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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	ascaad2023_070
id	ascaad2023_070
authors	Agrawal, Rohan; Karkoon, Rashi
year	2023
title	Reinterpreting the Courtyard in Modern Indian Architecture: A Computational Study on Configurations
source	C+++: Computation, Culture, and Context – Proceedings of the 11th International Conference of the Arab Society for Computation in Architecture, Art and Design (ASCAAD), University of Petra, Amman, Jordan [Hybrid Conference] 7-9 November 2023, pp. 253-274.
summary	India is a land of significantly varying cultures, climates, and hence, a myriad of architectural styles and elements. Courtyard, one such element, had emerged as a result of multiple factors including not only climate and its context but the community and its culture as well. It is true reflection of the diversity that the country showcases. From the Havelis in Rajasthan and Gujarat to the Wadas in Maharashtra, it has always been an integral part of Indian architecture and its heritage. However, despite being such deeply rooted in the country's heritage, it has started to go missing in modern construction. Various changes in social, cultural, and climatic patterns have made courtyards either an element of luxury or a lost element of the past. What exists today is a vague notion of this element, whose origin is muddled, and the science behind it is lost. One needs to understand that leaving an empty space or a cut-out is neither the true identity nor the authentic form of a courtyard. This configuration depends on a plethora of factors, one of which is Enclosure, governed by width, length, and height. Configurations formed with varied enclosed proportions not only have a psychological influence on the user owing to volume change but also affect air circulation and temperature change. However, the modern application of courtyards is often theoretically examined, resulting in a lack of practical application of its methodologies and design techniques. Hence, different spatial possibilities create an opportunity to use computational methods such as modeling and simulation techniques to form cases of varying degrees and forms of enclosures. It enables the research to reinterpret courtyards in today’s modern context using computer-aided design for a more data-driven exploration for higher human well-being in designed spaces, optimized microclimate, and a more sustainable building. Thus, the paper aims to understand the age-old concept of the courtyard through a scientific lens with the help of modern computational techniques. It will evaluate different configurations formed through simulations graphically. Through the case of Bengaluru, Karnataka, a modern city that experiences a temperate climate in India, the paper will showcase how changing enclosures and various positions of openings can incorporate the true essence of a courtyard in today’s modern architecture. Further, a similar study of different climatic conditions can bring back the lost heritage to the country in its truest form through a futuristic design process that is not only data-driven but also more human and community-centric.
series	ASCAAD
email
last changed	2024/02/13 14:40

_id	caadria2023_133
id	caadria2023_133
authors	Cabezon Pedroso, Tomas, Rhee, Jinmo and Byrne, Daragh
year	2023
title	Feature Space Exploration as an Alternative for Design Space Exploration Beyond the Parametric Space
doi	https://doi.org/10.52842/conf.caadria.2023.2.029
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. 29–38
summary	This paper compares the parametric design space with a feature space generated by the extraction of design features using deep learning (DL) as an alternative way for design space exploration. In this comparison, the parametric design space is constructed by creating a synthetic dataset of 15.000 elements using a parametric algorithm and reducing its dimensions for visualization. The feature space — reduced-dimensionality vector space of embedded data features — is constructed by training a DL model on the same dataset. We analyze and compare the extracted design features by reducing their dimension and visualizing the results. We demonstrate that parametric design space is narrow in how it describes the design solutions because it is based on the combination of individual parameters. In comparison, we observed that the feature design space can intuitively represent design solutions according to complex parameter relationships. Based on our results, we discuss the potential of translating the features learned by DL models to provide a mechanism for intuitive design exploration space and visualization of possible design solutions.
keywords	Deep Learning, VAE, Design Space, Feature Design Space, Parametric Design Space, Design Exploration
series	CAADRIA
email
last changed	2023/06/15 23:14

