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	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	ecaade2020_456
id	ecaade2020_456
authors	Farinea, Chiara, Awad, Lana, Dubor, Alex and El Atab, Mohamad
year	2020
title	Integrating biophotovoltaic and cyber-physical technologies into a 3D printed wall
doi	https://doi.org/10.52842/conf.ecaade.2020.2.463
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. 463-472
summary	The research presented in this paper investigates the development of "3D printed ceramic green wall", a technological Nature Based Solution (NBS) aimed at regenerating urban areas by improving spatial quality and sustainability through clean and autonomous energy production. Building upon previous research, the challenge of this system is to adapt additive manufacturing processes of ceramic 3D printing with biophotovoltaic systems while simultaneously developing digital and cyber-physical frameworks to generate site and user responsive design and autonomous solutions that optimize system performance and energy generation. The paper explores the complex design negotiations between these drivers, focusing particularly on their performance optimization, and finally highlights the system potential as exemplified through a successful implementation of a 1:1 site responsive wall prototype.
keywords	Nature based solutions; biophotovoltaic systems; additive manufacturing; responsive design; cyber-physical networks; augmented reality
series	eCAADe
email
last changed	2022/06/07 07:55

_id	acadia20_668
id	acadia20_668
authors	Pasquero, Claudia; Poletto, Marco
year	2020
title	Deep Green
doi	https://doi.org/10.52842/conf.acadia.2020.1.668
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. 668-677.
summary	Ubiquitous computing enables us to decipher the biosphere’s anthropogenic dimension, what we call the Urbansphere (Pasquero and Poletto 2020). This machinic perspective unveils a new postanthropocentric reality, where the impact of artificial systems on the natural biosphere is indeed global, but their agency is no longer entirely human. This paper explores a protocol to design the Urbansphere, or what we may call the urbanization of the nonhuman, titled DeepGreen. With the development of DeepGreen, we are testing the potential to bring the interdependence of digital and biological intelligence to the core of architectural and urban design research. This is achieved by developing a new biocomputational design workflow that enables the pairing of what is algorithmically drawn with what is biologically grown (Pasquero and Poletto 2016). In other words, and more in detail, the paper will illustrate how generative adversarial network (GAN) algorithms (Radford, Metz, and Soumith 2015) can be trained to “behave” like a Physarum polycephalum, a unicellular organism endowed with surprising computational abilities and self-organizing behaviors that have made it popular among scientist and engineers alike (Adamatzky 2010) (Fig. 1). The trained GAN_Physarum is deployed as an urban design technique to test the potential of polycephalum intelligence in solving problems of urban remetabolization and in computing scenarios of urban morphogenesis within a nonhuman conceptual framework.
series	ACADIA
type	paper
email
last changed	2023/10/22 12:06

_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
email
last changed	2022/06/07 07:56

_id	ecaade2020_089
id	ecaade2020_089
authors	Ardic, Sabiha Irem, Kirdar, Gulce and Lima, Angela Barros
year	2020
title	An Exploratory Urban Analysis via Big Data Approach: Eindhoven Case - Measuring popularity based on POIs, accessibility and perceptual quality parameters
doi	https://doi.org/10.52842/conf.ecaade.2020.2.309
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. 309-318
summary	The cities are equipped with the data as a result of the individuals' sharings and application usage. This significant amount of data has the potential to reveal relations and support user-centric decision making. The focus of the research is to examine the relational factors of the neighborhoods' popularity by implementing a big data approach to contribute to the problem of urban areas' degradation. This paper presents an exploratory urban analysis for Eindhoven at the neighborhood level by considering variables of popularity: density and diversity of points of interest (POI), accessibility, and perceptual qualities. The multi-sourced data are composed of geotagged photos, the location and types of POIs, travel time data, and survey data. These different datasets are evaluated using BBN (Bayesian Belief Network) to understand the relationships between the parameters. The results showed a positive and relatively high connection between popularity - population change, accessibility by walk - density of POIs, and the feeling of safety - social cohesion. For further studies, this approach can contribute to the decision-making process in urban development, specifically in real estate and tourism development decisions to evaluate the land prices or the hot-spot touristic places.
keywords	big data approach; neighborhood analysis; popularity; point of interest (POI); accessibility; perceptual quality
series	eCAADe
email
last changed	2022/06/07 07:54

