This book focuses on the fusion between the core technologies of the future ? Artificial Intelligence (AI), 5G, and the Internet of Things (IoT), exploring how they can be mutually supportive. AI, IoT, and 5G are the pillars that lead digital transformation, and the combination of super-fast 5th generation networks with AI and IoT will usher in a new age of intelligent connectivity, particularly beneficial to transportation, logistics, education, healthcare, entertainment, public safety/security and industrial and manufacturing operations. The book will offer technical and economic insights about intelligent connectivity as a key part of transformation in the 4th industrial revolution. The reader (technical and non-technical) will benefit from a comprehensive discussion of Artificial Intelligence, 5G, IoT and machine-learning and how they are vital in the period of open-source programming and moderate cloud computing.

Abdulrahman Yarali, Coordinator, Telecommunications Systems Management and Cybersecurity, Professor at Murray State University, USA. Professor Yarali received his BS, MS, and Ph.D. in Electrical Engineering from the University of Florida, George Washington University and Virginia Polytechnic Institute and State University respectively. During tenure in the wireless industry, he led research teams working on location, completing numerous contracts in wireless mobile communications systems design, implementation and optimization for leading telecommunications companies such as AT&T, NORTEL, and Sprint PCS in the U.S. He has been a faculty member at Institute of Engineering and TSM program at MSU since 2003 where he has developed a wireless option program for undergraduate students. His interest continues to be focused in the field of higher generations of wireless mobile communications systems, small satellites, IoT, Cloud and smart grid infrastructures. Dr. Yarali has presented articles, lectures, and keynote presentation in mobile communications networking and security in North America, the Middle East, and Europe.

 

              Preface

               Acknowledgement

               Introduction

 

 

1            Technology Adoption and Emerging Trends

1.1         Introduction

  1.2       Trends in Business technology

1.2.1      Trends that could disturb the industry

1.2.2      Adopting New Technology

     1.2.3       Best Practices and Risks Associated with Emerging Technologies

1.2.4       Power of Disruptive Technology

1.2.5       Driving Strategy Around our Priority

1.2.6       Strategic Partnerships to be Pursued

1.3          AI-Fueled Organizations

1.4          Connectivity of Tomorrow

1.4.1       Intelligent Interfaces

1.5         Moving Beyond Marketing

1.6         Cloud Computing

1.7         Cybersecurity, Privacy, and Risk Management

1.8         Conclusion

                References       

 

2           Telecommunication Transformation and Intelligent Connectivity

2.1        Introduction

2.1.1     Learning Algorithm and its Connections to AI

2.1.2     Machine Learning as a Precursor to AI

2.1.3      Deep Learning and Realization of AI

2.1.4      Consideration of the Next Generation Wireless Technology

2.1.5      Potential of AI and 5G Network Technology Together

2.2         Cybersecurity Concerns in the 5G World

2. 2.1     5G's potential in making Security a Priority

2.2.2       Key Features

2.2.2.1  Peak Data Rate

2.2.2.2  Mobile Data Volume

2.2.2.3  Mobility

2.2.2.4  Connected Devices

2.2.2.5  Energy Efficiency

2.2.2.6  Service Deployment

2.2.2.7 Reliability

2.2.2.8 Latency

2.3         Positive Effects of Addressing Cybersecurity Challenges in 5G

2.4         Intelligent Connectivity Use-Cases

2.4.1      Transportation and Logistics

2.4.2      AI-based Driver Assistance and Monitoring2.4.3 Self-Driving Vehicles

2.4.3      Self-Driving Vehicles

2.4.4      Deliveries with Unmanned Vehicles

2.5         Industrial and Manufacturing Operations

2.5.1      Factory Automation and Remote Control of Industrial Robots

 

2.5.2      Remote Inspections and Maintenance, and Worker's Training

2.6         Healthcare

2.6.1      Remote Health Monitoring and Illness Prevention

2.6.2      Remote Diagnosis and Medical Operation

2.7         Public Safety and Security

2.7.1      Intelligent Video-Surveillance and Security Systems

2.7.2      Emergency Services and Border Controls

2.7.3      Other Sectors

2.7.3.1 Virtual Personal Assistance

2.7.3.2 3D Hologram Displays

2.8         Conclusion

References

 

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

3.4.1      How IIoT Works

3.4.2      Benefits of IIoT

3.4.3      IIoT versus IoT

3.4.4      IIoT Applications and Examples

3.4.5      Vendors in IIoT

3.4.6      The Future of IIoT

3.5         Future Impact of IoT in Our Industry

3.6         Data Sharing in the IoT Environment

3.7         IoT Devises Environment Operation

3.7.1      Step One: Pick Your Protocol

3.7.2      Step Two: Understand Coexistence

3.7.3      Step Three: Pick Your Technique

3.7.4      Step Four: Create Your Test plan

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

               References

 

