基本服务的数字孪生

IF 6.2 2区计算机科学 Q1 COMPUTER SCIENCE, THEORY & METHODS

Future Generation Computer Systems-The International Journal of Escience Pub Date : 2025-09-18 DOI:10.1016/j.future.2025.108147

Alessio Bucaioni, Jakob Axelsson, Moris Behnam, Enxhi Ferko

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引用次数: 0

摘要

数字孪生，即物理系统的动态数字表示，正在成为加强关键社会部门危机准备和复原力的变革性工具。通过实现实时监控、模拟和优化，这些技术提供了可操作的见解，以支持主动降低风险、有效分配资源和持续改进危机响应策略。本研究提供了数字孪生的全面知识概述，重点关注其在能源、医疗保健和交通等关键领域的适用性和影响。具体来说，它研究了最适合采用数字孪生的基本服务，安全关键数据在其整个生命周期中的作用，以及它们在识别和减轻关键基础设施风险方面的效用。我们采用了混合方法的研究设计，将系统和灰色文献综述与专家访谈相结合，将学术见解与实践观点相结合。研究结果揭示了数字孪生体在提高运营效率、战略规划和危机管理方面的重大机遇。然而，实际实现仍处于起步阶段，面临着与成本、复杂性和有限的实际应用相关的挑战。此外，本研究还为利益相关者提供了可操作的建议，强调了对数字孪生技术的投资、稳健的数据治理和标准化协议的开发。未来的研究方向包括探索直接决策在危机准备和社会复原力等新兴领域的应用，推进人工智能集成，以及采用系统的视角全面应对社会挑战。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Digital twins for essential services

Digital twins, dynamic digital representations of physical systems, are emerging as transformative tools for enhancing crisis preparedness and resilience in critical societal sectors. By enabling real-time monitoring, simulation, and optimization, these technologies offer actionable insights to support proactive risk mitigation, efficient resource allocation, and continuous improvement of crisis response strategies. This study provides a comprehensive knowledge overview of digital twins, focusing on their applicability and impact in key sectors such as energy, healthcare, and transportation. Specifically, it examines the essential services most suited for digital twin adoption, the role of safety-critical data throughout their life-cycle, and their utility in identifying and mitigating risks within critical infrastructure. We employed a mixed-methods research design, combining systematic and gray literature reviews with expert interviews to integrate academic insights with practical perspectives. The findings reveal significant opportunities for digital twins to enhance operational efficiency, strategic planning, and crisis management. However, practical implementation remains in its infancy, with challenges related to cost, complexity, and limited real-world applications. In addition, this study provides actionable recommendations for stakeholders, emphasizing investment in digital twin technologies, robust data governance, and the development of standardized protocols. Future research directions include exploring applications of DTs in emerging sectors, such as crisis preparedness and societal resilience, advancing artificial intelligence integration, and adopting a system-of-systems perspective to address societal challenges comprehensively.

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来源期刊

Future Generation Computer Systems-The International Journal of Escience 工程技术-计算机：理论方法

CiteScore

19.90

自引率

2.70%

发文量

376

审稿时长

10.6 months

期刊介绍： Computing infrastructures and systems are constantly evolving, resulting in increasingly complex and collaborative scientific applications. To cope with these advancements, there is a growing need for collaborative tools that can effectively map, control, and execute these applications. Furthermore, with the explosion of Big Data, there is a requirement for innovative methods and infrastructures to collect, analyze, and derive meaningful insights from the vast amount of data generated. This necessitates the integration of computational and storage capabilities, databases, sensors, and human collaboration. Future Generation Computer Systems aims to pioneer advancements in distributed systems, collaborative environments, high-performance computing, and Big Data analytics. It strives to stay at the forefront of developments in grids, clouds, and the Internet of Things (IoT) to effectively address the challenges posed by these wide-area, fully distributed sensing and computing systems.