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	ecaade2017_181
id	ecaade2017_181
authors	Balaban, Özgün and Tunçer, Bige
year	2017
title	Visualizing and Analising Urban Leisure Runs by Using Sports Tracking Data
source	Fioravanti, A, Cursi, S, Elahmar, S, Gargaro, S, Loffreda, G, Novembri, G, Trento, A (eds.), ShoCK! - Sharing Computational Knowledge! - Proceedings of the 35th eCAADe Conference - Volume 1, Sapienza University of Rome, Rome, Italy, 20-22 September 2017, pp. 533-540
doi	https://doi.org/10.52842/conf.ecaade.2017.1.533
summary	Recently there has been a significant growth on the usage of personal fitness applications running on smart phones or fitness devices. These applications record millions of GPS points generated from the paths of runners. This data can be analyzed to comprehend behavior of runners within a specific location. In this study, using data generated from several sources such as Endomondo and Strava and other complementary data such as climate data, population data etc., we aim to find out the factors affecting running behavior in urban settings. For this purpose, visualizations of running activities are plotted with different variables by using BIG-DID, a software tool we developed as part of this study. Additionally, an evaluation of the tools used or can be used for data analysis and visualizations discussed. Finally, a linear regression model is introduced, which will be further developed in later stages of this study.
keywords	Big Data; Urban Visualization; Fitness Applications; Leisure Runs
series	eCAADe
email
last changed	2022/06/07 07:54

_id	ecaade2017_156
id	ecaade2017_156
authors	Tunçer, Bige and You, Linlin
year	2017
title	Informed Design Platform - Multi-modal Data to Support Urban Design Decision Making
source	Fioravanti, A, Cursi, S, Elahmar, S, Gargaro, S, Loffreda, G, Novembri, G, Trento, A (eds.), ShoCK! - Sharing Computational Knowledge! - Proceedings of the 35th eCAADe Conference - Volume 2, Sapienza University of Rome, Rome, Italy, 20-22 September 2017, pp. 545-552
doi	https://doi.org/10.52842/conf.ecaade.2017.2.545
summary	Evidence based urban design and planning support benefits from providing designers with multi-source, multi-scale and multi-time information, which is both 'big' and 'small', and quantitative and qualitative. We are developing a platform, namely Informed Design Platform, that adopts a (big) data driven approach to derive insights and principles in order to adaptively design or re-design various forms of urban public spaces based on usage patterns and perceptions of the public. This platform is designed using a four step methodology of data collection, integration, analysis, and visualization. Multi-source data is integrated based on three analysis dimensions: place, time and people; and four analysis pillars: utilization, activity, opinion and sensing. This paper describes the aims, the design principles, and partial results of development of this platform.
keywords	Evidence based urban design; Multi-modal data; Information modeling; Information visualization
series	eCAADe
email
last changed	2022/06/07 07:58

_id	cf2017_101
id	cf2017_101
authors	Chen, Nai Chun; Zhang, Yan; Stephens, Marrisa; Nagakura, Takehiko; Larson, Kent
year	2017
title	Urban Data Mining with Natural Language Processing: Social Media as Complementary Tool for Urban Decision Making
source	Gülen Çagdas, Mine Özkar, Leman F. Gül and Ethem Gürer (Eds.) Future Trajectories of Computation in Design [17th International Conference, CAAD Futures 2017, Proceedings / ISBN 978-975-561-482-3] Istanbul, Turkey, July 12-14, 2017, pp. 101-109.
summary	The presence of web2.0 and traceable mobile devices creates new opportunities for urban designers to understand cities through an analysis of user-generated data. The emergence of “big data” has resulted in a large amount of information documenting daily events, perceptions, thoughts, and emotions of citizens, all annotated with the location and time that they were recorded. This data presents an unprecedented opportunity to gauge public opinion about the topic of interest. Natural language processing with social media is a novel tool complementary to traditional survey methods. In this paper, we validate these methods using tourism data from Trip-Advisor in Andorra. “Natural language processing” (NLP) detects patterns within written languages, enabling researchers to infer sentiment by parsing sentences from social media. We applied sentiment analysis to reviews of tourist attractions and restaurants. We found that there were distinct geographic regions in Andorra where amenities were reviewed as either uniformly positive or negative. For example, correlating negative reviews of parking availability with land use data revealed a shortage of parking associated with a known traffic congestion issue, validating our methods. We believe that the application of NLP to social media data can be a complementary tool for urban decision making.
keywords	Short Paper, Urban Design Decision Making, Social Media, Natural Language Processing
series	CAAD Futures
email
last changed	2017/12/01 14:37

