Table of Content

Cooperative ML/DL and Intelligent Networks towards Vehicle Health Monitoring System (VHMS)

Submission Deadline: 31 December 2022 Submit to Special Issue

Guest Editors

Dr. Md Arafatur Rahman, University of Wolverhampton, United Kingdom
Dr. Arif Reza Anwary, Edinburgh Napier University, United Kingdom
Dr. Nour Moustafa, University of New South Wales, Australia

Summary

The dependency on vehicles is increasing tremendously due to its excellent transport capacity, fast, efficient, flexible, pleasant journey, minimal physical effort, and substantial economic impact. As a result, the demand for smart and intelligent feature enhancement is growing and becoming a prime concern for maximum productivity based on the current perspective. In this case, the Internet of Everything (IoE) is an emerging concept that can play an essential role in the automotive industry by integrating the stakeholders, process, data, and things via networked connections. But the unavailability of intelligent features leads to negligence about proper maintenance of vehicle vulnerable parts, reckless driving and severe accident, lack of instructive driving, and improper decision, which incurred extra expenses for maintenance besides hindering national economic growth.


It is therefore a challenge to choose the best methodologies for a central VHMS exploiting IoE-driven Multi-Layer Heterogeneous Networks (HetNet) and AI techniques to oversee individual vehicle health conditions, notify the respective owner driver real-timely and store the information for further necessary action. Another challenge is to find methodologies for VHMS, IoE-driven Multi-tire HetNet, with a secure and trustworthy data collection and analytics system. The aim of this Special Issue is to show recent and novel applications of VHMS in the field of automotive sector. This special issue aims to share and exchange innovative theories, practices, and approaches in Vehicular technologies and communications to unveil the challenging issues associated in deploying the VHMS applications. It may motivate the researcher to develop a central intelligent and secure vehicular condition diagnostic system to move this sector towards Industry 4.0.


List of potential topics include, but are not limited to:

· Innovative Technologies for VHMS

· VHMS framework/architecture towards Industry 4.0

· Technology support of essential VHMS operations

· Interventions and disaster risk reduction technologies

· VHMS science, participatory surveillance, and crowdsourcing

· Intelligent Networks for VHMS

· Internet of Things/sensors for VHMS

· Heterogeneous Networks infrastructure and/or architecture for VHMS

· Big data modeling and machine learning on VHMS

· VHMS response to emergencies

· Technology in community engagement for VHMS

· Methodological and technological challenges in VHMS

· Methodological and technological challenges in the implementation, transfer, and/or scaling up of VHMS

· Studies on the effectiveness and safety for VHMS

· Economic impact on VHMS– cost-effectiveness, budgetary impact, and opportunity costs  

· Micro-service for VHMS

· Security for VHMS

· Essential security protocols for VHMS

· Secure data analytics for VHMS

· Intrusion detection and resiliency for VHMS

· Secure development of VHMS

· Privacy-enhanced technologies for VHMS

· Relation of security and safety for VHMS

· Data Analytics for VHMS

· VHMS decision-support systems

· Artificial intelligence, machine/deep learning and other computational techniques in VHMS

· Application of Robotics in VHMS

· Psycho-social and behavioral aspects of VHMS

· Augmented, virtual and mixed reality in VHMS

· Governance, ethical and legal challenges of VHMS data and technologies

· Cybersecurity in VHMS



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