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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	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	caadria2024_87
id	caadria2024_87
authors	Li, Jiongye and Stouffs, Rudi
year	2024
title	Distribution of Carbon Storage and Potential Strategies to Enhance Carbon Sequestration Capacity in Singapore: A Study Based on Machine Learning Simulation and Geospatial Analysis
source	Nicole Gardner, Christiane M. Herr, Likai Wang, Hirano Toshiki, Sumbul Ahmad Khan (eds.), ACCELERATED DESIGN - Proceedings of the 29th CAADRIA Conference, Singapore, 20-26 April 2024, Volume 2, pp. 89–98
doi	https://doi.org/10.52842/conf.caadria.2024.2.089
summary	The expansion of urbanization leads to significant changes in land use, consequently affecting carbon storage. This research aims to investigate the carbon loss due to land use alterations and proposes strategies for mitigation. Utilizing existing land use data from 2017 and 2022, along with simulated data for 2025 generated by an ANN model and Cellular Automata, we identified changes in land use. These changes were then correlated with variations in carbon storage, both gains and losses. Our findings reveal a significant loss of 36,859 metric tons of carbon storage from 2017 to 2022. The projection for 2025 estimates a further reduction, reaching a total loss of 83,409 metric tons. By employing the LISA method, we identified that low-carbon storage zones are concentrated in the southeast region of the research site. By overlaying these zones with areas of carbon storage loss, we pinpointed regions severely affected by carbon depletion. Consequently, we propose that mitigation strategies should be imperatively implemented in these identified areas to counteract the trend of carbon storage loss. This approach offers urban planners a solution to identify areas experiencing carbon storage decline. Moreover, our research methodology provides a novel framework for scholars studying similar carbon issues.
keywords	land use and land cover (LULC) changes, simulated LULC, machine learning model, carbon storage changes, GIS
series	CAADRIA
email
last changed	2024/11/17 22:05

_id	caadria2022_255
id	caadria2022_255
authors	Wu, Zihao, Zhang, Yunsong and Tong, Ziyu
year	2022
title	Quantification of the Thermal Environmental Value of Urban Pores: A Case Study of Nanjing
source	Jeroen van Ameijde, Nicole Gardner, Kyung Hoon Hyun, Dan Luo, Urvi Sheth (eds.), POST-CARBON - Proceedings of the 27th CAADRIA Conference, Sydney, 9-15 April 2022, pp. 719-728
doi	https://doi.org/10.52842/conf.caadria.2022.2.719
summary	The term "Urban pores‚ refers to the space formed by the enclosure of buildings, which have great value for regulating the microclimate. Many previous studies have focused only on a single urban pore section, ignoring the spatial distribution at the urban scale. In this study, the openness of urban pores in Nanjing was quantified and grouped, and then the spatial distribution characteristics of each openness group were further calculated. Based on this, the study combined the spatial distribution characteristics of urban pores with urban thermal environment data and an LCZ urban form classification model to analyse the impact of urban pores on the urban thermal environment. The results show that 1) the impact of urban pores is greater in summer and autumn, where its spatial agglomeration has a higher cooling value for the urban thermal environment, while this is not significant in winter; 2) the spatial agglomeration of urban pores in the high openness group, mid-high openness group and mid-low openness group have a higher cooling effect, which mainly corresponds to water, open spaces or parks and urban roads. These spaces should be given more attention when developing urban design strategies. The results can provide some references for urban development.
keywords	urban pores, openness, spatial distribution, urban thermal environment, local climate zone (LCZ), SDG 11, SDG 13
series	CAADRIA
email
last changed	2022/07/22 07:34

