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	acadia20_658
id	acadia20_658
authors	Ho, Brian
year	2020
title	Making a New City Image
doi	https://doi.org/10.52842/conf.acadia.2020.1.658
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. 658-667.
summary	This paper explores the application of computer vision and machine learning to streetlevel imagery of cities, reevaluating past theory linking urban form to human perception. This paper further proposes a new method for design based on the resulting model, where a designer can identify areas of a city tied to certain perceptual qualities and generate speculative street scenes optimized for their predicted saliency on labels of human experience. This work extends Kevin Lynch’s Image of the City with deep learning: training an image classification model to recognize Lynch’s five elements of the city image, using Lynch’s original photographs and diagrams of Boston to construct labeled training data alongside new imagery of the same locations. This new city image revitalizes past attempts to quantify the human perception of urban form and improve urban design. A designer can search and map the data set to understand spatial opportunities and predict the quality of imagined designs through a dynamic process of collage, model inference, and adaptation. Within a larger practice of design, this work suggests that the curation of archival records, computer science techniques, and theoretical principles of urbanism might be integrated into a single craft. With a new city image, designers might “see” at the scale of the city, as well as focus on the texture, color, and details of urban life.
series	ACADIA
type	paper
email
last changed	2023/10/22 12:06

_id	acadia20_178
id	acadia20_178
authors	Meeran, Ahmed; Conrad Joyce, Sam
year	2020
title	Machine Learning for Comparative Urban Planning at Scale: An Aviation Case Study
doi	https://doi.org/10.52842/conf.acadia.2020.1.178
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. 178-187.
summary	Aviation is in flux, experiencing 5.4% yearly growth over the last two decades. However, with COVID-19 aviation was hard hit. This, along with its contribution to global warming, has led to louder calls to limit its use. This situation emphasizes how urban planners and technologists could contribute to understanding and responding to this change. This paper explores a novel workflow of performing image-based machine learning (ML) on satellite images of over 1,000 world airports that were algorithmically collated using European Space Agency Sentinel2 API. From these, the top 350 United States airports were analyzed with land use parameters extracted around the airport using computer vision, which were mapped against their passenger footfall numbers. The results demonstrate a scalable approach to identify how easy and beneficial it would be for certain airports to expand or contract and how this would impact the surrounding urban environment in terms of pollution and congestion. The generic nature of this workflow makes it possible to potentially extend this method to any large infrastructure and compare and analyze specific features across a large number of images while being able to understand the same feature through time. This is critical in answering key typology-based urban design challenges at a higher level and without needing to perform on-ground studies, which could be expensive and time-consuming.
series	ACADIA
type	paper
email
last changed	2023/10/22 12:06

_id	ecaade2020_167
id	ecaade2020_167
authors	Newton, David, Piatkowski, Dan, Marshall, Wesley and Tendle, Atharva
year	2020
title	Deep Learning Methods for Urban Analysis and Health Estimation of Obesity
doi	https://doi.org/10.52842/conf.ecaade.2020.1.297
source	Werner, L and Koering, D (eds.), Anthropologic: Architecture and Fabrication in the cognitive age - Proceedings of the 38th eCAADe Conference - Volume 1, TU Berlin, Berlin, Germany, 16-18 September 2020, pp. 297-304
summary	In the 20th and 21st centuries, urban populations have increased dramatically with a whole host of impacts to human health that remain unknown. Research has shown significant correlations between design features in the built environment and human health, but this research has remained limited. A better understanding of this relationship could allow urban planners and architects to design healthier cities and buildings for an increasingly urbanized population. This research addresses this problem by using discriminative deep learning in combination with satellite imagery of census tracts to estimate rates of obesity. Data from the California Health Interview Survey is used to train a Convolutional Neural Network that uses satellite imagery of selected census tracts to estimate rates of obesity. This research contributes knowledge on methods for applying deep learning to urban health estimation, as well as, methods for identifying correlations between urban morphology and human health.
keywords	Deep Learning; Artificial Intelligence; Urban Planning; Health; Remote Sensing
series	eCAADe
email
last changed	2022/06/07 07:58