_id	ecaade2017_029
id	ecaade2017_029
authors	Gadelhak, Mahmoud, Lang, Werner and Petzold, Frank
year	2017
title	A Visualization Dashboard and Decision Support Tool for Building Integrated Performance Optimization
source	Fioravanti, A, Cursi, S, Elahmar, S, Gargaro, S, Loffreda, G, Novembri, G, Trento, A (eds.), ShoCK! - Sharing Computational Knowledge! - Proceedings of the 35th eCAADe Conference - Volume 1, Sapienza University of Rome, Rome, Italy, 20-22 September 2017, pp. 719-728
doi	https://doi.org/10.52842/conf.ecaade.2017.1.719
summary	Analyzing the results of multi-objective optimization and building performance simulation can be a very tedious process that requires navigating between different software and tools. There is a clear scarcity in visualization tools that combine methods for big data analysis and design decision support tools that integrate detailed information for each design and parameter. Having a single visualization tool that provides methods to both visualize and analyze a large amount of data, understand the relation between objectives and variables, and having the ability to compare and analyze the preferred designs thoroughly can support the process of design decision making. In this paper, previous attempts to develop better data visualization tools for both integrated building simulation and optimization outputs were analyzed, then guidelines and a visualization tool prototype that can be effective in decision making and analyzing multi-objective optimizations results was presented.
keywords	Multi-objective optimization; Building Performance Simulation; Simulation; Visualization tools
series	eCAADe
email
last changed	2022/06/07 07:50

_id	caadria2021_354
id	caadria2021_354
authors	Huang, Chenyu, Gong, Pixin, Ding, Rui, Qu, Shuyu and Yang, Xin
year	2021
title	Comprehensive analysis of the vitality of urban central activities zone based on multi-source data - Case studies of Lujiazui and other sub-districts in Shanghai CAZ
source	A. Globa, J. van Ameijde, A. Fingrut, N. Kim, T.T.S. Lo (eds.), PROJECTIONS - Proceedings of the 26th CAADRIA Conference - Volume 2, The Chinese University of Hong Kong and Online, Hong Kong, 29 March - 1 April 2021, pp. 549-558
doi	https://doi.org/10.52842/conf.caadria.2021.2.549
summary	With the use of the concept Central Activities Zone in the Shanghai City Master Plan (2017-2035) to replace the traditional concept of Central Business District, core areas such as Shanghai Lujiazui will be given more connotations in the future construction and development. In the context of todays continuous urbanization and high-speed capital flow, how to identify the development status and vitality characteristics is a prerequisite for creating a high-quality Central Activities Zone. Taking Shanghai Lujiazui sub-district etc. as an example, the vitality value of weekday and weekend as well as 19 indexes including density of functional facilities and building morphology is quantified by obtaining multi-source big data. Meanwhile, the correlation between various indexes and the vitality characteristics of the Central Activities Zone are tried to summarize in this paper. Finally, a neural network regression model is built to bridge the design scheme and vitality values to realize the prediction of the vitality of the Central Activities Zone. The data analysis method proposed in this paper is versatile and efficient, and can be well integrated into the urban big data platform and the City Information Modeling, and provides reliable reference suggestions for the real-time evaluation of future urban construction.
keywords	multi-source big data; Central Activities Zone; Vitality; Lujiazui
series	CAADRIA
email
last changed	2022/06/07 07:50