_id	cdrf2022_223
id	cdrf2022_223
authors	Zhiyi Dou, Waishan Qiu, Wenjing Li, Dan Luo
year	2022
title	Evaluation Process of Urban Spatial Quality and Utility Trade-Off for Post-COVID Working Preferences
source	Proceedings of the 2022 DigitalFUTURES The 4st International Conference on Computational Design and Robotic Fabrication (CDRF 2022)
doi	https://doi.org/https://doi.org/10.1007/978-981-19-8637-6_19
summary	The formation of cities, and the relocation of workers to densely populated areas reflect a spatial equilibrium, in which the higher real consumption levels of urban areas are offset by lower non-monetary amenities [1]. However, as the society progress toward a post-COVID stage, the prevailing decentralized delivery systems and location-based services, the growing trend of working from home, with citizens’ shifting preference of de-appreciating densities and gathering, have not only changed the possible spatial distribution of opportunities, resources, consumption and amenities, but also transformed people’s preference regarding desirable urban spatial qualities, value of amenities, and working opportunities [2, 3]. This research presents a systematic method to evaluate the perceived trade-off between urban spatial qualities and urban utilities such as amenities, transportation, and monetary opportunities by urban residence in the post-COVID society. The outcome of the research will become a valid tool to drive and evaluate urban design strategies based on the potential self-organization of work-life patterns and social profiles in the designated neighbourhood. To evaluate the subjective perception of the urban residence, the study started with a comparative survey by asking residence to compare two randomly selected urban contexts in a data base of 398 contexts sampled across Hong Kong and state their living preference under the presumption of following scenarios: 1. working from home; 2. working in city centre offices. Core information influencing the spatial equilibrium are provided in the comparable urban context such as street views, housing price, housing space, travel time to city centre, adjacency to public transport and amenities, etc. Each context is given a preference score calculated with Microsoft TrueSkill Bayesian ranking algorithm [4] based on the comparison survey of two scenarios. The 398 contexts are further analysed via GIS and image processing, to be deconstructed into numerical values describing main features for each of the context that influence urban design strategies such as composition of spatial features, amenity allocation, adjacency to city centre and public transportations. Machine learning models are trained with the numerical values of urban features as input and two preference scores for the two working scenarios as the output. The correlation heat maps are used to identify main urban features and its p-value that influence residence’s preference under two working scenarios in post–COVID era. The same model could also be applied to inform the direction of urban design strategies to construct a sustainable community for each type of working population and validate the design strategies via predicting its competitiveness in attracting residence and developing target industries.
series	cdrf
email
last changed	2024/05/29 14:02

_id	cdrf2022_514
id	cdrf2022_514
authors	Jiaxiang Luo, Tianyi Gao, and Philip F. Yuan
year	2022
title	Fabrication of Reinforced 3D Concrete Printing Formwork
source	Proceedings of the 2022 DigitalFUTURES The 4st International Conference on Computational Design and Robotic Fabrication (CDRF 2022)
doi	https://doi.org/https://doi.org/10.1007/978-981-19-8637-6_44
summary	In recent years, the emerging 3D printing concrete technology has been proved to be an effective and intelligent strategy compared with conventional casting concrete construction. Due to the principle of additive manufacturing strategy, this concrete extrusion technique creates great opportunities for designing freeform geometries for surface decoration since this material has a promising performance of high compressive strength, low deformation, and excellent durability. However, the structure behavior is usually questioned, defined by the thickness and printing path. At the same time, the experiments for using 3D printing elements for structural and functional parts are still insufficient. Little investigation has been made into developing reinforcement strategies compatible with 3D printing concrete. In fact, conventional formwork and easy-to-install reinforcement support structures have various advantages in terms of labor costs but can hardly be reused. Thus, using 3D concrete printing as formwork for projects in different scales is an effective solution in the mass customized prefabrication era. Considering large-scale projects, the demand to provide concrete formwork with a proper reinforcement strategy for better toughness, flexibility, and strength is necessary. In this paper, we proposed different off-site reinforced 3D printing concrete strategies and evaluated them from time and material cost, deviation, and accessibility of fabrication.
series	cdrf
email
last changed	2024/05/29 14:03

