Joint Exploration and Analysis of High-Dimensional Design–Occupancy Templates

Usman, Muhammad; Schaumann, Davide; Haworth, Brandon; Kapadia, Mubbasir; Faloutsos, Petros

doi:10.1145/3359566.3360086

Cited by 4 publications

(3 citation statements)

References 25 publications

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“…18 Following this work, another framework is presented to automatically explore, both individually and jointly, the building and crowd behavioral parameters, to design crowd-efficient building layouts. 19 These approaches, however, are often integrated into specific environment design workflow and require certain hardware/software infrastructures and expertise to be utilized by the general audience.…”

Section: Crowd-aware Environment Analysis and Designmentioning

confidence: 99%

Simulation‐as‐a‐Service: Analyzing Crowd Movements in Virtual Environments

Usman

Haworth

Faloutsos

et al. 2021

Computer Animation & Virtual

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At present, environment designers mostly use their intuition and experience to predictively account for how environments might support dynamic activity. The majority of Computer-Aided Design tools only provide a static representation of space which potentially ignores the impact that an environment layout produces on its occupants and their movements. To address this, computational techniques such as crowd simulation have been developed. With few exceptions, crowd simulation frameworks are often decoupled from environment modeling tools. They usually require specific hardware/software infrastructures and expertise to be used, hindering the designers' abilities to seamlessly simulate, analyze, and incorporate movement-centric dynamics into their design workflows. To bridge this disconnect, we devise a cross-browser service-based simulation analytics platform to analyze environment layouts with respect to occupancy and activity. Our platform allows users to access simulation services by uploading three-dimensional environment models in numerous common formats, devise targeted simulation scenarios, run simulations, and instantly generate crowd-based analytics for their designs. We conducted a case study to showcase cross-domain applicability of our service-based platform, and a user study to evaluate the usability of this approach.

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Section: Crowd-aware Environment Analysis and Designmentioning

confidence: 99%

Simulation‐as‐a‐Service: Analyzing Crowd Movements in Virtual Environments

Usman

Haworth

Faloutsos

et al. 2021

Computer Animation & Virtual

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“…We showed occupants' trajectories and density heat maps for human-building interactions as analytics for designers and architects [49] (Figure 2). Using the work in [49], we presented a case study to investigate joint parameter exploration and sequential parameter exploration workflows to identify optimal set of environment and humanbehavioral parameters in a not-yet-built environment space [48].…”

Section: Parametric Workflowsmentioning

confidence: 99%

Chapter 9 Towards Democratizing Human–Building Simulation and Analytics

Usman

Haworth

Berseth

et al. 2021

Resilience in the Digital Age

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This work presents a concise summary of the workflows we have developed over time to simulate human-movements and dynamics of human-building interactions. We talk about the applications of humanbehaviour simulation in the analysis of building environments. We then discuss the approaches which use dynamic human-aware simulations in improving environment designs. We highlight the challenges in existing simulation workflows, which are usually decoupled from environment modeling tools or often tightly coupled with any specialized modeling platform. Such workflows require significant infrastructure and domain expertise, hindering the users' abilities to seamlessly simulate, analyze, and incorporate dynamics of human-building interactions into their preferred design workflows. We introduce a democratized approach using an on-demand service-based workflow for human-behaviour simulation and analysis of human-building interactions.

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“…Simulations are also used for informing the placement of environment elements (e.g., pillars and other obstacles) based on the movement flow in hallways [Berseth et al 2015;Haworth et al 2017]. The work presented in [Usman et al 2019] presented a comprehensive comparison of sequential and joint environment-crowd parameter exploration processes to generate efficient environments. In one of recent works [Haworth et al 2020], a gamification approach is adopted to showcase the potential of community-driven design of environment layouts with respect to crowd simulations using games and networking.…”

Section: Human-aware Building Designmentioning

confidence: 99%