these blueprints is a big problem to be solved. Based on the research on CAD system mechanics, this paper gives a solution that makes geometric access and use secure,, and gives an implementation on AutoCAD system. It designs a new encryption system compatible with the built-in encryption according to the exploration of variants and commands mechanism in AutoCAD system, and the analysis of structure of drawing database. The solution provides a safe access to files for different level users, and it places the control of edit authority on special geometrics via adding customized objects which contains authority information and password to the graphic information database.
keywords	geometric security, order mechanism, customized object
series	CAADRIA
email
last changed	2022/06/07 07:59

_id	caadria2007_113
id	caadria2007_113
authors	Li, Li; Jingwen Gu
year	2007
title	Research of the Multimedia Courseware Creation System Application in Architecture Education
source	CAADRIA 2007 [Proceedings of the 12th International Conference on Computer Aided Architectural Design Research in Asia] Nanjing (China) 19-21 April 2007
doi	https://doi.org/10.52842/conf.caadria.2007.x.e7l
summary	A new teaching model is constructed in the study, which can make students fully involved in the learning activity while keep the guidance from instructors. Compared with traditional courseware technology, it excels in following metrics:A framework to build multimedia courseware is constructed in the system, which helps instructors to customize their own courseware in a fast and convenient fashion _ The system can be used to build flexible knowledge structure and complicated information trees, which matches the practical architectural knowledge system and excels the traditional one-way flowing process_A flexible database is built within the system. The courseware created by this system can read from the database and take information out of the database at any time.
series	CAADRIA
last changed	2022/06/07 07:50

_id	acadia20_170
id	acadia20_170
authors	Li, Peiwen; Zhu, Wenbo
year	2020
title	Clustering and Morphological Analysis of Campus Context
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.
doi	https://doi.org/10.52842/conf.acadia.2020.2.170
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	caadria2022_195
id	caadria2022_195
authors	Li, Shuyang, Sun, Chengyu and Lin, Yinshan
year	2022
title	A Method of VR Enhanced POE for Wayfinding Efficiency in Mega Terminals of Airport
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. 79-88
doi	https://doi.org/10.52842/conf.caadria.2022.1.079
summary	The airport is one of the most essential infrastructures of cities. An important issue of the airport design is that passengers must be able to find their way efficiently. Although the designers adopt the post-evaluation after the operation, it takes a long time to conduct the on-site wayfinding experiment, and the number of participants of the experiment is also limited. Moreover, conventional post-occupancy evaluation suffers from security control and quarantine inspection that can not be carried out in the field. We proposed a VR enhanced POE approach that carries out an online wayfinding experiment to obtain numerous and detailed data, which significantly improves the efficiency of the post-occupancy evaluation project, and is validated by an affordable small-scale on-site experiment. Meanwhile, the cause for low wayfinding efficiencies, such as the symmetric space, the ambiguous direction and the redundant information on signboards are found and corresponding optimization suggestions are presented. The following signage system optimization project conducted in the terminal is welcomed by the passengers according to monthly questionnaires.
keywords	Transportation Building, Post-Occupancy Evaluation, Digital Twins, Signage System Design, Wayfinding, Virtual Reality, Eye-Tracking, SDG 9.
series	CAADRIA
email
last changed	2022/07/22 07:34

_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
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
doi	https://doi.org/10.52842/conf.caadria.2023.2.431
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	ijac20053405
id	ijac20053405
authors	Li, Siu-Pan; Kvan, Thomas
year	2005
title	Enhancing Interaction in Architectural Presentations with Laser Pointers
source	International Journal of Architectural Computing vol. 3 - no. 4, 503-517
summary	In a common meeting environment with projector-and-screen settings, the discussion may be dominated by a presenter who has the control of the content displayed. Although frequently used for architectural discussions, this digitally-engaged setting may not be optimal in its support of participation and discussion of design ideas. This paper presents a novel use of laser pointers to enhance the interaction in architectural presentations. A laser pointing system designed for a projector-and-screen environment was developed. To compare the performance of the laser pointer with other interaction devices, a controlled user study was carried out to test the efficiency of different devices in point-and-selection interactions. The usability of the system was also tested in a design critique. These two tests show that laser pointer is useful and able to encourage participation in group discussions. Details of the laser pointing system, the experiments and the results are reported in this paper.
series	journal
email
more	http://www.ingentaconnect.com/content/mscp/ijac/2006/00000004/00000001/art00002
last changed	2007/03/04 07:08