_id	caadria2022_344
id	caadria2022_344
authors	Krezlik, Adrian
year	2022
title	Considering Energy, Materials and Health Factors in Architectural Design, Two Renovation Strategies for the Portuguese Building Stock
source	Jeroen van Ameijde, Nicole Gardner, Kyung Hoon Hyun, Dan Luo, Urvi Sheth (eds.), POST-CARBON - Proceedings of the 27th CAADRIA Conference, Sydney, 9-15 April 2022, pp. 619-628
doi	https://doi.org/10.52842/conf.caadria.2022.2.619
summary	According to the Intergovernmental Panel on Climate Change, the built environment has a significant share in global final energy use, greenhouse gases emission, land-system change, and biodiversity loss to list some indicators. In Europe, the biggest challenge is to regenerate existing building stock to create a positive impact on Nature. The Portuguese housing stock is old: 56% is more than 30 years old, and it has a low level of thermal comfort and energy efficiency. The first thermal regulations appeared in 1990 and therefore most of the houses need urgent renovation to meet EU decarbonization goals, and to improve energy efficiency, as well as well-being and comfort of residents. This paper presents a method that aims to verify existing solutions known from vernacular architecture as complementary to existing strategies. It employs digital simulation to verify whether they could be used for renovation, measuring their impact on human and planetary health. The paper shows that there is a wide spectrum of parameters that influence the renovation process and that it is possible to enhance building performance using vernacular knowledge.
keywords	Building Energy Modelling, Life Cycle Assessment, Occupant Health, Energy Renovation, Vernacular Mimicry, SDG 3, SDG 11, SDG 13
series	CAADRIA
email
last changed	2022/07/22 07:34

_id	caadria2022_388
id	caadria2022_388
authors	Leong, Siew Leng and Janssen, Patrick
year	2022
title	Participatory Planning: Heritage Conservation Through Co-design and Co-decision
source	Jeroen van Ameijde, Nicole Gardner, Kyung Hoon Hyun, Dan Luo, Urvi Sheth (eds.), POST-CARBON - Proceedings of the 27th CAADRIA Conference, Sydney, 9-15 April 2022, pp. 505-514
doi	https://doi.org/10.52842/conf.caadria.2022.2.505
summary	Citizen participation in urban planning and architectural design has been long discussed and experimented with since the 1960s. With existing participatory design approaches, two key challenges can be identified. First, the power of citizens to directly affect the decision-making processes is typically quite limited. Second, the use of traditional face-to-face design workshop results in low levels of participation. This paper proposes an innovative participatory design approach with a focus on co-design and co-decision. The co-design stage provides citizens with a tool that empowers them to think critically of their built environment and to initiate design development in their own city. The co-decision stage gives citizens real power in determining the future changes to their city by embedding the participatory design approach into the planning permission system. This participatory design approach is implemented through a web application that allows participants to view design proposals within the existing site context from a birds-eye views and from multiple immersive views, leading to a better understanding of the design proposal‚s scale and impact. The design proposal viewer has been demonstrated on a heritage site in Singapore, showing its potential to be used as evidence for supporting or rejecting design proposals.
keywords	Participatory Planning, Co-design and Co-decision, Citizen Power, Visualisation Method, Bird's-eye View, Immersive View, Web Application, SDG 11
series	CAADRIA
email
last changed	2022/07/22 07:34