_id	caadria2017_113
id	caadria2017_113
authors	Huang, Weixin, Lin, Yuming and Wu, Mingbo
year	2017
title	Spatial-Temporal Behavior Analysis Using Big Data Acquired by Wi-Fi Indoor Positioning System
source	P. Janssen, P. Loh, A. Raonic, M. A. Schnabel (eds.), Protocols, Flows, and Glitches - Proceedings of the 22nd CAADRIA Conference, Xi'an Jiaotong-Liverpool University, Suzhou, China, 5-8 April 2017, pp. 745-754
doi	https://doi.org/10.52842/conf.caadria.2017.745
summary	Understanding of people's spatial behavior is fundamental to architectural and urban design. However, traditional investigation methods applied in environmental behavior studies is highly limited regarding the amount of samples and regions it covers, which is not sufficient for the exploration of complex dynamic human behaviors and social activities in architectural space. Only recently the developments in indoor positioning system (IPS) and big data analysis technique have made it possible to conduct a full-time, full-coverage study on human environmental behavior. Among the variety IPS systems, the Wi-Fi IPS system is increasingly widely used because it is easy to be applied with acceptable cost. In this paper, we analyzed a 60-days anonymized data set, collected by a Wi-Fi IPS system with 110 Wi-Fi access points. The analysis revealed interesting patterns on people's behavior besides temporal spatial distribution, ranging from the cyclical fluctuation in human flow to behavioral patterns of sub-regions, some of which are not easy to be identified and interpreted by the traditional field observation. Through this case study, behavioral data from IPS system has exhibited great potential in bringing about profound changes in the study of environmental behavior.
keywords	environmental behavior study; Wi-Fi; indoor positioning system; big data; spatial temporal behavior; ski resort
series	CAADRIA
email
last changed	2022/06/07 07:50

_id	ecaade2018_151
id	ecaade2018_151
authors	Kirschner, Ursula and Sperling, David
year	2018
title	Mapping Urban Information as an Interdisciplinary Method for Geography, Art and Architecture Representations
source	Kepczynska-Walczak, A, Bialkowski, S (eds.), Computing for a better tomorrow - Proceedings of the 36th eCAADe Conference - Volume 2, Lodz University of Technology, Lodz, Poland, 19-21 September 2018, pp. 215-224
doi	https://doi.org/10.52842/conf.ecaade.2018.2.215
summary	In the current context, access to daily realities is becoming increasingly mediated and processed by maps, flooding us with spatial data that appears to be objective but needs to be questioned, or even disputed. On the other hand, there are some relevant aspects of the urban experience that elude the main maps provided by apps or big data visualizing projects. So this article points out alternative ways of mapping urban information in this context, by means of presenting and discussing the methodology and results of a mapping workshop carried out at a German university in 2017 with interdisciplinary groups of students. The aim was to provide new insights and readings of the contemporary city. We explored and invented the urban with a mix of creative research methods.
keywords	urban mapping information; critical cartography; urban spirit; cooperative urban exploration
series	eCAADe
email
last changed	2022/06/07 07:52

