Intelligent Connectivity

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Intelligent Connectivity, Wiley
AI, IoT, and 5G
Von Abdulrahman Yarali, im heise Shop in digitaler Fassung erhältlich
(Hinweis: DRM-geschützt)

EXPLORE THE ECONOMICS AND TECHNOLOGY OF AI, IOT, AND 5G INTEGRATION Intelligent Connectivity: AI, IoT, and 5G delivers a comprehensive technological and economic analysis of intelligent connectivity and the integration of artificial intelligence, Internet of Things (IoT), and 5G. It covers a broad range of topics, including Machine-to-Machine (M2M) architectures, edge computing, cybersecurity, privacy, risk management, IoT architectures, and more. The book offers readers robust statistical data in the form of tables, schematic diagrams, and figures that provide a clear understanding of the topic, along with real-world examples of applications and services of intelligent connectivity in different sectors of the economy. Intelligent Connectivity describes key aspects of the digital transformation coming with the 4th industrial revolution that will touch on industries as disparate as transportation, education, healthcare, logistics, entertainment, security, and manufacturing. Readers will also get access to:

* A thorough introduction to technology adoption and emerging trends in technology, including business trends and disruptive new applications
* Comprehensive explorations of telecommunications transformation and intelligent connectivity, including learning algorithms, machine learning, and deep learning
* Practical discussions of the Internet of Things, including its potential for disruption and future trends for technological development
* In-depth examinations of 5G wireless technology, including discussions of the first five generations of wireless tech

Ideal for telecom and information technology managers, directors, and engineers, Intelligent Connectivity: AI, IoT, and 5G is also an indispensable resource for senior undergraduate and graduate students in telecom and computer science programs. ABDULRAHMAN YARALI, PHD is Professor of Cybersecurity and Network Management at Murray State University, Kentucky, USA. He also has extensive industry experience in wireless communications, with his research teams completing contracts for AT&T, Nortel, Spring PCS, and more.




