Artificial intelligent techniques for wireless communication and networking / edited by R. Kanthavel, [and three others].

Format:

Book

Contributor:

Kanthavel, R., 1974- editor.

Language:

English

Subjects (All):

Artificial intelligence--Computer programs.

Artificial intelligence.

Wireless communication systems.

Physical Description:

1 online resource (330 pages)

Place of Publication:

Hoboken, New Jersey : John Wiley & Sons, Inc., [2022]

Summary:

ARTIFICIAL INTELLIGENT TECHNIQUES FOR WIRELESS COMMUNICATION AND NETWORKING The 20 chapters address AI principles and techniques used in wireless communication and networking and outline their benefit, function, and future role in the field. Wireless communication and networking based on AI concepts and techniques are explored in this book, specifically focusing on the current research in the field by highlighting empirical results along with theoretical concepts. The possibility of applying AI mechanisms towards security aspects in the communication domain is elaborated; also explored is the application side of integrated technologies that enhance AI-based innovations, insights, intelligent predictions, cost optimization, inventory management, identification processes, classification mechanisms, cooperative spectrum sensing techniques, ad-hoc network architecture, and protocol and simulation-based environments. Audience Researchers, industry IT engineers, and graduate students working on and implementing AI-based wireless sensor networks, 5G, IoT, deep learning, reinforcement learning, and robotics in WSN, and related technologies.

Contents:

