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	acadia23_v2_340
id	acadia23_v2_340
authors	Huang, Lee-Su; Spaw, Gregory
year	2023
title	Augmented Reality Assisted Robotic: Tube Bending
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 340-349.
summary	The intent of this research is to study potential improvements and optimizations in the context of robotic fabrication paired with Augmented Reality (AR), leveraging the technology in the fabrication of the individual part, as well as guiding the larger assembly process. AR applications within the Architecture, Engineering, and Construction (AEC) industry have seen constant research and development as designers, fabricators, and contractors seek methods to reduce errors, minimize waste, and optimize efficiency to lower costs (Chi, Kang, and Wang 2013). Recent advancements have made the technology very accessible and feasible for use in the field, as demonstrated by seminal projects such as the Steampunk Pavilion in Tallinn, Estonia (Jahn, Newnham, and Berg 2022). These types of projects typically improve manual craft processes. They often provide projective guidelines, and make possible complex geometries that would otherwise be painstakingly slow to complete and require decades of artisanal experience (Jahn et al. 2019). Building upon a previously developed robotic tube bending workflow, our research implements a custom AR interface to streamline the bending process for multiple, large, complex parts with many bends, providing a pre-visualization of the expected fabrication process for safety and part-verification purposes. We demonstrate the utility of this AR overlay in the part fabrication setting and in an inadvertent, human-robot, collaborative process when parts push the fabrication method past its limits. The AR technology is also used to facilitate the assembly process of a spatial installation exploring a unique aesthetic with subtle bends, loops, knots, bundles, and weaves utilizing a rigid tube material.
series	ACADIA
type	paper
email
last changed	2024/12/20 09:12

_id	acadia22_598
id	acadia22_598
authors	Shen, Yang-Ting; Wang, Mi-Chi; Huang, Lien-Kai; Gao, You-Min; Yen, Chia-Chin
year	2022
title	The Reproduction of Chinese Traditional Timber Structure
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. 598-603.
summary	In Chinese traditional timber building, “Dou-gong” stands as one of the most distinctive features to present the Chinese structure style. However, the preservation and reproduction of Dou-gong face difficulties due to the withering craftsman issue. This paper proposes a method to digitize the structure into BIM (building information modeling) and reproduce it via robot-based fabrication. By modeling these Dou-gong components with BIM technologies, we can establish a geometrical and non-geometrical 3D database. Then we use Autodesk Fusion and Grasshopper to design the robotic fabrication information whose information is transferred from 3D database models. Based on the fabrication information, including work paths and tool parameters, the KUKA robotic arm with six axes can precisely mill the wood materials into Dou-gong components without any traditional craftsman’s processing.
series	ACADIA
type	paper
email
last changed	2024/02/06 14:04

_id	architectural_intelligence2022_7
id	architectural_intelligence2022_7
authors	Weixin Huang & Luying Wang
year	2022
title	Towards big data behavioral analysis: rethinking GPS trajectory mining approaches from geographic, semantic, and quantitative perspectives
doi	https://doi.org/https://doi.org/10.1007/s44223-022-00011-y
source	Architectural Intelligence Journal
summary	The question regarding the actual usage of built environments is of immense importance in behavioral research. Yet traditional methods of collecting and analyzing data on movements and activities often lack needed accuracy and granularity. Thus, this article reviewed and summarized the applicability of emergent GPS trajectory mining approaches in the field of architecture from geographic, semantic, and quantitative perspectives, respectively. Accordingly, three experiments based on a case study using real GPS trajectory data from visitors to the Palace Museum in China were conducted to examine the usefulness and weakness of the aforementioned approaches. The findings revealed that although all three dimensions of the trajectory mining approaches had the potential to provide useful information for architectural and urban design, the higher the dimensionality in utilizing the data, the more effective the approach was in discovering generalizable knowledge of human behavioral pattern. Furthermore, the results suggested that to gain insights into the typological characteristics of human behaviors related to the built environments, the contribution of trajectory data alone was limited, hence, conventional field surveys and questionnaires which contain information on individual characteristics and spatial features should be used in conjunction. Future research and practical implications were outlined.
series	Architectural Intelligence
email
last changed	2025/01/09 15:00