_id	acadia20_130
id	acadia20_130
authors	Newton, David
year	2020
title	Anxious Landscapes
doi	https://doi.org/10.52842/conf.acadia.2020.2.130
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. 130-137.
summary	Advances in the field of machine learning over the last decade have revolutionized artificial intelligence by providing a flexible means to build analytic, predictive, and generative models from large datasets, but the allied design disciplines have yet to apply these tools at the urban level to draw analytic insights on how the built environment might impact human health. Previous research has found numerous correlations between the built environment and both physical and mental health outcomes—suggesting that the design of our cities may have significant impacts on human health. Developing methods of analysis that can provide insight on the correlations between the built environment and human health could help the allied design disciplines shape our cities in ways that promote human health. This research addresses these issues and contributes knowledge on the use of deep learning (DL) methods for urban analysis and mental health, specifically anxiety. Mental health disorders, such as anxiety, have been estimated to account for the largest proportion of global disease burden. The methods presented allow architects, planners, and urban designers to make use of large remote-sensing datasets (e.g., satellite and aerial images) for design workflows involving analysis and generative design tasks. The research also contributes insight on correlations between anxiety prevalence and specific urban design features—providing actionable intelligence for the planning and design of the urban fabric.
series	ACADIA
type	paper
email
last changed	2023/10/22 12:06

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

_id	caadria2020_412
id	caadria2020_412
authors	Capunaman, Ozguc Bertug
year	2020
title	CAM as a Tool for Creative Expression - Informing Digital Fabrication through Human Interaction
doi	https://doi.org/10.52842/conf.caadria.2020.1.243
source	D. Holzer, W. Nakapan, A. Globa, I. Koh (eds.), RE: Anthropocene, Design in the Age of Humans - Proceedings of the 25th CAADRIA Conference - Volume 1, Chulalongkorn University, Bangkok, Thailand, 5-6 August 2020, pp. 243-252
summary	Contemporary digital design and fabrication tools often present deterministic and pre-programmed workflows. This limits the potential for developing a deeper understanding of materials within the process. This paper presents an interactive and adaptive design-fabrication workflow where the user can actively take turns in the fabrication process. The proposed experimental setup utilizes paste extrusion additive manufacturing in tandem with real-time control of an industrial robotic arm. By incorporating a computer-vision based feedback loop, it captures momentary changes in the fabricated artifact introduced by the users to inform the digital representation. Using the updated digital representation, the proposed system can offer simple design hypotheses for the user to evaluate and adapt future toolpaths accordingly. This paper presents the development of the experimental setup and delineates critical concepts and their motivation.
keywords	Computer-Aided Design (CAD) and Manufacturing (CAM); Human Computer Interaction; 3D Printing; Interactive Digital Fabrication; Robotic Fabrication
series	CAADRIA
email
last changed	2022/06/07 07:54

_id	caadria2020_402
id	caadria2020_402
authors	Ezzat, Mohammed
year	2020
title	A Framework for a Comprehensive Conceptualization of Urban Constructs - SpatialNet and SpatialFeaturesNet for computer-aided creative urban design
doi	https://doi.org/10.52842/conf.caadria.2020.2.111
source	D. Holzer, W. Nakapan, A. Globa, I. Koh (eds.), RE: Anthropocene, Design in the Age of Humans - Proceedings of the 25th CAADRIA Conference - Volume 2, Chulalongkorn University, Bangkok, Thailand, 5-6 August 2020, pp. 111-120
summary	Analogy is thought to be foundational for designing and for design creativity. Nonetheless, practicing analogical reasoning needs a knowledge-base. The paper proposes a framework for constructing a knowledge-base of urban constructs that builds on an ontology of urbanism. The framework is composed of two modules that are responsible for representing either the concepts or the features of any urban constructs' materialization. The concepts are represented as a knowledge graph (KG) named SpatialNet, while the physical features are represented by a deep neural network (DNN) called SpatialFeaturesNet. For structuring SpatialNet, as a KG that comprehensively conceptualizes spatial qualities, deep learning applied to natural language processing (NLP) is employed. The comprehensive concepts of SpatialNet are firstly discovered using semantic analyses of nine English lingual corpora and then structured using the urban ontology. The goal of the framework is to map the spatial features to the plethora of their matching concepts. The granularity Ã nd the coherence of the proposed framework is expected to sustain or substitute other known analogical, knowledge-based, inspirational design approaches such as case-based reasoning (CBR) and its analogical application on architectural design (CBD).
keywords	Domain-specific knowledge graph of urban qualities; Deep neural network for structuring KG; Natural language processing and comprehensive understanding of urban constructs; Urban cognition and design creativity; Case-based reasoning (CBR) and case-based design (CBD)
series	CAADRIA
email
last changed	2022/06/07 07:55

