Artificial Intelligence Techniques for Autonomous Moving Platforms (AMP) in 5G and Beyond

  in Special Issue   Posted on May 5, 2020

Information for the Special Issue

Submission Deadline: Thu 01 Jul 2021
Journal Impact Factor : 3.111
Journal Name : Computer Networks
Journal Publisher:
Website for the Special Issue: https://www.journals.elsevier.com/computer-networks/call-for-papers/special-issue-on-artificial-intelligence-techniques-for-auto
Journal & Submission Website: https://www.journals.elsevier.com/computer-networks

Special Issue Call for Papers:

Autonomous Moving Platforms (AMP) have gained a lot of popularity in the recent times due to their usage in wide range of applications in modern smart cities including healthcare, transportation, disaster management, crowd sensing, surveillance, object localization and identification, service delivery to name a few. AMP include unmanned aerial vehicles (UAVs), autonomous underwater vehicles (AUVs), autonomoussurface vehicles (ASVs) as

well as autonomous land vehicles (ALVs). It has been observed from the literature that AMPs applications are not limited to aerial traffic management but these are being used in water, and on earth surface in various applications as mentioned above. For providing QoS and QoE for all these applications, an efficient communication infrastructure support is required so that information can be transferred on time. With an advent of 5G communications, AMPs are expected to extend their usage in a wide range of applications in domestic as well as commercial fields in years to come. For example, in a report released by US Federation Aviation Administration, the number of AMPs is expected to increase to 2.4 million by 2022 which can be used in many emerging applications. Also, the commercial AMPs market is anticipated to reach 17 billion by the year 2024. These insights have fuelled the use of AMPs in various domains. However, for smooth delivery of services to the end users, a strong backbone architecture support is required which can influence the delivered QoS and QoE. So, to augment the potential usage of AMPs, it is important to integrate 5G backbone infrastructure in AMP using 5G based heterogeneous networks which provides minimum latency.

5G wireless network is an emerging technology which includes high data rates, low latency in transmission results in an increase in the reliability of service. There is a considerable difference in QoS provisions from the currently available 4G networks due to the limited capacity of base stations. There are two ways in which the AMP can be integrated into 5G networks. First, by making it a user itself using the cellular network for mission exclusive applications. Second, by making them aerial base stations for the cellular operator. AMP communication is categorized into three domains viz AMP – to- AMP, AMP – to- ground stations and AMP – to- satellite stations. However, eertain problems such as collision among the aerial devices, resource allocation/management, managing the huge amount of data in real-time, transmission delay due to atmospheric hindrance and susceptibility to security breaches need to be handled efficiently.

We envision that artificial intelligence techniques can play an important role in providing possible solutions to the problems mentioned above. As compared to existing algorithms artificial intelligence are capable of processing enormous amounts of heterogeneous raw data using automatic hierarchical feature extraction mechanisms. Thus, they can achieve refined information and reduce pre-processing efforts. If used in wireless communication, especially in the 5G environment, artificial intelligence can overcome the limitations of existing traditional problem-solving approaches.

This proposed special invited proposals from researchers, academicians, industry professionals, and scholars in the related areas to share their valuable insights and state-of-the-art results on usage of artificial intelligence and 5G enabled for AMP communications. Prospective authors are invited to submit articles on topics including, but not limited to:

  • Artificial Intelligence Techniques for signal processing in 5G-enabled Autonomous Moving Platforms (AMP)
  • Artificial Intelligence Techniques for traffic monitoring in 5G-enabled Autonomous Moving Platforms (AMP)
  • Artificial Intelligence Techniques for Spatio-temporal data mining in 5G-enabled Autonomous Moving Platforms (AMP)
  • Artificial Intelligence Techniques for Data collection, analysis, processing and delivery in 5G-enabled Autonomous Moving Platforms (AMP)
  • Artificial Intelligence Techniques for Distributed caching and security in 5G-enabled in Autonomous Moving Platforms (AMP)
  • Artificial Intelligence Techniques for Energy-efficiency in 5G-enabled Autonomous Moving Platforms (AMP)
  • Artificial Intelligence Techniques for UAV path planning in 5G-enabled Autonomous Moving Platforms (AMP)
  • Artificial Intelligence Techniques for resource allocation in 5G-enabled Autonomous Moving Platforms (AMP)
  • Artificial Intelligence Techniques for object detection and localization in 5G-enabled Autonomous Moving Platforms (AMP)
  • Artificial Intelligence Techniques for security and privacy preservation in 5G-enabled Autonomous Moving Platforms (AMP)
  • Artificial Intelligence Techniques for network management in 5G-enabled Autonomous Moving Platforms (AMP)

Submission Guidelines

Submitted papers should present original, unpublished work, relevant to one of the topics of the Special Issue. All submitted papers will be evaluated on the basis of relevance, significance of contribution, technical quality, and quality of presentation, by at least three independent reviewers. Manuscripts are requested according to the Guide for Authors available from the online submission page of the COMPUTER NETWORKS at https://www.evise.com/profile/#/COMNET/login. We invite the prospective authors to submit their manuscript, via the online submission system in the main journal page. Please make sure you mention in your cover letter that you are submitting to this special issue.

Important Dates

Manuscripts Due: 15 October2020
Feedback to Authors: 15 January 2021
Revised Manuscripts Due: 15 February 2021
Second-Round Reviews to Authors: 15 March2021
Final Accepted Manuscript Due: July 2021

 

Guest Editors

Prof. Neeraj Kumar

Thapar Institute of Engineering and Technology, Patiala, India

Email: neeraj.kumar@thapar.edu

Prof. Min Chen

Huazhong University of Science and Technology, China

Emailminchen@ieee.org

 

Dr. Xinlei Chen

Carnegie Mellon University, USA

Emailxinlei.chen@sv.cmu.edu

 

Dr. Tamer Khattab

Qatar University, Doha, Qatar

Emailtkhattab@ieee.org

 

Dr. Ammar Rayes

Cisco Systems, USA

Emailrayes@cisco.com

 

Dr. Xiaoyong Yuan

Michigan Technological University, USA

Email: chbrian@ufl.edu

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