_id	acadia17_366
id	acadia17_366
authors	Lin, Yuming; Huang, Weixin
year	2017
title	Behavior Analysis and Individual Labeling Using Data from Wi-Fi IPS
source	ACADIA 2017: DISCIPLINES & DISRUPTION [Proceedings of the 37th Annual Conference of the Association for Computer Aided Design in Architecture (ACADIA) ISBN 978-0-692-96506-1] Cambridge, MA 2-4 November, 2017), pp. 366- 373
doi	https://doi.org/10.52842/conf.acadia.2017.366
summary	It is fairly important for architects and urban designers to understand how different people interact with the environment. However, traditional investigation methods for studying environmental behavior are quite limited in their coverage of samples and regions, which are not sufficient to delve into the behavioral differences of people. Only recently, the development of indoor positioning systems (IPS) and data-mining techniques has made it possible to collect full-time, full-coverage data for behavioral difference research and individualized identification. In our research, the Wi-Fi IPS system is chosen among the various IPS systems as the data source due to its extensive applicability and acceptable cost. In this paper, we analyzed a 60-day anonymized dataset from a ski resort, collected by a Wi-Fi IPS system with 110 Wi-Fi access points. Combining this with mobile phone data and questionnaires, we revealed some interesting characteristics of tourists from different origins through spatial-temporal behavioral data, and further conducted individual labeling through supervised learning. Through this case study, temporal-spatial behavioral data from an IPS system exhibited great potential in revealing individual characteristics besides exploring group differences, shedding light on the prospect of architectural space personalization.
keywords	design methods; information processing; data mining; big data
series	ACADIA
email
last changed	2022/06/07 07:59

_id	acadia17_426
id	acadia17_426
authors	Moorman, Andrew
year	2017
title	Pattern Making and Learning: Non-Routine Practices in Generative Design
source	ACADIA 2017: DISCIPLINES & DISRUPTION [Proceedings of the 37th Annual Conference of the Association for Computer Aided Design in Architecture (ACADIA) ISBN 978-0-692-96506-1] Cambridge, MA 2-4 November, 2017), pp. 426- 435
doi	https://doi.org/10.52842/conf.acadia.2017.426
summary	We now witness an upsurge in mainstream generative design tools fortified by simulation that speed up the concealed linear synthesis of optimized design alternatives. In pursuit of optimality, these tools saturate local machines or cloud servers with analysis and design iteration data, only to discard it once the procedure has concluded. Largely absent, however, are tools for an active, adaptive relationship with design exploration and the reuse of corresponding design data and metadata. In Pattern Making and Pattern Learning, we propose that these characteristics are mutually beneficial. This paper presents a series of revisions to the optimization framework for routine design synthesis that examine a potential symbiosis between the production of large datasets (big data) and non-routine practices of making in design. Our engagement with iterative design exercises is twofold: as a supply of computer-generated design information to foster user intuition and explore the design space on non-objective terms, and as a supply of human-generated design information to learn artifacts of user preference in the interest of design software personalization. These concepts are applied to the generation of functionally graded patterning in chair design, combining methods of physical production with programmable sheet material behavior through a custom interactive synthesis framework.
keywords	design methods; information processing; ai & machine learning; simulation & optimization; generative system
series	ACADIA
email
last changed	2022/06/07 07:58

_id	ecaade2017_079
id	ecaade2017_079
authors	Qabshoqa, Mohammad, Kocaturk, Tuba and Kiviniemi, Arto
year	2017
title	A value-driven perspective to understand Data-driven futures in Architecture
source	Fioravanti, A, Cursi, S, Elahmar, S, Gargaro, S, Loffreda, G, Novembri, G, Trento, A (eds.), ShoCK! - Sharing Computational Knowledge! - Proceedings of the 35th eCAADe Conference - Volume 2, Sapienza University of Rome, Rome, Italy, 20-22 September 2017, pp. 407-416
doi	https://doi.org/10.52842/conf.ecaade.2017.2.407
summary	This paper reports on an investigation of the potentials of data utilisation in Architecture from a value generation and business creation points of view, based on an ongoing PhD research by the first author. It is of crucial importance to, first, identify what data actually signifies for Architecture, and secondly to explore how the value obtained through data-driven approaches in other industries could potentially be transferred and applied in our professional context. These objectives have been achieved through a qualitative comparative analysis of various cases. Additionally, the paper discusses the multiplicity of factors which contribute to different interpretations and utilisation of data with reference to various value systems embedded into our profession (e.g. design as ideology, design as profession, design as service). A comparative analysis of the existing data utilisation methods in connection with various value systems provide crucial insights in order to answer the following questions: How can data assess values in architectural design/practice? How can data utilisation give way to the emergence of new values for the profession?
keywords	Big Data in Architecture; Data-Driven Architecture Design; Data in Architecture Design; Computational Data Design; Digital Value in Architecture
series	eCAADe
email
last changed	2022/06/07 07:58