_id	ecaade2020_222
id	ecaade2020_222
authors	Ikeno, Kazunosuke, Fukuda, Tomohiro and Yabuki, Nobuyoshi
year	2020
title	Automatic Generation of Horizontal Building Mask Images by Using a 3D Model with Aerial Photographs for Deep Learning
doi	https://doi.org/10.52842/conf.ecaade.2020.2.271
source	Werner, L and Koering, D (eds.), Anthropologic: Architecture and Fabrication in the cognitive age - Proceedings of the 38th eCAADe Conference - Volume 2, TU Berlin, Berlin, Germany, 16-18 September 2020, pp. 271-278
summary	Information extracted from aerial photographs is widely used in urban planning and design. An effective method for detecting buildings in aerial photographs is to use deep learning for understanding the current state of a target region. However, the building mask images used to train the deep learning model are manually generated in many cases. To solve this challenge, a method has been proposed for automatically generating mask images by using virtual reality 3D models for deep learning. Because normal virtual models do not have the realism of a photograph, it is difficult to obtain highly accurate detection results in the real world even if the images are used for deep learning training. Therefore, the objective of this research is to propose a method for automatically generating building mask images by using 3D models with textured aerial photographs for deep learning. The model trained on datasets generated by the proposed method could detect buildings in aerial photographs with an accuracy of IoU = 0.622. Work left for the future includes changing the size and type of mask images, training the model, and evaluating the accuracy of the trained model.
keywords	Urban planning and design; Deep learning; Semantic segmentation; Mask image; Training data; Automatic design
series	eCAADe
email
last changed	2022/06/07 07:50

_id	ecaade2020_367
id	ecaade2020_367
authors	Jorgensen, Jens, Tamke, Martin and Poulsgaard, Kare Stokholm
year	2020
title	Occupancy-informed:Introducing a method or flexible behavioural mapping in architecture using machine vision
doi	https://doi.org/10.52842/conf.ecaade.2020.2.251
source	Werner, L and Koering, D (eds.), Anthropologic: Architecture and Fabrication in the cognitive age - Proceedings of the 38th eCAADe Conference - Volume 2, TU Berlin, Berlin, Germany, 16-18 September 2020, pp. 251-258
summary	The feedback-loops of the modern architectural design practice are broken, as architects rarely get to experience and learn about life in their buildings in a systematic way. Through novel survey and annotation methods, this project aims to develop tools and methodologies that assist architects in getting insights into the built environment. This paper describes the initial development of a framework for surveying and annotating occupant behaviour within architecture, called "Behavioural Situations". Using object recognition on embedded devices, it is possible to build an understanding of occupant behaviour, by coupling behavioural signifiers and their relations as nodes and edges in a graph representation.
keywords	Occupant behaviour; Behaviour sensing; Computer-vision
series	eCAADe
email
last changed	2022/06/07 07:52

