Intelligent and Cognitive Techniques for Internet of Things

Submission Deadline: 01 February 2019

Submission Deadline: 01 February 2019

IEEE Access invites manuscript submissions in the area of Intelligent and Cognitive Techniques for Internet of Things.

As a large-scale network to promote information in big data, Internet of Things (IoT) has been widely used in the fields of modern intelligent services such as ecological protection, intelligent homes, food safety, energy-saving and emission-reduction, logistics, transport, and national information coverage, etc. The development of related communication and networking technologies also provides strong technical support for the popularization of the IoT. However, due to the increasing demands of multiple users for efficient access to the massive and heterogeneous IoT information, improving the autonomous cognitive ability of IoT and realizing the intelligent information transmission and optimization processing have become urgent problems. Currently, the research on intelligent and cognitive IoT is at its initial stage. Although some intelligent algorithms and self-organization networking technologies for IoT have been proposed, there still exist some problems such as complex management, high maintenance cost and insufficient self-adaptability. Moreover, the traditional self-organization networking technology has been unable to fully adapt to a more complex transmission environment due to the lack of flexible self-management ability. Hence, existing IoT technologies needs to add intelligent elements and change from “perception” to “cognition” through combining IoT with cognitive methods. In cognitive IoT, the self-organization networking technology can use the group collaboration between nodes to accomplish the common mission, which reflects wisdom, distribution, and robustness of IoT. Cognitive IoT can improve the transmission performance through establishing dynamic routing, searching optimal transmission path adaptively and optimizing configuration of each node in the network. Cognitive IoT enables organizations to learn from data coming from connected devices, sensors, machines and other sources, and infuses intelligence into business operations, customer experiences, products and people.

Motivated by the above challenges, this Special Section in IEEE Access aims to capture the state-of-the-art advances in intelligent and cognitive techniques for Internet of Things and other related research. This Special Section will trigger new research interest in intelligent and cognitive concepts from both industry and academia, aiming to solve some challenging problems in the context of intelligent and cognitive techniques. Review papers on this topic are also welcome.

The topics of interest include, but are not limited to:

  • Cognitive techniques for hybrid IoT and satellite communications
  • Spectrum sensing and spectrum sharing for cognitive IoT
  • Cognitive self-organization networks
  • Self-organization network related issues in self-maintenance and self-installation
  • Smart network management and resource allocation techniques
  • Large-scale cognitive communications and networks
  • Self-organization network related issues in self-maintenance and self-installation
  • Smart network management and resource allocation techniques
  • Self-organization network based on environmental monitoring
  • Current and future trends in cognitive IoT
  • Performance evaluation metrics of cognitive IoT
  • Optimization techniques for efficient resources planning
  • Energy management and green technology
  • Metrics, fundamental limits, and trade-offs involving cognitive IoT
  • Joint learning and cognitive radio for IoT
  • Intelligent image processing technique
  • Cloud and edge computing and identification or detection

We also highly recommend the submission of multimedia with each article as it significantly increases the visibility, downloads, and citations of articles.


Associate Editor: Min Jia, Harbin Institute of Technology, China

Guest Editors:

  1. Qilian Liang, University of Texas at Arlington, USA
  2. Jinsong Wu, University of Chile, South America
  3. Tariq S. Durrani, University of Strathclyde, UK
  4. Qihui Wu, Nanjing University Aeronautics and Astronautics, China
  5. Wei Xiang, James Cook University, Australia
  6. Xin Wang, Qualcomm Inc, USA


Relevant IEEE Access Special Sections:

  1. Mobile Edge Computing
  2. Intelligent Systems for the Internet of Things
  3. Networks of Unmanned Aerial Vehicles: Wireless Communications, Applications, Control and Modelling

IEEE Access Editor-in-Chief:
Michael Pecht, Professor and Director, CALCE, University of Maryland

Paper submission: Contact Associate Editor and submit manuscript to:

For inquiries regarding this Special Section, please contact:  jiamin@hit.edu.cn