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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	sigradi2020_52
id	sigradi2020_52
authors	Hadi, Khatereh; Gomez, Paula; Swarts, Matthew; Marshall, Tyrone; Bernal, Marcelo
year	2020
title	Healthcare Design Metrics for Human-Centric Building Analytics
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. 52-59
summary	Healthcare design practice has shown increasing interest in the assessment of design alternatives from a human-centered approach, focusing on organizational performance, patient health, and wellness outcomes, in addition to building performance. The goal of this research is to advance building analytics by identifying, defining and implementing computational human-centered design metrics. The knowledge is extracted from an exhaustive literature review in the field of evidence-based design (EBD), which has studied the associations between building features and the occupants’ outcomes but has not yet consolidated the findings into metrics and implications for design practice in a systematic manner. In consultation with industry experts, we have prioritized the evaluation aspects and developed a weighted evaluation framework for assessment of various design options. The developed metrics that input building parameters and output potential health and performance outcomes are implemented in a a parametric environment utilizing add-ons accordingly, and using an ambulatory clinic designed by Perkins&Will as a case study.
keywords	Building analytics, Healthcare design, Design metrics, Human-centered analytics
series	SIGraDi
email
last changed	2021/07/16 11:48

_id	sigradi2020_991
id	sigradi2020_991
authors	Gomez, Paula; Hadi, Khatereh; Kemenova, Olga; Swarts, Matthew
year	2020
title	Spatiotemporal Modeling of COVID-19 Spread in Built Environments
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. 991-996
summary	This research proposes a Spatiotemporal Modeling approach to understand the role of architecture, specifically the built environment, in the COVID-19 pandemic. The model integrates spatial and temporal parameters to calculate the probability of spread of and exposure to SARS-CoV-2 virus (responsible of COVID-19 disease) due to the combination of four aspects: Spatial configuration, organizational schedules, people’s behavior, and virus characteristics. Spatiotemporal Modeling builds upon the current models of building analytics for architecture combined with predictive models of COVID-19 spread. While most of the current research on COVID-19 spread focuses on mathematical models at regional scales and the CDC guidelines emphasizing on human behavior, our research focuses on the role of buildings in this pandemic, as the intermediate mechanism where human and social activities occur. The goal is to understand the most significant parameters that influence the virus spread within built environments, including human-to-human, fomite (surface-to-human), and airborne ways of transmission, with the purpose of providing a comprehensive parametric model that may help identify the most influential design and organizational decisions for controlling the pandemic. The proof-of-concept study is a healthcare facility.
keywords	Spatiotemporal modeling, Agent-based simulation, COVID-19, Virus spread, Built environments, Human behavior, Social distancing
series	SIGraDi
email
last changed	2021/07/16 11:53

_id	sigradi2020_586
id	sigradi2020_586
authors	Perelli Soto, Bruno; Soza Ruiz, Pedro; Tapia Zarricueta, Ricardo
year	2020
title	Towards the development of Smart Buildings: A Lowcost IoT Healthcare Management Proposal in Times of a World Pandemic
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. 586-593
summary	This research addresses the impact that technologies, particularly the Internet of Things, have when facing - directly or indirectly - the current panorama of a pandemic due to COVID-19. First, we review the literature and propose a context that allows for efficient clarification regarding two concerns: where should we insert this project? What are the implications and scope of such a decision? Secondly, we present experiences of implementation of IoT prototypes, which – in context - consider the education of the population of an apartment building, the mitigation and detection of COVID-19 symptoms, and the ability to obtain data from these experiences.
keywords	COVID-19, IoT, Design, Smart buildings, Lockdown
series	SIGraDi
email
last changed	2021/07/16 11:52

_id	caadria2020_443
id	caadria2020_443
authors	Abuzuraiq, Ahmed M. and Erhan, Halil
year	2020
title	The Many Faces of Similarity - A Visual Analytics Approach for Design Space Simplification
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. 485-494
doi	https://doi.org/10.52842/conf.caadria.2020.1.485
summary	Generative design methods may involve a complex design space with an overwhelming number of alternatives with their form and design performance data. Existing research addresses this complexity by introducing various techniques for simplification through clustering and dimensionality reduction. In this study, we further analyze the relevant literature on design space simplification and exploration to identify their potentials and gaps. We find that the potentials include: alleviating the choice overload problem, opening up new venues for interrelating design forms and data, creating visual overviews of the design space and introducing ways of creating form-driven queries. Building on that, we present the first prototype of a design analytics dashboard that combines coordinated and interactive visualizations of design forms and performance data along with the result of simplifying the design space through hierarchical clustering.
keywords	Visual Analytics; Design Exploration; Dimensionality Reduction; Clustering; Similarity-based Exploration
series	CAADRIA
email
last changed	2022/06/07 07:54