_id	ecaade2020_245
id	ecaade2020_245
authors	Kampani, Anna and Varoudis, Tasos
year	2020
title	Perceptive Machine - Visuospatial Configurations Through Machine Intuition
doi	https://doi.org/10.52842/conf.ecaade.2020.1.419
source	Werner, L and Koering, D (eds.), Anthropologic: Architecture and Fabrication in the cognitive age - Proceedings of the 38th eCAADe Conference - Volume 1, TU Berlin, Berlin, Germany, 16-18 September 2020, pp. 419-428
summary	Computational tools in architecture have yet to adequately address the issue of evaluating and informing design through the prism of visual perception in 3-dimensional environments. Previous research has demonstrated that although the issue of understanding and designing public spaces is of significant importance, existing methods of data representation in VR are not extensively investigated. The present paper reports on research into the development of a computational model that evaluates and visualises information regarding permeability of the urban fabric in a virtual environment. Primary aim is to create an additional layer for early design stages that will assist in projecting all information in VR space so that the user can explore and grasp through data the impact of each design step in an immersive, human scale.
keywords	Computational Design; Virtual reality development; Machine Learning; Urban Analytics; Visual perception
series	eCAADe
email
last changed	2022/06/07 07:52

_id	acadia20_136p
id	acadia20_136p
authors	López Lobato, Déborah; Charbel, Hadin
year	2020
title	Foll(i)cle
source	ACADIA 2020: Distributed Proximities / Volume II: Projects [Proceedings of the 40th Annual Conference of the Association of Computer Aided Design in Architecture (ACADIA) ISBN 978-0-578-95253-6]. Online and Global. 24-30 October 2020. edited by M. Yablonina, A. Marcus, S. Doyle, M. del Campo, V. Ago, B. Slocum. 136-141
summary	In the early months of 2019, air pollution in Bangkok reached a record high, bringing national and international attention to the air quality in the South East Asian cosmopolitan. Although applications such as real-time pollution maps provide an environmental reading from the exterior, such information reveals the ‘here and now,’ where its record is inevitably lost through the ‘refreshing’ process of the live update and does not take increment and accumulation as factors to consider. The project was conceived around understanding the human body as precisely that medium that resists classification as either an interior or exterior environment that inherently performs as an impressionable record of its surroundings. Can a city’s toxicity be read through its living constituents? Can the living bodies that dwell, navigate, breathe, and process habitable environments be accessed? Can architecture retain a degree of independence while also performing as a beacon for the collective? Along this line of questioning, it was found that human hair can be transformed from a material that is effortlessly and continuously grown, cut, stylized, and discarded, and instead be intercepted and used in the production of public information gathering. Foll(i)cle is a collective being made of discarded human hair. Performing as a parliament for collectivity embedded with a protocol; the hairy pavilion invites the public in and presents them with a device at the center that hosts all the necessary equipment and information for anonymously and voluntarily providing hair samples for heavy metal analysis, the data of which is used in making a publically accessible toxi-cartography. Although humans are the primary subject for this study, the results suggest that extending the methodology to non-humans could prove useful in reading urban toxicity through various life forms.
series	ACADIA
type	project
email
last changed	2021/10/26 08:03

_id	sigradi2020_549
id	sigradi2020_549
authors	Rodríguez-Velásquez, Maribel
year	2020
title	Socio-technical interactions in the relationship between social movements and internet: a review of the state of the art and the theoretical framework
source	SIGraDi 2020 [Proceedings of the 24th Conference of the Iberoamerican Society of Digital Graphics - ISSN: 2318-6968] Online Conference 18 - 20 November 2020, pp. 549-554
summary	The paper recognizes the relationship between social movements and internet how new practices of resistance through technological appropriation (Castells, 2012). This social interaction mediated by technology, understood as socio-technical interaction, establish new dynamics between human-technology-human and other heterogeneous actants (Latour, 2008), such as power and counter-power institutions that also connect to the socio-technical network. Therefore, the studies about digital interaction of the instrumental line are expanded, towards an understanding of socio-technical interactions, from the dynamics of design/use interconnected with cultural, political and economic contexts (Scolari, 2004, 2019), because the technology must satisfy social needs.
keywords	Socio-technical interaction, Social movements, Internet, Human-Computer Interaction, Socio- technical network
series	SIGraDi
email
last changed	2021/07/16 11:52

