社论:人类数字孪生技术

M. Tada, T. Inamura
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引用次数: 0

摘要

随着物联网、人工智能等信息技术的发展,网络物理系统正在进入社会。这些系统的核心是数字孪生,即建立在网络空间中的物理实体的计算机模型(孪生),用于基于模拟的预测。目前,数字孪生主要针对人造物体,如飞机发动机和工厂。然而,如果它可以扩展到人类,它可以导致实现人机协作系统和健康促进服务,从而解决社会老龄化带来的社会问题。然而,人类是系统中最薄弱的环节,如果要实现人类数字孪生,还需要解决许多技术问题,例如实现对人类行为的测量、建模和预测。这期特刊包含了9篇关于开发人类数字孪生的关键技术和构建特定应用的人机系统的论文。涵盖的主题包括学习算法、运动测量和分析技术、人类感知、系统开发和系统开发的平台软件。这些都清楚地表明,跨学科的努力对于实现人类数字孪生至关重要。我们感谢为本期特刊提交论文的作者。我们相信,作者提供的信息对专家和非专业人士都具有启发性和信息性。我们也衷心感谢审稿人的努力。他们的贡献使本期特刊成为可能。我们希望这期特刊能够在实现人类数字孪生的道路上,促进跨研究领域的共享。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Editorial: Human Digital Twin Technology
With the advancement of information technologies such as the Internet of Things and artificial intelligence, cyber-physical systems are being introduced into society. At the core of these systems is the digital twin, a computer model (twin) of a physical entity built in cyberspace for simulation-based prediction. Currently, the digital twin mainly targets artificial objects, such as aircraft engines and factories. However, if it can be extended to humans, it could lead to the realization of human-machine cooperative systems and health promotion services, thereby solving social issues stemming from the aging of society. However, humans are the weakest link in the system, and many technical problems remain to be solved, such as realizing the measurement, modeling, and prediction of human behavior, if the human digital twin is to become reality. This special issue contains 9 papers on developing essential technologies for the human digital twin and constructing human-machine systems for specific applications. The topics covered include learning algorithms, motion measurement and analysis techniques, human perception, system development, and platform software for system development. These clearly show that cross-disciplinary efforts are essential to the realization of the human digital twin. We thank the authors of the papers submitted for this special issue. We are confident that the information provided by the authors is suggestive and informative for both specialists and non-specialists alike. We also sincerely appreciate the efforts of the reviewers. Their contributions helped to make this special issue possible. We hope that this special issue will catalyze sharing across the boundaries of research fields along the path to realizing a human digital twin.
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