Wireless Communications and Mobile Computing

Theories, Technologies, and Applications of Artificial Intelligence in Cloud-Based Internet of Things


Publishing date
01 May 2022
Status
Open
Submission deadline
17 Dec 2021

Lead Editor

1Taif University, Taif, Saudi Arabia

2MIT World Peace University, Pune, India

3International Islamic University Malaysia, Gombak, Malaysia


Theories, Technologies, and Applications of Artificial Intelligence in Cloud-Based Internet of Things


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Description

The rapid growth in wireless communication technologies has led to the development of the Internet of Things (IoT) and the optimization of many smart applications and technologies to meet the requirements of users. The use of artificial intelligence (AI) methods in cloud-based Internet of things applications is important for making services and social interaction processes more intelligent. Smart and high-performance cloud-based Internet of Things (C-IoT) technologies have the ability to accurately identify patterns and predict operational processes, especially in industrial and self-adapting applications.

One of the most important challenges facing the smart C-IoT is how to improve the smart sensing, analysis, and management of big data. In addition, confidentiality of information and security of operations on wireless networks is one of the greatest challenges facing IoT applications. The use of artificial intelligence (AI) and its integration with wireless communication environments has several benefits, including the ability to provide smart services and automate various processes in C-IoT applications. It also helps improve the high-performance of C-IoT-based communication systems.

This Special Issue aims to present a number of basic concepts and theoretical analyses for smart IoT technologies and a set of applications that depend on the use of artificial intelligence methods, in addition to high-performance C-IoT structures. The main topics of the Special Issue will cover modern technologies for IoT networks, systems, transmission infrastructure, and data exchange. We welcome work that envisions the use of AI-powered mechanisms in a number of applications and future wireless network architectures. These will contribute to major new technological developments in this field of smart and high-performance C-IoT and current research trends in the industrial and service fields. We hope to collect a balance of theoretical and analytical issues, and to cover the analysis and evaluation of original and novel studies in the field, especially in the use of artificial intelligence-based cloud applications in IoT networks. We welcome both original research and review articles.

Potential topics include but are not limited to the following:

  • High-performance cloud-based IoT technologies, architectures, theories, and transmission
  • Cloud-based IoT security and privacy preservation and anomaly detection based on deep learning
  • Artificial Intelligent based C-IoT Systems, networks, and smart applications
  • Cloud, edge, and fog computing-based AI in the IoT
  • C-IoT data analytics based on AI technologies
  • Artificial intelligence-based low power wide area network (LPWAN) technologies and narrowband IoT (NB-IoT)
  • Quality of service (QoS) and quality of experience (QoE) for C-IoT services
  • AI-based cloud-based Internet of Underwater Things communications
  • Machine learning for industrial C-IoT
  • Machine learning and deep learning in cloud-based Internet of Vehicles (IoV)
  • Optimization algorithms and resource management in C-IoV, C-IoT, and cloud-based Internet of unmanned arial vehicles (C-IoUAV)
  • Machine learning in cyber-physical systems and its applications in C-IoT
  • Scalability for infrastructure as a service (IaaS), platform as a Service (PaaS), and software as a service (SaaS) C-IoT
  • Artificial intelligence-based cognitive radio in C-IoT, system design, spectrum sharing, and management models, and blockchain- enabled CR for cloud-based IoT systems
  • Provisioning software-defined IoT cloud systems and IoT applications with Python-based cloud simulators (PCS)
  • Cloud-based network virtualization in IoT
  • AI architectures for IoT applications and scenarios and AI accuracy
  • Large-scale training of AI models and feasibility of AI-based complex environments with multi-players
  • Trust, privacy, and explainability of AI models for C-IoT
Wireless Communications and Mobile Computing
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 Journal metrics
Acceptance rate33%
Submission to final decision81 days
Acceptance to publication37 days
CiteScore4.300
Journal Citation Indicator0.390
Impact Factor2.336

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