4             The Wild Wonders of 5G Wireless Technology

4.1         Introduction

4.1.1      First Generation (1G)

4.1.2      Second Generation (2G)

4.1.3      Third generation (3G)

4.1.4      Advanced third generation (3.5G)

4.1.5      Fourth Generation (4G)

4.1.6      Fifth Generation (5G)

4.2         5G Architecture

4.3         5G Applications

4. 3.1     5G and Video Surveillance

4.3.2      5G and Fixed Wireless Access (FWA)

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

References

 

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

5.7.1      Artificial Intelligence in Energy

5.7.2      Artificial Intelligence in Healthcare

5.7.3      Artificial Intelligence in Education

5.7.4      Artificial Intelligence in Manufacturing

5.7.5      Artificial Intelligence in Financial Services

5.7.6      Artificial Intelligence in Transport

5.8         Challenges of Artificial Intelligence

5.8.1      Data

5.8.1.1 Data Quantity and Quality

5.8.1.2 Data Labeling

5.8.1.3 Clarity

5.8.1.4  Case-Specific Learning

5.8.1.5 Bias

5.1.8.6 Model Accuracy

5.8.1.7 People

5.8.1.8 Deficiency of Field Experts

5.8.1.9 Business

5.8.1.10 Challenges in Evaluating Vendors

5.8.1.11 Challenges with Integration

5.8.1.12 Legal Matters

5.9         Funding Trends in Artificial Intelligence

5.9.1      Artificial Readiness

5.9.2      Foundational Readiness

5.9.3      Operational Readiness

5.9.3      Transformational Readiness

5.10       Conclusion

References

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

References

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

7.1         Introduction

7.1.1      Artificial intelligence

 7.1.2     The 5^th Generation Networks

7.1.3      The Internet of Things

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

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

7.3.1      The Benefits of Intelligent Connectivity

7.4         Intelligent Connectivity Applications

7.4.1      Industry

7.4.2      Transport and Logistics

7.4.3      Healthcare

7.4.4      Security

7.4.5      Smart homes, and Personal Assistant

7.4.6      Wearable Technology

7.4.7      Entertainment

7.4.8      Communication

7.4.9      Resource Management

7.4.10   Agriculture

7.4.11   Education

7.5         Challenges and Risks of Intelligent Connectivity

7.5.1      Economic Risks

7.5.3      Risks to Human Safety and Agency

7.5.4      Social Risk

7.5.5      Secondary Risks

7.5.6      Confidentiality and Scalability

7.6         Recommendations

7.7         Conclusion

References

 

8             IoT: Laws, Policies and Regulations

8.1         Introduction

8.2         Recently Published laws and Regulations

8.2 .1     IoT Cybersecurity Improvement Act of 2017

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

8.6.1      Investment by US Department of Home Land Security

8.6.2      United States Guiding Principles for IoT Security

8.6.3      The United Kingdom on IoT

8.6.4      United States Department of Commerce

8.6.5      Federal Trade Commission & Creating IoT Security Solution

8.7         Recommendations

8.8         Conclusion

References

 

9             Artificial Intelligence and Blockchain

9.1         Introduction

9.2         Decentralized Intelligence

9.2.1      Data Protection

9.2.2      Trusting AI Decision Making

9.2.3      AI and Encryption

9.3         Applications

9.3.1      The Coordination of Blockchain into AI

9.3.2      Essential Blockchain Benefits

9.4         How Artificial Intelligence and Blockchain will Affect Society

9.4.1      Banking and Payments

9.4.2      Cybersecurity

9.4.3      Internet of Things

9.4.4      Unified Communications

9.4.5      Government

9.4.6      Crowdfunding and Donating to Charities

9.4.7      Healthcare

9.4.8      Rentals and Ride-Sharing

9.4.9      Augmented Reality

9.4.10   Augmented Reality in the Production Context

9.5         How Augmented Reality Works

9.5.1      Marker and Marker-less AR

9.5.2      Layered AR

9.5.3      Projection AR

9.5.4      AR in Education

9.5.5      AR in Navigation

9.5.6      AR in Games

9.6         Mixed Reality

9.7         Virtual Reality

9.7.1      Virtual World

9.7.2      Mental Immersion

9.7.3      Physical Immersion

9.7.4      Tangible Feedback

 

