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, Journal Year: 2024, Volume and Issue: 3(1)

Published: Oct. 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

Language: Английский

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Urban stormwater resilience: Global insights and strategies for climate adaptation

Urban Climate, Journal Year: 2025, Volume and Issue: 59, P. 102290 - 102290

Published: Jan. 16, 2025

Language: Английский

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Adaptive multi-model fusion learning for sparse-reward reinforcement learning

Neurocomputing, Journal Year: 2025, Volume and Issue: unknown, P. 129748 - 129748

Published: Feb. 1, 2025

Language: Английский

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Comprehensive digital twin for infrastructure: A novel ontology and graph-based modelling paradigm

Advanced Engineering Informatics, Journal Year: 2024, Volume and Issue: 62, P. 102747 - 102747

Published: July 30, 2024

Language: Английский

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3D laser scanning for automated structural modeling and deviation monitoring of multi-section prefabricated cable domes

Automation in Construction, Journal Year: 2024, Volume and Issue: 165, P. 105573 - 105573

Published: June 22, 2024

Language: Английский

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How Artificial Intelligence (AI) Is Powering New Tourism Marketing and the Future Agenda for Smart Tourist Destinations

Electronics, Journal Year: 2024, Volume and Issue: 13(21), P. 4151 - 4151

Published: Oct. 23, 2024

Artificial intelligence (AI) is a disruptive technology that being used by smart tourist destinations (STDs) to develop new business models and marketing services increase tourists’ experiences sales, revenue, productivity, efficiency STDs. However, the adoption of AI applications platforms requires high economic budget for STDs want integrate this digital tool into their future agenda tourism development plans, especially when they set them up plans operational processes. This iterative needs regular maintenance as well, leading recurring costs specialised crews in advanced technologies activities. study aims show impact advancements on STDs’ enhance quality illustrate improve experiences. A comprehensive literature review has been conducted agenda. Moreover, presents real examples context better understand potential tool. The findings current support idea multipurpose helps manage, monitor, analyse sales information; revenue management; minimise prediction errors; streamline operations; strategies, optimising resources, reducing costs, responding dynamically changing tourists residents Furthermore, investment products services, attract investments, which benefit regional economies population’s life. first address use STDs, its primary uniqueness. Also, identifies opportunities initiatives through can be developed help

Language: Английский

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Synergistic Integration of Digital Twins and Neural Networks for Advancing Optimization in the Construction Industry: A Comprehensive Review

Construction Materials and Products, Journal Year: 2024, Volume and Issue: 7(4), P. 7 - 7

Published: Aug. 9, 2024

The object of research is the potential application digital twins and neural network modeling for optimizing construction processes. Method. Adopting a perspective approach, conducts an extensive review existing literature delineates theoretical framework integrating technologies. Insights from inform development methodologies, while case studies practical applications are explored to deepen understanding these integrated approaches system optimization. Results. yields following key findings: Digital Twins: Offer capability create high-fidelity virtual representations physical systems, enabling real-time data collection, analysis, visualization throughout project lifecycle. This allows proactive decision-making, improved constructability enhanced coordination between design field operations. Neural Network Modeling: Possesses power learn complex relationships vast datasets, predictive optimization behavior. networks can be employed forecast timelines, identify risks, optimize scheduling resource allocation. Integration Twins Networks: Presents transformative avenue processes by facilitating data-driven design, maintenance equipment infrastructure, performance monitoring. synergistic approach lead significant improvements in efficiency, reduced costs, overall quality.

Language: Английский

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Advances and Challenges of Digital Twin Technology in Urban Drainage Systems

Sustainable Development, Journal Year: 2025, Volume and Issue: 15(01), P. 46 - 54

Published: Jan. 1, 2025

Language: Английский

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Moving beyond 3D digital representation to behavioral digital twins in building, infrastructure, and urban assets

Advanced Engineering Informatics, Journal Year: 2025, Volume and Issue: unknown, P. 103130 - 103130

Published: Jan. 1, 2025

Language: Английский

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AIoT-powered building digital twin for smart firefighting and super real-time fire forecast

Advanced Engineering Informatics, Journal Year: 2025, Volume and Issue: 65, P. 103117 - 103117

Published: Jan. 21, 2025

Language: Английский

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