_id	caadria2023_149
id	caadria2023_149
authors	Goepel, Garvin, Guida, George and Loayza Nolasco, Ana Gabriela
year	2023
title	Towards Hyper-Reality – A Case Study Mixed Reality Art Installation
doi	https://doi.org/10.52842/conf.caadria.2023.1.383
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. 383–392
summary	This paper reflects on the notion of hyper-reality through the creation of ‘Self-Compass’, an immersive mixed reality art installation. By merging the physical with overlayed digital 3D content, this study proposes a view of current notions of the metaverse as an extension of reality rather than a digitized replacement of it. This was demonstrated by augmenting a modular installation with an immersive digital counterpart through an augmented reality (AR) application accessible through mobile devices. ‘Self-compass’ combines a timber structure and a digital AR overlay into a radial configuration that framed eight views, revealing an historical connection beyond the immediate context, and inviting reflections on the relationship between oneself and place. The AR overlay merges meaning with data, allowing one to rethink the physical through the digital, and providing awareness of our impact on place across time. The paper discusses and evaluates applied methods of merging digital and physical objects through a mixed reality (MR) installation. It expands on current workflows through the development of an AR mobile application and examines simultaneous localization and mapping (SLAM) techniques, essential in the alignment of digital content within real-world environments. The paper concludes by illustrating the potential applications and impact of AR technologies within design practices by augmenting the physical and revealing a new hyper-reality.
keywords	Virtual and Augmented Environments, Mixed-Reality installation, Hyper-Reality
series	CAADRIA
email
last changed	2023/06/15 23:14

_id	ecaade2023_392
id	ecaade2023_392
authors	Johanes, Mikhael and Huang, Jeffrey
year	2023
title	Generative Isovist Transformer: Machine learning for spatial sequence synthesis
doi	https://doi.org/10.52842/conf.ecaade.2023.2.471
source	Dokonal, W, Hirschberg, U and Wurzer, G (eds.), Digital Design Reconsidered - Proceedings of the 41st Conference on Education and Research in Computer Aided Architectural Design in Europe (eCAADe 2023) - Volume 2, Graz, 20-22 September 2023, pp. 471–480
summary	While isovists have been used widely to quantify and analyze architectural space, its utilization for generative design still needs to be explored. On the other hand, advanced deep learning has shown opportunities for data-driven generative design. This research revisits the isovist capacity to represent architecture as a series of spatial sequences and extends the role of isovists beyond merely a perception model to projective agents. This paper presents the development of GIsT: Generative Isovists Transformer in sampling, learning, and generating architectural spatial sequences. By coupling isovists with discrete representation and generative deep learning models, we untapped the generative potential of isovist representation for spatial sequence synthesis. We demonstrated its capacity to learn the architectural spatial sequence and extendability via few-shots learning. The results show a promising direction toward integrating data-driven experiential spatial synthesis in future computational design tools.
keywords	Isovist, Spatial sequence, Generative Design, Discrete representation learning, Transformers, Machine Learning
series	eCAADe
email
last changed	2023/12/10 10:49

_id	ecaade2023_44
id	ecaade2023_44
authors	Mayrhofer-Hufnagl, Ingrid and Ennemoser, Benjamin
year	2023
title	From Linear to Manifold Interpolation: Exemplifying the paradigm shift through interpolation
doi	https://doi.org/10.52842/conf.ecaade.2023.2.419
source	Dokonal, W, Hirschberg, U and Wurzer, G (eds.), Digital Design Reconsidered - Proceedings of the 41st Conference on Education and Research in Computer Aided Architectural Design in Europe (eCAADe 2023) - Volume 2, Graz, 20-22 September 2023, pp. 419–429
summary	The advent of artificial intelligence, specifically neural networks, has marked a significant turning point in the field of computation. During such transformative times, we are often faced with a dearth of appropriate vocabulary, which forces us to rely on existing terms, regardless of their inadequacy. This paper argues that the term “interpolation,” typically used in deep learning (DL), is a prime example of this phenomenon. It is not uncommon for beginners to misunderstand its meaning, as DL pioneer Francois Chollet (2017) has noted. This misreading is especially true in the discipline of architecture, and this study aims to demonstrate how the meaning of “interpolation” has evolved in the second digital turn. We begin by illustrating, using 2D data, the difference between linear interpolation in the context of topological figures and its use in DL algorithms. We then demonstrate how 3DGANs can be employed to interpolate across different topologies in complex 3D space, highlighting the distinction between linear and manifold interpolation. In both 2D and 3D examples, our results indicate that the process does not involve continuous morphing but instead resembles the piecing together of a jigsaw puzzle to form many parts of a larger ambient space. Our study reveals how previous architectural research on DL has employed the term “interpolation” without clarifying the crucial differences from its use in the first digital turn. We demonstrate the new possibilities that manifold interpolation offers for architecture, which extend well beyond parametric variations of the same topology.
keywords	Interpolation, 3D Generative Adversarial Networks, Deep Learning, Hybrid Space
series	eCAADe
email
last changed	2023/12/10 10:49