_id	ecaade2022_169
id	ecaade2022_169
authors	Chen, Ting-Chia, Tsai, Tsung-Han, Huang, Ching-Wen and Wang, Shih-Yuan
year	2022
title	Compliant Mechanism Moulding via NiChrome Wire Sintering Method
doi	https://doi.org/10.52842/conf.ecaade.2022.1.281
source	Pak, B, Wurzer, G and Stouffs, R (eds.), Co-creating the Future: Inclusion in and through Design - Proceedings of the 40th Conference on Education and Research in Computer Aided Architectural Design in Europe (eCAADe 2022) - Volume 1, Ghent, 13-16 September 2022, pp. 281–290
summary	This research proposed a unique process for the rapid manufacturing of large-scale compliant mechanism components. Using the characteristics of the NiChrome wire sintering method, it aims to rapidly fabricate a large-scale compliant mechanism model at low cost. NiChrome wire sintering is a method in which NiChrome wire is wound into a target pattern and then placed in a hot-melt material (TPU powder) to be energized and moulded. The low cost, high degree of freedom and one-piece characteristic of this new method bring new possibilities for the manufacturing process of compliant mechanism components. This research applies a new fabrication method to reduce the production cost and manufacturing difficulty of large kinetic installations. In benefitting from the non-mechanical wear characteristics of compliant mechanisms, the service life of manufactured installations can be greatly prolonged as well. The new fabrication method demonstrates an efficient way to produce a large scale of kinetic structure and provides a toolkit for designers.
keywords	Nichrome Wire Sintering, Rapid Prototyping, Elastic Material, Digital Fabrication, Compliant Mechanism
series	eCAADe
email
last changed	2024/04/22 07:10

_id	caadria2022_242
id	caadria2022_242
authors	Cheng, Chung-Chieh, Sheng, Yu-Ting and Wang, Shih-Yuan
year	2022
title	Robotic Fabrication Process of Glued Laminated Bamboo for Material Efficient Construction
doi	https://doi.org/10.52842/conf.caadria.2022.2.213
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. 213-222
summary	This paper aims to introduce the development of a new-style glue-laminated bamboo (GLB) board structure and evaluating computational technologies aiming to enhance the performance of fibre materials and a set of digital manufacturing processes. Specifically, this paper develops a method to introduce the concept of topology optimisation into the properties of fibre materials. At the same time, it explains the unique structure optimisation design and manufacturing process (including the design process, digital tools and auxiliary equipment system). To test the design, this paper compares the data obtained via the gravity suspension test of the physical model and the simulation. Through digital manufacturing methods, the project aims to establish structural elements that could improve material efficiency. Furthermore, it may establish a GLB floor structure system in line with the material economy.
keywords	Digital fabrication, Robotic Assembly, Glued Laminate Bamboo, SDG 11, SDG 12, SDG 15
series	CAADRIA
email
last changed	2022/07/22 07:34

_id	cdrf2022_3
id	cdrf2022_3
authors	Deli Liu and Keqi Wang
year	2022
title	Spatial Analysis of Villages in Jilin Province Based on Space Syntax and Machine Learning
doi	https://doi.org/https://doi.org/10.1007/978-981-19-8637-6_1
source	Proceedings of the 2022 DigitalFUTURES The 4st International Conference on Computational Design and Robotic Fabrication (CDRF 2022)
summary	The development of machine learning technology gives architects and urban planners a new tool that can be used for research and design. The topic of this paper is to analyze the rural space of Jilin Province with the machine learning algorithms and space syntax theory, and to obtain the inherent formation and development laws of rural spatial forms, which can be used as a reference and evaluation system for subsequent rural development, and also can emphasize the locality and continuity of rural development. First, based on geographic information data, researching the connection between the distribution of villages and geographic data at a macro level and to classify them. Then, from each category, selecting one township and use all villages in its area as samples for the more specific study. Spatial features of individual village are extracted based on space syntax theory, and representative spatial features which can as feature values for cluster analysis are selected through comparative analysis. Then classify villages from high-dimensional data and explore their type characteristics. Finally, we hope the result of this study can help provide useful theoretical references for rural construction and nature conservation in the future.
series	cdrf
email
last changed	2024/05/29 14:02