Intro

Table of Contents

Title Page

Copyright

Preface

1 Comprehensive and Self-Contained Introduction to Deep Reinforcement Learning

1.1 Introduction

1.2 Comprehensive Study

1.3 Deep Reinforcement Learning: Value-Based and Policy-Based Learning

1.4 Applications and Challenges of Applying Reinforcement Learning to Real-World

1.5 Conclusion

References

2 Impact of AI in 5G Wireless Technologies and Communication Systems

2.1 Introduction

2.2 Integrated Services of AI in 5G and 5G in AI

2.3 Artificial Intelligence and 5G in the Industrial Space

2.4 Future Research and Challenges of Artificial Intelligence in Mobile Networks

2.5 Conclusion

3 Artificial Intelligence Revolution in Logistics and Supply Chain Management

3.1 Introduction

3.2 Theory-AI in Logistics and Supply Chain Market

3.3 Factors to Propel Business Into the Future Harnessing Automation

3.4 Conclusion

4 An Empirical Study of Crop Yield Prediction Using Reinforcement Learning

4.1 Introduction

4.2 An Overview of Reinforcement Learning in Agriculture

4.3 Reinforcement Learning Startups for Crop Prediction

4.4 Conclusion

5 Cost Optimization for Inventory Management in Blockchain and Cloud

5.1 Introduction

5.2 Blockchain: The Future of Inventory Management

5.3 Cost Optimization for Blockchain Inventory Management in Cloud

5.4 Cost Reduction Strategies in Blockchain Inventory Management in Cloud

5.5 Conclusion

6 Review of Deep Learning Architectures Used for Identification and Classification of Plant Leaf Diseases

6.1 Introduction

6.2 Literature Review

6.3 Proposed Idea

6.4 Reference Gap

6.5 Conclusion

7 Generating Art and Music Using Deep Neural Networks

7.1 Introduction

7.2 Related Works.

7.3 System Architecture

7.4 System Development

7.5 Algorithm-LSTM

7.6 Result

7.7 Conclusions

8 Deep Learning Era for Future 6G Wireless Communications-Theory, Applications, and Challenges

8.1 Introduction

8.2 Study of Wireless Technology

8.3 Deep Learning Enabled 6G Wireless Communication

8.4 Applications and Future Research Directions

Conclusion

9 Robust Cooperative Spectrum Sensing Techniques for a Practical Framework Employing Cognitive Radios in 5G Networks

9.1 Introduction

9.2 Spectrum Sensing in Cognitive Radio Networks

9.3 Collaborative Spectrum Sensing for Opportunistic Access in Fading Environments

9.4 Cooperative Sensing Among Cognitive Radios

9.5 Cluster-Based Cooperative Spectrum Sensing for Cognitive Radio Systems

9.6 Spectrum Agile Radios: Utilization and Sensing Architectures

9.7 Some Fundamental Limits on Cognitive Radio

9.8 Cooperative Strategies and Capacity Theorems for Relay Networks

9.9 Research Challenges in Cooperative Communication

9.10 Conclusion

10 Natural Language Processing

10.1 Introduction

10.2 Conclusions

11 Class Level Multi-Feature Semantic Similarity-Based Efficient Multimedia Big Data Retrieval

11.1 Introduction

11.2 Literature Review

11.3 Class Level Semantic Similarity-Based Retrieval

11.4 Results and Discussion

12 Supervised Learning Approaches for Underwater Scalar Sensory Data Modeling With Diurnal Changes

12.1 Introduction

12.2 Literature Survey

12.3 Proposed Work

12.4 Results

12.5 Conclusion and Future Work

13 Multi-Layer UAV Ad Hoc Network Architecture, Protocol and Simulation

13.1 Introduction

13.2 Background

13.3 Issues and Gap Identified

13.4 Main Focus of the Chapter

13.5 Mobility.

13.6 Routing Protocol

13.7 High Altitude Platforms (HAPs)

13.8 Connectivity Graph Metrics

13.9 Aerial Vehicle Network Simulator (AVENs)

13.10 Conclusion

14 Artificial Intelligence in Logistics and Supply Chain

14.1 Introduction to Logistics and Supply Chain

14.2 Recent Research Avenues in Supply Chain

14.3 Importance and Impact of AI

14.4 Research Gap of AI-Based Supply Chain

15 Hereditary Factor-Based Multi-Featured Algorithm for Early Diabetes Detection Using Machine Learning

15.1 Introduction

15.2 Literature Review

15.3 Objectives of the Proposed System

15.4 Proposed System

15.5 HIVE and R as Evaluation Tools

15.6 Decision Trees

15.7 Results and Discussions

15.8 Conclusion

16 Adaptive and Intelligent Opportunistic Routing Using Enhanced Feedback Mechanism

16.1 Introduction

16.2 Related Study

16.3 System Model

16.4 Experiments and Results

16.5 Conclusion

17 Enabling Artificial Intelligence and Cyber Security in Smart Manufacturing

17.1 Introduction

17.2 New Development of Artificial Intelligence

17.3 Artificial Intelligence Facilitates the Development of Intelligent Manufacturing

17.4 Current Status and Problems of Green Manufacturing

17.5 Artificial Intelligence for Green Manufacturing

17.6 Detailed Description of Common Encryption Algorithms

17.6.1 Triple DES (3DES)-(Triple Data Encryption Standard)

17.7 Current and Future Works

17.8 Conclusion

18 Deep Learning in 5G Networks

18.1 5G Networks

18.2 Artificial Intelligence and 5G Networks

18.3 Deep Learning in 5G Networks

19 EIDR Umpiring Security Models for Wireless Sensor Networks

19.1 Introduction

19.2 A Review of Various Routing Protocols

19.3 Scope of Chapter.

19.4 Conclusions and Future Work

20 Artificial Intelligence in Wireless Communication

20.1 Introduction

20.2 Artificial Intelligence: A Grand Jewel Mine

20.3 Wireless Communication: An Overview

20.4 Wireless Revolution

20.5 The Present Times

20.6 Artificial Intelligence in Wireless Communication

20.6.1 How the Two Worlds Collided

20.6.2 Cognitive Radios

20.7 Artificial Neural Network

20.8 The Deployment of 5G

20.9 Looking Into the Features of 5G

20.10 AI and the Internet of Things (IoT)

20.11 Artificial Intelligence in Software-Defined Networks (SDN)

20.12 Artificial Intelligence in Network Function Virtualization

20.13 Conclusion

Index

Also of Interest

End User License Agreement.

Notes:

Description based on print version record.

Includes bibliographical references and index.

ISBN:

9781119821793

1119821797

9781119821809

1119821800

9781119821786

1119821789

OCLC:

1301901984