_id	caadria2023_84
id	caadria2023_84
authors	Chen, Bowen, Lao, Pui Kuan, Dou, Zhiyi, Qiu, Wai-Shan and Luo, Dan
year	2023
title	Analyst Patterns of Influence Between a Commercial Distribution and Neighbourhood Dynamic in a Residential Neighbourhood
doi	https://doi.org/10.52842/conf.caadria.2023.1.525
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. 525–534
summary	The spatial distribution of urban commercial spaces significantly impacts the overall efficiency and vibrancy of adjacent neighbourhoods. As such, it is an important factor to consider during urban development. This study aims to examine the patterns of impact between commercial distributions and neighbourhood dynamics in a residential neighbourhood, based on the case study of a highly populated, thriving commercial, and culturally rich area situated in Mong Kok, Hong Kong. In this research, a series of numeric evaluations and statistical analyses of liveability and vibrancy metrics are presented, uncovering the tension created by existing commercial forms and local living patterns. This research started with multi-dimensional data mining, such as accessing planning data using Geographic Information Systems (GIS), perception data using Street View Images (SVI), and business performance data from Google; secondly, analysing the data via machine learning (ML) algorithm and statistical correlation to identify correlations overlaid with a mapping of spaces of measurable characteristics. The goal is to establish a measurable evaluation of the relationship between commercial vibrance and urban features that can further inform the impact of urban design strategies on fostering the vitality of community commercial centres.
keywords	Mong Kok, Model Learning Machine (ML), SVM, PSPnet, MaskRCNN, POI, Commercial vibrance, Heatmap correlation, Visualization, QGIS, Google Maps Information
series	CAADRIA
email
last changed	2023/06/15 23:14

_id	ecaaderis2023_30
id	ecaaderis2023_30
authors	Fiuza, Rebeca, Barcelos, Letícia and Cardoso, Daniel
year	2023
title	COVID-19 and the City: An Analysis of the Correlation between Urban and Social Factors and COVID-19 in Fortaleza, Brazil
source	De Luca, F, Lykouras, I and Wurzer, G (eds.), Proceedings of the 9th eCAADe Regional International Symposium, TalTech, 15 - 16 June 2023, pp. 45–52
summary	The COVID-19 pandemic has been the biggest sanitary crisis humanity has ever faced, the virus has contaminated 662.717.929 people worldwide and killed 6.701.270 people. However, these numbers were not distributed equally at international, national or urban scale. In Fortaleza, Brazil, city studied in this paper, data from 2021 and 2022 epidemiologic reports suggest a contamination pattern that starts in neighborhoods with higher Human Development Index (HDI) and then goes to lower HDI neighborhoods, however, throughout all of this cycle, low HDI neighborhoods tend to have a higher lethality rate. These facts raised the hypothesis that those neighborhoods have specific urban and social factors that affect the capacity to respond and prevent COVID-19. The main objective of this paper is to identify the correlation of some urban and social factors with COVID-19 data. To achieve that, the authors selected seven variables (access to water rate, literacy rate, waste collection rate, population density, access to electric energy rate, sanitation rate and average monthly income) to correlate with four COVID- 19 indicators (total number of cases, total number of deaths, contamination rate and lethality rate). For this, it was chosen to apply Spearman’s correlation coefficient and for the calculation the statistical software Jamovi was used. The results show that the literacy rate, the access to electric energy rate and average monthly income have a positive correlation with the contamination rate, however these same variables have a negative correlation with the lethality rate.
keywords	COVID-19, Urban Factors, Spearman's Coefficient Correlation, Public Health
series	eCAADe
email
last changed	2024/02/05 14:28