_id	ecaade2020_499
id	ecaade2020_499
authors	Ashour, Ziad and Yan, Wei
year	2020
title	BIM-Powered Augmented Reality for Advancing Human-Building Interaction
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. 169-178
doi	https://doi.org/10.52842/conf.ecaade.2020.1.169
summary	The shift from computer-aided design (CAD) to building information modeling (BIM) has made the adoption of augmented reality (AR) promising in the field of architecture, engineering and construction. Despite the potential of AR in this field, the industry and professionals have still not fully adopted it due to registration and tracking limitations and visual occlusions in dynamic environments. We propose our first prototype (BIMxAR), which utilizes existing buildings' semantically rich BIM models and contextually aligns geometrical and non-geometrical information with the physical buildings. The proposed prototype aims to solve registration and tracking issues in dynamic environments by utilizing tracking and motion sensors already available in many mobile phones and tablets. The experiment results indicate that the system can support BIM and physical building registration in outdoor and part of indoor environments, but cannot maintain accurate alignment indoor when relying only on a device's motion sensors. Therefore, additional computer vision and AI (deep learning) functions need to be integrated into the system to enhance AR model registration in the future.
keywords	Augmented Reality; BIM; BIM-enabled AR; GPS; Human-Building Interactions; Education
series	eCAADe
email
last changed	2022/06/07 07:54

_id	acadia20_350
id	acadia20_350
authors	Atanasova, Lidia; Mitterberger, Daniela; Sandy, Timothy; Gramazio, Fabio; Kohler, Matthias; Dörfler, Kathrin
year	2020
title	Prototype As Artefact
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. 350-359.
doi	https://doi.org/10.52842/conf.acadia.2020.1.350
summary	In digital design-to-fabrication workflows in architecture, in which digitally controlled machines perform complex fabrication tasks, all design decisions are typically made before production. In such processes, the formal definition of the final shape is explicitly inscribed into the design model by means of corresponding step-by-step machine instructions. The increasing use of augmented reality (AR) technologies for digital fabrication workflows, in which people are instructed to carry out complex fabrication tasks via AR interfaces, creates an opportunity to question and adjust the level of detail and the nature of such explicit formal definitions. People’s cognitive abilities could be leveraged to integrate explicit machine intelligence with implicit human knowledge and creativity, and thus to open up digital fabrication to intuitive and spontaneous design decisions during the building process. To address this question, this paper introduces open-ended Prototype-as-Artefact fabrication workflows that examine the possibilities of designing and creative choices while building in a human-robot collaborative setting. It describes the collaborative assembly of a complex timber structure with alternating building actions by two people and a collaborative robot, interfacing via a mobile device with object tracking and AR visualization functions. The spatial timber assembly being constructed follows a predefined grammar but is not planned at the beginning of the process; it is instead designed during fabrication. Prototype-as-Artefact thus serves as a case study to probe the potential of both intuitive and rational aspects of building and to create new collaborative work processes between humans and machines.
series	ACADIA
type	paper
email
last changed	2023/10/22 12:06