_id	ascaad2022_022
id	ascaad2022_022
authors	Marey, Ahmed; Goubran, Sherif
year	2022
title	Low-cost Portable Wireless Electroencephalography to Detect Emotional Responses to Visual Cues: Validation and Potential Applications
source	Hybrid Spaces of the Metaverse - Architecture in the Age of the Metaverse: Opportunities and Potentials [10th ASCAAD Conference Proceedings] Debbieh (Lebanon) [Virtual Conference] 12-13 October 2022, pp. 139-154
summary	This paper validates the using a low-cost EEG headset – Emotiv Insight 2.0 – for detecting emotional responses to visual stimuli. The researchers detected, based on brainwave activity, the viewer’s emotional states in reference to a series of visuals and mapped them on valance and arousal axes. Valence in this research is defined as the viewer’s positive or negative state, and arousal is defined as the intensity of the emotion or how calm or excited the viewer is. A set of thirty images – divided into two categories: Objects and Scenes – was collected from the Open Affective Standard Image Set (OASIS) and used as a reference for validation. We collected a total of 720 data points for six different emotional states: Engagement, Excitement, Focus, Interest, Relaxation, and Stress. To validate the emotional state score generated by the EEG headset, we created a regression model using those six parameters to estimate the valence and arousal level, and compare them to values reported by OASIS. The results show the significance of the Engagement parameter in predicting the valence level in the Objects category and the significance of the Excitement parameter in the Scenes category. With the emergence of personal EEG headsets, understanding the emotional reaction in different contexts will help in various fields such as urban design, digital art, and neuromarketing. In architecture, the findings can enable designers to generate more dynamic and responsive design solutions informed by users’ emotions.
series	ASCAAD
email
last changed	2024/02/16 13:24

_id	caadria2022_177
id	caadria2022_177
authors	Pan, Yongjie and Zhang, Tong
year	2022
title	Outdoor Thermal Environment Assessment of Existing Residential Areas Supported by UAV Thermal Infrared and 3D Reconstruction Technology
source	Jeroen van Ameijde, Nicole Gardner, Kyung Hoon Hyun, Dan Luo, Urvi Sheth (eds.), POST-CARBON - Proceedings of the 27th CAADRIA Conference, Sydney, 9-15 April 2022, pp. 729-738
doi	https://doi.org/10.52842/conf.caadria.2022.2.729
summary	The underlying surface temperature is an effective evaluation index to study the urban micro-scale thermal environment. For surface temperature acquisition, the thermal infrared camera mounted on a unmanned aerial vehicle (UAV) can reduce field work intensity, improve data collection efficiency, and ensure high accuracy at low cost. In order to convert the 2D thermal image into a more intuitive 3D thermal model, the UAV-based thermal infrared 3D reconstruction is adopted. The key element of thermal infrared 3D model reconstruction lies in the processing of thermal infrared images with low resolution and different temperature scales. In order to improve the quality of the final thermal 3D model, this paper proposes the reconstruction of the detailed 3D mesh using visible images (higher resolution), and map then mapping thermal textures onto the mesh using thermal images (low resolution). In addition, absolute temperature values are extracted from thermal images with different temperature ranges to ensure consistence between color and temperature values in the reconstructed thermal 3D model. The thermal 3D model generated for an existing residential area in Nanjing successfully displays the temperature distribution of the underlying surface and provides a valuable basis for outdoor thermal environment assessment.
keywords	Thermal image, UAV, 3D reconstruction, Residential outdoor space, Underlying surface temperature, SDG 3, SDG 11
series	CAADRIA
email
last changed	2022/07/22 07:34

_id	caadria2022_85
id	caadria2022_85
authors	Reinhardt, Dagmar, Holloway, Leona, Silveira, Sue and Larkin, Nicole
year	2022
title	Tactile Oceans - Enabling Inclusive Access to Ocean Pools for Blind and Low Vision Communities
source	Jeroen van Ameijde, Nicole Gardner, Kyung Hoon Hyun, Dan Luo, Urvi Sheth (eds.), POST-CARBON - Proceedings of the 27th CAADRIA Conference, Sydney, 9-15 April 2022, pp. 709-718
doi	https://doi.org/10.52842/conf.caadria.2022.2.709
summary	This research explores implementing computation to enhance access to ocean pool and marine landscapes for the inclusion of people who are blind or have low vision (BLV). Constructing reliable representations, explanations and descriptions can support interactions with objects and participation in activities, particularly in these ocean environments. We discuss the adoption of a series of computational design strategies to leverage the impact of recent scanning technologies in information transfer. The paper introduces a background to touch access and universal design. It presents a case study of aerial photogrammetry for an ocean pool in NSW, Australia, and presents multi-scalar workflows and processes across computational design and advanced fabrication methods, including a) photogrammetry through drone-flight on a macro-scale and 3D-scanning to establish data-sets; b) parametric design and scale adaptations;†and c) 3D printing and robotic milling for touch access.
keywords	Blind, Universal Design, Touch Access, Photogrammetry, 3D Printing, SDG 3, SDG 10, SDG 14
series	CAADRIA
email
last changed	2022/07/22 07:34