_id	sigradi2023_219
id	sigradi2023_219
authors	Fiuza, Rebeca, Cardoso, Daniel, Moreira, Eugenio, Colares, Teresa, Freitas, Vitória and Paiva, Ricardo
year	2023
title	Correlations between urban and demographic data and COVID-19 data: a case study in Fortaleza, Brazil
source	García Amen, F, Goni Fitipaldo, A L and Armagno Gentile, Á (eds.), Accelerated Landscapes - Proceedings of the XXVII International Conference of the Ibero-American Society of Digital Graphics (SIGraDi 2023), Punta del Este, Maldonado, Uruguay, 29 November - 1 December 2023, pp. 1667–1678
summary	COVID-19 was a sanitary crisis of international impact. However, its effects weren’t experienced equally. In Fortaleza, epidemiological reports (2021;2022) point to different infection patterns between high Human Development Index (HDI) and low HDI neighborhoods, which surfaced the hypothesis that certain territories’ characteristics could correlate to COVID-19 data. This article describes a phase of a three-phase research, whose objective is to identify correlations between urban and demographic (UD) data to COVID-19 data. To this, a literature review was done to select seven UD variables and four COVID-19 ones, then, Spearman’s correlation was applied in four pandemic time frames (TF). Results show that literacy rates, monthly income and energy have either low or moderate positive correlations with contamination rates in most TF. However, they’ve shown low or moderate correlations with lethality rates in three TF. Population density showed low positive correlations to either lethality rates or total number of deaths in three TF.
keywords	COVID-19, Urban Data, Demographic Data, Spearman's Coefficient Correlation, Public Health
series	SIGraDi
email
last changed	2024/03/08 14:09

_id	sigradi2023_125
id	sigradi2023_125
authors	García Amen, Fernando
year	2023
title	Manufacturing worlds. Towards a Metaverse of Uruguayan Heritage.
source	García Amen, F, Goni Fitipaldo, A L and Armagno Gentile, Á (eds.), Accelerated Landscapes - Proceedings of the XXVII International Conference of the Ibero-American Society of Digital Graphics (SIGraDi 2023), Punta del Este, Maldonado, Uruguay, 29 November - 1 December 2023, pp. 729–738
summary	This project seeks to digitally recover, restore and preserve the architectural heritage of Uruguay through 3D scanning, with the aim of creating an interactive Metaverse that represents this heritage. To do this, virtual reality, augmented reality and mixed reality (VR/AR/MR) technologies will be used as key tools. The spectrum of relevant buildings is wide, considering works of architecture with structural, formal and testimonial value. The digitization of these works presents diverse challenges, from urban to rural settings. It seeks to establish a consistent methodology using data capture and processing tools, as well as open standards for the exchange of information. In addition, the importance of involving the community in the study and use of the selected architectural heritage is emphasized.
keywords	Digital heritage, Metaverse, 3D Scanning, Virtual Reality, Interaction
series	SIGraDi
email
last changed	2024/03/08 14:07

_id	ecaaderis2023_13
id	ecaaderis2023_13
authors	Giraud, Iason and Artopoulos, Georgios
year	2023
title	A Data-enabled Participatory Application towards Better Engagement and Neighborhood Accessibility
source	De Luca, F, Lykouras, I and Wurzer, G (eds.), Proceedings of the 9th eCAADe Regional International Symposium, TalTech, 15 - 16 June 2023, pp. 25–34
summary	This paper presents a novel workflow for managing urban data and visualizing them with the use of a mixed reality interface for studying historic urban cores in participatory design scenarios, using as a case study the Strovolos historic core in Nicosia, Cyprus. The application provides a data-enabled interactive medium to measure key aspects of urban accessibility with real time data feedback, to test design hypothesis and record user input. The goal is the creation of a user driven urban database and facilitate decision making of urban scenarios in consideration of walkable cities.
keywords	15-minute city, isochrones, accessibility, participatory
series	eCAADe
email
last changed	2024/02/05 14:28

