JOIN: an integrated platform for joint simulation of occupant-building interactions

Schaumann, Davide; Moon, Seonghyeon; Usman, Muhammad; Goldstein, Rhys; Breslav, Simon; Khan, Azam; Faloutsos, Petros; Kapadia, Mubbasir

doi:10.1080/00038628.2019.1662767

Cited by 9 publications

(4 citation statements)

References 21 publications

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“…Te probability of users' travel choice can also be obtained from the solved parameters. Other models that study transportation demand are from the perspective of simulation [51][52][53], which optimizes parameters to make the interaction between individuals and the environment more realistic and predict future behavioral choices. In this paper, we focus on the impact of the built environment on the demand for takeout orders, so the frst type of modeling approach is more relevant.…”

Section: Modeling Methodsmentioning

confidence: 99%

Investigating the Nonlinear Relationship between Takeout Order Demand and Built Environment under Different Periods of COVID-19

Guo

Zhang

2023

Journal of Advanced Transportation

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The COVID-19 pandemic has hit the global restaurant business hard, especially dine-in. However, it has also provided opportunities for online dining, with takeout becoming a fulcrum for the economic resilience of the urban restaurant industry. Currently, research on the factors affecting takeout order demand under the pandemic has been inadequate. Therefore, this study uses multisource data from Nanjing to explore the changes in takeout order demand as the pandemic develops. And based on the Light gradient boosting machine (Light GBM) model, the nonlinear relationship between the built environment and order demand under different periods of pandemic is investigated, and the important factors affecting the demand are obtained. The results show that daily orders on average during COVID-19 decline by 25.6% than before COVID-19, while during the stabilization phase of the pandemic, they are 20.0% higher than before COVID-19. According to the relative importance ranking of factors in the model, land use diversity and road design influence takeout the most and the crucial influencing factors vary across pandemic periods. In the postpandemic era, special attention needs to be paid to the impact of the number of restaurants, colleges, offices, and main roads on takeout services. In addition, the thresholds of key built environment factors through partial dependency plots can enhance operators’ understanding of takeout services and provide suggestions for the spatial layout of takeout resources. While satisfying people’s dietary needs, the role of takeout in restoring the restaurant economy can be better utilized.

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Section: Modeling Methodsmentioning

confidence: 99%

Investigating the Nonlinear Relationship between Takeout Order Demand and Built Environment under Different Periods of COVID-19

Guo

Zhang

2023

Journal of Advanced Transportation

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“…In MAS, prospective building occupants are modeled as agents that interact among them as well as with the surrounding built environments to goals related to the type of organization that occupies the building 99 . These approaches have been applied to model operational performance in process-driven facilities like hospitals 100 , wayfinding in multi-level buildings 101 , occupancy patterns in university campuses 102 , thermal and acoustic comfort in office spaces 103 , and emergency evacuation scenarios 104 . Generative design approaches also show promise in coupling human-centered evaluation metrics with parametric models of buildings to automatically generate, sort through, and evaluate several design options and recommend the ones that balance tradeoffs between building and human performance metrics 105 .…”

Section: Hbi Research Dimensionsmentioning

confidence: 99%

The field of human building interaction for convergent research and innovation for intelligent built environments

Becerik-Gerber

Lucas

Aryal

et al. 2022

Sci Rep

Self Cite

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Human-Building Interaction (HBI) is a convergent field that represents the growing complexities of the dynamic interplay between human experience and intelligence within built environments. This paper provides core definitions, research dimensions, and an overall vision for the future of HBI as developed through consensus among 25 interdisciplinary experts in a series of facilitated workshops. Three primary areas contribute to and require attention in HBI research: humans (human experiences, performance, and well-being), buildings (building design and operations), and technologies (sensing, inference, and awareness). Three critical interdisciplinary research domains intersect these areas: control systems and decision making, trust and collaboration, and modeling and simulation. Finally, at the core, it is vital for HBI research to center on and support equity, privacy, and sustainability. Compelling research questions are posed for each primary area, research domain, and core principle. State-of-the-art methods used in HBI studies are discussed, and examples of original research are offered to illustrate opportunities for the advancement of HBI research.

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“…vironmental and occupancy phenomena that unfold at different time scales [37,38]. We have developed a node-based representation to jointly parameterize different spatial and human behavioural parameters to model human activities and interactions in a building design [49].…”

Section: Joint Modeling Of Human-building Interactionsmentioning

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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JOIN: an integrated platform for joint simulation of occupant-building interactions

Cited by 9 publications

References 21 publications

Investigating the Nonlinear Relationship between Takeout Order Demand and Built Environment under Different Periods of COVID-19

Investigating the Nonlinear Relationship between Takeout Order Demand and Built Environment under Different Periods of COVID-19

The field of human building interaction for convergent research and innovation for intelligent built environments

Chapter 9 Towards Democratizing Human–Building Simulation and Analytics

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