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.
Sprache
Verlagsort
Verlagsgruppe
Zielgruppe
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Höhe: 250 mm
Breite: 175 mm
Dicke: 23 mm
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ISBN-13
978-1-119-68518-0 (9781119685180)
Schweitzer Klassifikation
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 5th 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
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