_id	ecaade2020_214
id	ecaade2020_214
authors	Chen, Hsien and Hsu, Pei-Hsien
year	2020
title	Data Mining as a User-oriented Tool in Participatory Urban Design
doi	https://doi.org/10.52842/conf.ecaade.2020.1.011
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. 11-18
summary	In this research, we did the datamining to the POI(point-of-interest) of the city, and shows how Popular times data and NPL(Natural language processing) analysis transformed user data into new tools of participatory design of urban planning. After analyzing and visualizing the popular time data of the city POI, we showed the city users' preferred place to go at different point in time. And this will figured out that at some time, same type of POI has different using condition. Based on above mentioned, we used NPL to analyze user reviews to find out the causes and provide planning suggestions. This method can offer planner a chance to understand the experience of city user at the planning stage. Comparing to the traditional method, fetching data from the social platform could be able to get the daily preference, perspective and emotion of the users, and these data can make the result of participatory urban planning accord with the demand of the users.
keywords	Popular times; NLP; Social Media; Urban Design Tool; Smart Cities
series	eCAADe
email
last changed	2022/06/07 07:55

_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_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	acadia20_38
id	acadia20_38
authors	Mueller, Stephen
year	2020
title	Irradiated Shade
doi	https://doi.org/10.52842/conf.acadia.2020.1.038
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. 38-46.
summary	The paper details computational mapping and modeling techniques from an ongoing design research project titled Irradiated Shade, which endeavors to develop and calibrate a computational toolset to uncover, represent, and design for the unseen dangers of ultraviolet radiation, a growing yet underexplored threat to cities, buildings, and the bodies that inhabit them. While increased shade in public spaces has been advocated as a strategy for “mitigation [of] climate change” (Kapelos and Patterson 2014), it is not a panacea to the threat. Even in apparent shade, the body is still exposed to harmful, ambient, or “scattered” UVB radiation. The study region is a binational metroplex, a territory in which significant atmospheric pollution and the effects of climate change (reduced cloud cover and more “still days” of stagnant air) amplify the “scatter” of ultraviolet wavelengths and UV exposure within shade, which exacerbates urban conditions of shade as an “index of inequality” (Bloch 2019) and threatens public health. Exposure to indirect radiation correlates to the amount of sky visible from the position of an observer (Gies and Mackay 2004). The overall size of a shade structure, as well as the design of openings along its sides, can greatly impact the UV protection factor (UPF) (Turnbull and Parisi 2005). Shade, therefore, is more complex than ubiquitous urban and architectural “sun” and “shadow studies” are capable of representing, as such analyses flatten the three-dimensional nature of radiation exposure and are “blind” to the ultraviolet spectrum. “Safe shade” is contingent on the nuances of the surrounding built environment, and designers must be empowered to observe and respond to a wider context than current representational tools allow.
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	ecaade2020_150
id	ecaade2020_150
authors	Stojanovski, Todor
year	2020
title	Role-playing planning games as educational tool - Experiences of teaching with educational games in Sweden
doi	https://doi.org/10.52842/conf.ecaade.2020.1.525
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. 525-534
summary	Teaching about cities and planning involves complexities of understanding urban development in space and time, evolution and transformation of cities, urban politics, actors and stakeholders. Delivering efficient ways of teaching, is very important for educators, particularly among lecturers at universities who work with urban planning and design. Games can be used as educational tools and role-playing games can capture the political struggle of different actors and stakeholders involved in planning processes. Games can enable students to experience urban development and take roles of different actors and stakeholders in the planning and development processes and practice the art of negotiations in urban politics. Two educational games were written for the planning courses at KTH Royal Institute of Technology, Sweden. Since 2011, 17 games were played in different courses. Data from the evaluation forms was collected on 14 games and 277 students answered questions. This paper analyses the evaluation forms and the comments of the students who took part in the games and discusses gaming as an educational tool. The experiences with role-playing planning games are very positive. These ratings occurs consistently in each game that was played with very small variations.
keywords	urban planning; urban design; role-playing games; education tool; teaching; gaming
series	eCAADe
email
last changed	2022/06/07 07:56

_id	ecaade2020_185
id	ecaade2020_185
authors	Wurzer, Gabriel, Lorenz, Wolfgang E., Forster, Julia, Bindreiter, Stefan, Lederer, Jakob, Gassner, Andreas, Mitteregger, Mathias, Kotroczo, Erich, Pöllauer, Pia and Fellner, Johann
year	2020
title	M-DAB - Towards re-using material resources of the city
doi	https://doi.org/10.52842/conf.ecaade.2020.1.127
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. 127-132
summary	If we strive for a de-carbonized future, we need to think of buildings within a city as resources that can be re-used rather than being disposed of. Together with considerations on refurbishment options and future building materials, this gives a decision field for stakeholders which depends on the current "building stock" - the set of pre-existing buildings which are characterized e.g. by building period, location and material composition. Changes in that context are hard to argue for since (1.) some depend on statistics, other (2.) on the concrete neighborhood and thus the space in which buildings are embedded, yet again others on (3.) future extrapolations again dealing with both of the aforementioned environments. To date, there exists no tool that can handle this back-and-forth between different abstraction levels and horizons in time; nor is it possible to pursue such an endeavor without a proper framework. Which is why the authors of this paper are aiming to provide one, giving a model of change in the context of re-using material resource of the city, when faced with numerous abstraction levels (spatial or abstract; past, current or future) which have feedback loops between them. The paper focuses on a concrete case study in the city of Vienna, however, chances are high that this will apply to every other building stock throughout the world if enough data is available. As a matter of fact, this approach will ensure that argumentation can happen on multiple levels (spatial, statistical, past, now and future) but keeps its focus on making the building stock of a city a resource for sustainable development.
keywords	material reuse; sustainability; waste reduction; Design and computation of urban and local systems – XS to XL; Health and materials in architecture and cities
series	eCAADe
email
last changed	2022/06/07 07:57

