Augmented Urban Experiences: Technologically Enhanced Design Research Methods for Revealing Hidden Qualities of the Built Environment

Andreani, Stefano; Sayegh, Allen

doi:10.52842/conf.acadia.2017.082

Cited by 5 publications

(3 citation statements)

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“…Nonetheless, objective measurements of individual perception are more conducive to revealing the 'hidden' qualities of space than traditional methods such as self-reported questionnaires. Only when the applicable evidence-based tools are available to designers, the "hidden" quality that influences human behavior can be fully revealed, 28 and the sustainable environment of people-oriented can be truly shaped.…”

Section: Methodsmentioning

confidence: 99%

Computational Urban Design: An Exploration of New Urban Science

Qiang,

Ye,

Zhang

2022

Empower

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Classic urban design theories and research methods have been limited to qualitative approaches, such as subjective intuition and small-scale surveys. With the emergence of new urban science, adopting big data, virtual reality (VR), and wearable sensors, it is possible to achieve a precise analysis of people’s perceptions and behaviors in urban spaces. In this way, not only will new insights in urban studies be inspired but also high-quality, human-scale space design can be generated. This study constructs a systematic and computational urban design system that covers the three aspects of technical applications, data-informed, evidence-based, and algorithm-driven urban design. First, the data-informed urban design helps identify problems and formulate strategies. Multi-source city data, such as Point of Interest (PoIs)data and AutoNavi map path planning API, help to identify the needs, functions, and characteristics of the citizens. The evidence-based urban design with specific inquiries helps to select the design intervention point and control spatial elements. VR technology, wearable biosensors, and the visualizationSP method are combined to measure space utility. The final algorithm-driven part can use sDNA, UNA, and visualizer to summarize the types of urban spaces, perform morphological analysis and vitality evaluation, and further adjust the design. It can be seen that the application of this framework can make the entire design process more automatic, efficient, and robust under the existing constraints. In addition, it helps the perspective of urban design expand from the previous “top-down” perspective to the “bottom up” perspective, transforming from a two-dimensional to a three-dimensional, obtaining real-time feedback and optimizing design accordingly, emphasizing human perception and human-oriented scale.

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Section: Methodsmentioning

confidence: 99%

Computational Urban Design: An Exploration of New Urban Science

Qiang,

Ye,

Zhang

2022

Empower

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“…Researchers today have built upon these by incorporating novel technologies from eye-trackers , biometric sensors (Poh et al, 2010, camera analysis (Schlickman & Domlesky, 2019), to AI/machine learning (ESUM, 2017). Using these tools, experience research has been conducted in a variety of physical settings, from within passenger automobiles (Healey & Picard, 2005) to city centers (Andreani & Sayegh, 2017).…”

Section: Literature Reviewmentioning

confidence: 99%

SIGraDi 2022. Critical Appropriations

Z.¹

2023

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SIGraDi 2022. Critical Appropriations es la XXVI Conferencia Internacional de la Sociedad Iberoamericana de Gráfica Digital, organizada por la Facultad de Arquitectura de la Universidad Peruana de Ciencias Aplicadas (UPC) y SIGraDi. Este volumen contiene los artículos seleccionados por el comité científico de SIGraDi, los cuales fueron presentados en línea entre el 9 y 11 de noviembre de 2022, además, a partir de estos trabajos se desarrollaron10 talleres y un taller para doctorandos. SIGraDi 2022. Apropiaciones Críticas se organizó en 7 tópicos y 30 subtópicos, como culturas de la programación, robótica y fabricación digital, BIM, diseño bio inspirado, educación digital. Una publicación de difusión e intercambio de ideas sobre Arquitectura, Diseño, Arte y disciplinas asociadas.

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“…92.57% accuracy for four emotions; 94.86% for valence and 94.43 % for arousal . The reliable emotional benchmark from EEG data has been applied to various spatial-related studies and most of them are evaluation studies with classification from Emotiv (Ramirez, 2012;Emotiv, 2017), covering issue on the influence of street space on people's emotion (Andreani, 2017;Mavros, 2012), the form of space and people's feeling inside (Shemesh, 2015) and the sound and emotive feedback (Dorothea, 2014).…”

Section: Eeg Based Environmental Interactionmentioning

confidence: 99%

Proceedings of the 26th Conference on Computer Aided Architectural Design Research in Asia (CAADRIA) [Volume 2]

2021

CAADRIA Proceedings

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Augmented Urban Experiences: Technologically Enhanced Design Research Methods for Revealing Hidden Qualities of the Built Environment

Cited by 5 publications

References 0 publications

Computational Urban Design: An Exploration of New Urban Science

Computational Urban Design: An Exploration of New Urban Science

SIGraDi 2022. Critical Appropriations

Proceedings of the 26th Conference on Computer Aided Architectural Design Research in Asia (CAADRIA) [Volume 2]

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