Hyper-Intelligent Networks : Exploring the Future of Connectivity for Society 5. 0.

Format:

Book

Author/Creator:

Gantayat, Pradosh Kumar.

Series:

Industry 5. 0 Transformation Applications Series

Language:

English

Subjects (All):

Computer networks--Technological innovations.

Computer networks.

Physical Description:

1 online resource (523 pages)

Edition:

1st ed.

Place of Publication:

Newark : John Wiley & Sons, Incorporated, 2026.

Summary:

Prepare for the next technological frontier with this essential, multidisciplinary guide that delves into hyper-intelligent networks, providing a comprehensive overview of how AI and machine learning are revolutionizing telecommunications, healthcare, and other vital sectors with cognitive, autonomous connectivity.

Contents:

Cover

Series Page

Title Page

Copyright Page

Dedication Page

Contents

Preface

Acknowledgement

Part 1: Artificial Intelligence and Blockchain in Hyper Intelligent Network

Chapter 1 Introduction to Hyper-Intelligent Networks

1.1 A Comprehensive Overview

1.2 Definition of Hyper-Intelligent Networks

1.3 Key Components of Hyper-Intelligent Networks

1.3.1 Artificial Intelligence (AI)

1.3.2 Machine Learning (ML)

1.3.3 Internet of Things (IoT)

1.3.4 Big Data Analytics (BDA)

1.3.5 Edge Computing

1.4 Literature Review

1.5 Applications of Hyper-Intelligent Networks

1.5.1 Smart Cities

1.5.2 Healthcare

1.5.3 Industrial Automation

1.5.4 Autonomous Vehicles

1.5.5 Financial Services

1.6 Challenges of Hyper-Intelligent Networks

1.6.1 Data Security and Privacy

1.6.2 Interoperability

1.6.3 Ethical Considerations

1.6.4 Reliability and Resilience

1.6.5 Scalability

1.7 Future Trends in Hyper-Intelligent Networks

1.7.1 Quantum Computing

1.7.2 5G Technology

1.7.3 Augmented Reality (AR) and Virtual Reality (VR)

1.7.4 Blockchain

1.8 Conclusions

References

Chapter 2 Hyper-Intelligence in Machine Learning: Unleashing the Next Evolution of AI

2.1 Introduction to Hyper-Intelligence

2.1.1 Defining Hyper-Intelligence

2.1.2 Historical Context

2.2 Theoretical Foundations

2.2.1 Autonomous Learning

2.2.2 Complex Problem Solving

2.2.3 Contextual Understanding

2.3 Core Technologies

2.3.1 Advanced Neural Networks

2.3.2 Reinforcement Learning (RL)

2.3.3 Meta-Learning

2.3.4 Quantum Computing

2.4 Practical Applications

2.4.1 Healthcare

2.4.2 Autonomous Systems

2.4.3 Financial Services

2.4.4 Natural Language Processing (NLP)

2.5 Ethical and Societal Implications

2.5.1 Bias and Fairness

2.5.2 Transparency.

2.5.3 Accountability

2.5.4 Privacy Concerns

2.6 Future Prospects

2.6.1 Human-AI Collaboration

2.6.2 Continuous Learning

2.6.3 Societal Transformation

2.7 Case Studies

2.8 Prospective Research Avenues

2.9 Core Technologies

2.9.1 Advanced Neural Networks

2.9.2 Reinforcement Learning

2.9.3 Pioneering Efforts

2.9.4 Neuroscience-Inspired AI

2.10 Collaborative AI

2.10.1 Breakthrough Innovations

2.10.2 Self-Supervised Learning

2.11 Challenges and Future Directions

2.11.1 Future Directions of Artificial Intelligence

2.12 Future Directions

Chapter 3 Edge Computing and Its Role in Hyper-Intelligent Networks

3.1 Introduction

3.2 Literature Review

3.3 Proposed Study

3.3.1 Critical Analysis of Wireless Communication Protocols

3.3.2 Choosing the Right Protocol for Your Smart Home Needs

3.3.3 Smart Home Communication Requirements

3.3.4 Procedure for Connection of Wireless Communication Protocol

3.4 Future Trends

3.5 Conclusion

Chapter 4 Emerging Horizons: Exploring Blockchain-Driven Hyper-Intelligent Network in Healthcare

4.1 Introduction

4.2 Understanding Blockchain

4.2.1 Role of Consensus in Blockchain

4.2.2 Criteria of Selecting a Consensus Model

4.3 Understanding Federated Learning

4.4 Related Works

4.5 Simulating Blockchain

4.5.1 Simulating Using Simulators

4.5.2 Architecture Design

4.5.3 Creating A Blockchain

4.6 Conclusion

Chapter 5 Med3: Blockchain-Based Privacy Preservation of Patient Health Records in Hyper-Intelligent Network

5.1 Introduction

5.2 Motivation

5.3 Related Work

5.4 Problem Formulation

5.5 Architecture of the Proposed Healthcare System

5.6 Results and Discussion

5.7 Conclusions and Future Work

References.