_id	acadia17_178
id	acadia17_178
authors	Charbel, Hadin; López, Déborah
year	2017
title	In(di)visible: Computing Immersive Environments through Hybrid Senses
source	ACADIA 2017: DISCIPLINES & DISRUPTION [Proceedings of the 37th Annual Conference of the Association for Computer Aided Design in Architecture (ACADIA) ISBN 978-0-692-96506-1] Cambridge, MA 2-4 November, 2017), pp. 178-189
doi	https://doi.org/10.52842/conf.acadia.2017.178
summary	The research presented in this paper seeks to examine how architecture and computational tools can be used to communicate on multiple levels by incorporating a series of qualitative and quantitative measures as criteria for a spatial and architectural design. Air is taken as a material that has the capacity to create boundaries, yet unless under extreme conditions often remains invisible. Varying in qualities such as temperature, humidity and pollution, the status of air is highly local to a particular context. The research explores how rendering air visible through an architectural intervention made of networked sentient prototypes can be used in the reation of a responsive outdoor public space. Although humans' ability to perceive and respond to stimuli is highly advanced, it is nevertheless limited in its spectrum. Within the urban context specifically, the information, material and flux being produced is becoming ever more complex and incomprehensible. While computational tools, sensors and data are increasingly accessible, advancements in the fields of cognitive sciences and biometrics are unraveling how the mind and body works. These developments are explored in tandem and applied through a proposed methodology. The project aims to negotiate the similarities and differences between humans and machines with respect to the urban environment. The hypothesis is that doing so will create a rich output, irreducible to a singular reading while heightening user experience and emphasizing a sense of place.
keywords	design methods; information processing; hybrid practices; data visualization; computational / artistic cultures
series	ACADIA
email
last changed	2022/06/07 07:55

_id	sigradi2017_077
id	sigradi2017_077
authors	Soto Muñoz, Jaime; Jesús Pulido Arcas, Rodrigo García Alvarado, Gastón Arias Aravena
year	2017
title	La implementación de la Metodología Building Information Modeling (BIM) para edificios existentes en Chile [La implementación de la Metodología Building Information Modeling (BIM) para edificios existentes en Chile]
source	SIGraDi 2017 [Proceedings of the 21th Conference of the Iberoamerican Society of Digital Graphics - ISBN: 978-956-227-439-5] Chile, Concepción 22 - 24 November 2017, pp.528-533
summary	BIM technology is currently being implemented in the construction industry, though it is still underdeveloped in relation to Facility Management (FC) of extant buildings. There is a strong potential for future development due to the visualization and data analysis capabilities of this technology, amongst others (Becerik-Gerber, Jazizadeh, Li, & Calis, 2012). This research investigates how BIM can be implemented in existing buildings currently in operation. Using a public facility at the University of Bio-Bio as a case study, conclusions are drawn with respect the capabilities of BIM in order to optimize maintenance and operation of existing buildings.
series	SIGRADI
email
last changed	2021/03/28 19:59

