Deep Learning Based Solutions for Vehicular Adhoc Networks

Language: English

Published by Springer, Springer Jun 2025, 2025

9819651891 / 9789819651894

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This item is printed on demand - Print on Demand Titel. Neuware -This book provides a holistic and comprehensive approach to deep learning for vehicular ad hoc networks (VANETs), covering various aspects such as applications, agency involvement, and potential ethical and legal issues. It begins with discussions on how the transportation system has been converted into Intelligent Transportation System (ITS). The use of VANETs is increasing in the development of ITS to enhance road safety, traffic efficiency, and driver comfort. However, the dynamic nature of vehicular environments and the high mobility of vehicles pose significant challenges to designing and implementing VANETs and ensuring reliable and efficient communication. Deep learning, a subset of machine learning, has the potential to revolutionize vehicular ad hoc networks (VANETs) to enable various applications such as traffic management, collision avoidance, and infotainment. DL has demonstrated great potential in addressing various challenges involved in VANETs by leveraging its ability to learn from vast data and make accurate predictions. It reviews the state-of-the-art DL-based approaches for various applications in VANETs, including routing, congestion control, autonomous driving, and security. In addition, this book provides a comprehensive analysis of these approaches' advantages and limitations and discusses their future research directions. The study in this book shows that DL-based techniques can significantly improve the performance and reliability of VANETs. Still, in-depth research is required to address the challenges of deploying these methods in real-world scenarios. Finally, the book discusses the potential of DL-based VANETs in supporting other emerging technologies, such as autonomous driving and smart cities. It explores the simulation/emulation tools for practical exposure to the vehicular ad hoc network.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 408 pp. Englisch.

Seller Inventory # 9789819651894

Title
Deep Learning Based Solutions for Vehicular Adhoc Networks
Author
Jitendra Bhatia
Publisher
Springer, Springer Jun 2025
Publication year
2025
Condition
Neu
Binding
Buch
Language
English
ISBN 10
9819651891
ISBN 13
9789819651894
Item weight
848 grams
Dimensions
241x160x26 mm

buchversandmimpf2000

Emtmannsberg, BAYE, Germany

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