Crowdsourcing with online quantitative design analysis. (October 2018)

• Record Type: Journal Article
• Authors: Birch, David; Simondetti, Alvise; Guo, Yi-ke
• Is Part Of: Advanced engineering informatics. Volume 38(2018)
• Page Start: 242
• Page End: 251
• Publication Date: 2018-10
• Subjects: Design -- Crowdsourcing -- Architecture -- Cloud -- Masterplanning -- Optimization; Computer-aided engineering -- Periodicals; Engineering -- Data processing -- Periodicals; 620.00285
• DOI: 10.1016/j.aei.2018.07.004
• Languages: English
• ISSNs: 1474-0346

Abstract

Abstract: Design is a balancing act between people's competing concerns, design options and design performance. Recently collecting data on such concerns such as sustainability or aesthetics has become possible through online crowdsourcing, particularly in 3d. However, such systems rarely present more than a single design alternative or allow users to change the design and seldom provide quantitative design analysis to gauge design performance. This precludes a more participatory approach including a wider audience and their insight in the design process. To improve the design process we propose a system to assist the design team in exploring the balance of concerns, design options and their performance. We augment a 3d visualisation crowdsourcing environment with quantitative on-demand assessment of design variants run in the cloud. This enables crowdsourced exploration of the design space and its performance. Automated participant tracking and explicit submitted feedback on design options are collated and presented to aid the design team in balancing the demands of urban master planning. We report application of this system to an urban masterplan with Arup.