Survey of advances and challenges in intelligent autonomy for distributed cyber-physical systems

CAAI Transactions on Intelligence Technology

article

David W. McKee¹  Stephen J. Clement¹  Jaber Almutairi¹  Jie Xu¹ 

[1] Faculty of Engineering, School of Computing, University of Leeds

关键词: security of data;    cloud computing;    Big Data;    production engineering computing;    Internet of Things;    cyber-physical systems;    smart cities;    energy conservation;    intelligent manufacturing systems;    service-oriented architecture;    big data;    distributed cyber-physical systems;    smart cities;    fog computing;    complex cyber-physical systems;    deep learning;    autonomous systems;    autonomous vehicles;    energy efficiency;    smart manufacturing;    data streams;    computational infrastructure;    intelligent autonomy survey;    internet of things;    edge computing;    cloud computing;    smart systems;    automating systems;    augmenting systems;    integrating systems;    healthcare;    intelligence service;    data safety;    data security;    C6110B Software engineering techniques;    C6130S Data security;    C6170K Knowledge engineering techniques;    C7480 Production engineering computing;    E0410D Industrial applications of IT;    E0430 Information resources and networks;    E1510 Manufacturing systems;    C6190J Internet software;   

DOI  :  10.1049/trit.2018.0010

学科分类：数学（综合）

来源: Wiley

【 摘 要 】

With the evolution of the Internet of things and smart cities, a new trend of the Internet of simulation has emerged to utilise the technologies of cloud, edge, fog computing, and high-performance computing for design and analysis of complex cyber-physical systems using simulation. These technologies although being applied to the domains of big data and deep learning are not adequate to cope with the scale and complexity of emerging connected, smart, and autonomous systems. This study explores the existing state-of-the-art in automating, augmenting, and integrating systems across the domains of smart cities, autonomous vehicles, energy efficiency, smart manufacturing in Industry 4.0, and healthcare. This is expanded to look at existing computational infrastructure and how it can be used to support these applications. A detailed review is presented of advances in approaches providing and supporting intelligence as a service. Finally, some of the remaining challenges due to the explosion of data streams; issues of safety and security; and others related to big data, a model of reality, augmentation of systems, and computation are examined.

【 授权许可】

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