Chapter 6 Deep Learning for Hyper-Intelligent Networks

6.1 Introduction

6.1.1 Key Characteristics

6.1.2 Essential Role in Society 5.0

6.2 Importance of Deep Learning in Hyper-Intelligent Networks

6.2.1 Key Contributions of Deep Learning

6.3 Related Work

6.4 Fundamentals of Deep Learning

6.4.1 Neural Networks and Deep Learning

6.4.2 Types of Deep Learning Models

6.5 Applications of Deep Learning in Hyper-Intelligent Networks

6.5.1 Network Traffic Prediction

6.5.2 Network Security and Intrusion Detection

6.5.3 Quality-of-Service Optimization

6.5.4 Autonomous Network Management

6.6 Key Technologies and Techniques

6.7 Challenges and Limitations of Hyper-Intelligent Networks

6.8 Research Directions and Prospects for the Future

6.9 Case Study: Application of Hyper-Intelligent Networks in Smart Cities

6.10 Conclusion

Chapter 7 Machines Learning in Networking

7.1 Introduction

7.1.1 Scalability

7.1.2 Security

7.1.3 Core Concepts

7.1.4 Challenges and Considerations

7.2 Networking Challenges and Machine Learning Solution

7.3 Bandwidth Management

7.3.1 Importance of Bandwidth Management

7.3.2 Challenges in Bandwidth Management

7.3.3 Machine Learning for Traffic Prediction

7.4 Challenges and Future Directions

Conclusion

Part 2: Privacy and Security of Healthcare in Hyper Intelligent Network

Chapter 8 Security and Privacy in Hyper-Intelligent Networks

8.1 Introduction

8.1.1 Issues with Current Scenario

8.1.2 Ethical and Regulatory Challenges Required in Smart City Development

8.2 Literature Review

8.3 Proposed Study

8.3.1 Limitations on IaaS in the Context of Cloud Security

8.3.2 Limitations on PaaS in the Context of Cloud Security

8.3.3 Limitations on SaaS in the Context of Cloud Security.

8.3.4 Other Key Security Concerns for Cloud Computing

8.3.5 Access Control Challenges

8.3.6 Comparative Analysis of Existing Models

8.3.7 Findings from Comparative Analysis

8.4 Conclusion

Chapter 9 Internet-of-Things Integrated Blockchain-Based Supply Chain Management Across Various Industries

9.1 Introduction

9.2 Literature Review

9.3 Blockchain Technology

9.3.1 Blockchain Features

9.3.2 Processes in the Supply Chain

9.4 IoT in the Supply Chain

9.4.1 The Implications of the IoT on the Supply Chain

9.5 Implementing a Blockchain Supply Chain

9.5.1 Supply Chain and Logistics Blockchain and IoT Applications

9.5.2 Blockchain and IoT Benefits for Supply Chain and Logistics

9.6 Supply Chain IoT and Blockchain Use Cases

9.7 Challenges in Traditional Supply Chain

9.8 Conclusion and Feature Directions

Chapter 10 Hyper-Intelligent Networks in Healthcare

10.1 Introduction

10.2 Overview of Traditional Healthcare Systems

10.3 Challenges Faced by Healthcare Systems

10.4 Personalized Medicine and Treatment Recommendations through Hyper-Intelligent Networks in Healthcare

10.5 Predictive Analytics for Disease Prevention and Early Detection through Hyper-Intelligent Networks in Healthcare

10.6 Remote Patient Monitoring and Telemedicine through Hyper-Intelligent Networks in Healthcare

10.7 Hyper-Intelligent Networks in Shaping the Future of Healthcare

Chapter 11 AI-Driven Remote Health Monitoring for Predicting Diabetes and Heart Diseases Using ULMCSO and PGND Models

11.1 Introduction

11.2 Related Work

11.3 Proposed Methodology

11.3.1 Normalization of Datasets with Pre-Processing

11.3.2 Feature Selection Using ULMCSO Model

11.3.3 Classifying PGND

11.4 Outcome and Conversation

11.5 Conclusion

Chapter 12 Cloud Manufacturing and Intelligent Network Importance in Healthcare Applications

12.1 Introduction

12.2 Key Components

12.3 Benefits of Cloud Manufacturing

12.4 Importance of Healthcare Applications

12.4.1 Integrating Cloud Manufacturing in the Healthcare Sector

12.4.2 Efficient Resource Utilization Optimized Resource Allocation

12.4.3 Improved Data Management and Security

12.4.4 Innovation and Research Accelerate Research

12.4.5 Cooperation Platform

12.4.6 Regulatory Compliance and Reporting Simplify Compliance

12.4.7 Data Review and Traceability

12.5 Fundamentals of Cloud Manufacturing Technical Foundation

12.5.1 Internet of Things (IoT)

12.5.2 Big Data

12.5.3 Artificial Intelligence (AI) and Machine Learning (ML)

12.5.4 Traditional Healthcare Manufacturing

12.5.5 Pharmaceutical Manufacturing

12.5.6 High Cost and Low Efficiency

12.5.7 The Supply Chain is Complex Supply Chain Characteristics

12.5.8 Limited Flexibility and Scalability the Production System is Not Flexible

12.6 Quality Control and Assurance Task

12.6.1 Integration of Cloud Manufacturing in Healthcare

12.6.2 Cloud Manufacturing Platforms

12.6.3 Telemedicine and Remote Healthcare Services

12.6.4 Working

12.7 Economical Aspect

12.7.1 Improved Patient Involvement

12.7.2 Customized Prosthetics and Orthotics

12.7.3 Working

12.7.4 Outcomes

12.7.5 Drug Production and Quality Control Context

12.7.6 Smart Factory

12.8 Conclusion

Chapter 13 Analysis on E-Services Platform in Context of Intelligent Cities

13.1 Introduction

13.2 Literature Review

13.3 Research Gap

13.4 Comparative Analysis of Existing Work

13.4.1 Findings from Comparative Analysis

13.4.2 Analysis

13.4.3 Future Scope

13.5 Conclusion

Part 3: Future Trends and Applications in Hyper Intelligent Network.

Notes:

Chapter 4 Emerging Horizons: Exploring Blockchain-Driven Hyper-Intelligent Network in Healthcare

Description based on publisher supplied metadata and other sources.

ISBN:

1-394-31563-5

1-394-31562-7

9781394315628

OCLC:

1561174801