_id	ab84
authors	Li, Thomas S.P. and Will, Barry F.
year	1997
title	A Computer-Aided Evaluation Tool for the Visual Aspects in Architectural Design for High-Density and High- Rise Buildings
source	CAAD Futures 1997 [Conference Proceedings / ISBN 0-7923-4726-9] München (Germany), 4-6 August 1997, pp. 345-356
summary	The field of view, the nature of the objects being seen, the distances between the objects and the viewer, daylighting and sunshine are some major factors affecting perceived reactions when viewing through a window. View is one major factor that leads to the satisfaction and comfort of the users inside the building enclosure. While computer technologies are being widely used in the field of architecture, designers still have to use their own intelligence, experience and preferences in judging their designs with respect to the quality of view. This paper introduces an alternative approach to the analysis of views by the use of computers. The prototype of this system and its underlying principles were first introduced in the C A A D R I A 1997 conference. This paper describes the further development of this system where emphasis has been placed on the high- rise and high-density environments. Architects may find themselves facing considerable limitations for improving their designs regarding views out of the building under these environmental conditions. This research permits an interactive real-time response to altering views as the forms and planes of the building are manipulated.
series	CAAD Futures
email
last changed	2001/05/27 18:39

_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
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
doi	https://doi.org/10.52842/conf.ecaade.2024.2.557
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
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
doi	https://doi.org/10.52842/conf.ecaade.2024.2.059
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
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
doi	https://doi.org/10.52842/conf.caadria.2024.1.029
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	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
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
doi	https://doi.org/10.52842/conf.ecaade.2024.2.685
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	caadria2023_390
id	caadria2023_390
authors	Li, Yu, Li, Lingling and Yue, Naihua
year	2023
title	A Surrogate-Assisted Optimization Approach to Improve Thermal Comfort and Energy Efficiency of Sports Halls in Subtropical Climates
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. 301–310
doi	https://doi.org/10.52842/conf.caadria.2023.1.301
summary	Balancing the thermal comfort and energy efficiency has been recognized as a critical issue in sports hall design, which is yet to be properly implemented in early design stages due to the huge computational cost and delayed simulation feedback. This paper develops an accelerated optimization approach for thermal comfort and energy efficiency of sports halls by combining surrogate modelling with evolutionary algorithms. An integrated computational workflow designated for early-stage application was established that consists of Design of experiments, Surrogate modelling, Surrogate-assisted multi-objective optimization, and Multi-criteria decision making. Specifically, a parametric sports hall model was set up for batch physics-based simulations to generate abundant training samples, which was then utilized to develop surrogate models for the rapid prediction of thermal comfort and energy efficiency. The validated surrogate models were eventually linked with evolutionary algorithms to quickly identify the optimal design solution(s). The performance of the developed approach was evaluated against the traditional simulation-based optimization (SBMOO) method. Results indicated that the proposed approach could save 70.91% of total computational time for this case study, whilst achieving better optimized thermal comfort and energy efficiency with a reduction of mean PMV and site EUI by 0.001 and 1.60 kWh/m2/yr versus the SBMOO method.
keywords	Thermal comfort, Energy efficiency, Multi-objective optimization, Surrogate model, Sports hall
series	CAADRIA
email
last changed	2023/06/15 23:14

_id	acadia22_714
id	acadia22_714
authors	Li, Yunqin; Zhang, Jiaxin; Wang, Xueqiang; Ma, Kai
year	2022
title	Measuring Street Vitality Based on Video-image Using Deep Learning
source	ACADIA 2022: Hybrids and Haecceities [Proceedings of the 42nd Annual Conference of the Association of Computer Aided Design in Architecture (ACADIA) ISBN 979-8-9860805-8-1]. University of Pennsylvania Stuart Weitzman School of Design. 27-29 October 2022. edited by M. Akbarzadeh, D. Aviv, H. Jamelle, and R. Stuart-Smith. 714-725.
summary	This paper proposes a deep convolutional neural network-based framework for fine-scale studies on automatic evaluation of street-level vitality using multiple object tracking and image segmentation with video data. A deep learning model for street vitality evaluation was proposed based on the intensity and complexity of pedestrian activities.
series	ACADIA
type	paper
email
last changed	2024/02/06 14:04