_id	acadia21_76
id	acadia21_76
authors	Smith, Rebecca
year	2021
title	Passive Listening and Evidence Collection
doi	https://doi.org/10.52842/conf.acadia.2021.076
source	ACADIA 2021: Realignments: Toward Critical Computation [Proceedings of the 41st Annual Conference of the Association of Computer Aided Design in Architecture (ACADIA) ISBN 979-8-986-08056-7]. Online and Global. 3-6 November 2021. edited by B. Bogosian, K. Dörfler, B. Farahi, J. Garcia del Castillo y López, J. Grant, V. Noel, S. Parascho, and J. Scott. 76-81.
summary	In this paper, I present the commercial, urban-scale gunshot detection system ShotSpotter in contrast with a range of ecological sensing examples which monitor animal vocalizations. Gunshot detection sensors are used to alert law enforcement that a gunshot has occurred and to collect evidence. They are intertwined with processes of criminalization, in which the individual, rather than the collective, is targeted for punishment. Ecological sensors are used as a “passive” practice of information gathering which seeks to understand the health of a given ecosystem through monitoring population demographics, and to document the collective harms of anthropogenic change (Stowell and Sueur 2020). In both examples, the ability of sensing infrastructures to “join up and speed up” (Gabrys 2019, 1) is increasing with the use of machine learning to identify patterns and objects: a new form of expertise through which the differential agendas of these systems are implemented and made visible. I trace the differential agendas of these systems as they manifest through varied components: the spatial distribution of hardware in the existing urban environment and / or landscape; the software and other informational processes that organize and translate the data; the visualization of acoustical sensing data; the commercial factors surrounding the production of material components; and the apps, platforms, and other forms of media through which information is made available to different stakeholders. I take an interpretive and qualitative approach to the analysis of these systems as cultural artifacts (Winner 1980), to demonstrate how the political and social stakes of the technology are embedded throughout them.
series	ACADIA
type	paper
email
last changed	2023/10/22 12:06

_id	ecaade2020_075
id	ecaade2020_075
authors	Yoffe, Hatzav, Plaut, Pnina, Fried, Shaked and J. Grobman, Yasha
year	2020
title	Enriching the Parametric Vocabulary of Urban Landscapes - A framework for computer-aided performance evaluation of sustainable development design models
doi	https://doi.org/10.52842/conf.ecaade.2020.1.047
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. 47-56
summary	Three decades past since the adoption of sustainability rating systems (SRS) by the Architecture Engineering and Construction industry (AEC) as standard methods for sustainable development evaluation. Nevertheless, these methods still suffer from a low adoption and implementation rate due to their manual, labor-intensive, expert dependent, and time-demanding process. The partial success of urban development evaluation puts forth the question: Are there faster, more accurate quantitative methods for advancing sustainability evaluation? The paper describes a prototype workflow for evaluating the performance of urban landscape design in a single digital workflow, based on ecological key indicator criteria. Grasshopper and Python parametric platforms were used to translate the criteria into quantitative spatial metrics. This study demonstrates optimized biomass measurement in two urban scales in line with the SITES rating system for landscape development: (XS) site development and (XL) neighborhood scale. The measured biomass density is used as a positive indication of ecosystem services capacity in the development site. The framework's quantitative workflow contributes to additional spatial feedbacks compared to the original numeric-based rating system method. Through these, composition and configuration metrics such as ecological connectivity, edge contrast, and patch shape can be visualized, measured, and compared. The metrics, which indicate performance characteristics of the design, generate new opportunities for data-rich sustainability evaluations of urban landscapes, using a single computer-aided workflow.
keywords	Sustainable development; Urban landscape
series	eCAADe
email
last changed	2022/06/07 07:57

