research-article

AI-Based Vehicular Network toward 6G and IoT: Deep Learning Approaches

Authors:

Li-Xiang HuangAuthors Info & Claims

ACM Transactions on Management Information System (TMIS), Volume 13, Issue 1

Article No.: 6, Pages 1 - 12

https://doi.org/10.1145/3466691

Published: 05 October 2021 Publication History

Abstract

In recent years, vehicular networks have become increasingly large, heterogeneous, and dynamic, making it difficult to meet strict requirements of ultralow latency, high reliability, high security, and massive connections for next generation (6G) networks. Recently, deep learning (DL) has emerged as a powerful artificial intelligence (AI) technique to optimize the efficiency and adaptability of vehicle and wireless communication. However, rapidly increasing absolute numbers of vehicles on the roads are leading to increased automobile accidents, many of which are attributable to drivers interacting with their mobile phones. To address potentially dangerous driver behavior, this study applies deep learning approaches to image recognition to develop an AI-based detection system that can detect potentially dangerous driving behavior. Multiple convolutional neural network (CNN)-based techniques including VGG16, VGG19, Densenet, and Openpose were compared in terms of their ability to detect and identify problematic driving.

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Cited By

Annu Rajalakshmi P(2024)Towards 6G V2X Sidelink: Survey of Resource Allocation—Mathematical Formulations, Challenges, and Proposed SolutionsIEEE Open Journal of Vehicular Technology10.1109/OJVT.2024.33682405(344-383)Online publication date: 2024
https://doi.org/10.1109/OJVT.2024.3368240
Wan YQu YNi WXiang YGao LHossain E(2024)Data and Model Poisoning Backdoor Attacks on Wireless Federated Learning, and the Defense Mechanisms: A Comprehensive SurveyIEEE Communications Surveys & Tutorials10.1109/COMST.2024.336145126:3(1861-1897)Online publication date: 1-Jul-2024
https://dl.acm.org/doi/10.1109/COMST.2024.3361451
Tian QZhang SMao SLin Y(2024)Adversarial attacks and defenses for digital communication signals identificationDigital Communications and Networks10.1016/j.dcan.2022.10.01010:3(756-764)Online publication date: Jun-2024
https://doi.org/10.1016/j.dcan.2022.10.010
Show More Cited By

Index Terms

AI-Based Vehicular Network toward 6G and IoT: Deep Learning Approaches
1. Computing methodologies
  1. Artificial intelligence
  2. Machine learning
2. Information systems
  1. Information systems applications

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Published In

cover image ACM Transactions on Management Information Systems

ACM Transactions on Management Information Systems Volume 13, Issue 1

March 2022

203 pages

ISSN:2158-656X

EISSN:2158-6578

DOI:10.1145/3483343

Editor:
Daniel Zeng
Chinese Academy of Sciences, China

Issue’s Table of Contents

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 05 October 2021

Accepted: 01 May 2021

Revised: 01 April 2021

Received: 01 December 2020

Published in TMIS Volume 13, Issue 1

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Ministry of Science and Technology (MOST), Taiwan, R.O.C.

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Cited By

Annu Rajalakshmi P(2024)Towards 6G V2X Sidelink: Survey of Resource Allocation—Mathematical Formulations, Challenges, and Proposed SolutionsIEEE Open Journal of Vehicular Technology10.1109/OJVT.2024.33682405(344-383)Online publication date: 2024
https://doi.org/10.1109/OJVT.2024.3368240
Wan YQu YNi WXiang YGao LHossain E(2024)Data and Model Poisoning Backdoor Attacks on Wireless Federated Learning, and the Defense Mechanisms: A Comprehensive SurveyIEEE Communications Surveys & Tutorials10.1109/COMST.2024.336145126:3(1861-1897)Online publication date: 1-Jul-2024
https://dl.acm.org/doi/10.1109/COMST.2024.3361451
Tian QZhang SMao SLin Y(2024)Adversarial attacks and defenses for digital communication signals identificationDigital Communications and Networks10.1016/j.dcan.2022.10.01010:3(756-764)Online publication date: Jun-2024
https://doi.org/10.1016/j.dcan.2022.10.010
Spitzer EMiles R(2023)A Survey of the Interpretability Aspect of Deep Learning ModelsJournal of Biomedical and Sustainable Healthcare Applications10.53759/0088/JBSHA202303006(56-65)Online publication date: 5-Jan-2023
https://doi.org/10.53759/0088/JBSHA202303006
Zeng YChen XJin R(2023)Ensemble Active Learning by Contextual Bandits for AI Incubation in ManufacturingACM Transactions on Intelligent Systems and Technology10.1145/362782115:1(1-26)Online publication date: 19-Dec-2023
https://dl.acm.org/doi/10.1145/3627821
Guo Q(2023)Style Recognition and Generation Model Simulation of Sculpture Works Based on Machine Learning Algorithm2023 International Conference on Internet of Things, Robotics and Distributed Computing (ICIRDC)10.1109/ICIRDC62824.2023.00063(309-314)Online publication date: 29-Dec-2023
https://doi.org/10.1109/ICIRDC62824.2023.00063
Parikh SMoharana A(2023)A Survey of ML for the Physical Layer in 5G and Future Wireless Networks2023 International Conference on Artificial Intelligence and Smart Communication (AISC)10.1109/AISC56616.2023.10084939(1315-1322)Online publication date: 27-Jan-2023
https://doi.org/10.1109/AISC56616.2023.10084939
K. JS. R(2022)Defending IoT Security Infrastructure with the 6G Network, and Blockchain and Intelligent Learning Models for the Future Research RoadmapChallenges and Risks Involved in Deploying 6G and NextGen Networks10.4018/978-1-6684-3804-6.ch012(177-203)Online publication date: 24-Jun-2022
https://doi.org/10.4018/978-1-6684-3804-6.ch012
Tanveer JHaider AAli RKim A(2021)Machine Learning for Physical Layer in 5G and beyond Wireless Networks: A SurveyElectronics10.3390/electronics1101012111:1(121)Online publication date: 30-Dec-2021
https://doi.org/10.3390/electronics11010121

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