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	sigradi2022_52
id	sigradi2022_52
authors	Frutuôso, Joyce; Pereira, Liryan; Verniz, Debora; Pontes, Thiago; Santos, Deborah
year	2022
title	JOI - Personal equipment to manipulate knobs without direct hands contact
source	Herrera, PC, Dreifuss-Serrano, C, Gómez, P, Arris-Calderon, LF, Critical Appropriations - Proceedings of the XXVI Conference of the Iberoamerican Society of Digital Graphics (SIGraDi 2022), Universidad Peruana de Ciencias Aplicadas, Lima, 7-11 November 2022 , pp. 983–992
summary	The contagious COVID-19 pandemic made it necessary to adopt strategies to avoid contamination. COVID-19 spreads when someone is in direct contact with small droplets and particles that contain the virus. These droplets and particles can be active on surfaces that are shared by many people, so hand sanitation became an important aspect to prevent virus contamination. However, products for hand sanitation may not be available easily everywhere. Moreover, the excessive use of products like hand sanitizers and hand soaps can cause dryness and dermatitis on certain users. This paper describes the rapid prototyping of JOI, a device for users to avoid touching doorknobs, door bolts, switchers, and call buttons. The device was 3D printed (more than 400 units) and distributed to an academic community, which then answered a usability survey. Results show that the device is efficient to avoid the direct contact of users and surfaces that may be contaminated.
keywords	COVID-19, Digital Fabrication, 3D Print, Personal Protective Equipment, Good Health and Well-Being
series	SIGraDi
email
last changed	2023/05/16 16:57

_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_74
id	caadria2022_74
authors	Mazza, Domenico, Kocaturk, Tuba and Kaljevic, Sofija
year	2022
title	Geelong Digital Outdoor Museum (GDOM) - Photogrammetry as the Surface for a Portable Museum
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. 677-686
doi	https://doi.org/10.52842/conf.caadria.2022.1.677
summary	This paper presents the development and evaluation of the Geelong Digital Outdoor Museum (GDOM) prototype accessible at https://gdom.mindlab.cloud. GDOM is a portable museum‚our novel adaptation of the distributed museum model (Stuedahl & Lowe, 2013) which uses mobile devices to present museum collections attached to physical sites. Our prototype defines a way for intangible heritage associated with tangible landscapes to be accessible via personal digital devices using 360 3D scanned digital replicas of physical landscapes (photogrammetric digital models). Our work aligns with efforts set out in the UN Sustainable Development Goal 11 (SDG 11) to safeguard cultural and natural heritage, by openly disseminating the heritage of physical sites seamlessly through the landscape. Using a research by design methodology we delivered our prototype as a modular web-based platform that leveraged the Matterport digital model platform. We qualitatively evaluated the prototype's usability and future development opportunities with 32 front-end users and 13 potential stakeholders. We received a wide gamut of responses that included: users feeling empowered by the greater accessibility, users finding a welcome common ground with comparable physical experiences, and users and potential stakeholders seeing the potential to re-create physical world experiences with modifications to the digital model along with on-site activation. Our potential stakeholders suggested ways in which GDOM could be integrated into the arts, education, and tourism to widen its utility and applicability. In future we see design potential in breaking out of the static presentation of the digital model and expanding our portable museum experience to work on-site as a complement to the remote experience. However, we recognise the way in which on-site activation integrate into users' typical activities can be tangential (McGookin et al., 2019) and this would necessitate further investigation into how to best integrate the experience on-site.
keywords	Cultural Heritage, Intangible Heritage, Digital Heritage, Web Platform, 3D Scanning, Photogrammetry, Digital model, Portable Museum, Distributed Museum, SDG 11
series	CAADRIA
email
last changed	2022/07/22 07:34