_id	caadria2020_161
id	caadria2020_161
authors	Kido, Daiki, Fukuda, Tomohiro and Yabuki, Nobuyoshi
year	2020
title	Mobile Mixed Reality for Environmental Design Using Real-Time Semantic Segmentation and Video Communication - Dynamic Occlusion Handling and Green View Index Estimation
doi	https://doi.org/10.52842/conf.caadria.2020.1.681
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. 681-690
summary	Mixed reality (MR), that blends the real and virtual worlds, attracted attention for consensus-building among stakeholders in environmental design with the visualization of planned landscape onsite. One of the technical challenges in MR is the occlusion problem which occurs when virtual objects hide physical objects that should be rendered in front of virtual objects. This problem may cause inappropriate simulation. And the visual environmental assessment of present and proposed landscape with MR can be effective for the evidence-based design, such as urban greenery. Thus, this study aims to develop a MR-based environmental assessment system with dynamic occlusion handling and green view index estimation using semantic segmentation based on deep learning. This system was designed for the use on a mobile device with video communication over the Internet to implement a real-time semantic segmentation whose computational cost is high. The applicability of the developed system is shown through case studies.
keywords	Mixed Reality (MR); Environmental Design; Dynamic Occlusion Handling; Semantic Segmentation; Green View Index
series	CAADRIA
email
last changed	2022/06/07 07:52

_id	sigradi2021_260
id	sigradi2021_260
authors	Lima Ferreira, Claudio and Vaz Lima, Larissa
year	2021
title	Architecture and Neuroscience: Green Areas Contributions to Hospitalized Patients’ Homeostasis
source	Gomez, P and Braida, F (eds.), Designing Possibilities - Proceedings of the XXV International Conference of the Ibero-American Society of Digital Graphics (SIGraDi 2021), Online, 8 - 12 November 2021, pp. 927–939
summary	Hospitalization is, for the patient, a neuropsychophysiological stressor, thus pertinent theories point to architectural stimuli as a tool for the homeostasis restoration and consequent well-being. Furthermore, they compile advantages to the patients’ treatment and highlight, mainly, the natural environments benefits, which is elucidated by the Biophilia theory. Through literature review and analysis of applied research in national and international hospitals, extracted from indexing databases of scientific production in the 2000-2020 timeframe, it was found that these areas [a] promote stimuli that enhance emotions and positive feelings; [b] act to restore stress and anxiety; [c] reduce pain, analgesic intake and length of stay; and [d] increase patient satisfaction. By sharing the results of this research, the objective is, in addition to stimulating future research on the organism behavior in the environments, to indicate perspectives for hospital ambiences.
keywords	Neurociencias, Arquitetura Hospitalar, Áreas Verdes, Biophilia, Equilíbrio Homeostático.
series	SIGraDi
email
last changed	2022/05/23 12:11

_id	sigradi2020_983
id	sigradi2020_983
authors	Neves, Thayssa Barbosa da Silva; Labaki, Lucila Chebel
year	2020
title	Indicators for Urban Green (IUG): Proposal for a Computational Implementation
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. 983-990
summary	Due to the reality of the constructive densification process at urban areas in disproportion to urban vegetation cover, the aim of this paper is to formulate two indicators for measuring vegetated density. A proportion between vegetated density and built density was proposed. In order to develop a system of computational tools, an algorithmic-parametric framework called Indicators for Urban Green (IUG) was implemented. The focus is on the internal validation of the IUG through testing hypothetical urban situations. The proposed method leans on the premise of contributing to quanti-qualitative studies focused on mitigating the impacts of anthropogenic action caused at the microclimatic scale of cities.
keywords	Urban green, Urban indicators, Vegetated density, Built density, Computational implementation
series	SIGraDi
email
last changed	2021/07/16 11:53

_id	ijac202018102
id	ijac202018102
authors	Seifert, Nils; Michael Mühlhaus and Frank Petzold
year	2020
title	Urban strategy playground: Rethinking the urban planner’s toolbox
source	International Journal of Architectural Computing vol. 18 - no. 1, 20-40
summary	This article presents the results of the Urban Strategy Playground research group. Over the last 5 years, the focus of an interdisciplinary team of researchers was the conception, implementation and evaluation of a decision-support system for inner-city urban and architectural planning. The overall aim of past and ongoing research is to enable planners to validate and compare possible planning measures based on objective criteria. The Urban Strategy Playground software framework is an expandable toolbox that supports planners in developing strategies, evaluating them and visually preparing them for political decision-making processes and public participation. Examples of implemented tools are the simulation and monitoring of building codes, analysis of key density indicators and green space provision, simulation of shading, building energy and noise dispersion. For visualising the planning results, the framework provides interfaces for rapid prototyping of haptic models, as well as web viewers and a connection to Augmented Reality applications. Core aspects of the system were evaluated through case studies in cooperation with urban planning offices, housing companies and municipalities, proving feasibility, high acceptance of the decision-support software, and need for more tailored tools.
keywords	Urban planning, decision support, participation, augmented reality, 3D printing, visual programming, 3D city model
series	journal
email
last changed	2020/11/02 13:34

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