홈으로IssuesSpecial Issues
IssuesSpecial Issues
Artificial Intelligence and Cybertwin-assisted Pervasive Computing: Concepts, Advancements and Future Perspectives

Overview

The explosion of data volumes generated by the large number of connected devices, integrated with recent technology in terms of privacy preservation of such sensitive data that is driving the entire artificial intelligence (AI) process to the network's communication. Data users are increasingly unwilling to freely manage their sensitive data to design and develop the AI applications. Moreover, the data on the network platform is totally different from the cloud platform data that become the inspiration of new learning frameworks designed to address the various interconnected issues. This is the case, for example, with cybertwin, a context-aware distributed learning system is required in which devices carrying data information to train the shared AI models. The challenges of learning the data are numerous, since the learning algorithm must account for a variety of characteristics such as local data and device heterogeneity, technological deficiencies such as intermittent connectivity, and devices with limited CPU resources, to mention a few. Overcoming the limitations imposed by the network scenario by designing the smart pervasive models over cybertwin datasets, cybertwin metaheuristic methods, privacy mechanisms, and implementation of real systems. This special issue invites the researchers to share their research innovation and experiences for novel applications of cybertwin, distributed learning for next-generation pervasive systems.

Topics of Interests

The main topics of interest include but are not limited to the following:

• Cybertwin algorithms for network intelligent systems

• Classification of cybertwin-based pervasive systems

• Optimization algorithms in cybertwin and artificial intelligence

• Communication efficient distributed/decentralized machine learning

• Personalized cybertwin machine and deep learning methods

• Multi-modal sensing for intelligent transportation infrastructure inspection

• Artificial intelligence approaches for unmanned aerial vehicles (UAVs)

• Edge/IoT based wireless communication

• Deep learning for edge computing networks

• Training scheme of cybertwin models

Important Dates

Submission deadline: 30 March 2023

Author notification: within 4 weeks after submission

Revised manuscript due: within 2 weeks after notification

Notification of acceptance: within 2 weeks after revision submission

Tentative accepted paper publication date: within 2 months after final version

Tentative SI paper collection and its web open: 4th Quarter, 2023 (TBA)


Submission Guideline

All submitted papers must be clearly written in excellent English and contain only original work. All papers must be submitted in an electronic format, e.g., PDF format (preferred) or MS Word. Manuscripts should follow the formatting of the sample manuscript and references. You can refer to the details in the submission menu http://hcisj.com/submission/preparing_manuscript.php All papers and some supplementary materials should be submitted through ScholarOne Manuscripts. The authors must select "SI2023-01AI and Cybertwin-PerCom”. when they reach the “Article Type” step in the submission process https://mc04.manuscriptcentral.com/hcis


Guest Editors

Dr. Gaurav Dhiman (Lead Guest Editor)
Department of Computer Science and Engineering, Graphic Era Deemed to be University, India
University Centre for Research and Development, Department of Computer Science and Engineering, Chandigarh University, Gharuan, Mohali, India
Google Scholar: https://scholar.google.com/citations?user=E3Z7oJcAAAAJ&hl=en
Email: gdhiman0001@gmail.com, gauravdhiman.cse@geu.ac.in

Prof. Atulya Nagar
Liverpool Hope University, United Kingdom
Google Scholar: https://scholar.google.co.in/citations?user=uaoZ40wAAAAJ&hl=en
Email: atulya.nagar@hope.ac.uk

Prof. Wattana Viriyasitavat
Chulalongkorn University, Thailand
Google Scholar: https://scholar.google.com/citations?hl=en&user=RKI-mqcAAAAJ
Email: hardgolf@gmail.com

Dr. Vicente García-Díaz
Department of Computer Science, University of Oviedo, Spain
Google Scholar: https://scholar.google.com/citations?user=RBNrJrkAAAAJ&hl=en
Email: garciavicente@uniovi.es