_id	ascaad2022_068
id	ascaad2022_068
authors	Moustafa, Mohab; Ashour, Shaimaa; Bakir, Ramy
year	2022
title	Augmenting Landmarks: Extending "Places" in the Hybrid City
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. 731-742
summary	Several recent technological advancements are substantially altering how we interact with urban spaces. The existing physical space as we know it now encompasses a plethora of emerging realities into which we shift in and out, resulting in what is called Hybrid Spaces. Augmented Reality (AR) today gives way to forms of hybrid realities that are accessible through our handheld devices, and which allow us to engage with our physical reality in a new way. These devices allow us to access and view digital information that is saturating our urban spaces, and yet appear invisible to the naked eye. When this information is localized, it can be used to augment physical space with virtual overlays. These augmentations may become physically linked to the environment, establishing virtual landmarks that could only be accessed via these handheld or wearable digital portals through digital applications. This gives way to new forms of engaging in real-time with our socio-cultural daily activities. The literature shows that urban space is reimagined through augmented reality (AR) which plays a significant role in introducing new augmented “places” supporting our physical ones as hybrid realities. This paper, accordingly, investigates the notion of location-based AR experiences on landmarks in the urban space in accordance with our spatial memory, and how augmented reality through mobile devices, plays an important role as a gateway between our physical space and the virtual one. It also seeks to understand how these augmentations might insert and employ symbolic or personal meanings to the space, based on our different interpretations. In doing so, we conducted an integrative analytical review of the most recent literature, to study the forms of augmentations in multiple cities, and how they are used as agents in our spatial experience. The paper then introduced a framework that could be used to assess users’ satisfaction and the design considerations of the AR spatial experience. Finally, the paper adopts a few recent AR practices to be assessed by the proposed framework.
series	ASCAAD
email
last changed	2024/02/16 13:29

_id	ecaade2022_001
id	ecaade2022_001
authors	Pak, Burak, Wurzer, Gabriel and Stouffs, Rudi
year	2022
title	eCAADe 2022 Co-creating the Future: Inclusion in and through Design- Volume 2
source	Pak, B, Wurzer, G and Stouffs, R (eds.), Co-creating the Future: Inclusion in and through Design - Proceedings of the 40th Conference on Education and Research in Computer Aided Architectural Design in Europe (eCAADe 2022) - Volume 2, Ghent, 13-16 September 2022, 646 p.
doi	https://doi.org/10.52842/conf.ecaade.2022.2
summary	Spatial design is becoming an increasingly social, participatory and inclusive practice. In the last decade, ordinary people all around the world have started to claim a shaping power over the processes of urbanization; over the ways in which our cities are made and remade (Harvey, 2013). There has been a resurgence in the number of do-it-yourself cooperatives initiated by non-designer citizens, activists, artists and designers. In parallel to these developments, a plethora of social technologies, tools and platforms have been developed to include a variety of stakeholders in the architectural design, urban design, planning and decision-making processes. Crowdsourcing and crowdfunding applications started to be widely used to tap into the wisdom of the crowd. Novel developments in parametric design and digital fabrication created possibilities for user participation in the making of customized and highly diversified products. With the combination of artificial intelligence and the Internet of Things, smart buildings, autonomous devices, robots and software started to transform into agents and active participants. The attempts to harness collective human and artificial intelligence opened up new avenues for combining practice, research and education. On the other hand, there is a growing concern over the possible negative impact of the digital devices, tools, platforms and agents integrated in the making of our buildings and cities, public, private and collective spaces. Examples of those are the potential exclusion of vulnerable and disadvantaged citizens, transfer of citizen power to the corporations, privatization of personal life and data, as well as spatial exclusion through increased technological control and surveillance.
keywords	Proceedings, Front Matter
series	eCAADe
email
last changed	2024/04/22 07:10

_id	ecaade2022_000
id	ecaade2022_000
authors	Pak, Burak, Wurzer, Gabriel and Stouffs, Rudi
year	2022
title	eCAADe 2022 Co-creating the Future: Inclusion in and through Design - Volume 1
source	Pak, B, Wurzer, G and Stouffs, R (eds.), Co-creating the Future: Inclusion in and through Design - Proceedings of the 40th Conference on Education and Research in Computer Aided Architectural Design in Europe (eCAADe 2022) - Volume 1, Ghent, 13-16 September 2022, 672 p.
doi	https://doi.org/10.52842/conf.ecaade.2022.1
summary	Spatial design is becoming an increasingly social, participatory and inclusive practice. In the last decade, ordinary people all around the world have started to claim a shaping power over the processes of urbanization; over the ways in which our cities are made and remade (Harvey, 2013). There has been a resurgence in the number of do-it-yourself cooperatives initiated by non-designer citizens, activists, artists and designers. In parallel to these developments, a plethora of social technologies, tools and platforms have been developed to include a variety of stakeholders in the architectural design, urban design, planning and decision-making processes. Crowdsourcing and crowdfunding applications started to be widely used to tap into the wisdom of the crowd. Novel developments in parametric design and digital fabrication created possibilities for user participation in the making of customized and highly diversified products. With the combination of artificial intelligence and the Internet of Things, smart buildings, autonomous devices, robots and software started to transform into agents and active participants. The attempts to harness collective human and artificial intelligence opened up new avenues for combining practice, research and education. On the other hand, there is a growing concern over the possible negative impact of the digital devices, tools, platforms and agents integrated in the making of our buildings and cities, public, private and collective spaces. Examples of those are the potential exclusion of vulnerable and disadvantaged citizens, transfer of citizen power to the corporations, privatization of personal life and data, as well as spatial exclusion through increased technological control and surveillance.
series	eCAADe
email
last changed	2024/04/22 07:10

