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Big data analytics for manufacturing internet of things: opportunities, challenges and enabling technologies

- Dai, Hong-Ning, Wang, Hao, Xu, Guangquan, Wan, Jiafu, Imran, Muhammad

  • Authors: Dai, Hong-Ning , Wang, Hao , Xu, Guangquan , Wan, Jiafu , Imran, Muhammad
  • Date: 2020
  • Type: Text , Journal article
  • Relation: Enterprise Information Systems Vol. 14, no. 9-10 (2020), p. 1279-1303
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  • Description: Data analytics in massive manufacturing data can extract huge business values while can also result in research challenges due to the heterogeneous data types, enormous volume and real-time velocity of manufacturing data. This paper provides an overview on big data analytics in manufacturing Internet of Things (MIoT). This paper first starts with a discussion on necessities and challenges of big data analytics in manufacturing data of MIoT. Then, the enabling technologies of big data analytics of manufacturing data are surveyed and discussed. Moreover, this paper also outlines the future directions in this promising area. © 2019 Informa UK Limited, trading as Taylor & Francis Group.

Unmanned aerial vehicle for internet of everything : opportunities and challenges

- Liu, Yalin, Dai, Hong-Ning, Wang, Qubeijian, Shukla, Mahendra, Imran, Muhammad

  • Authors: Liu, Yalin , Dai, Hong-Ning , Wang, Qubeijian , Shukla, Mahendra , Imran, Muhammad
  • Date: 2020
  • Type: Text , Journal article , Review
  • Relation: Computer Communications Vol. 155, no. (2020), p. 66-83
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  • Description: The recent advances in information and communication technology (ICT) have further extended Internet of Things (IoT) from the sole “things” aspect to the omnipotent role of “intelligent connection of things”. Meanwhile, the concept of internet of everything (IoE) is presented as such an omnipotent extension of IoT. However, the IoE realization meets critical challenges including the restricted network coverage and the limited resource of existing network technologies. Recently, Unmanned Aerial Vehicles (UAVs) have attracted significant attentions attributed to their high mobility, low cost, and flexible deployment. Thus, UAVs may potentially overcome the challenges of IoE. This article presents a comprehensive survey on opportunities and challenges of UAV-enabled IoE. We first present three critical expectations of IoE: (1) scalability requiring a scalable network architecture with ubiquitous coverage, (2) intelligence requiring a global computing plane enabling intelligent things, (3) diversity requiring provisions of diverse applications. Thereafter, we review the enabling technologies to achieve these expectations and discuss four intrinsic constraints of IoE (i.e., coverage constraint, battery constraint, computing constraint, and security issues). We then present an overview of UAVs. We next discuss the opportunities brought by UAV to IoE. Additionally, we introduce a UAV-enabled IoE (Ue-IoE) solution by exploiting UAVs's mobility, in which we show that Ue-IoE can greatly enhance the scalability, intelligence and diversity of IoE. Finally, we outline the future directions in Ue-IoE. © 2020 Elsevier B.V.
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