_id	acadia23_v2_242
id	acadia23_v2_242
authors	Hoenerloh, Aileen; Arnardottir, Thora; Bridgens, Ben; Dade-Robertson, Martyn
year	2023
title	Living Morphogenesis: Bacteria-Driven Form Exploration through Aeration Scaffolding
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 242-255.
summary	Increasing interest in living materials has pushed scientists and designers to explore the potential of fungi, algae, yeast, and bacteria as part of the fabrication process. The microbially-produced biopolymer, bacterial cellulose (BC), shows great potential as an alternative building material due to its high durability, tensile strength, moisture resistance, and lightweight nature. Current BC fabrication methods primarily involve post-processing the naturally forming flat material after its growth phase. This research investigates an approach into co-designing with cellulose-producing bacteria to explore its morphogenetic tendencies in order to create intricate 3-dimensional forms. This paper looks at a fabrication approach that diverges from conventional BC material production towards form-finding by creating explorative methods that guide BC formation through the control of airflow. We present an experimental workflow with a bacteria and yeast that employs a strategy to identify parameters for guiding the morphological development of BC. To capture the form of the delicate material samples, a multi-step preservation process was developed, providing data on both the external and internal structure of the material. Photographic documentation of the growth process enabled the categorization of bacterial behavior in response to distinct environmental stimuli. Based on these obser- vations, a set of design principles was established to allow us to predict the morphological development of BC growth within a bioreactor. These experiments address a new type of unconventional computational approach to form-finding by studying the native growth mechanism of living bacteria, and offering a new perspective on our design engagement with these processes.
series	ACADIA
type	paper
email
last changed	2024/12/20 09:12

_id	caadria2023_50
id	caadria2023_50
authors	Jiang, Mingrui and Cai, Chenyi
year	2023
title	Communication With Detroit: Machine Learning in Open Source Community Housing Design
doi	https://doi.org/10.52842/conf.caadria.2023.1.049
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. 49–58
summary	Traditional pre-design investigation includes conceptual studies, site analysis, and programming processes to analyze the site and design for users. Instead, designers and architects should consider users' ideas and their actual usage of space, which are recorded and reflected on the social media platform. To introduce more citizens' voices in the design and learn more about people's expression of Detroit city and its housing, we propose to involve the machine learning analysis in the earlier stage of the housing project using users' reflections from social media to support the conceptual design. This paper introduces a novel design framework that deals with the lacking public programs in Detroit using an online data clustering platform and demonstrates a conceptual open-source community housing design according to related findings. This framework incorporates data collection from the Twitter platform, implementation of clustering for user-oriented programs, and design applications based on the findings. Our research demonstrates an efficient and flexible approach to the open-source community housing project.
keywords	Machine learning, Decision making, Social Media, User-oriented design, Open source community
series	CAADRIA
email
last changed	2023/06/15 23:14

_id	sigradi2023_370
id	sigradi2023_370
authors	Karnani, Vasudha
year	2023
title	Internet of Me: Experiential Exploration of Personal Digital Information Consumption with an AR Tool
source	García Amen, F, Goni Fitipaldo, A L and Armagno Gentile, Á (eds.), Accelerated Landscapes - Proceedings of the XXVII International Conference of the Ibero-American Society of Digital Graphics (SIGraDi 2023), Punta del Este, Maldonado, Uruguay, 29 November - 1 December 2023, pp. 925–936
summary	The convergence of cyber-physical systems, expansive internet growth, and intensified human-device interactions have led to exponential data consumption, resulting in information overload within society. This research addresses this information overload and its impact on digital wellbeing through development of an augmented reality (AR) tool, aiming to facilitate personalized data-driven introspection and enhance the utility of consumed information. By merging digital and physical realms, the tool facilitates tangible data exploration, transforming complex information into understandable interactions. It extracts and categorizes user browsing history data by domains, days, and time and leverages OpenAI's LLM GPT model to categorize the consumed digital content. Developed with Unity, the AR tool visualizes the data in layers in users' environments, promoting active personalized data sense-making. This research introduces an approach to data presentation that promotes information literacy and envisions an empowered society having a holistic, informed relationship with technology where users seamlessly interact with their digital presence.
keywords	AR/VR/MR, Information Overload, Data Sense-making, Phygital Landscape, Experiential Data Exploration
series	SIGraDi
email
last changed	2024/03/08 14:07