_id	caadria2022_260
id	caadria2022_260
authors	Ricafort, Kim, Koch, Ethan and Makki, Mohammed
year	2022
title	Addressing Flood Resilience In Jakarta‚s Kampungs Through The Use Of Sequential Evolutionary Simulations
source	Jeroen van Ameijde, Nicole Gardner, Kyung Hoon Hyun, Dan Luo, Urvi Sheth (eds.), POST-CARBON - Proceedings of the 27th CAADRIA Conference, Sydney, 9-15 April 2022, pp. 655-664
doi	https://doi.org/10.52842/conf.caadria.2022.1.655
summary	The urban superblock of Kampung Melayu, located in Jakarta, Indonesia, is a typology amalgamated by the environmental and infrastructural challenges caused by Jakarta‚s urban sprawl. Rapid and unregulated urban growth, fluctuating tropical conditions, rising sea levels and unprecedented environmental stresses have led to a city that is sinking, leaving unregulated low-income settlements, such as Kampung Melayu, most vulnerable. To address these issues, the presented research employs the use of a multi-objective evolutionary algorithm for an in-depth analysis of the various relationships within the urban fabric. The simulations present an alternative urban approach to the design of a flood resilient Kampung; addressing environmental and demographic stresses while maintaining the irregularity that has become ingrained in the history of the urban form.
keywords	jakarta, kampung melayu, sequential simulations, evolutionary algorithm, computational design, urban growth, flood resilience, SDG 3, SDG 6, SDG 10, SDG 11, SDG 13
series	CAADRIA
email
last changed	2022/07/22 07:34

_id	caadria2022_497
id	caadria2022_497
authors	Varinlioglu, Guzden, Vaez Afshar, Sepehr, Eshaghi, Sarvin, Balaban, Ozgun and Nagakura, Takehiko
year	2022
title	GIS-Based Educational Game Through Low-Cost Virtual Tour Experience- Khan Game
source	Jeroen van Ameijde, Nicole Gardner, Kyung Hoon Hyun, Dan Luo, Urvi Sheth (eds.), POST-CARBON - Proceedings of the 27th CAADRIA Conference, Sydney, 9-15 April 2022, pp. 69-78
doi	https://doi.org/10.52842/conf.caadria.2022.1.069
summary	The pandemic brought new norms and techniques of pedagogical strategies in formal education. The synchronous/ asynchronous video streaming brought an emphasis on virtual and augmented realities, which are rapidly replacing textbooks as the main medium for learning and teaching. This transformation requires more extensive online and interactive content with simpler user interfaces. The aim of this study is to report on the design, implementation, and testing of a game based on low-cost and user-friendly content for digital cultural heritage. In this project, a game aimed at inclusive and equitable education was developed using 360 images of the targeted architectural heritage geographically distributed in a pilot site. We promote lifelong learning opportunities for all, following the SDG4, aiming for quality education with the easy-to-use online platform and easy access to immersive education through mobile platforms. Towards a post-carbon future without the need for travel, computational design methods such as using 360 videos and images in combination with virtual reality (VR) headsets allow a low-cost approach to remotely experiencing cultural heritage. We propose developing and testing a GIS-based educational game using a low-cost 360 virtual tour of architectural heritage, more specifically, caravanserais of Anatolia.0864108000
keywords	digital heritage, 360 images, educational games, caravanserais, SDG 4
series	CAADRIA
email
last changed	2022/07/22 07:34