9.7.5      Intelligence

9.7.6      Types of Virtual Reality

9.7.7      Semi-Immersive                                                                       

9.7.8      Completely Immersive

9.8         Key Components in a Virtual Reality System

9.8.1      PC (Personal Computer)/Console/Smartphone

9.8.2      Head-Mounted Display

9.8.3      Information Devices

9.8.4      Augmented Reality versus Augmented Reality

9.8.5      Benefits of Augmented Reality

9.9         Augmented Reality Uses

9.9.1      Retail

9.9.2      Real Estate

9.9.3      Interior Design

9.9.4      Tourism and Maps

9.9.5      Training and Education

9.9.6      Healthcare

9.10       Applications of Virtual Reality in Business

9.10.1   Training

9.10.2   Retail

9.10.3   Construction

9.10.4   Data Representation

9.10.5   Manufacture

9.11       The Future of Blockchain

9.12       Blockchain Applications

9.12.1   National Cryptographic Money

9.12.2   Blockchain into Government

9.12.3   Blockchain Specialists

9.13       Blockchain and the Internet of Things

9.14       Law Coordination

9.15       Collaboration for Blockchain Success

References

 

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

10.3.1   Cloud Services

10.3.2   Cyber-Physical Systems

10.4       The Dimension of Digital Twins Models

10.4       The Dimension of Digital Twins Models

10.4.1   Digital Twins Data

10.4.2   Services in Digital Twins

10.4.3   Connection in Digital Twins

10.4.5   Physical Assets in Digital Twins

10.4.6   Virtual Entities in Digital Twins

10.5       Digital Twin and Other Technologies

10.5.1   Digital Twins and Internet of Things

10.5.2   Digital Twins and Artificial Intelligence

10.5.3   Digital Twins and Analytics

10.5.4   Digital Twins and Connectivity

10.5.5   Digital Twins and Machine Learning

10.6       Digital Twin Technology Implementation

10.7       Benefits of Digital Twin

10.8       Application of Digital Twins

10.8.1   Manufacturing

10.8.2   Healthcare

10.8.3   Smart Cities

10.8.4   Space Exploration

10.8.5   Business

10.9       Challenges of Digital Twins

10.9.1   Privacy and Data Security

10.9.2   Infrastructure

10.9.3   Data

10.9.4   Trust

10.9.5   Expectations

References

 

11          Artificial Intelligence, Big Data Analytics, and IoT

11.1       Introduction

11.2       Analytic

11.2.1   Predictive Analytics

11.2.2   Prescriptive Analytics

11.2.3   Descriptive Analytics

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

11.5.1   AI Predictive Analytics in Vertical Market 

11. 6      AI in Big Data and IoT Market Analysis and Forecasts

11.7       Conclusion

References

 

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

12.3.1   Big Data

12.3.2   Product Development

12.4       Services of Data-Driven Business Model

12.5       Values of New Services in the New Automotive Industry

12.5.1   Consumer Trust

12.6       Conclusion

References

 

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

13.6.1   Smart Grid Security

13.7       Smart Grid and Artificial Intelligence

13.8       Smart Grid Programming

13.9       Conclusion

References

 

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

14.5.1   The Current State of IoT Security

14.6      Conclusion

             References

 

 

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

15.3.1   IoT Sensors Available for Specific Agriculture Applications

15.3.2   Challenges Faced while Implementing Sensor Technologies

 15.4      IoT Devices and Communication Techniques

15.5       IoT and all Crop Stages

15.6       Drone in Farming Applications

15.7       Conclusion

References

 

16          Applications of Artificial Intelligence, ML, and DL

16.1       Introduction

16.2       Building Artificial Intelligence Capabilities

16.3       What is Machine Learning?

16.3.1   Machine Learning Methods

16.4       Deep Learning

16.4.1   Use cases

16.4.2   The Working Mechanism

16.4.3   Deep Learning Models

16.4.4   Deep Learning and MATLAB

16.5       Machine Learning vs. Deep Learning Comparison

16.5.1   Data Dependencies

16.5.2   Hardware Dependencies

16.5.3   Problem Solving Approach

16.6       Feature Engineering

16.6.1   Layer -Wise Features by Deep Learning

16.6.2   Execution time in DL

16.6.3   Interpretability

16.7       Application of Machine Learning

16.8       Applications of Deep learning

16.9       Future Trends

References

 

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

17.1       Introduction

17.2       Big Data

17.1.2   Big Data Need for Organizations

17.1.3   Big data and Applications

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

17.8.1   Disruptive Innovation

17.8.2   Recruitment of Skilled Taskforce

17.8.3   Reliable Performance

17.9       AI and Production

17.10     AI and ML Operations Research

17.10.1                Smart Maintenance

17.10.2                Intelligent Manufacturing

17.10.3                IoT-Enabled Manufacturing

17.10.4                Cloud Manufacturing

17.10.5                Suitability of ML with AI

17.11     Collaboration Between Machines and Human

17.12     Generative Designs

17.13     Adapting to a Changing Market

17.14     Conclusion

References

 

 

 

Index