IEEE Transactions on Consumer Electronics
Call for Papers
Special Section on “Advances in Artificial intelligence (AI) enabled Vehicular
Edge Computing (VEC) for consumer electronics"
Theme:
Smart vehicles, particularly new energy vehicles, represent a fusion of real-time
sensing, communication, and computation that transcends their role as meretransportation. From a consumer's perspective, they resemble scintillating electronic
to in the field of consumer electronics. These IoT-enabled smart vehicles constantly
generate substantial volumes of data (or tasks), encompassing both time-criticalinformation vital for driving safety and time-insensitive data relevant to infotainment
services. To address the data processing requirements, Vehicular Edge Computing(VEC) has emerged as a promising computing paradigm, focusing on the efficient
processing of tasks and data close to their source. However, VEC faces formidable
challenges due to the dynamic topology inherent in vehicular ad hoc networks(VANET), the rapid mobility of vehicles, and the inherent limitations of computing
resources in edge servers. These challenges, including the need to maintain highthroughput, underscore the complexity of VEC systems and networks.
In the field of consumer electronics, the delivery of high-quality computing services
holds paramount importance for consumers. Simultaneously, AI has achieved
remarkable breakthroughs in diverse fields such as image processing, natural
language processing, and self-driving technology. AI-enabled VEC is poised torevolutionize data processing, task offloading, and resource scheduling, particularly
from the consumer electronics perspective. However, AI-enabled VEC is also facingsome critical challenges. Some of these include the absence of a universally accepted
dataset and comprehensive methodology to guide research in this domain. Moreover,resource-constrained smart vehicles struggle to deploy computationally intensive AI
algorithms or train large AI models. The paradigm of cloud-based training and edgebased inference in AI-enabled VEC requires further investigation to reach its fullpotential. Additionally, there are substantial concerns related to cyber-physical security
and the reliability of AI-enabled VEC systems. These challenges serve as a compelling
motivation for the proposal of this special section dedicated to AI-enabled VEC for
consumer electronics. Its primary objective is to bring together the latest and highquality research studies to foster substantial progress in this burgeoning field,
ultimately benefiting consumers and advancing the state of consumer electronics.
Topics of interest in this Special Section include (but are not limited to):•AI-enabled crowdsensing for smart vehicle applications

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DNN based theory/model/architecture for VECIntelligent localization, navigation, and tracking in VEC
Vehicular networks with autonomous systems for consumer electronics
Deep reinforcement learning for VECIntelligent algorithm design for task offloading, data processing and resourcescheduling
Caching assisted task undertaking in VEC for consumer electronics
Information model & protocols facilitating AI-enabled VEC for consumer
electronics
Human-vehicle interactive intelligence for consumer electronics
Privacy & security schemes targeting AI-enabled VEC for consumer electronics
Demonstration of prototypes/systems of AI-enabled VEC for consumer
electronics

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Important dates:•End of submission of Manuscripts: March 31, 2024•

Expected publication date (tentative): 4th quarter 2024

Guest Editors:••••

Huaming Wu, Tianjin University , China, Email: whming@tju.edu.cn
Chaogang Tang, China University of Mining and Technology, China, Email:cgtang@cumt.edu.cn
Shui Yu, University of Technology Sydney, Australia, Email: Shui.yu@uts.edu.au
Ruidong Li, Kanazawa University, Japan, Email: lrd@se.kanazawa-u.ac.jp

Instructions for authors:
Manuscripts
shouldbepreparedfollowing
guidelines
at:https://ctsoc.ieee.org/publications/ieee-transactions-on-consumer-electronics.html
and must be submitted online following the IEEE Transactions on Consumer
Electronics
instructions:
https://ctsoc.ieee.org/publications/ieee-transactions-onconsumer-electronics.html. During submission, the Special Section on “Advances in
Artificial intelligence (AI) enabled Vehicular Edge Computing (VEC) for
consumer electronics” should be selected.