_id	caadria2020_240
id	caadria2020_240
authors	Stojanovic, Djordje and Vujovic, Milica
year	2020
title	How to Share a Home - Towards Predictive Analysis for Innovative Housing Solutions
doi	https://doi.org/10.52842/conf.caadria.2020.1.547
source	D. Holzer, W. Nakapan, A. Globa, I. Koh (eds.), RE: Anthropocene, Design in the Age of Humans - Proceedings of the 25th CAADRIA Conference - Volume 1, Chulalongkorn University, Bangkok, Thailand, 5-6 August 2020, pp. 547-556
summary	Renewed interest in cohousing solutions is driven by the rapid population growth and a lack of affordable housing in many cities across the world. The home share has become more prevalent in recent years due to the cost benefits and social gains it provides. While it involves challenges primarily concerned with the usage of communal areas, the viability of this housing model increases with the advancement of technology enabling new tools for analysis and optimisation of spatial usage. This paper introduces a method of sensor application in the occupancy analysis to provide grounding for future studies and the implementation of advanced computational methods. The study focuses on the underexplored potential of the communal spaces and provides a method for the measuring of specific aspects of their usage. The study applies principles of mathematical set theory, to give a more conclusive understanding of how communal areas are used, and therefore contributes to the improvement of housing design. Presented outcomes include an algorithmic chart and a blueprint of a behavioural model.
keywords	Cohousing; Housing share; Post Occupancy Evaluation; Machine Learning ; Predictive Analysis
series	CAADRIA
email
last changed	2022/06/07 07:56

_id	ecaade2020_366
id	ecaade2020_366
authors	Temizel, Ensar
year	2020
title	The Cybernetic Relevance of Architecture:An Essay on Gordon Pask's Evolving Discourse on Architecture
doi	https://doi.org/10.52842/conf.ecaade.2020.1.471
source	Werner, L and Koering, D (eds.), Anthropologic: Architecture and Fabrication in the cognitive age - Proceedings of the 38th eCAADe Conference - Volume 1, TU Berlin, Berlin, Germany, 16-18 September 2020, pp. 471-480
summary	Gordon Pask, as one of the leading figures in the field of cybernetics, had an extensive impact on architecture through his lifelong connections with architectural circles in the UK and the USA from the early 1960s until his death in 1996. He is mostly known to architects by his collaboration with Cedric Price on a number of occasions; however, his affiliation with architecture include several other instances that involved designing architectural projects, teaching in architectural schools, writing on architectural issues and more. This paper aims to review these instances to scrutinize how his discourse on architecture unfolded in time by addressing his evolving understanding concerning the relationship between architecture and cybernetics. In doing so, the paper examines key aspects of his own work in relation to key instances of his relationship with architecture.
keywords	Cybernetics; Architecture; Design; Gordon Pask; Conversation Theory; Human-Machine Interaction
series	eCAADe
email
last changed	2022/06/07 07:58

_id	ecaade2020_121
id	ecaade2020_121
authors	Trossman Haifler, Yaala and Fisher-Gewirtzman, Dafna
year	2020
title	Urban Well-Being in Dense Cities - The influence of densification strategies, experiment in virtual reality
doi	https://doi.org/10.52842/conf.ecaade.2020.1.323
source	Werner, L and Koering, D (eds.), Anthropologic: Architecture and Fabrication in the cognitive age - Proceedings of the 38th eCAADe Conference - Volume 1, TU Berlin, Berlin, Germany, 16-18 September 2020, pp. 323-332
summary	Urban morphology significantly impacts resident's well-being. This study examines the impact of urban environments on the sense of well-being, using virtual reality as a research environment. Most of the world's population already live in urban localities; and it is expected that in two decades, more than 70% of the total population of the planet will be city dwellers(UN 2018). This study examines the impact of various urban configurations on dwellers well-being. Participants were presented with simulated pedestrian movement through 24 virtual urban environments. The environments differed by density level, spatial configurations, vegetation, and commerce. Participants assessed each alternative through structured questionnaires. It has been found that the density and presence of vegetation and commerce in the urban area have a significant impact on the subject's well-being in urban environments. extreme levels of densification have a negative effect on subjects' feelings, but vegetation and commerce, especially at the high levels of density, can improve them. In this research we established the framework for planning principles that can improve urban densification processes. An understanding of the wellbeing of urban dwellers, and the parameters that can influence this, will help urban designers and planners in creating better urbanized future environments.
series	eCAADe
email
last changed	2022/06/07 07:57