_id	caadria2022_90
id	caadria2022_90
authors	Veloso, Pedro, Rhee, Jinmo, Bidgoli, Ardavan and Ladron de Guevara, Manuel
year	2022
title	Bubble2Floor: A Pedagogical Experience With Deep Learning for Floor Plan Generation
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. 373-382
doi	https://doi.org/10.52842/conf.caadria.2022.1.373
summary	This paper reports a pedagogical experience that incorporates deep learning to design in the context of a recently created course at the Carnegie Mellon University School of Architecture. It analyses an exercise called Bubble2Floor (B2F), where students design floor plans for a multi-story row-house complex. The pipeline for B2F includes a parametric workflow to synthesise an image dataset with pairs of apartment floor plans and corresponding bubble diagrams, a modified Pix2Pix model that maps bubble diagrams to floor plan diagrams, and a computer vision workflow to translate images to the geometric model. In this pedagogical research, we provide a series of observations on challenges faced by students and how they customised different elements of B2F, to address their personal preferences and problem constraints of the housing complex as well as the obstacles from the computational workflow. Based on these observations, we conclude by emphasising the importance of training architects to be active agents in the creation of deep learning workflows and make them accessible for socially relevant and constrained design problems, such as housing.
keywords	Architectural Pedagogy, Deep Learning, Conditional GAN, Space Planning, Floor Plan, SDG 4, SDG 9
series	CAADRIA
email
last changed	2022/07/22 07:34

_id	caadria2022_167
id	caadria2022_167
authors	Aman, Jayedi, Matisziw, Timothy C, Kim, Jong Bum and Luo, Dan
year	2022
title	Sensing the City: Leveraging Geotagged Social Media Posts and Street View Imagery to Model Urban Streetscapes Using Deep Neural Networks
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. 595-604
doi	https://doi.org/10.52842/conf.caadria.2022.1.595
summary	Understanding the relationships between individuals and the urban streetscape is an essential component of sustainable city planning. However, analysis of these relationships involves accounting for a complex mix of human behaviour, perception, as well as geospatial context. In this context, a comprehensive framework for predicting preferred streetscape characteristics utilizing deep learning and geospatial techniques is proposed. Geotagged social media posts and street view imagery are employed to account for individual sentiment and geospatial context. Natural Language Processing (NLP) and computer vision (CV) are then used to infer sentiment and model the visual environment within which individuals make posts to social media. An application of the developed framework is provided using Instagram posts and Google Street View imagery of the urban environment. A spatial analysis is conducted to assess the extent to which urban attributes correlate with the sentiment of social media postings. The results shed light on sustainable streetscape planning by focusing on the relationship between users and the built environment in a complex urban setting. Finally, limitations of the developed methodology as well as future directions are discussed.
keywords	Urban sustainability, data mining, pedestrian sentiments, transportation behavior, street level imagery, transformers, SDG 11
series	CAADRIA
email
last changed	2022/07/22 07:34

