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Smart city article details
| Title | Building Resilient Smart Cities: The Role Of Digital Twins And Generative Ai In Disaster Management Strategy |
|---|---|
| ID_Doc | 13070 |
| Authors | Razavi H.; Titidezh O.; Asgary A.; Bonakdari H. |
| Year | 2024 |
| Published | Urban Sustainability, Part F3988 |
| DOI | http://dx.doi.org/10.1007/978-981-97-8483-7_5 |
| Abstract | The advent of Digital Twin (DT) technology represents a significant milestone in the evolution of smart city management, introducing virtual models and data-driven simulations that enhance our understanding, planning, and management of urban environments. Generative Artificial Intelligence (GenAI) integration enriches digital twins by boosting their predictive capabilities and simulating more realistic and interactive scenarios. By leveraging generative algorithms, digital twins can create synthetic data, to simulate a wide range of potential outcomes. These additional capabilities enable more accurate modeling of complex systems, predicting variations and potential issues. Moreover, Generative AI can contribute to creating high-quality simulations, improving the accuracy and reliability of digital twins in representing real-world environments and processes. This chapter provides an exploration of the synergies between GenAI and digital twins in the context of disaster management and smart cities. The chapter begins with an introduction, offering a contextual background integrating generative AI and digital twins for simulating disaster and emergency scenarios. It then delves into the foundations of generative AI, discussing its principles, applications, and success stories across various domains, with a specific focus on its relevance to urban disaster management. The subsequent sections clarify the evolution of digital twins and their pivotal role in predicting and mitigating disasters and emergency response. The chapter then navigates the intersection between generative AI and digital twins and the functionalities that GenAI brings to improving the simulation process, providing examples of successful integrations while addressing potential challenges and proposing solutions. Furthermore, it explores how smart cities contribute to disaster resilience, detailing the technologies and strategies employed for disaster preparedness. The chapter concludes with an in-depth analysis of specific GenAI-enhanced digital twins’ applications in disaster management, anticipating future challenges and developments in the field, and emphasizing emerging trends and potential directions. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024. |
| Author Keywords | Data synthesis; Digital twin; Disaster and emergency management; Generative AI; Scenario generation; Smart cities; Urban intelligence; Urban resilience |
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