_id	caadria2023_340
id	caadria2023_340
authors	Kimm, Geoff, White, Marcus and Burry, Mark
year	2023
title	Extending Visuospatial Analysis in Design Computing: An Exploration With a Novel GPU-Based Algorithm and Form-Based Codes
doi	https://doi.org/10.52842/conf.caadria.2023.1.655
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. 655–664
summary	This paper responds to a gap observed between the contemporary capacity for calculation and analysis of visibility of built environment features, such as buildings, in digital urban and architectural computational research models and the functionality of off-the-shelf software tools available to professionals. The research investigates the potential of visibility analysis to be embedded and extended within computational-based workflows of software tools to better meet urban design and planning industry needs. We introduce a novel method for visibility calculation that exposes output data for further analysis within a computational workflow and implement it in a game development engine used by software tool providers. Based in our engagement with a local government authority, we then use that method to demonstrate a workflow in the context of form-based building codes in which the visual impact of a building is considered rather than prescriptive limits on dimensions and use. Our results indicate the novel method has substantial performance improvements compared to an alternative mode of visibility calculation and that software providers could more thoroughly integrate and extend visibility analysis to meet industry needs.
keywords	design computing, viewsheds, isovists, GPU shader, Unity 3D, genetic algorithm, generative design, form-based building codes
series	CAADRIA
email
last changed	2023/06/15 23:14

_id	ijac202321203
id	ijac202321203
authors	Kudless, Andrew
year	2023
title	Hierarchies of bias in artificial intelligence architecture: Collective, computational, and cognitive
source	International Journal of Architectural Computing 2023, Vol. 21 - no. 2, 256–279
summary	This paper examines the prevalence of bias in artificial intelligence text-to-image models utilized in the architecture and design disciplines. The rapid pace of advancements in machine learning technologies, particularly in text-to-image generators, has significantly increased over the past year, making these tools more accessible to the design community. Accordingly, this paper aims to critically document and analyze the collective, computational, and cognitive biases that designers may encounter when working with these tools at this time. The paper delves into three hierarchical levels of operation and investigates the possible biases present at each level. Starting with the training data for large language models (LLM), the paper explores how these models may create biases privileging English-language users and perspectives. The paper subsequently investigates the digital materiality of models and how their weights generate specific aesthetic results. Finally, the report concludes by examining user biases through their prompt and image selections and the potential for platforms to perpetuate these biases through the application of user data during training.
keywords	Bias in artificial intelligence, language bias, aesthetic bias, latent diffusion models, digital materiality
series	journal
last changed	2024/04/17 14:30

_id	ecaade2023_52
id	ecaade2023_52
authors	Le, Thanh-Luan and Kim, Sung-Ah
year	2023
title	Game-based Platform for Daylight Analysis using Deep Learning
doi	https://doi.org/10.52842/conf.ecaade.2023.2.481
source	Dokonal, W, Hirschberg, U and Wurzer, G (eds.), Digital Design Reconsidered - Proceedings of the 41st Conference on Education and Research in Computer Aided Architectural Design in Europe (eCAADe 2023) - Volume 2, Graz, 20-22 September 2023, pp. 481–490
summary	Daylight analysis is not easy and requires skills in specific software and techniques and significant computation time. These skills are necessary for architecture education, but some students may find them challenging. For this reason, a software-free and simulation-free approach that quickly calculates daylight performance may be a more effective way for students to learn and practice architecture design. From these ideas, a game environment, which is familiar to the young generation, may enhance the excitement and engagement of education in this field. The development of a cubic builder game platform that utilizes the Deep Learning Model (DLM) to help users learn about daylight analysis within the game environment is currently underway. This paper presents the preliminary results of this study that focused on exploring methods for implementing and using DLM to predict daylight performance in a game environment. Using a drawing canvas, users can give design inputs in this environment. A framework involving three steps has been developed to combine data from the design and gaming environments. First, small-scale building models with specific design contexts and simulation data were created in Rhino and Grasshopper using LadyBugs and HoneyBee. Second, a DLM was trained on these data to make predictions. Last, developing the game environment with the well-trained DLM in Unity3D. Through analysis, the DLM's performance in game environments confirmed the potential of this approach. A building system will fully implement the game environment in future research. The DLM's predictive performance will be enhanced using more extensive and diverse data sets.
keywords	Daylight Simulation, Architecture Education, Game-based, Unity3D, Deep Learning
series	eCAADe
email
last changed	2023/12/10 10:49