_id	cdrf2022_326
id	cdrf2022_326
authors	Zidong Liu, Yan Li, and Xiao Xiao
year	2022
title	Predicting the Vitality of Stores Along the Street Based on Business Type Sequence via Recurrent Neural Network
source	Proceedings of the 2022 DigitalFUTURES The 4st International Conference on Computational Design and Robotic Fabrication (CDRF 2022)
doi	https://doi.org/https://doi.org/10.1007/978-981-19-8637-6_29
summary	The rational planning of store types and locations to maximize street vitality is essential in real estate planning. Traditional business planning relies heavily on the subjective experience of developers. Currently, developers have access to low-resolution urban data to support their decision making, and researchers have done much image-based machine learning research from the scale of urban texture. However, there is still a lack of research on the functional layout with shop-level accuracy. This paper uses a sequence-based neural network (RNN) to explore the relationship between the sequence of store types along a street and its commercial vitality. Currently, the use of RNNs in the architectural and urban fields is very rare. We use customer review data of 80streets from O2O platforms to represent the store vitality degree. In the machine learning model, the input is the sequence of store types on the street, and the output is the corresponding sequence of business vitality indexes. After training and evaluation, the model was shown to have acceptable accuracy. We further combined this evaluation model with a genetic algorithm to develop a business planning optimization tool to maximize the overall street business value, thus guiding real estate business planning at a high resolution.
series	cdrf
email
last changed	2024/05/29 14:03

_id	caadria2022_458
id	caadria2022_458
authors	Gong, Pixin, Huang, Xiaoran, Huang, Chenyu and White, Marcus
year	2022
title	Machine Learning-Based Walkability Modeling in Urban Life Circle
source	Jeroen van Ameijde, Nicole Gardner, Kyung Hoon Hyun, Dan Luo, Urvi Sheth (eds.), POST-CARBON - Proceedings of the 27th CAADRIA Conference, Sydney, 9-15 April 2022, pp. 645-654
doi	https://doi.org/10.52842/conf.caadria.2022.1.645
summary	With China's fast urbanization, the study of the walkability of residents' life circles has become critical to improve people's quality of life. Traditional walkability calculations are based on Lawrence Frank's theory. However, the weighted calculation method cannot be adapted to ever-changing and complicated scenarios as the scope and topic of research transforming. This study investigated walkability at the community level by combining machine learning techniques with multi-source data. Feature indicators affecting walkability were estimated from multi-source data. Machine learning was used to refine the weighting calculation under the previous indicator framework. We compared the performance of 20 regression models from 6 different machine learning algorithms for estimating the walkability of 14578 communities in downtown Shanghai. It is concluded that the Bagged Tree Model (R2=0.86, RMSE=0.36862) achieves the best performance, which is used to revise the initial walkability index values. The workflow proposed in this paper allows for rapid application of expert empirical consensus to comprehensive urban design and detailed urban governance in the future.
keywords	Life Circle, Walkability Indicator, Multi-source Data, Machine Learning, Refined Urban Design, SDG 3, SDG 10, SDG 11
series	CAADRIA
email
last changed	2022/07/22 07:34