_id	caadria2022_47
id	caadria2022_47
authors	An, Yudi
year	2022
title	Impact of Covid-19 on Associations between Land Use and Bike-Sharing Usage
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. 605-614
doi	https://doi.org/10.52842/conf.caadria.2022.1.605
summary	Bike-sharing as a human-centred, zero-emission, sustainable, alternative, and easily accessible transport mode has been implemented globally and consistently contributing to communities and the environment by alleviating consumption of natural sources, traffic congestion, and air pollution, which is considered a solution for future cities. The appearance of Covid-19 significantly impacts public transportation modes, including the bike-sharing system. The intention of this study was to investigate the spatiotemporal impact of the Covid-19 pandemic on associations between urban factors and bike-sharing usage in Los Angeles, United States, by analysing a sizeable actual trip dataset and employing geographically weighted regression (GWR) models. GWR was conducted for examining the varying spatial association between bike infrastructure, public transport, and urban land use factors, and bike-sharing trip volume. The results indicated that bike-sharing usage significantly decreased during the pandemic and essential service as restaurant was found consistently and positively associated with bike-sharing use. GWR provided clear spatial patterns of bike usage based on urban land use and big user databases. The outcomes of this study could inspire policymakers and shared mobility operators to support these safe, sustainable transport alters (such as rebalancing bike stations), help city resilience, and shape a sustainable future of mobility in the post-Covid-19 era.
keywords	Bike-Sharing, Covid-19, Land Use, Geographically Weighted Regression, Big Data, SDG 11
series	CAADRIA
email
last changed	2022/07/22 07:34

_id	caadria2022_325
id	caadria2022_325
authors	Cui, Qinyu, Zhang, Shuyu and Huang, Yiting
year	2022
title	Retail Commercial Space Clustering Based on Post-carbon Era Context: A Case Study of Shanghai
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. 515-524
doi	https://doi.org/10.52842/conf.caadria.2022.1.515
summary	In the post-carbon era, it has become a development and research trend on adjusting commercial locations to help achieve resource conservation by using big data. This paper uses multi-source urban data and machine learning to make reasonable evaluations and adjustments to commercial district planning. Many relevant factors are affecting urban commercial agglomeration, but how to select the appropriate ones among the many factors is a problem to be considered and studied, while there may be spatial differences in the strength of each influencing factor on commercial agglomeration. Therefore, this paper takes Shanghai, a city with a high economic and commercial development level in China, as an example and identifies the influencing factors through a literature review. Next, this paper uses the machine learning BORUTA algorithm of features selection to screen the influencing factors. It then uses multi-scale geographically weighted regression model (MGWR) to analyse the spatial heterogeneity of factors affecting retail spatial agglomeration. Finally, based on the background of the changing transportation modes and the unchanged social activities in the post-carbon era, the future spatial planning pattern of retail commercial space is discussed to provide particular suggestions for the future location adjustment of urban commerce.
keywords	Business District Hierarchy, Agglomeration Effect, Spatial Variability, Multi-scale Geographically Weighted Regression Model, Machine Learning, Big Data Analysis, SDG 8, SDG 12
series	CAADRIA
email
last changed	2022/07/22 07:34

_id	caadria2022_93
id	caadria2022_93
authors	Feng, Jiajia, Liang, Yuebing, Hao, Qi, Xu, Ke and Qiu, Waishan
year	2022
title	POI Data Versus Land Use Data, Which Are Most Effective in Modelling Theft Crimes?
source	Jeroen van Ameijde, Nicole Gardner, Kyung Hoon Hyun, Dan Luo, Urvi Sheth (eds.), POST-CARBON - Proceedings of the 27th CAADRIA Conference, Sydney, 9-15 April 2022, pp. 425-434
doi	https://doi.org/10.52842/conf.caadria.2022.1.425
summary	Alleviating crime and improving urban safety is important for sustainable development of society. Prior studies have used either land use data or point-of-interests (POI) data to represent urban functions and investigate their associations with urban crime. However, inconsistent and even contrary results were yielded between land use and POI data. There is no agreement on which is more effective. To fill this gap, we systematically compare land use and POI data regarding their strength as well as the divergence and coherence in profiling urban functions for crime studies. Three categories of urban function features, namely the density, fraction, and diversity, are extracted from POI and land use data, respectively. Their global and local strength are compared using ordinary least square (OLS) regression and geographically weighted regression (GWR), with a case study of Beijing, China. The OLS results indicate that POI data generally outperforms land use data. The GWR models reveal that POI Density is superior to other indicators, especially in areas with concentrated commercial or public service facilities. Additionally, Land Use Fraction performs better for large-scale functional areas like green space and transportation hubs. This study provides important reference for city planners in selecting urban function indicators and modelling crimes.
keywords	POI, Land Use, Urban Functions, Theft crime, Predictive Power, SDG 16
series	CAADRIA
email
last changed	2022/07/22 07:34