_id	ecaade2023_227
id	ecaade2023_227
authors	Moorhouse, Jon and Freeman, Tim
year	2023
title	Towards a Genome for Zero Carbon Retrofit of UK Housing
doi	https://doi.org/10.52842/conf.ecaade.2023.2.197
source	Dokonal, W, Hirschberg, U and Wurzer, G (eds.), Digital Design Reconsidered - Proceedings of the 41st Conference on Education and Research in Computer Aided Architectural Design in Europe (eCAADe 2023) - Volume 2, Graz, 20-22 September 2023, pp. 197–206
summary	The United Kingdom has some of the worst insulated housing stock in Northern Europe. This is in part due to the age of housing in the UK, with over 90% being built before 1990 [McCrone 2017, Piddington 2020]. Moreover, 85% of current UK housing will still be in use in 2050 by which stage their Government are targeting Net Carbon Zero [Eyre 2019]. Domestic energy use accounts for around 25% of UK carbon emissions. The UK will need to retrofit 20 million dwellings in order to meet this target. If this delivery were evenly spread, it would equate to over 2,000 retrofit completions each day. Government-funded initiatives are stimulating the market, with upwards of 60,000 social housing retrofits planned for 2023, but it is clear that a system must be developed to enable the design and implementation of housing-stock improvement at a large scale.This paper charts the 20-year development of a digital approach to the design for low-carbon domestic retrofit by architects Constructive Thinking Studio Limited and thence documents the emergence of a collaborative approach to retrofit patterns on a National scale. The author has led the Research and Development stream of this practice, developing a Building Information Modelling methodology and integrated Energy Modelling techniques to optimise design for housing retrofit [Georgiadou 2019, Ben 2020], and then inform a growing palette of details and a database of validated solutions [Moorhouse 2013] that can grow and be used to predict options for future projects [D’Angelo 2022]. The data is augmented by monitoring energy and environmental performance, enabling a growing body of knowledge that can be aligned with existing big data to simulate the benefits of nationwide stock improvement. The paper outlines incremental case studies and collaborative methods pivotal in developing this work The proposed outcome of the work is a Retrofit Genome that is available at a national level.
keywords	Retrofit, Housing, Zero-Carbon, BIM, Big Data, Design Genome
series	eCAADe
email
last changed	2023/12/10 10:49

_id	ascaad2023_014
id	ascaad2023_014
authors	Natsheh, Bahijah
year	2023
title	Using Geographic Information Systems (GIS) to Locate Neighborhood Parks Based on their Catchment Area
source	C+++: Computation, Culture, and Context – Proceedings of the 11th International Conference of the Arab Society for Computation in Architecture, Art and Design (ASCAAD), University of Petra, Amman, Jordan [Hybrid Conference] 7-9 November 2023, pp. 424-440.
summary	The city of Amman suffers from a shortage of open spaces and parks, which are vital for increasing physical exercise, boosting the quality of life in a community, and stimulating social interaction. This problem draws attention to the absence of planning criteria in addition to the poor regulatory framework for the distribution and location selection of open spaces and parks and their proportions that are commensurate with the population of Amman, a critical issue that requires immediate planning solutions. This study focuses on using geographic information systems (GIS) to determine the optimal neighborhood park locations in Bader, one of Amman's districts, and collects data from specific documents about neighborhood parks, examples of guidelines, and criteria for distributing parks in different countries to determine the criteria and catchment area of neighborhood parks. Using ArcGIS 10.1's Network Analyst Tool and its applications on the catchment area and the network analysis, the study analyzes data on land use, population density, accessibility, and surrounding variables to determine catchment areas to analyze neighborhood park accessibility. The study results show that the selected case study, the Bader District, which is one of Amman's most densely populated areas, experienced an erroneous distribution of neighborhood parks due to a lack of established planning regulations, resulting in a shortage of the percentage of the district's open spaces and parks dedicated to the population comparable to international standards. The research emphasizes GIS's potential as a significant tool for urban planning and community development, as well as insights into how parks might be strategically positioned to improve a neighborhood's livability by identifying areas in the neighborhood underserved by current parks and prospective locations for additional parks. Consequently, criteria are proposed and applied to the case study, and new locations for any suggested future parks are selected based on catchment areas. It should be noted that the results of this research may apply to different categories of parks in various Greater Amman Municipality (GAM) locations.
series	ASCAAD
email
last changed	2024/02/13 14:34