_id	ecaade2022_16
id	ecaade2022_16
authors	Bailey, Grayson, Kammler, Olaf, Weiser, Rene, Fuchkina, Ekaterina and Schneider, Sven
year	2022
title	Performing Immersive Virtual Environment User Studies with VREVAL
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, pp. 437–446
doi	https://doi.org/10.52842/conf.ecaade.2022.2.437
summary	The new construction that is projected to take place between 2020 and 2040 plays a critical role in embodied carbon emissions. The change in material selection is inversely proportional to the budget as the project progresses. Given the fact that early-stage design processes often do not include environmental performance metrics, there is an opportunity to investigate a toolset that enables early-stage design processes to integrate this type of analysis into the preferred workflow of concept designers. The value here is that early-stage environmental feedback can inform the crucial decisions that are made in the beginning, giving a greater chance for a building with better environmental performance in terms of its life cycle. This paper presents the development of a tool called LearnCarbon, as a plugin of Rhino3d, used to educate architects and engineers in the early stages about the environmental impact of their design. It facilitates two neural networks trained with the Embodied Carbon Benchmark Study by Carbon Leadership Forum, which learns the relationship between building geometry, typology, and construction type with the Global Warming potential (GWP) in tons of C02 equivalent (tCO2e). The first one, a regression model, can predict the GWP based on the massing model of a building, along with information about typology and location. The second one, a classification model, predicts the construction type given a massing model and target GWP. LearnCarbon can help improve the building life cycle impact significantly through early predictions of the structure’s material and can be used as a tool for facilitating sustainable discussions between the architect and the client.
keywords	Pre-Occupancy Evaluation, Immersive Virtual Environment, Wayfinding, User Centered Design, Architectural Study Design
series	eCAADe
email
last changed	2024/04/22 07:10

_id	sigradi2020_260
id	sigradi2020_260
authors	Bhattacharya, Maharshi; Jung, Francisco
year	2020
title	Multi-Mission Space Exploration Vehicle (MMSEV) Nosecone Design Optimization
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. 260-266
summary	This paper addresses ergonomic drawbacks in NASA’s modular Multi-Mission Space Exploration Vehicle’s (MMSEV) latest prototype, 2B’s nosecone, to propose new iteration based on considerations such as mass minimization, visibility maximization, and structural integrity. With 2B as a benchmark, and using computational tools typically used in the AEC industry to carry out FEA analysis, comparisons are made with potential design changes. The numerical and visual data such as weight, and stress distribution, provided by the benchmark analysis, served as metrics for comparison and redesign. In turn, this design development exercise attempts to bring together the different design approaches to design, held by human- factors designers and structural engineers.
keywords	Form, Optimization, Finite Element Analysis, Space-Exploration Vehicle, Stress-Analysis
series	SIGraDi
email
last changed	2021/07/16 11:49

_id	caadria2020_012
id	caadria2020_012
authors	Chatzi, Anna-Maria and Wesseler, Lisa-Marie
year	2020
title	OGOS+ - A Tool to Visualize Densification potential
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. 773-782
doi	https://doi.org/10.52842/conf.caadria.2020.1.773
summary	OGOS+ is a GIS data-based tool, which would offer urban planners, architects, and researchers visualisations of potential building mass in the form of 3D models. It compares the height of existing buildings to the maximum permitted height by German zoning law and calculates the potential building mass. To ensure minimum building footprints it only calculates the densification potential on top of existing buildings. It summarises information of the building potential for future utilisation. The goal is an increase of urban density achieved with micro interventions.
keywords	Urban densification; City Information Modeling and GIS; Big Data and Analytics in Architecture
series	CAADRIA
email
last changed	2022/06/07 07:55

_id	caadria2020_423
id	caadria2020_423
authors	Erhan, Halil, Zarei, Maryam, Abuzuraiq, Ahmed M., Haas, Alyssa, Alsalman, Osama and Woodbury, Robert
year	2020
title	FlowUI: Combining Directly-Interactive Design Modeling with Design Analytics
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. 475-484
doi	https://doi.org/10.52842/conf.caadria.2020.1.475
summary	In a systems building experiment, we explored how directly manipulating non-parametric geometries can be used together with a real-time parametric performance analytics for informed design decision-making in the early phases of design. This combination gives rise to a design process where considerations that would traditionally take place in the late phases of design can become part of the early phases. The paper presents FlowUI, a prototype tool for performance-driven design that is developed in a collaboration with our industry partner as part of our design analytics research program. The tool works with and responds to changes in the design modeling environment, processes the design data and presents the results in design (data) analytics interfaces. We discuss the system's design intent and its overall architecture, followed by a set of suggestions on the comparative analysis of design solutions and design reports generation as integral parts of design exploration tasks.
keywords	Non-Parametric Modeling; Performance-Driven Design; Design Analytics; Information Visualization
series	CAADRIA
email
last changed	2022/06/07 07:55