_id	caadria2022_456
id	caadria2022_456
authors	Gong, Pixin, Huang, Xiaoran, Huang, Chenyu and White, Marcus
year	2022
title	Quantifing the Imbalance of Spatial Distribution of Elderly Service with Muti-source Data
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. 455-464
doi	https://doi.org/10.52842/conf.caadria.2022.1.455
summary	With the growing challenge of aging populations around the world, the study of the elderly service is an essential initiative to accommodate the particular needs of the disadvantaged communities and promote social equity. Previous research frameworks are very case-specific with limited evaluation indicators that cannot be extended to other scenarios and fields. Based on multi-source data and Geographic Information System (GIS), this paper quantifies and visualises the imbalance in the spatial distribution of elderly services in 218 neighbourhoods in Shijingshan District, Beijing, China. Mortality data were obtained, and the most contributing indicators to mortality were investigated by correlation analysis. Finally, mapping between other facility indicators to mortality rates was constructed using machine learning to further investigate the factors influencing the quality of elderly services at the community level. The conclusion shows that the functional density of transportation facilities, medical facilities, living services facilities, and the accessibility of elderly care facilities are most negatively correlated with mortality. The correlation conclusion is combined with a machine learning prediction model to provide future recommendations for the construction of unbalanced elderly neighbourhoods. This research offers a novel systematic method to study urban access to elderly services as well as a new perspective on improving social fairness.
keywords	elderly service facilities, multi-source data, machine learning, SDG 3, SDG 10, SDG 11
series	CAADRIA
email
last changed	2022/07/22 07:34

_id	caadria2022_195
id	caadria2022_195
authors	Li, Shuyang, Sun, Chengyu and Lin, Yinshan
year	2022
title	A Method of VR Enhanced POE for Wayfinding Efficiency in Mega Terminals of Airport
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. 79-88
doi	https://doi.org/10.52842/conf.caadria.2022.1.079
summary	The airport is one of the most essential infrastructures of cities. An important issue of the airport design is that passengers must be able to find their way efficiently. Although the designers adopt the post-evaluation after the operation, it takes a long time to conduct the on-site wayfinding experiment, and the number of participants of the experiment is also limited. Moreover, conventional post-occupancy evaluation suffers from security control and quarantine inspection that can not be carried out in the field. We proposed a VR enhanced POE approach that carries out an online wayfinding experiment to obtain numerous and detailed data, which significantly improves the efficiency of the post-occupancy evaluation project, and is validated by an affordable small-scale on-site experiment. Meanwhile, the cause for low wayfinding efficiencies, such as the symmetric space, the ambiguous direction and the redundant information on signboards are found and corresponding optimization suggestions are presented. The following signage system optimization project conducted in the terminal is welcomed by the passengers according to monthly questionnaires.
keywords	Transportation Building, Post-Occupancy Evaluation, Digital Twins, Signage System Design, Wayfinding, Virtual Reality, Eye-Tracking, SDG 9.
series	CAADRIA
email
last changed	2022/07/22 07:34

_id	architectural_intelligence2022_3
id	architectural_intelligence2022_3
authors	Mario Carpo
year	2022
title	Design and automation at the end of modernity: the teachings of the pandemic
source	Architectural Intelligence Journal
doi	https://doi.org/https://doi.org/10.1007/s44223-022-00001-0
summary	Many in the design community have long claimed that digital mass-customization is cheaper, faster, smarter and more environmentally sustainable than the mechanical mass-production of standardized industrial products; and that the electronic transmission of information is cheaper, faster, smarter, and more environmentally sustainable than the mechanical transportation of people and goods. The global pandemic has tragically proven that a computational alternative to the modern, mechanical way of making, working, and living, now exists, and it is viable. When we had to shut down corporate offices, global megafactories, suburban shopping malls, and intercontinental airports, we did. We did because we had to; but also because today's technology already allows us to do so.
series	Architectural Intelligence
email
last changed	2025/01/09 15:00

_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

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