_id	caadria2022_427
id	caadria2022_427
authors	Ding, Xinyue, Guo, Xiangmin, Lo, Tian Tian and Wang, Ke
year	2022
title	The Spatial Environment Affects Human Emotion Perception-Using Physiological Signal Modes
doi	https://doi.org/10.52842/conf.caadria.2022.2.425
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. 425-434
summary	In the past, spatial design was mainly from the perspective of designers. With the increasing demand for quality spaces, contemporary architecture has gradually shifted from focusing on form creation to human well-being, once again advocating the concept of "human-centered" spatial design. Exploring how the spatial environment affects human emotions and health is conducive to quantifying the emotional perception characteristics of space and promoting the improvement of human quality of life and sustainable survival. At the same time, the development of contemporary technology and neuroscience has promoted the study of the impact of spatial environment on human emotion perception. This paper summarizes the research on the impact of the spatial environment on human emotion perception in recent years. First, 28 relevant studies were screened using the PRISMA framework. Then a set of research processes applicable to this study is proposed. Next, the physiological signals currently used to study the effects of the spatial environment on human emotions are summarized and analyzed, including electroencephalography (EEG), skin response (GSR), pulse (PR), and four other signals. The architectural features studied in the related literature are mainly building structural features, building spatial geometric features, and building spatial functional attributes. The study of urban space is divided into different parts, such as urban environment characteristics and urban wayfinding behavior. Finally, we point out the shortcomings and perspectives of studies related to the influence of spatial environment on human emotion perception.
keywords	Architectural space environment, urban space, human emotional feelings, Physiological signals, SDG 11
series	CAADRIA
email
last changed	2022/07/22 07:34

_id	caadria2022_114
id	caadria2022_114
authors	Dong, Zhiyong, Lin, Jinru, Wang, Siqi, Xu, Yijia, Xu, Jiaqi and Liu, Xiao
year	2022
title	Where Will Romance Occur, A New Prediction Method of Urban Love Map through Deep Learning
doi	https://doi.org/10.52842/conf.caadria.2022.1.213
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. 213-222
summary	Romance awakens fond memories of the city. Finding out the relationship between romantic scene and urban morphology, and providing a prediction, can potentially facilitate the better urban design and urban life. Taking the Yangtze River Delta region of China as an example, this study aims to predict the distribution of romantic locations using deep learning based on multi-source data. Specifically, we use web crawlers to extract romance-related messages and geographic locations from social media platforms, and visualize them as romance heatmap. The urban environment and building features associated with romantic information are identified by Pearson correlation analysis and annotated in the city map. Then, both city labelled maps and romance heatmaps are fed into a Generative Adversarial Networks (GAN) as the training dataset to achieve final romance distribution predictions across regions for other cities. The ideal prediction results highlight the ability of deep learning techniques to quantify experience-based decision-making strategies that can be used in further research on urban design.
keywords	Romance Heatmap, Generative Adversarial Networks, Deep Learning, Big Data Analysis, Correlation Analysis, SDG 11
series	CAADRIA
email
last changed	2022/07/22 07:34

_id	cdrf2022_165
id	cdrf2022_165
authors	DongLai Yang, Likai Wang, and Ji Guohua
year	2022
title	Embedding Design Intent into Performance-Based Architectural Design—Case Study of Applying Soft Constraints to Design Optimization
doi	https://doi.org/https://doi.org/10.1007/978-981-19-8637-6_14
source	Proceedings of the 2022 DigitalFUTURES The 4st International Conference on Computational Design and Robotic Fabrication (CDRF 2022)
summary	The lack of consideration of subjective design intents hinders the application of performance-based design optimization to architectural design because building performance is not the only aspect that designers need to solve. In response, this study proposes a method integrating subjective design intents into performance-based design optimization using soft constraints. To demonstrate the method, a case study is presented, where the design optimization continuously provides feedback to the designer and helps them reformulate and redefine the design problem. The case study shows how the application of design optimization and soft constraints is able to assist designers in identifying implicit and hidden design problems and stimulate design exploration at the early design stage.
series	cdrf
email
last changed	2024/05/29 14:02