_id	caadria2020_403
id	caadria2020_403
authors	Ghandi, Mona
year	2020
title	Reducing Energy Consumption through Cyber-Physical Adaptive Spaces and Occupants' Biosignals
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. 121-130
doi	https://doi.org/10.52842/conf.caadria.2020.2.121
summary	The field of architecture has long embraced adaptive approaches to address issues of sustainability and efficiency. Building energy consumption accounts for about 40% of the total energy consumption in the U.S. This energy is mainly used for lighting, heating, cooling, and ventilation. Researches show that 30% of that energy is wasted. One of the main reasons for such high energy waste in the commercial (and even private) sectors is a generic assumption about the occupants' preferences. To fill this gap, the objective of this project is to optimize building energy retrofits by creating smart environments that autonomously respond to the occupants' comfort level using affective computing and adaptive systems. This adaptive approach will help optimizing energy consumption without sacrificing occupants' comfort through passive cooling and heating strategy, responding to occupants' preferences detected from their biological and neurological data. Progress towards achieving this goal will make building energy costs more affordable to the benefit of families and businesses and reduce energy waste.
keywords	Human-Computer Interaction; Optimizing Energy Consumption; Sustainability + High Performance Built Environment; Adaptive and Interactive Architecture; Cyber-Physical Spaces, Affective Computing, Occupantsâ€™ Comfort and Well-Being
series	CAADRIA
email
last changed	2022/06/07 07:51

_id	caadria2020_444
id	caadria2020_444
authors	Higgs, Baptiste and Doherty, Ben
year	2020
title	Sanitary Sanity: Evaluating Privacy Preserving Machine Learning Methods for Post-occupancy Evaluation
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. 697-706
doi	https://doi.org/10.52842/conf.caadria.2020.2.697
summary	Traditional post-occupancy evaluation (POE) of building performance has typically privileged physical building attributes over human behavioural data. This is due to a lack of capability and is especially the case for private spaces such as Sanitary Facilities (SFs). A privacy-preserving sensor-based system using Machine Learning (ML) was previously developed, however it was limited to basic body position classification. Yet, SF usage behaviour can be significantly more complex. This research accordingly builds on the aforementioned work to expand behavioural classifications using a sensor-based ML system. Specifically, the case study uses a GridEYE thermal sensor array, which is trained on a cubicle location within a workplace SF. A variety of ML algorithms are then evaluated on their behaviour-classifying ability. A detailed analysis of behaviour-classification performance is then provided. A system with greater fidelity is thus demonstrated, albeit hampered by imprecise behaviour definitions. Regardless, this contributes to the capability of the broader field of research that is investigating Evidence Based Design (EBD) by extending the ability to examine human behaviour, especially in private spaces. This further contributes to the growing body of work surrounding SF provision.
keywords	EBD; Data; Internet of Things; Machine Learning; Post Occupancy Evaluation
series	CAADRIA
email
last changed	2022/06/07 07:50

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

_id	ecaade2022_161
id	ecaade2022_161
authors	Kharbanda, Kritika, Papadopoulou, Iliana, Pouliou, Panagiota, Daw, Karim, Belwadi, Anirudh and Loganathan, Hariprasath
year	2022
title	LearnCarbon - A tool for machine learning prediction of global warming potential from abstract designs
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, pp. 601–610
doi	https://doi.org/10.52842/conf.ecaade.2022.2.601
summary	The new construction that is projected to take place between 2020 and 2040 plays a critical role in embodied carbon emissions. The change in material selection is inversely proportional to the budget, as the project progresses. Given the fact that early-stage design processes often do not include environmental performance metrics, there is an opportunity to investigate a toolset that enables early-stage design processes to integrate this type of analysis into the preferred workflow of concept designers. The value here is that early-stage environmental feedback can inform the crucial decisions that are made in the beginning, giving a greater chance for a building with better environmental performance in terms of its life cycle. This paper presents the development of a tool called LearnCarbon, as a plugin of Rhino3d, used to educate architects and engineers in the early stages about the environmental impact of their design. It facilitates two neural networks trained with the Embodied Carbon Benchmark Study by Carbon Leadership Forum, which learn the relationship between building geometry, typology, and structure with the Global Warming potential in tCO2e. The first one, a regression model, is able to predict the GWP based on the massing model of a building, along with information about typology and location. The second one, a classification model, predicts the construction type given a massing model and target GWP. LearnCarbon can help improve the building life cycle impact significantly, through early predictions of the structure’s material, and can be used as a tool for facilitating sustainable discussions between the architect and the client.
keywords	Machine Learning, Carbon Emissions, LCA, Rhino Plug-in
series	eCAADe
email
last changed	2024/04/22 07:10