_id	ecaade2024_60
id	ecaade2024_60
authors	Wan, Zijun; Sun, Shuaibing; Meng, Fanjing; Yan, Yu
year	2024
title	How Augment Reality Support Public Participation in the Urban Design Decision-Making: A ten - year literature review
doi	https://doi.org/10.52842/conf.ecaade.2024.2.455
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. 455–464
summary	Emerging applications of AR have demonstrated its powerful visualization capabilities, which is a potential solution to enhance public participation in the urban design process. However, there is still a lack of complete understanding of how AR gets involved in this decision-making process. Therefore, this paper reviews 33 empirical studies relating to the topic through the four steps of “PRISMA”. The results indicate that the quantity and quality of research is increasing yearly. As AR technology progresses, the techniques and research methods used in those studies show a trend toward diversification and customization; this has also led to a shift in the scale of urban design from large and abstract to small and concrete. In terms of content, the topics have gradually changed from “people group” to “technology”, and then to “environment”. Notably, a small number of cases in tangible interaction and multi-user collaboration have emerged from 2020 — areas showing great promise. In terms of user assessments, most studies give positive feedback, but there are currently concerns about problems in poor AR visualizations, privacy risks, and the social inequality caused by technical affordance.
keywords	Augment reality, Urban design and planning, Public participation, Collaborative and participative design, Design decision-making
series	eCAADe
email
last changed	2024/11/17 22:05

_id	sigradi2020_945
id	sigradi2020_945
authors	Estrada Calderon, Gibsy Marcela; Becerra Santacruz, Habid
year	2020
title	Responsive Surface Design to Reduce the Urban Heat Island Effect (UHI)
source	SIGraDi 2020 [Proceedings of the 24th Conference of the Iberoamerican Society of Digital Graphics - ISSN: 2318-6968] Online Conference 18 - 20 November 2020, pp. 945-952
summary	The present project aims to influence the reduction of the urban heat island effect (UHI) by designing sensitive surfaces that respond to changes in temperature. This research presents a scenario with a vision of cities with adaptive designs that is generated from the insertion of elements sensitive to the environment (elements that respond to environmental stimuli). Responsive elements become constant factors in small-scale or large-scale design that transform the way environment is changed to a sensitive and resilient urban environment against possible adverse environmental conditions.
keywords	Urban heat island, Surface design, Sensitive environments, Resilient
series	SIGraDi
email
last changed	2021/07/16 11:53

_id	acadia20_84
id	acadia20_84
authors	Kirova, Nikol; Markopoulou, Areti
year	2020
title	Pedestrian Flow: Monitoring and Prediction
doi	https://doi.org/10.52842/conf.acadia.2020.1.084
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. 84-93.
summary	The worldwide lockdowns during the first wave of the COVID-19 pandemic had an immense effect on the public space. The events brought up an opportunity to redesign mobility plans, streets, and sidewalks, making cities more resilient and adaptable. This paper builds on previous research of the authors that focused on the development of a graphene-based sensing material system applied to a smart pavement and utilized to obtain pedestrian spatiotemporal data. The necessary steps for gradual integration of the material system within the urban fabric are introduced as milestones toward predictive modeling and dynamic mobility reconfiguration. Based on the capacity of the smart pavement, the current research presents how data acquired through an agent-based pedestrian simulation is used to gain insight into mobility patterns. A range of maps representing pedestrian density, flow, and distancing are generated to visualize the simulated behavioral patterns. The methodology is used to identify areas with high density and, thus, high risk of transmitting airborne diseases. The insights gained are used to identify streets where additional space for pedestrians is needed to allow safe use of the public space. It is proposed that this is done by creating a dynamic mobility plan where temporal pedestrianization takes place at certain times of the day with minimal disruption of road traffic. Although this paper focuses mainly on the agent-based pedestrian simulation, the method can be used with real-time data acquired by the sensing material system for informed decision-making following otherwise-unpredictable pedestrian behavior. Finally, the simulated data is used within a predictive modeling framework to identify further steps for each agent; this is used as a proof-of-concept through which more insights can be gained with additional exploration.
series	ACADIA
type	paper
email
last changed	2023/10/22 12:06