_id	caadria2022_317
id	caadria2022_317
authors	Grugni, Francesco, Voltolina, Marco and Cattaneo, Tiziano
year	2022
title	Use of Object Recognition AI in Community and Heritage Mapping for the Drafting of Sustainable Development Strategies Suitable for Individual Communities, With Case Studies in China, Albania and Italy
source	Jeroen van Ameijde, Nicole Gardner, Kyung Hoon Hyun, Dan Luo, Urvi Sheth (eds.), POST-CARBON - Proceedings of the 27th CAADRIA Conference, Sydney, 9-15 April 2022, pp. 717-726
doi	https://doi.org/10.52842/conf.caadria.2022.1.717
summary	In order to plan effective strategies for the sustainable development of individual communities, as prescribed by the United Nations‚ Sustainable Development Goal 11, it is necessary for designers and policy makers to gain a deep awareness of the bond that connects people to their territory. AI-driven technologies, and specifically Object Recognition algorithms, are powerful tools that can be used to this end, as they make it possible to analyse huge amounts of pictures shared on social media by residents and visitors of a specific area. A model of the emotional, subjective point of view of the members of the community is thus generated, giving new insights that can support traditional techniques such as surveys and interviews. For the purposes of this research, three case studies have been considered: the neighbourhood around Siping Road in Shanghai, China; the village of Moscopole in southeastern Albania; the rural area of Oltrep Pavese in northern Italy. The results demonstrate that a conscious use of AI-driven technologies does not necessarily imply homogenisation and flattening of individual differences: on the contrary, in all three cases diversities tend to emerge, making it possible to recognise and enhance the individuality of each community and the genius loci of each place.
keywords	sustainable communities, artificial intelligence, object recognition, social media, SDG 11
series	CAADRIA
email
last changed	2022/07/22 07:34

_id	cdrf2022_175
id	cdrf2022_175
authors	Xingzhao Zhang, Xinyu Wu, Luqiao Yang, Jiaqi Xu, Ruizhe Luo, and Jiawei Yao
year	2022
title	Effect of Morphological Indicators on the Pedestrian Level Wind of the Existing Workers Villages in Shanghai
source	Proceedings of the 2022 DigitalFUTURES The 4st International Conference on Computational Design and Robotic Fabrication (CDRF 2022)
doi	https://doi.org/https://doi.org/10.1007/978-981-19-8637-6_15
summary	The workers villages are typical residential type during Shanghai’s urbanization built from the 1950s to the 1980s. Due to changes in the urban environment and climatic circumstances, the workers villages have inadequate natural ventilation and difficulty in dispersing pollutants, putting residents’ health at risk. In the context of urban renewal, it is necessary to clarify the effect of building morphological indicators on pedestrian level wind, especially in such old residential communities. In this paper, 100 workers villages representatives were gathered by GIS. Their summer ventilation conditions were simulated using the CFD solving the LES turbulence equation. The correlation between 9 morphological indicators and 2 pedestrian level wind indicators was obtained quantitatively by Pearson analysis and regression analysis. The result shows increasing the building coverage of 0.94% in the workers villages, the ratio of the area of the static wind in summer will increase subsequently by 10%. The results highlight the importance of considering morphological indicators to enhance the wind environment, and provide suggestions for the environmental transformation of communities with similar characteristic in the high-density city.
series	cdrf
email
last changed	2024/05/29 14:02

_id	cdrf2022_150
id	cdrf2022_150
authors	Ana Zimbarg
year	2022
title	Mapping Plant Microclimates on Building Envelope Using Environmental Analysis Tools
source	Proceedings of the 2022 DigitalFUTURES The 4st International Conference on Computational Design and Robotic Fabrication (CDRF 2022)
doi	https://doi.org/https://doi.org/10.1007/978-981-19-8637-6_13
summary	Can we build our cities not only for humans but also for all living systems? How can we consider other species occupants of the built environment? Planning cities as an element of the natural domain can reshape our relationship with nature and help redefine sustainability in architecture. Although current design strategies of reducing energy use does not rectify past/continuing im-balances in the natural environment. Landscape architect John Tillman Lyle expanded the regenerative design concept based on a range of ecological concepts. The environment's complexity, and the urge to use resources smartly, encouraged him to think about architecture and the environment as a whole system. John Lyle's regenerative design strategies scaffold a conceptual framework of treating the building as part of the landscape. Environmental tools such as Ladybug can map out the different conditions surrounding the building's envelope. This information can assist in selecting and populating a building façade with suitable plant species. The framework presents the building as a feature in the landscape, creating microclimatic conditions for various plant habitats. This conceptual workflow has the potential to become a tool to include regenerative principles in the urban context.
series	cdrf
email
last changed	2024/05/29 14:02