1 Technology Adoption and Emerging Trends

1.1 Introduction

1.2 Trends in Business technology

1.3 AI-Fueled Organizations

1.4 Connectivity of Tomorrow

1.5 Moving Beyond Marketing

1.6 Cloud Computing

1.7 Cybersecurity, Privacy, and Risk Management

1.8 Conclusion

2 Telecommunication Transformation and Intelligent Connectivity

2.1 Introduction

2.2 Cybersecurity Concerns in the 5G World

2.3 Positive Effects of Addressing Cybersecurity Challenges in 5G

2.4 Intelligent Connectivity Use-Cases

2.5 Industrial and Manufacturing Operations

2.6 Healthcare

2.7 Public Safety and Security

2.8 Conclusion

3 The Internet of Things (IoT): Potentials and the Future Trends

3.1 Introduction

3.2 Achieving the Future of IoT

3.3 Commercial Opportunities for IoT

3.4 The Industrial Internet of Things

3.5 Future Impact of IoT in Our Industry

3.6 Data Sharing in the IoT Environment

3.7 IoT Devises Environment Operation

3.8 Interoperability Issues of IoT

3.9 IoT-Cloud –Application

3.10 Regulation and Security Issues of IoT

3.11 Achieving IoT Innovations While Tackling Security and Regulation Issues

3.12 Future of IoT

3.13 Conclusion

4 The Wild Wonders of 5G Wireless Technology

4.1 Introduction

4.2 5G Architecture

4.3 5G Applications

4.4 5G Network Architecture

4.5 Security and Issues of 5G

4.6 IoT Devices in 5G Wireless

4.7 Big Data Analytics in 5G

4.8 AI Empowers a Wide Scope of Use Cases

4.9 Conclusion

5 Artificial Intelligence Technology

5.1 Introduction

5.2 Core Concepts of Artificial Intelligence

5.3 Machine Learning and Applications

5.4 Deep Learning

5.5 Neural Networks Follow a Natural Model

5.6 Classifications of Artificial Intelligence

5.7 Trends in Artificial Intelligence

5.8 Challenges of Artificial Intelligence

5.9 Funding Trends in Artificial Intelligence

5.10 Conclusion

6 AI, 5G, & IoT: Driving Forces Towards the Industry Technology Trends

6.1 Introduction

6.2 Fifth Generation of Network Technology

6.3 Internet of Things (IoT)

6.4 Industrial Internet of Things

6.5 IoT in Automotive

6.6 IoT in Agriculture

6.7 AI, IoT, and 5G Security

6.8 Conclusion

7 Intelligent Connectivity: A New Capabilities to Bring Complex Use Cases

7.1 Introduction

7.2 Machine-to-Machine Communication and the Internet of Things

7.3 Convergence of Internet of Things, Artificial Intelligence and 5G

7.4 Intelligent Connectivity Applications

7.5 Challenges and Risks of Intelligent Connectivity

7.6 Recommendations

7.7 Conclusion

8 IoT: Laws, Policies and Regulations

8.1 Introduction

8.2 Recently Published laws and Regulations

8.3 Developing Innovation and Growing the Internet of Things (DIGIT) Act

8.4 General View

8.5 Relaxation of laws by the Federal Aviation Administration's (FAA)

8.6 Supporting Innovation of Self Driving Cars by Allowing Policies

8.7 Recommendations

8.8 Conclusion

9 Artificial Intelligence and Blockchain

9.1 Introduction

9.2 Decentralized Intelligence

9.3 Applications

9.4 How Artificial Intelligence and Blockchain will Affect Society

9.5 How Augmented Reality Works

9.6 Mixed Reality

9.7 Virtual Reality

9.8 Key Components in a Virtual Reality System

9.9 Augmented Reality Uses

9.10 Applications of Virtual Reality in Business

9.11 The Future of Blockchain

9.12 Blockchain Applications

9.13 Blockchain and the Internet of Things

9.14 Law Coordination

9.15 Collaboration for Blockchain Success

10 Digital Twin Technology

10.1 Introduction

10.2 The Timeline and History of Digital Twin Technology

10.3 Technologies Employed in Digital Twin Models

10.4 The Dimension of Digital Twins Models

10.5 Digital Twin and Other Technologies

10.6 Digital Twin Technology Implementation

10.7 Benefits of Digital Twin

10.8 Application of Digital Twins

10.9 Challenges of Digital Twins

11 Artificial Intelligence, Big Data Analytics, and IoT

11.1 Introduction

11.2 Analytic

11.3 AI Technology in Big Data and IoT

11.4 AI Technology Applications and Use Cases

11.5 AI Technology Impact on the Vertical Market

11.6 AI in Big Data and IoT Market Analysis and Forecasts

11.7 Conclusion

12 Digital Transformation Trends in the Automotive Industry

12.1 Introduction

12.2 Evolution of Automotive Industry

12.3 Data-Driven Business Model and data monetization

12.4 Services of Data-Driven Business Model

12.5 Values of New Services in the New Automotive Industry

12.6 Conclusion

13 Wireless Sensors/IoT and Artificial Intelligence for Smart Grid and Smart Home

13.1 Introduction

13.2 Wireless Sensor Networks

13.3 Power Grid Impact

13.4 Benefits of Smart Grid

13.5 Internet of Things

13.6 Internet of Things on Smart Grid

13.7 Smart Grid and Artificial Intelligence

13.8 Smart Grid Programming

13.9 Conclusion

14 Artificial Intelligence, 5G and IoT: Security

14.1 Introduction

14.2 Understanding IoT

14.3 Artificial Intelligence

14.4 5G Network

14.5 Emerging Partnership of Artificial Intelligence, IoT, 5G, and Cybersecurity

14.6 Conclusion

15 Intelligent Connectivity and Agriculture

15.1 Introduction

15.2 The Potential of Wireless Sensors and IoT in Agriculture

15.3 IoT Sensory Technology with Traditional Farming

15.4 IoT Devices and Communication Techniques

15.5 IoT and all Crop Stages

15.6 Drone in Farming Applications

15.7 Conclusion

16 Applications of Artificial Intelligence, ML, and DL

16.1 Introduction

16.2 Building Artificial Intelligence Capabilities

16.3 What is Machine Learning?

16.4 Deep Learning

16.5 Machine Learning vs. Deep Learning Comparison

16.6 Feature Engineering

16.7 Application of Machine Learning

16.8 Applications of Deep learning

16.9 Future Trends

17 Big Data and Artificial Intelligence: Strategies for Leading Business Transformation

17.1 Introduction

17.2 Big Data

17.2 Machine Learning-Based Medical Systems

17.3 Artificial Intelligence for Stock Market Prediction

17.3.1 Application of Artificial Intelligence by Investors

17.4 Trends in AI and Big Data Technologies Drive Business Innovation

17.5 Driving Innovation Through Big Data

17.6 The Convergence of AI and Big Data

17.7 How AI and Big Data Will Combine to Create Business Innovation

17.8 AI and Big Data for Technological Innovation

17.9 AI and Production

17.10 AI and ML Operations Research

17.11 Collaboration Between Machines and Human

17.12 Generative Designs

17.13 Adapting to a Changing Market

17.14 Conclusion

Abdulrahman Yarali

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