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Secure and Reliable Big-Data-Based Decision Making Using Quantum Approach in IIoT Systems.

Abir El Azzaoui1, Mikail Mohammed Salim1, Jong Hyuk Park1

  • 1Department of Computer Science and Engineering, Seoul National University of Science and Technology, Seoul 01811, Republic of Korea.

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Summary
This summary is machine-generated.

Quantum computing offers a powerful solution for industrial Internet of Things (IIoT) challenges. This research introduces a quantum cloud model for smart factories, enhancing scalability and productivity.

Keywords:
IIoTquantum algorithmsquantum approximate optimization algorithmquantum neural networksmart factory

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Area of Science:

  • Quantum Information Science
  • Computer Science
  • Industrial Engineering

Background:

  • Industrial Internet of Things (IIoT) and smart factories face significant computational and data processing challenges with big data analytics.
  • Classical solutions like machine learning, cloud computing, and artificial intelligence (AI) are becoming insufficient for complex IIoT systems.
  • The rapid advancement of Quantum Information Systems (QIS) presents opportunities for more efficient and faster data processing.

Purpose of the Study:

  • To explore the implementation of quantum solutions for reliable and sustainable IIoT-based smart factory development.
  • To identify applications where quantum algorithms can enhance the scalability and productivity of IIoT systems.
  • To propose a universal system model enabling smart factories to leverage quantum computing without direct hardware ownership.

Main Methods:

  • Discussing the application of quantum algorithms in IIoT systems.
  • Designing a universal system model utilizing quantum cloud servers and edge-based quantum terminals.
  • Implementing and evaluating two real-world case studies to demonstrate model feasibility.

Main Results:

  • Quantum algorithms show potential for improving scalability and productivity in IIoT systems.
  • The proposed quantum cloud model allows smart factories to run quantum algorithms without needing expert knowledge or quantum hardware.
  • Case study evaluations confirm the benefits of quantum solutions across various smart factory sectors.

Conclusions:

  • Quantum computing offers a viable and beneficial approach to address current limitations in IIoT and smart factory big data processing.
  • The developed quantum cloud model provides accessible and efficient quantum algorithm execution for industrial applications.
  • This research highlights the transformative potential of quantum solutions for the future of smart manufacturing.