_id	ecaade2021_203
id	ecaade2021_203
authors	Arora, Hardik, Bielski, Jessica, Eisenstadt, Viktor, Langenhan, Christoph, Ziegler, Christoph, Althoff, Klaus-Dieter and Dengel, Andreas
year	2021
title	Consistency Checker - An automatic constraint-based evaluator for housing spatial configurations
source	Stojakovic, V and Tepavcevic, B (eds.), Towards a new, configurable architecture - Proceedings of the 39th eCAADe Conference - Volume 2, University of Novi Sad, Novi Sad, Serbia, 8-10 September 2021, pp. 351-358
doi	https://doi.org/10.52842/conf.ecaade.2021.2.351
summary	The gradual rise of artificial intelligence (AI) and its increasing visibility among many research disciplines affected Computer-Aided Architectural Design (CAAD). Architectural deep learning (DL) approaches are being developed and published on a regular basis, such as retrieval (Sharma et al. 2017) or design style manipulation (Newton 2019; Silvestre et al. 2016). However, there seems to be no method to evaluate highly constrained spatial configurations for specific architectural domains (such as housing or office buildings) based on basic architectural principles and everyday practices. This paper introduces an automatic constraint-based consistency checker to evaluate the coherency of semantic spatial configurations of housing construction using a small set of design principles to evaluate our DL approaches. The consistency checker informs about the overall performance of a spatial configuration followed by whether it is open/closed and the constraints it didn't satisfy. This paper deals with the relation of spaces processed as mathematically formalized graphs contrary to existing model checking software like Solibri.
keywords	model checking, building information modeling, deep learning, data quality
series	eCAADe
email
last changed	2022/06/07 07:54

_id	cf2017_084
id	cf2017_084
authors	Chen, Kian Wee; Janssen, Patrick; Norford, Leslie
year	2017
title	Automatic Generation of Semantic 3D City Models from Conceptual Massing Models
source	Gülen Çagdas, Mine Özkar, Leman F. Gül and Ethem Gürer (Eds.) Future Trajectories of Computation in Design [17th International Conference, CAAD Futures 2017, Proceedings / ISBN 978-975-561-482-3] Istanbul, Turkey, July 12-14, 2017, pp. 84-100.
summary	We present a workflow to automatically generate semantic 3D city models from conceptual massing models. In the workflow, the massing design is exported as a Collada file. The auto-conversion method, implemented as a Python library, identifies city objects by analysing the relationships between the geometries in the Collada file. For example, if the analysis shows that a closed poly surface satisfies certain geometrical relationships, it is automatically converted to a building. The advantage of this workflow is that no extra modelling effort is required, provided the designers are consistent in the geometrical relationships while modelling their massing design. We will demonstrate the feasibility of the workflow using three examples of increasing complexity. With the success of the demonstrations, we envision the utoconversion of massing models into semantic models will facilitate the sharing of city models between domain-specific experts and enhance communications in the urban design process.
keywords	Interoperability, GIS, City Information Modelling, Conceptual Urban Design, Collaborative Urban Design Process
series	CAAD Futures
email
last changed	2017/12/01 14:37

_id	ijac201715201
id	ijac201715201
authors	Weizmann, Michael; Oded Amir and Yasha Jacob Grobman
year	2017
title	Topological interlocking in architecture: A new design method and computational tool for designing building floors
source	International Journal of Architectural Computing vol. 15 - no. 2, 107-118
summary	This article presents a framework for the design process of structural systems based on the notion of topological interlocking. A new design method and a computational tool for generating valid architectural topological interlocking geometries are discussed. In the heart of the method are an algorithm for automatically generating valid two-dimensional patterns and a set of procedures for creating several types of volumetric blocks based on the two-dimensional patterns. Additionally, the computational tool can convert custom sets of closed planar curves into structural elements based on the topological interlocking principle. The method is examined in a case study of a building floor. The article concludes with discussions on the potential advantages of using the method for architectural design, as well as on challenging aspects of further development of this method toward implementation in practice.
keywords	Parametric design, topological interlocking, form generation, structural floor system
series	other
type	normal paper
email
last changed	2019/08/02 08:29