_id	caadria2022_336
id	caadria2022_336
authors	Araujo, Goncalo, Santos, Luis, Leitao, Antonioand Gomes, Ricardo
year	2022
title	AD-Based Surrogate Models for Simulation and Optimization of Large Urban Areas
source	Jeroen van Ameijde, Nicole Gardner, Kyung Hoon Hyun, Dan Luo, Urvi Sheth (eds.), POST-CARBON - Proceedings of the 27th CAADRIA Conference, Sydney, 9-15 April 2022, pp. 689-698
doi	https://doi.org/10.52842/conf.caadria.2022.2.689
summary	Urban Building Energy Model (UBEM) approaches help analyze the energy performance of urban areas and predict the impact of different retrofit strategies. However, UBEM approaches require a high level of expertise and entail time-consuming simulations. These limitations hinder their successful application in designing and planning urban areas and supporting the city policy-making sector. Hence, it is necessary to investigate alternatives that are easy-to-use, automated, and fast. Surrogate models have been recently used to address UBEM limitations; however, they are case-specific and only work properly within specific parameter boundaries. We propose a new surrogate modeling approach to predict the energy performance of urban areas by integrating Algorithmic Design, UBEM, and Machine Learning. Our approach can automatically model and simulate thousands of building archetypes and create a broad surrogate model capable of quickly predicting annual energy profiles of large urban areas. We evaluated our approach by applying it to a case study located in Lisbon, Portugal, where we compare its use in model-based optimization routines against conventional UBEM approaches. Results show that our approach delivers predictions with acceptable accuracy at a much faster rate.
keywords	urban building energy modelling, algorithmic design, machine learning in Architecture, optimization of urban areas, SDG 7, SDG 12, SDG 13
series	CAADRIA
email
last changed	2022/07/22 07:34

_id	caadria2022_59
id	caadria2022_59
authors	Banihashemi, Farzan, Reitberger, Roland and Lang, Werner
year	2022
title	Investigating Urban Heat Island and Vegetation Effects Under the Influence of Climate Change in Early Design Stages
source	Jeroen van Ameijde, Nicole Gardner, Kyung Hoon Hyun, Dan Luo, Urvi Sheth (eds.), POST-CARBON - Proceedings of the 27th CAADRIA Conference, Sydney, 9-15 April 2022, pp. 679-688
doi	https://doi.org/10.52842/conf.caadria.2022.2.679
summary	Different criteria need to be considered for optimal strategies in the early design stages of urban developments. Under the influence of climate change, the urban heat island effect (UHI) is a phenomenon that gains importance in the early design stages. Here, different parameters, for instance, vegetation ratio in the city district and building density, play a significant role in the UHI effect. These parameters need to be quantified through different simulation tools for optimal climate adaptation and mitigation measures on the urban district scale. However, not all parameters and their influence are clear to the decision-makers and actors in the early design stages. Hence, we propose a Monte Carlo based sensitivity analysis (SA) and uncertainty analysis (UA) to show the significance of different parameters and quantify them. The SA aims to identify the major influencing parameters, whereas the UA quantifies the effect on the energy performance and indoor thermal comfort of occupants. The workflow is integrated into a collaborative design platform and applied in a case study to support decision-makers in the early design stages for new developments, densification, or refurbishment scenarios.
keywords	Monte Carlo Simulation, Sensitivity Analysis, Uncertainty Analysis, Building Energy Simulation, SDG 13, SDG 11
series	CAADRIA
email
last changed	2022/07/22 07:34

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