_id	caadria2022_112
id	caadria2022_112
authors	Guo, Yiyao, Luo, Yang, Wang, Sihan, Tan, Ying Yi and Tracy, Kenneth
year	2022
title	Robotic Fabrication of Topology Optimized Concrete Components With Reusable Formwork
doi	https://doi.org/10.52842/conf.caadria.2022.2.091
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. 91-100
summary	In this paper, we introduce a design-to-fabrication workflow to create topology optimised concrete components by clay printing a temporary mould and simultaneously casting concrete into it. Our fabrication approach addresses the United Nation's Sustainability Development Goal (SDG) 12 of reducing waste in construction by employing the phase changing properties of clay, allowing this natural resource to be broken down and reused for subsequent projects. We implemented our workflow in the design and fabrication of a resilient infrastructure that responds to SDG 9 - an urban furniture that braces large trees during high-speed typhoon winds and serving as a bench for locals to rest under the tree. This paper documents our workflow with considerations of its overall workability, material properties and fabrication efficiency. We showcase our final prototype and discuss the feasibility and challenges of this approach in fabricating complex freeform components on a large scale.
keywords	Robotic Fabrication, Topology Optimisation, Freeform Concrete, Reusable Formwork, SDG 9, SDG 12.
series	CAADRIA
email
last changed	2022/07/22 07:34

_id	cdrf2022_25
id	cdrf2022_25
authors	Hao Zhang, Yuetao Wang, Yuhan Tan, and Jilong Zhao
year	2022
title	Parametric Skin Design Method Based on Plane Crystallographic Group Operation Principle
doi	https://doi.org/https://doi.org/10.1007/978-981-19-8637-6_3
source	Proceedings of the 2022 DigitalFUTURES The 4st International Conference on Computational Design and Robotic Fabrication (CDRF 2022)
summary	Under the dual constraints of industrialization and digitalization, the building skin and structure are further integrated to form standardized units to meet the requirements of architectural performance, industrial prefabrication and “complexity” aesthetic characteristics. The complex and diverse forms of today's building skin hide profound mathematical logic relations and operation rules of form generation. Crystallographic group with regular symmetry and the operation principles reflected by it is one of the most important rules and methods of form and pattern processing in skin design. The study of the mural symbols in ancient Egypt, the murals in the Alhambra, the manuscripts of Escher and the window lattice in ancient Chinese architecture profoundly reflects the basic operation principle of crystal group in shaping the skin form of architecture. Abundant and diverse architectural skin forms can be formed through the operation of symmetry group on basic graphic units. On the basis of clarifying the basic principle of crystal group action, the operation matrix of crystallographic symmetry group can be transformed into parameterized operation steps through programming language for visual operation, and then the skin form with high complexity and leap dimension can be generated by geometric algorithm, and the design method of building skin generation based on crystallographic group is constructed. In the selection of operation form, combined with the calculation of building performance and structure, the construction skin can be used in practical engineering is generated. Based on crystallographic group operation, the unifications of building skin and the classification simplification of components can meet the requirements of modular and unifications design in the process of building industrialization, and meet the requirements of current building industrialization and digitization. It has great research significance and value in the aspects of design and construction efficiency and material economic cost.
series	cdrf
email
last changed	2024/05/29 14:02

_id	acadia22_638
id	acadia22_638
authors	Hosmer, Tyson; Wang, Jiaqi; Jiang, Wanzhu; He, Ziming
year	2022
title	Integrated Reconfigurable Autonomous Architecture System
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. 638-651.
summary	Integrated Reconfigurable Autonomous Architecture System (IRAAS) is composed of three components: 1) an interactive platform for user and environmental data input, 2) an agent-based generative space planning algorithm with deep reinforcement learning for continuous spatial adaptation, 3) a distributed robotic material system with bidirectional cyber-physical control protocols for simultaneous state alignment.
series	ACADIA
type	paper
email
last changed	2024/02/06 14:04

