Application of Cloud Computing in Industrial Internet of Things

Special Issue Editors


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Guest Editor
Cyber Technology Institute, De Montfort University, The Gateway, Leicester LE1 9BH, UK
Interests: cloud computing; internet of things; industrial internet of things; edge computing; edge AI; AI in cyber security

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Guest Editor
Cyber Technology Institute, De Montfort University, The Gateway, Leicester LE1 9BH, UK
Interests: machine learning; deep learning; security and privacy; internet of things; cryptography
Special Issues, Collections and Topics in MDPI journals

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Guest Editor
Institute of Computer Science, University of Tartu, Narva Mnt. 18, 51009 Tartu, Estonia
Interests: chemoinformatics; distributed systems; software engineering

Special Issue Information

Dear Colleagues,

The Internet of Things (IoT) has become a global network that interconnects an extensive range of devices, enabling them to collect and exchange data, thereby facilitating advancements across a large number of sectors. The Industrial Internet of Things (IIoT) builds upon this interconnected fabric, specifically tailored to industrial environments, where it enhances operational efficiency by integrating machine learning and big data technology to harness sensor data, machine-to-machine (M2M) communication, and automation technologies. Cloud computing serves as the cornerstone of the IIoT infrastructure, providing a dynamic, scalable, and powerful platform for data processing and analytics. The integration of cloud computing into the IIoT paradigm is instrumental in reducing decision-making latency, optimising resources, and enhancing privacy protection.

This Special Issue invites academics, professionals, and business experts to exchange knowledge in this rapidly growing field. It comprehensively covers the most recent developments in the closely linked topics of Industrial Internet of Things and cloud computing.

Researchers are encouraged to contribute their unpublished original findings on the following topics, although they are not limited to them:

  • Cloud-based big data analytics and machine learning in IIoT;
  • Cloud service models for IIoT device management;
  • Digital twins using the cloud for IIoT;
  • Security and privacy of cloud-based IIoT;
  • Energy-efficient cloud computing in IIoT;
  • Impact of 5G/6G on cloud-integrated IIoT;
  • Blockchain as a cloud service for IIoT;
  • Edge computing in IIoT;
  • Cloud-driven supply chain optimisation in IIoT;
  • Optimisation of algorithms for cloud-based IIoT systems;
  • Cloud-enhanced smart manufacturing and robotics.

We look forward to receiving your contributions. 

Dr. Muhammad Kazim
Dr. Mujeeb Ur Rehman
Dr. Stefan Kuhn
Guest Editors

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Keywords

  • cloud computing
  • internet of things
  • industrial internet of things
  • security and privacy
  • big data analytics
  • machine learning
  • digital twins
  • supply chain optimisation
  • smart manufacturing and robotics
  • blockchain
  • edge computing

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Published Papers (1 paper)

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Research

21 pages, 7488 KiB  
Article
Low-Cost Embedded System Applications for Smart Cities
by Victoria Alejandra Salazar Herrera, Hugo Puertas de Araújo, César Giacomini Penteado, Mario Gazziro and João Paulo Carmo
Big Data Cogn. Comput. 2025, 9(2), 19; https://doi.org/10.3390/bdcc9020019 - 22 Jan 2025
Viewed by 545
Abstract
The Internet of Things (IoT) represents a transformative technology that allows interconnected devices to exchange data over the Internet, enabling automation and real-time decision making in a variety of areas. A key aspect of the success of the IoT lies in its integration [...] Read more.
The Internet of Things (IoT) represents a transformative technology that allows interconnected devices to exchange data over the Internet, enabling automation and real-time decision making in a variety of areas. A key aspect of the success of the IoT lies in its integration with low-resource hardware, such as low-cost microprocessors and microcontrollers. These devices, which are affordable and energy efficient, are capable of handling basic tasks such as sensing, processing, and data transmission. Their low cost makes them ideal for IoT applications in low-income communities where the government is often absent. This review aims to present some applications—such as a flood detection system; a monitoring system for analog and digital sensors; an air quality measurement system; a mesh video network for community surveillance; and a real-time fleet management system—that use low-cost hardware such as ESP32, Raspberry Pi, and Arduino, and the MQTT protocol used to implement low-cost monitoring systems applied to improve the quality of life of people in small cities or communities. Full article
(This article belongs to the Special Issue Application of Cloud Computing in Industrial Internet of Things)
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