Literature DB >> 35531371

A Survey on Industrial Internet of Things: A Cyber-Physical Systems Perspective.

Hansong Xu1, Wei Yu1, David Griffith2, Nada Golmie2.   

Abstract

The vision of Industry 4.0, otherwise known as the fourth industrial revolution, is the integration of massively deployed smart computing and network technologies in industrial production and manufacturing settings for the purposes of automation, reliability, and control, implicating the development of an Industrial Internet of Things (I-IoT). Specifically, I-IoT is devoted to adopting the Internet of Things (IoT) to enable the interconnection of anything, anywhere, and at anytime in the manufacturing system context to improve the productivity, efficiency, safety and intelligence. As an emerging technology, I-IoT has distinct properties and requirements that distinguish it from consumer IoT, including the unique types of smart devices incorporated, network technologies and quality of service requirements, and strict needs of command and control. To more clearly understand the complexities of I-IoT and its distinct needs, and to present a unified assessment of the technology from a systems perspective, in this paper we comprehensively survey the body of existing research on I-IoT. Particularly, we first present the I-IoT architecture, I-IoT applications (i.e., factory automation (FA) and process automation (PA)) and their characteristics. We then consider existing research efforts from the three key systems aspects of control, networking and computing. Regarding control, we first categorize industrial control systems and then present recent and relevant research efforts. Next, considering networking, we propose a three-dimensional framework to explore the existing research space, and investigate the adoption of some representative networking technologies, including 5G, machine-to-machine (M2M) communication, and software defined networking (SDN). Similarly, concerning computing, we again propose a second three-dimensional framework that explores the problem space of computing in I-IoT, and investigate the cloud, edge, and hybrid cloud and edge computing platforms. Finally, we outline particular challenges and future research needs in control, networking, and computing systems, as well as for the adoption of machine learning, in an I-IoT context.

Entities:  

Keywords:  Application and Service; Big Data Analytics; Computing; Control; Future Research Directions; Industrial Cyber Physical Systems; Industrial Internet of Things; Machine Learning; Networking; Survey

Year:  2018        PMID: 35531371      PMCID: PMC9074819          DOI: 10.1109/access.2018.2884906

Source DB:  PubMed          Journal:  IEEE Access        ISSN: 2169-3536            Impact factor:   3.476


  3 in total

1.  Towards Integrating Distributed Energy Resources and Storage Devices in Smart Grid.

Authors:  Guobin Xu; Wei Yu; David Griffith; Nada Golmie; Paul Moulema
Journal:  IEEE Internet Things J       Date:  2016-12-15       Impact factor: 9.471

2.  Combining Fog Computing with Sensor Mote Machine Learning for Industrial IoT.

Authors:  Mehrzad Lavassani; Stefan Forsström; Ulf Jennehag; Tingting Zhang
Journal:  Sensors (Basel)       Date:  2018-05-12       Impact factor: 3.576

3.  Efficient Deployment of Key Nodes for Optimal Coverage of Industrial Mobile Wireless Networks.

Authors:  Xiaomin Li; Di Li; Zhijie Dong; Yage Hu; Chengliang Liu
Journal:  Sensors (Basel)       Date:  2018-02-10       Impact factor: 3.576

  3 in total
  1 in total

1.  Delay and Energy Consumption of MQTT over QUIC: An Empirical Characterization Using Commercial-Off-The-Shelf Devices.

Authors:  Sidna Jeddou; Fátima Fernández; Luis Diez; Amine Baina; Najid Abdallah; Ramón Agüero
Journal:  Sensors (Basel)       Date:  2022-05-12       Impact factor: 3.847

  1 in total

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