_id	caadria2024_186
id	caadria2024_186
authors	Huang, Jingfei and Tu, Han
year	2024
title	Inconsistent Affective Reaction: Sentiment of Perception and Opinion in Urban Environments
doi	https://doi.org/10.52842/conf.caadria.2024.2.395
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. 395–404
summary	The ascension of social media platforms has transformed our understanding of urban environments, giving rise to nuanced variations in sentiment reaction embedded within human perception and opinion, and challenging existing multidimensional sentiment analysis approaches in urban studies. This study presents novel methodologies for identifying and elucidating sentiment inconsistency, constructing a dataset encompassing 140,750 Baidu and Tencent Street view images to measure perceptions, and 984,024 Weibo social media text posts to measure opinions. A reaction index is developed, integrating object detection and natural language processing techniques to classify sentiment in Beijing Second Ring for 2016 and 2022. Classified sentiment reaction is analysed and visualized using regression analysis, image segmentation, and word frequency based on land-use distribution to discern underlying factors. The perception affective reaction trend map reveals a shift toward more evenly distributed positive sentiment, while the opinion affective reaction trend map shows more extreme changes. Our mismatch map indicates significant disparities between the sentiments of human perception and opinion of urban areas over the years. Changes in sentiment reactions have significant relationships with elements such as dense buildings and pedestrian presence. Our inconsistent maps present perception and opinion sentiments before and after the pandemic and offer potential explanations and directions for environmental management, in formulating strategies for urban renewal.
keywords	Urban Sentiment, Affective Reaction, Social Media, Machine Learning, Urban Data, Image Segmentation.
series	CAADRIA
email
last changed	2024/11/17 22:05

_id	sigradi2022_15
id	sigradi2022_15
authors	Jiang, Wanzhu; Wang, Jiaqi
year	2022
title	Autonomous Collective Housing Platform: Digitization, Fluidization and Materialization of Ownership
source	Herrera, PC, Dreifuss-Serrano, C, Gómez, P, Arris-Calderon, LF, Critical Appropriations - Proceedings of the XXVI Conference of the Iberoamerican Society of Digital Graphics (SIGraDi 2022), Universidad Peruana de Ciencias Aplicadas, Lima, 7-11 November 2022 , pp. 15–26
summary	New social phenomena like digital nomads urge an upgrade in housing ownership. This research proposes an autonomous housing platform that shapes residential communities into adaptive and reconfigurable systems, framing a cycle of digitalization, fluidization and materialization of housing ownership. Specifically, the interactive interface carries the flexible ownership model that uses virtual space voxels as digital currency; the artificial intelligence algorithm drives the multilateral ownership negotiation and circulation, and modular robots complete the mapping from ownership status to real spaces. Taking project TESSERACT as a case study, we verified the feasibility of this method and presented expected co-living scenarios: the spaces and ownership are constantly adjusted according to demands and are always in the closest interaction with users. By exploring the ownership evolution, this research guides an integrated and inclusive housing system paradigm, triggering critical evaluation of traditional models and providing new ideas for solving housing problems in the post-digital era.
keywords	Agent-Based Systems, Digital Platform, Housing Ownership, Space Planning Algorithm, Discrete Material System
series	SIGraDi
email
last changed	2023/05/16 16:55

_id	acadia22pr_76
id	acadia22pr_76
authors	Jiang, Wanzhu; Wang, Jiaqi; Hosmer, Tyson; He, Ziming
year	2022
title	TESSERACT?Integrated Reconfigurable Autonomous Architecture System
source	ACADIA 2022: Hybrids and Haecceities [Projects Catalog of the 42nd Annual Conference of the Association of Computer Aided Design in Architecture (ACADIA) ISBN 979-8-9860805-7-4]. University of Pennsylvania Stuart Weitzman School of Design. 27-29 October 2022. edited by M. Akbarzadeh, D. Aviv, H. Jamelle, and R. Stuart-Smith. 76-81.
summary	TESSERACT is an autonomous architecture developed through a voxel-based robotic material system that continuously reshapes communities through a socio-economic model with shifting fractional ownership. This incentivizes users to trade and share portions of physical space in real-time.
series	ACADIA
type	project
email
last changed	2024/02/06 14:04

