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Data and Decision Intelligence for Human-in-the-Loop Cyber-Physical Systems: Reference Model, Recent Progresses and Challenges

机译:人在环网络物理系统的数据和决策智能:参考模型,最新进展和挑战

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摘要

With the rapid development of sensing technology, Cyber-Physical Systems (CPS) are connecting our real-world and cyber spaces by real-time situation awareness and intelligent control. In this process, one of the major challenge is how to make fast, accurate and intelligent decisions based on high-dimension, speed and volume sensing data stream. In this paper, we put human into the traditional CPS data process model and formulate a closed-loop computing paradigm for CPS data and decision intelligence. We propose a human-in-the-loop reference model for CPS, which extends the traditional cyber-physical interaction into a closed-loop process based on cyber, physical and human factors. We define the key features of human-in-the-loop CPS, summarize it as three aspects: semantic, interactive, iterative and analyze the major challenges from the perspective of data characteristics. Recent progresses in three typical application domains are reviewed and examined for their decision models and whether they have solved the target issues of human-in-the-loop CPS. According to the review and comparison, the paper finally summarizes several key future opportunities to establish an intelligent human-in-the-loop CPS.
机译:随着传感技术的飞速发展,网络物理系统(CPS)通过实时的态势感知和智能控制将我们的现实世界与网络空间联系在一起。在此过程中,主要挑战之一是如何基于高维度,速度和体积感测数据流做出快速,准确和智能的决策。在本文中,我们将人引入了传统的CPS数据处理模型,并为CPS数据和决策智能制定了闭环计算范例。我们提出了一种针对CPS的人在环参考模型,该模型将传统的网络与物理交互扩展为基于网络,物理和人为因素的闭环过程。我们定义了在环CPS的关键特征,将其概括为三个方面:语义,交互,迭代,并从数据特征的角度分析了主要挑战。对三个典型应用领域的最新进展进行了审查和检查,以了解它们的决策模型以及它们是否已经解决了“人在环CPS”的目标问题。根据审查和比较,本文最后总结了建立智能的在环CPS的几个关键的未来机会。

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