_id	ecaade2020_517
id	ecaade2020_517
authors	Lharchi, Ayoub, Ramsgaard Thomsen, Mette and Tamke, Martin
year	2020
title	Connected Augmented Assembly - Cloud based Augmented Reality applications in architecture
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. 179-186
doi	https://doi.org/10.52842/conf.ecaade.2020.1.179
summary	Current design practices rely on a set of computational tools to simulate and optimize the design in regards to questions concerning architecture, engineering, and construction. However, little progress has been made in tools related to the design and execution of a building assembly. This paper aims to present an integrated procedure that targets the assembly of complex structures. Two challenges are identified and addressed: first, the necessity of a connected design environment where multiple stakeholders can communicate, modify, and give feedback on the assembly sequence. Second, the instructions for the assembly of structures to untrained users. The suggested method is based on the Assembly Information Modeling framework, which provides a general approach to generate assembly information from CAD data and utilizes AEC cloud platforms as a base for communication and Augmented Reality devices as a Human Machine Interface. Ultimately, both cases are combined to constitute Connected Augmented Assembly, a bidirectional approach to assembly design, review, and execution.
keywords	assembly sequence; augmented reality; assisted assembly; cloud aec; assembly information modeling
series	eCAADe
email
last changed	2022/06/07 07:52

_id	caadria2020_301
id	caadria2020_301
authors	Li, Bin, Guo, Weihong, Schnabel, Marc Aurel and Moleta, Tane
year	2020
title	Feng-Shui and Computational Fluid Dynamics (CFD) - Analyzing Natural Ventilation and Human Comfort
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. 731-740
doi	https://doi.org/10.52842/conf.caadria.2020.1.731
summary	The paper explores the analogies between Computational Fluid Dynamics (CFD) and Feng-Shui by undertaking an analysis of natural ventilation in Jiangmen city, Southern China. Feng-Shui has been used to inform the orientation, layout, and design of buildings in China for thousands of years. The research questions if these concepts are still valid for contemporary building design. Noting that computational simulation methods such as CFD allow architects to analyse the natural ventilation of buildings, this paper provides a novel study that examines if Feng-Shui principles can be reconciled against contemporary design processes. The research simulates 'community', 'block', and 'single courtyard' via CFD study to confirm the scientifically measurable concepts of Feng-Shui have concerning natural ventilation. We conclude that Feng-Shui concepts enhance natural ventilation and subsequently makes a positive contribution to sustainable building and design.
keywords	Human comfort; Natural ventilation; CFD; Feng-Shui
series	CAADRIA
email
last changed	2022/06/07 07:52

_id	caadria2020_107
id	caadria2020_107
authors	Meng, Leo Lin, Graham, Jeremy and Haeusler, M. Hank
year	2020
title	t-SNE: A Dimensionality Reduction Tool for Design Data Visualisation
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. 629-638
doi	https://doi.org/10.52842/conf.caadria.2020.2.629
summary	One can argue that data is the 'new oil'. Yet more important than the sheer quantity of data is the question, in the context of architecture and design, how data is represented in design, as this is becoming a more relevant question to the architecture profession. We argue that data, in particular n-dimensional, is often hidden even in BIM models. Hence we propose a new way of understanding the space by (1) generate and integrate space analytics data using space syntax method as well as space usage data and (2) visualise the data using t-Distributed Stochastic Neighbour Embedding (t-SNE), an unsupervised learning and dimensionality reduction tool to help intuitively display high dimensions of data. This approach may help to discover the 'hidden layers' of the building information that may be otherwise omitted. This investigation, its proposed hypothesis, methodology, implications, significance and evaluation are presented in the paper.
keywords	Data-Driven Design; t-SNE; Machine Learning; Space Syntax
series	CAADRIA
email
last changed	2022/06/07 07:58

