A digital twin is defined as a virtual representation of a physical asset enabled through data and simulators for real-time prediction, optimization, monitoring, controlling, and improved decision-making. Unfortunately, the term remains vague and says little about its capability. Recently, the concept of capability level has been introduced to address this issue. Based on its capability, the concept states that a digital twin can be categorized on a scale from zero to five, referred to as standalone, descriptive, diagnostic, predictive, prescriptive, and autonomous, respectively. The current work introduces the concept in the context of the built environment. It demonstrates the concept by using a modern house as a use case. The house is equipped with an array of sensors that collect timeseries data regarding the internal state of the house. Together with physics-based and data-driven models, these data are used to develop digital twins at different capability levels demonstrated in virtual reality. The work, in addition to presenting a blueprint for developing digital twins, also provided future research directions to enhance the technology.
翻译:数字双胞胎被定义为通过实时预测、优化、监测、控制和改进决策的数据和模拟器所促成的有形资产的虚拟表示。不幸的是,该词仍然模糊不清,对其能力没有多少说明。最近,引入了能力水平概念来解决这一问题。基于其能力,该概念指出,数字双胞胎可分为零至五级,分别称为独立、描述、诊断、预测、指令和自主。目前的工作在建筑环境的背景下引入了这一概念。它通过使用现代房子来展示这一概念。该房子配备一系列传感器,收集有关室内内部状况的时间序列数据。这些数据与基于物理学和数据驱动的模式一起,用于在虚拟现实中展示不同能力层次上开发数字双胞胎。除了提出发展数字双胞胎的蓝图外,这项工作还为加强技术提供了未来的研究方向。