_id	caadria2023_264
id	caadria2023_264
authors	Rico Carranza, Eduardo, Huang, Sheng-Yang, Besems Julian and Gao, Wanqi
year	2023
title	(In)visible Cities: What Generative Algorithms Tell Us About Our Collective Memory Schema
doi	https://doi.org/10.52842/conf.caadria.2023.1.463
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. 463–472
summary	The last decade has witnessed a turn in AI technologies working with differentiable neural network architectures learning the embedded functions between data points and performing generative operations synthesising unseen data. The move to a continuous and generative AI paradigm aligns with ideas in the field of cognition and psychology, where a growing body of authors are beginning to conceptualise memory and our representation of the past as a dynamic, malleable and ultimately generative field. So, how effective are generative algorithms in supporting and enabling this creative process of remembrance? To answer this research question, we propose an experiment on how the spatial movement and exploration of maps of real and imagined images can help our brain reconstruct its memories in a dynamic yet accurate manner. We develop an application allowing visitors to dynamically explore real and AI-generated images of a given site clustered by similarity in a virtual 3D space. Analysing visitor paths and observed images helps us understand visitors’ perspectives on real and AI-generated data such as an increased preference for synthetic images by visitors familiarised with the site. We conclude with recommendations on how to approach visitor experience in generative AI-powered applications for engagement with historical and archival data.
keywords	Collective Memory, Embedded Differentiable Functions, Latent Space, Spatial Cognition, StyleGAN2, Schema, Visitor Paths
series	CAADRIA
type	normal paper
email
last changed	2024/01/09 06:17

_id	ecaade2024_46
id	ecaade2024_46
authors	Talmor-Blaistain, Anat; Merhav, Maayan; Fisher-Gewirtzman, Dafna
year	2024
title	Grid to Star Network Transformation: Developing a Topological Assessment and Transformation Model to Enhance Spatial Memory and Route Learning for Wayfinding
doi	https://doi.org/10.52842/conf.ecaade.2024.2.329
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. 329–338
summary	Wayfinding is the cognitive process of determining and following a path from one location to another. During navigation, a route-learning process occurs in which individuals encode spatial information. Older populations and individuals with cognitive difficulties face challenges in spatial learning and navigating complex environments. This study builds on Merhav and Fisher-Gewirtzman (2023), which suggests that star-shaped pedestrian paths, containing a distinct center through which all paths pass between origins and destinations, improve spatial memory and learning abilities for wayfinding compared to grid networks, benefiting all age groups. The research aims to bridge the gap in the analysis of pedestrian network topological shapes by developing a quantitative analytical model to evaluate how close each network is to a grid-type or a star-type and potentially transform these networks, from a grid-type into star-type topology. The proposed model suggests a methodology for assessing and modifying network topologies through spatial manipulations. The model utilizes a combination of open-source components (such as Space Syntax axial analysis and the Galapagos optimization plugin) and combines novel computational tools (python code) to rank nodes in the network and identify networks where isolated areas were created during the optimization process.
keywords	Spatial Computing, Spatial memory, Route learning, Wayfinding, Grid and star network’s Topological Shape, Space Syntax, analytical model
series	eCAADe
email
last changed	2024/11/17 22:05

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