_id	ecaade2020_053
id	ecaade2020_053
authors	Ren, Yue, Chu, Jie and Zheng, Hao
year	2020
title	Dynamic Symbiont - An Interactive Urban Design Method Combining Swarm Intelligence and Human Decisions
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. 383-392
doi	https://doi.org/10.52842/conf.ecaade.2020.1.383
summary	Can a virtual city game be built by both the public and computer-based on real-site data? In the current process of deepening global connectivity, requirements for an effective urban design are no longer limited to functions or aesthetics, but a smart, dynamic complex with multi-interactions of data, group behaviours, and physical space. This paper introduces the logic of swarm intelligence and particle system for proposing a new urban design methodology. The platforms range from simulations that quantify the impact of the disruptive interventions of city activities to communicable collaboration between different users in a UI system, which creates virtual connections between optimized urbanscape and users. In the design system, based on the context data, the computer firstly simulates and optimizes the existing 2D activity joints between the people and analyzed the current spatial connection nodes into certain design rules. Through optimal programming for spatial connection and data iterations, the activity connection structures in the second simulation are abstracted into a set of interactive 3D topographic. The final data-visualization results are presented as a co-building megacity in a virtual construction game. Users can choose the virtual building unit types and intuitively influence the future urbanscape decision through virtual construction.
keywords	Swarm Intelligence; Particle System; Digital Simulation; Human-Machine Interaction; Data Visualization
series	eCAADe
email
last changed	2022/06/07 07:56

_id	acadia23_v1_220
id	acadia23_v1_220
authors	Ruan, Daniel; Adel, Arash
year	2023
title	Robotic Fabrication of Nail Laminated Timber: A Case Study Exhibition
source	ACADIA 2023: Habits of the Anthropocene: Scarcity and Abundance in a Post-Material Economy [Volume 1: Projects Catalog of the 43rd Annual Conference of the Association of Computer Aided Design in Architecture (ACADIA) ISBN 979-8-9860805-8-1]. Denver. 26-28 October 2023. edited by A. Crawford, N. Diniz, R. Beckett, J. Vanucchi, M. Swackhamer 220-225.
summary	Previous research projects (Adel, Agustynowicz, and Wehrle 2021; Adel Ahmadian 2020; Craney and Adel 2020; Adel et al. 2018; Apolinarska et al. 2016; Helm et al. 2017; Willmann et al. 2015; Oesterle 2009) have explored the use of comprehensive digital design-to-fabrication workflows for the construction of nonstandard timber structures employing robotic assembly technologies. More recently, the Robotically Fabricated Structure (RFS), a bespoke outdoor timber pavilion, demonstrated the potential for highly articulated timber architecture using short timber elements and human-robot collaborative assembly (HRCA) (Adel 2022). In the developed HRCA process, a human operator and a human fabricator work alongside industrial robotic arms in a shared working environment, enabling collaborative fabrication approaches. Building upon this research, we present an exploration adapting HRCA to nail-laminated timber (NLT) fabrication, demonstrated through a case study exhibition (Figures 1 and 2).
series	ACADIA
type	project
email
last changed	2024/04/17 13:58

_id	caadria2020_154
id	caadria2020_154
authors	Stojanovic, Vladeta, Hagedorn, Benjamin, Trapp, Matthias and DÃ¶llner, JÃ¼rgen
year	2020
title	Ontology-Driven Analytics for Indoor Point Clouds
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. 537-546
doi	https://doi.org/10.52842/conf.caadria.2020.2.537
summary	Automated processing, semantic enrichment and visual analytics methods for point clouds are often use-case specific for a given domain (e.g, for Facility Management (FM) applications). Currently, this means that applicable processing techniques, semantics and visual analytics methods need to be selected, generated or implemented by human domain experts, which is an error-prone, subjective and non-interoperable process. An ontology-driven analytics approach can be used to solve this problem by creating and maintaining a Knowledge Base, and utilizing an ontology for automatically suggesting optimal selection of processing and analytics techniques for point clouds. We present an approach of an ontology-driven analytics concept and system design, which supports smart representation, exploration, and processing of indoor point clouds. We present and provide an overview of high-level concept and architecture for such a system, along with related key technologies and approaches based on previously published case studies. We also describe key requirements for system components, and discuss the feasibility of their implementation within a Service-Oriented Architecture (SOA).
keywords	Knowledge Base; Point Clouds; Semantic Enrichment; Service-Oriented Architecture; Ontology
series	CAADRIA
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last changed	2022/06/07 07:56

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