_id	caadria2024_386
id	caadria2024_386
authors	Liang, Jiadong, Zhong, Ximing and Koh, Immanuel
year	2024
title	Bridging Bim and AI: A Graph-Bim Encoding Approach for Detailed 3D Layout Generation Using Variational Graph Autoencoder
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. 221–230
doi	https://doi.org/10.52842/conf.caadria.2024.1.221
summary	Building Information Modelling (BIM) data provides an abundant source with hierarchical and detailed information on architectural elements. Nevertheless, transforming BIM data into an understandable format for AI to learn and generate controllable and detailed three-dimensional (3D) models remains a significant research challenge. This paper explores an encoding approach for converting BIM data into graph-structured data for AI to learn 3D models, which we define as Graph-BIM encoding. We employ the graph reconstruction capabilities of a Variational Graph Autoencoder (VGAE) for the unsupervised learning of BIM data to identify a suitable encoding method. VGAE's graph generation capabilities also reason for spatial layouts. Results demonstrate that VGAE can reconstruct BIM 3D models with high accuracy, and can reason the entire spatial layout from partial layout information detailed with architectural components. The primary contribution of this research is to provide a novel encoding approach for bridging AI and BIM encoding. The Graph-BIM encoding method enables low-cost, self-supervised learning of diverse BIM data, capable of learning and understanding the complex relationships between architectural elements. Graph-BIM provides foundational encoding for training general-purpose AI models for 3D generation.
keywords	BIM, graph-structured, encoding approach, VGAE, graph reconstruction and generation
series	CAADRIA
email
last changed	2024/11/17 22:05

_id	ecaade2024_198
id	ecaade2024_198
authors	Liang, Jiadong; Zhong, Ximing; Koh, Immanuel
year	2024
title	Building-VGAE: Generating 3D detailing and layered building models from simple geometry
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 1, pp. 625–634
doi	https://doi.org/10.52842/conf.ecaade.2024.1.625
summary	In the current field of AI-assisted architectural design, deep learning models primarily focus on simulating the highly detailed final models designed by human architects. However, in practical design tasks, the final model demands a high level of detail and clear layered classification information for building components. This presents a more significant challenge. We propose a three-dimensional(3D) building generation framework—Building-VGAE, based on Variational Graph Autoencoder (VGAE). Building-VGAE can generate 3D models with detailed building components and layered structure information from end to end, according to design constraints and building volumes. Building-VGAE’s experiment involves transforming 27,965 Housegan data into 3D data represented as graph-structured. The VGAE model then learns the data features and predicts the building component categories to which nodes and edges belong in the experiment. The results demonstrate that the framework can precisely reconstruct and predict building layouts that comply with design constraints and enable unified editing of building components of the same category. Building-VGAE contributes to its ability to learn the generative relationship from design constraints and building volumes to complex high-detail models compared to existing AI generative models. It also possesses prediction and editing capabilities based on the layered classification information of building components. This framework has the potential to position AI as a design partner for human architects, offering end-to-end 3D generative intelligence.
keywords	Variational Graph Auto-Encoder, 3D Spatial Grid Structure, Detailed Building Components, Layered Structure, Graph Reconstruction and Generation
series	eCAADe
email
last changed	2024/11/17 22:05

_id	caadria2009_074
id	caadria2009_074
authors	Liang, Rung-Huei; Ying-Ming Huang
year	2009
title	Visualizing Bits as Urban Semiotics
source	Proceedings of the 14th International Conference on Computer Aided Architectural Design Research in Asia / Yunlin (Taiwan) 22-25 April 2009, pp. 33-42
doi	https://doi.org/10.52842/conf.caadria.2009.033
summary	Geosemiotics, defined as the study of meaning of placing signs in the material world, concerns the interaction of spatial, individual, social, and cultural contexts. Mobile technology, enabling spatial awareness successfully, has turned our living space into coordinates to broaden geosemiotics study. With interdisciplinary perspectives, there is an emerging potential to integrate the study of mobile spatial interaction and geosemiotics and we address several open issues of geospatial applications in this paper. Since indexicality is the focus of geosemiotics study, we focus on digital indexicalities referring to physical space. Physical indexical signs are usually set by government or organizations rather than individuals, and therefore we propose a new concept to place personal indexical signs in the physical space with mobile devices and augmented reality technology. Overlapped onto the physical world via visual, iconic, and metaphorical methods, what these unique personal semiotics bring is a living space with novel urban landscape and geosemiotics.
keywords	locative media; geosemiotics; augmented reality; ubiquitous computing; mobile spatial interaction
series	CAADRIA
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last changed	2022/06/07 07:59

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