_id	acadia17_102
id	acadia17_102
authors	Aparicio, German
year	2017
title	Data-Insight-Driven Project Delivery: Approach to Accelerated Project Delivery Using Data Analytics, Data Mining and Data Visualization
source	ACADIA 2017: DISCIPLINES & DISRUPTION [Proceedings of the 37th Annual Conference of the Association for Computer Aided Design in Architecture (ACADIA) ISBN 978-0-692-96506-1] Cambridge, MA 2-4 November, 2017), pp. 102-109
doi	https://doi.org/10.52842/conf.acadia.2017.102
summary	Today, 98% of megaprojects face cost overruns or delays. The average cost increase is 80% and the average slippage is 20 months behind schedule (McKinsey 2015). It is becoming increasingly challenging to efficiently support the scale, complexity and ambition of these projects. Simultaneously, project data is being captured at growing rates. We continue to capture more data on a project than ever before. Total data captured back in 2009 in the construction industry reached over 51 petabytes, or 51 million gigabytes (Mckinsey 2016). It is becoming increasingly necessary to develop new ways to leverage our project data to better manage the complexity on our projects and allow the many stakeholders to make better more informed decisions. This paper focuses on utilizing advances in data mining, data analytics and data visualization as means to extract project information from massive datasets in a timely fashion to assist in making key informed decisions for project delivery. As part of this paper, we present an innovative new use of these technologies as applied to a large-scale infrastructural megaproject, to deliver a set of over 4,000 construction documents in a six-month period that has the potential to dramatically transform our industry and the way we deliver projects in the future. This paper describes a framework used to measure production performance as part of any project’s set of project controls for accelerated project delivery.
keywords	design methods; information processing; data mining; big data; data visualization
series	ACADIA
email
last changed	2022/06/07 07:55

_id	ecaade2017_001
id	ecaade2017_001
authors	Fioravanti, A, Cursi, S, Elahmar, S, Gargaro, S, Loffreda, G, Novembri, G, Trento, A (eds.)
year	2017
title	ShoCK! – Sharing of Computable Knowledge!, Volume 2
source	ShoCK! - Sharing Computational Knowledge! - Proceedings of the 35th eCAADe Conference - Volume 2, Sapienza University of Rome, Rome, Italy, 20-22 September 2017, 760 p.
doi	https://doi.org/10.52842/conf.ecaade.2017.2
summary	Internet of Things, pervasive nets, Knowledge ‘on tap’, Big Data, Wearable devices and the ‘Third wave’ of AI are disruptive technologies that are upsetting our globalised world as far as it can be foreseen from now. So academicians, professionals, researchers, innovation factories... are warmly invited to further shake up and boost our innovative and beloved CAAD world with new ideas, paradigms and points of view. Will our fine buildings and design traditions survive? Or, will they ‘simply’ be hybridized and enhanced by methods, techniques and CAAD tools? Obviously computation is needed to match the evergrowing performance requirements, but this is not enough to answer all these questions we have to deal with the essence of problems: improve design solutions for a better life. As life is not a matter of single individuals, we need to increase collaboration and to improve knowledge sharing. This means taking care of human beings, and involves a humanistic approach, and the long history of humankind ... from humans to thinking to technology ... and vice versa. A circle of human beings as eternal as our city.
series	eCAADe
last changed	2022/06/07 07:49