_id	acadia23_v3_111
id	acadia23_v3_111
authors	Markopoulou, Areti
year	2023
title	Urban Mining: Material Resources for Circular Construction
source	ACADIA 2023: Habits of the Anthropocene: Scarcity and Abundance in a Post-Material Economy [Volume 3: Proceedings of the 43rd Annual Conference for the Association for Computer Aided Design in Architecture (ACADIA) ISBN 979-8-9891764-1-0]. Denver. 26-28 October 2023. edited by A. Crawford, N. Diniz, R. Beckett, J. Vanucchi, M. Swackhamer 24-32.
summary	The material balance of the Earth is being challenged. The year 2020 was marked as the year when the total weight of human-made materials globally surpassed the weight of all life on Earth, while it is estimated that in the years to come the growth rate of mass added to the anthroposphere will increase exponentially (Elhacham et al., 2020). In this context of hypergrowth coupled with the climate emergency, the growing rate of urbanization and the increasing social and political awareness on the matters of the Anthropocene, the topics of resource depletion or insufficiency are being reframed. This keynote lecture at ACADIA 2023 highlights the importance of redefining resources and is introducing a new cultural, design and construction paradigm. Operating from an abundance mindset rather than from scarcity (Gausa et al., 2020) presents a new paradigm, particularly relevant in the design and production of the built environment. This approach expands the definition of resources, encompassing raw, non-raw, renewable, and recyclable materials. Shifting attention to the Anthroposphere as a source rather than just a destination for processed goods has the potential to disrupt linear design patterns and enhance circularity in cities and the built environment.
series	ACADIA
type	keynote
email
last changed	2024/04/17 13:59

_id	caadria2020_054
id	caadria2020_054
authors	Shen, Jiaqi, Liu, Chuan, Ren, Yue and Zheng, Hao
year	2020
title	Machine Learning Assisted Urban Filling
doi	https://doi.org/10.52842/conf.caadria.2020.2.679
source	D. Holzer, W. Nakapan, A. Globa, I. Koh (eds.), RE: Anthropocene, Design in the Age of Humans - Proceedings of the 25th CAADRIA Conference - Volume 2, Chulalongkorn University, Bangkok, Thailand, 5-6 August 2020, pp. 679-688
summary	When drawing urban scale plans, designers should always define the position and the shape of each building. This process usually costs much time in the early design stage when the condition of a city has not been finally determined. Thus the designers spend a lot of time working forward and backward drawing sketches for different characteristics of cities. Meanwhile, machine learning, as a decision-making tool, has been widely used in many fields. Generative Adversarial Network (GAN) is a model frame in machine learning, specially designed to learn and generate image data. Therefore, this research aims to apply GAN in creating urban design plans, helping designers automatically generate the predicted details of buildings configuration with a given condition of cities. Through the machine learning of image pairs, the result shows the relationship between the site conditions (roads, green lands, and rivers) and the configuration of buildings. This automatic design tool can help release the heavy load of urban designers in the early design stage, quickly providing a preview of design solutions for urban design tasks. The analysis of different machine learning models trained by the data from different cities inspires urban designers with design strategies and features in distinct conditions.
keywords	Artificial Intelligence; Urban Design; Generative Adversarial Networks; Machine Learning
series	CAADRIA
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last changed	2022/06/07 07:56

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