Leveraging generative AI for urban digital twins: a scoping review on the autonomous generation of urban data, scenarios, designs, and 3D city models for smart city advancement

Urban Informatics, Год журнала: 2024, Номер 3(1)

Опубликована: Окт. 14, 2024

Abstract The digital transformation of modern cities by integrating advanced information, communication, and computing technologies has marked the epoch data-driven smart city applications for efficient sustainable urban management. Despite their effectiveness, these often rely on massive amounts high-dimensional multi-domain data monitoring characterizing different sub-systems, presenting challenges in application areas that are limited quality availability, as well costly efforts generating scenarios design alternatives. As an emerging research area deep learning, Generative Artificial Intelligence (GenAI) models have demonstrated unique values content generation. This paper aims to explore innovative integration GenAI techniques twins address planning management built environments with focuses various such transportation, energy, water, building infrastructure. survey starts introduction cutting-edge generative AI models, Adversarial Networks (GAN), Variational Autoencoders (VAEs), Pre-trained Transformer (GPT), followed a scoping review existing science leverage intelligent autonomous capability facilitate research, operations, critical subsystems, holistic environment. Based review, we discuss potential opportunities technical strategies integrate into next-generation more intelligent, scalable, automated development

Язык: Английский

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A predictive model for daylight performance based on multimodal generative adversarial networks at the early design stage

Energy and Buildings, Год журнала: 2024, Номер 305, С. 113876 - 113876

Опубликована: Янв. 3, 2024

Язык: Английский

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Uncertainty-aware Fragility Modeling of Urban Building Exteriors Subjected to Hurricane-induced Windborne Debris with Conditional Generative Adversarial Nets

Advances in wind engineering., Год журнала: 2025, Номер unknown, С. 100042 - 100042

Опубликована: Фев. 1, 2025

Язык: Английский

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Smart urban windcatcher: Conception of an AI-empowered wind-channeling system for real-time enhancement of urban wind environment

Building and Environment, Год журнала: 2024, Номер 253, С. 111357 - 111357

Опубликована: Фев. 26, 2024

Язык: Английский

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A review of surrogate-assisted design optimization for improving urban wind environment

Building and Environment, Год журнала: 2024, Номер 253, С. 111157 - 111157

Опубликована: Янв. 4, 2024

Язык: Английский

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Machine learning-based surrogate models for fast impact assessment of a new building on urban local microclimate at design stage

Building and Environment, Год журнала: 2024, Номер unknown, С. 112142 - 112142

Опубликована: Сен. 1, 2024

Язык: Английский

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Conditional generative adversarial networks for image-based sunlight analysis of residential blocks

Energy and Buildings, Год журнала: 2024, Номер 316, С. 114295 - 114295

Опубликована: Май 15, 2024

Язык: Английский

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Review of OpenFOAM applications in the computational wind engineering: from wind environment to wind structural engineering

Meccanica, Год журнала: 2024, Номер unknown

Опубликована: Июнь 6, 2024

Abstract The use of computational fluid dynamics (CFD) in the wind engineering (WE) is generally defined as (CWE). Since its foundation 2004, OpenFOAM CWE has been increasing progressively and covers nowadays a wide range topics, from environment to structural engineering. This paper was drafted response invitation organizers 18th workshop held Genoa (Italy) on 11–14 July 2023, when technical session Civil Engineering Wind organized. In this author briefly reviews history WE surveys evolution, methods, future challenges CWE. Topics are here regrouped into three main research areas discussed physical, purely perspective. study does not cover Energy related since can be considered stand-alone subfield WE. review confirms that versatile tool widely used for applications often require new models developed ad hoc by CFD users. It coupled easily with numerical weather prediction mesoscale-microscale thermal studies, building energy simulation determine demand, finite element method design. represents an extraordinary opportunity all users worldwide share codes case explore potential functionalities strengthen network within community.

Язык: Английский

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A rapid indoor 3D wind field prediction model based on Conditional Generative Adversarial Networks

Journal of Building Engineering, Год журнала: 2025, Номер unknown, С. 111756 - 111756

Опубликована: Янв. 1, 2025

Язык: Английский

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Advancing Synergistic Urban Heat Island Mitigation Based on Multimodal Data Integration and a Novel Cyclegan-Pix2pix(Cp-Gan) Model

Опубликована: Янв. 1, 2025

Язык: Английский

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