_id	ecaade2017_000
id	ecaade2017_000
authors	Fioravanti, A, Cursi, S, Elahmar, S, Gargaro, S, Loffreda, G, Novembri, G, Trento, A (eds.)
year	2017
title	ShoCK! – Sharing of Computable Knowledge!, Volume 1
source	ShoCK! - Sharing Computational Knowledge! - Proceedings of the 35th eCAADe Conference - Volume 1, Sapienza University of Rome, Rome, Italy, 20-22 September 2017, 770 p.
doi	https://doi.org/10.52842/conf.ecaade.2017.1
summary	Internet of Things, pervasive nets, Knowledge ‘on tap’, Big Data, Wearable devices and the ‘Third wave’ of AI are disruptive technologies that are upsetting our globalised world as far as it can be foreseen from now. So academicians, professionals, researchers, innovation factories... are warmly invited to further shake up and boost our innovative and beloved CAAD world with new ideas, paradigms and points of view. Will our fine buildings and design traditions survive? Or, will they ‘simply’ be hybridized and enhanced by methods, techniques and CAAD tools? Obviously computation is needed to match the evergrowing performance requirements, but this is not enough to answer all these questions we have to deal with the essence of problems: improve design solutions for a better life. As life is not a matter of single individuals, we need to increase collaboration and to improve knowledge sharing. This means taking care of human beings, and involves a humanistic approach, and the long history of humankind ... from humans to thinking to technology ... and vice versa. A circle of human beings as eternal as our city.
series	eCAADe
last changed	2022/06/07 07:49

_id	ecaade2017_301
id	ecaade2017_301
authors	Kalantari, Saleh and Ghandi, Mona
year	2017
title	Data-responsive Architectural Design Processes
source	Fioravanti, A, Cursi, S, Elahmar, S, Gargaro, S, Loffreda, G, Novembri, G, Trento, A (eds.), ShoCK! - Sharing Computational Knowledge! - Proceedings of the 35th eCAADe Conference - Volume 2, Sapienza University of Rome, Rome, Italy, 20-22 September 2017, pp. 503-512
doi	https://doi.org/10.52842/conf.ecaade.2017.2.503.2
summary	Current advancements in information technology and mechanical components offer incredible new possibilities for innovation in architecture. Many aspects of our physical environment are becoming integrated with information systems, a phenomenon that has been referred to as the "Internet of Things." The implications and applications of this technology are far-reaching, and students who are learning about design in today's environment have a bewildering array of new tools available for their exploration. This paper reviews some of the central concepts of contemporary data-driven design, and describes how these concepts can be used in a pedagogical framework to encourage student innovation. The authors provide details about their work with students in IDR Studios, and highlight some of the innovative design solutions created by students using information-based toolsets. This research provides a pedagogical framework for helping design students to engage with new technological resources as they work to develop the architectural intelligence.
keywords	Adaptive Systems; Internet of Things; Big Data; Data Driven Design Process
series	eCAADe
email
last changed	2022/06/07 07:52

_id	caadria2017_086
id	caadria2017_086
authors	Koh, Immanuel, Keel, Paul and Huang, Jeffrey
year	2017
title	Decoding Parametric Design Data - Towards a Heterogeneous Design Search Space Remix
source	P. Janssen, P. Loh, A. Raonic, M. A. Schnabel (eds.), Protocols, Flows, and Glitches - Proceedings of the 22nd CAADRIA Conference, Xi'an Jiaotong-Liverpool University, Suzhou, China, 5-8 April 2017, pp. 117-126
doi	https://doi.org/10.52842/conf.caadria.2017.117
summary	Designers or Non-Designers are not able to effectively access, view, search, discover, collect, reuse, remix and share parametric design data (PDD) for either professional or educational purposes. PDD here refers to the meta-data of 3D models generated by visual dataflow modelling software packages used in CAD/CAM industry. This ineffectiveness is a direct consequence of the deliberately proprietary nature of most PDD file formats and the restricted use within their respective desktop-based software environments. This paper presents an initial software prototype capable of automating the process of decoding a commonly used PDD file format and then re-encoding it with new set of metrics to facilitate multiple PDD searchability, comparability and interoperability, via an integrated web interface querying a design data repository. All PDDs are conceptualized as genealogies of numerical or geometric transformations and explicitly encoded with a graph-based data structure. The goal is to eventually learn from its own big data and begin to artificially generate novel PDDs heterogeneously.
keywords	Design Decoder; Design Space Exploration; Parametric Design; Visual Analytics; Design Data
series	CAADRIA
email
last changed	2022/06/07 07:51

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