_id	cdrf2022_263
id	cdrf2022_263
authors	Jiaqi Wang and Wanzhu Jiang
year	2022
title	Demand-Driven Distributed Adaptive Space Planning Based on Reinforcement Learning
doi	https://doi.org/https://doi.org/10.1007/978-981-19-8637-6_23
source	Proceedings of the 2022 DigitalFUTURES The 4st International Conference on Computational Design and Robotic Fabrication (CDRF 2022)
summary	In the second digital turn, the architecture driven by big data logic is gradually shifting from a traditional static entity to an intellective living organism. This paper explores a space planning algorithm that applies reinforcement learning to the multi-agent system to achieve condition adaptability. This algorithm contains an inclusive environment and programmable agents that represent independent spaces. Through reinforcement learning, personalized space needs are quantified as the agent’s Space Schema, which can provide adaptive behavior strategies to adjust volumetric room boundaries. The spatial organization emerges in multi-agent competition, guided by the Negotiation Schema, realizing the dynamic equilibrium of spatial relations and the stable maximization of collective interests. Through real-time interaction and distributed decision-making, this bottom-up method defines a new architectural paradigm that continuously changes based on demands with its high degree of variability, adaptability and evolvability.
series	cdrf
email
last changed	2024/05/29 14:02

_id	caadria2024_365
id	caadria2024_365
authors	Lahtinen, Aaro, Gardner, Nicole, Ramos Jaime, Cristina and Yu, Kuai
year	2024
title	Visualising Sydney's Urban Green: A Web Interface for Monitoring Vegetation Coverage between 1992 and 2022 using Google Earth Engine
doi	https://doi.org/10.52842/conf.caadria.2024.2.515
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. 515–524
summary	With continued population growth and urban expansion, the severity of environmental concerns within cities is likely to increase without proper urban ecosystem monitoring and management. Despite this, limited efforts have been made to effectively communicate the ecological value of urban vegetation to Architecture, Engineering and Construction (AEC) professionals concerned with mitigating these effects and improving urban liveability. In response, this research project proposes a novel framework for identifying and conveying historical changes to vegetation coverage within the Greater Sydney area between 1992 and 2022. The cloud-based geo-spatial analysis platform, Google Earth Engine (GEE), was used to construct an accurate land cover classification of Landsat imagery, allowing the magnitude, spatial configuration, and period of vegetation loss to be promptly identified. The outcomes of this analysis are represented through an intuitive web platform that facilitates a thorough understanding of the complex relationships between anthropogenic activities and vegetation coverage. A key finding indicated that recent developments in the Blacktown area had directly contributed to heightened land surface temperature, suggesting a reformed approach to urban planning is required to address climatic concerns appropriately. The developed web interface provides a unique method for AEC professionals to assess the effectiveness of past planning strategies, encouraging a multi-disciplinary approach to urban ecosystem management.
keywords	Urban Vegetation, Web Interface, Landsat Imagery, Land Cover Classification, Google Earth Engine
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	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	ecaade2022_167
id	ecaade2022_167
authors	Lin, Han, Tsai, Tsung-Han, Chen, Ting-Chia, Sheng, Yu-Ting and Wang, Shih-Yuan
year	2022
title	Robotic Additive Manufacturing of Glass Structures
doi	https://doi.org/10.52842/conf.ecaade.2022.2.379
source	Pak, B, Wurzer, G and Stouffs, R (eds.), Co-creating the Future: Inclusion in and through Design - Proceedings of the 40th Conference on Education and Research in Computer Aided Architectural Design in Europe (eCAADe 2022) - Volume 2, Ghent, 13-16 September 2022, pp. 379–388
summary	This paper proposes a glass 3D printing system that can be used at room temperature. The system employs high-frequency electromagnetic induction heaters and stone-ground carbon tubes to heat glass raw materials. In this study, a digital control system was fully utilised to control the extrusion of borosilicate glass materials. Through a calculated design and communication between a six-axis robot arm and an external computer, the robot’s printing path and speed and the feeding state of the glass printing machine can be automatically controlled for different geometric shapes and velocities. This study examines digital manufacturing processes and material properties to investigate the novel glass printing of textures and free-form surface modelling.
keywords	Glass, Induction Heating, Rapid Prototype, 3D Printing, Robotic Fabrication
series	eCAADe
email
last changed	2024/04/22 07:10

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