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Internet of Things and Data Analytics Handbook

Hwaiyu Geng (Editor)
ISBN: 978-1-119-17364-9
800 pages
January 2017
Internet of Things and Data Analytics Handbook (1119173647) cover image

Description

This book examines the Internet of Things (IoT) and Data Analytics from a technical, application, and business point of view.

Internet of Things and Data Analytics Handbook describes essential technical knowledge, building blocks, processes, design principles, implementation, and marketing for IoT projects. It provides readers with knowledge in planning, designing, and implementing IoT projects. The book is written by experts on the subject matter, including international experts from nine countries in the consumer and enterprise fields of IoT. The text starts with an overview and anatomy of IoT, ecosystem of IoT, communication protocols, networking, and available hardware, both present and future applications and transformations, and business models. The text also addresses big data analytics, machine learning, cloud computing, and consideration of sustainability that are essential to be both socially responsible and successful. Design and implementation processes are illustrated with best practices and case studies in action. In addition, the book:

  • Examines cloud computing, data analytics, and sustainability and how they relate to IoT
  • overs the scope of consumer, government, and enterprise applications
  • Includes best practices, business model, and real-world case studies
Hwaiyu Geng, P.E., is a consultant with Amica Research (www.AmicaResearch.org, Palo Alto, California), promoting green planning, design, and construction projects. He has had over 40 years of manufacturing and management experience, working with Westinghouse, Applied Materials, Hewlett Packard, and Intel on multi-million high-tech projects. He has written and presented numerous technical papers at international conferences.  Mr. Geng, a patent holder, is also the editor/author of Data Center Handbook (Wiley, 2015).
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Table of Contents

 

List of Contributors xix

Foreword xxiii

Preface xxvii

Acknowledgments xxix

Part I INTERNET OF THINGS 1

1 Internet of Things and Data Analytics in the Cloud with Innovation and Sustainability 3
Hwaiyu Geng

1.1 Introduction 3

1.2 The IoT and the Fourth Industrial Revolution 4

1.3 Internet of Things Technology 6

1.4 Standards and Protocols 11

1.5 IoT Ecosystem 11

1.6 Definition of Big Data 13

1.7 IoT, Data Analytics, and Cloud Computing 18

1.8 Creativity, Invention, Innovation, and Disruptive Innovation 18

1.9 Polya’s “How to Solve it” 20

1.10 Business Plan and Business Model 20

1.11 Conclusion and Future Perspectives 23

2 Digital Services and Sustainable Solutions 29
Rikke Gram-Hansen

2.1 Introduction 29

2.2 Why IoT is not Just “Nice to Have” 30

2.3 Services in a Digital Revolution 32

2.4 Mobile Digital Services and the Human Sensor 32

2.5 Not Just Another App 33

2.6 The Hidden Life of Things 34

2.7 The Umbrellas are not what they Seem 35

2.8 Interacting with the Invisible 36

2.9 Society as Open Source 36

2.10 Learn from your Hackers 37

2.11 Ensuring High-Quality Services to Citizens 37

2.12 Government as a Platform 38

2.13 Conclusion 38

3 The Industrial Internet of Things (Iiot): Applications and Taxonomy 41
Stan Schneider

3.1 Introduction to the IioT 41

3.2 Some Examples of Iiot Applications 43

3.3 Toward a Taxonomy of the Iiot 52

3.4 Standards and Protocols for Connectivity 66

3.5 Connectivity Architecture for the Iiot 73

3.6 Data-Centricity Makes Dds Different 79

3.7 The Future of the Iiot 80

4 Strategic Planning for Smarter Cities 83
Jonathan Reichental

4.1 Introduction 83

4.2 What is a Smart City? 84

4.3 Smart Cities and the Internet of Things 85

4.4 Why Strategic Planning Matters 86

4.5 Beginning the Journey: First Things First 87

4.6 From Vision to Objectives to Execution 89

4.7 Pulling it all Together 91

5 Next-Generation Learning: Smart Medical Team Training 95
Brenda Bannan, Shane Gallagher and Bridget Lewis

5.1 Introduction 95

5.2 Learning, Analytics, and Internet of Things 96

5.3 IoT Learning Design Process 98

5.4 Conclusion 103

6 The Brain–Computer Interface in the Internet of Things 107
Jim McKeeth

6.1 Introduction 107

6.2 The Science Behind Reading the Brain 109

6.3 The Science of Writing to the Brain 112

6.4 The Human Connectome Project 113

6.5 Consumer Electroencephalography Devices 113

6.6 Summary 115

7 Iot Innovation Pulse 119
John Mattison

7.1 The Convergence of Exponential Technologies as a Driver of Innovation 119

7.2 Six Dimensions of the Plecosystem 119

7.3 Five Principles of the Plecosystem 120

7.4 The Biologic Organism Analogy for the IoT 121

7.5 Components for Innovation with the Organismal Analog 122

7.6 Spinozan Value Trade-Offs 123

7.7 Human IoT Sensor Networks 123

7.8 Role of the IoT in Social Networks 124

7.9 Security and Cyberthreat Resilience 124

7.10 IoT Optimization for Sustainability of our Planet 124

7.11 Maintenance of Complex IoT Networks 125

7.12 The Accordion Model of Learning as a Source of Innovation 126

7.13 Summary 126

Part II INTERNET OF THINGS TECHNOLOGIES 129

8 Internet of Things Open-Source Systems 131
Scott Amyx

8.1 Introduction 131

8.2 Background of Open Source 131

8.3 Drivers for Open Source 132

8.4 Benefits of Using Open Source 132

8.5 IoT Open-Source Consortiums and Projects 134

8.6 Finding the Right Open-Source Project for the Job 137

8.7 Conclusion 143

9 MEMS: An Enabling Technology for the Internet of Things (IoT) 147
Michael A. Huff

9.1 The Ability to Sense, Actuate, and Control 148

9.2 What are MEMS? 150

9.3 MEMS as an Enabling Technology for the IoT 153

9.4 MEMS Manufacturing Techniques 155

9.5 Examples of MEMS Sensors 158

9.6 Example of MEMS Actuator 163

9.7 The Future of MEMS for the IoT 163

9.8 Conclusion 165

10 Electro-Optical Infrared Sensor Technologies for the Internet of Things 167
Venkataraman Sundareswaran, Henry Yuan, Kai Song, Joseph Kimchi and Jih-Fen Lei

10.1 Introduction 167

10.2 Sensor Anatomy and Technologies 169

10.3 Design Considerations 176

10.4 Applications 179

10.5 Conclusion 184

11 Ipv6 for IoT and Gateway 187
Geoff Mulligan

11.1 Introduction 187

11.2 Ip: The Internet Protocol 187

11.3 IPv6: The Next Internet Protocol 189

11.4 6LoWPAN: Ip for IoT 191

11.5 Gateways: A Bad Choice 191

11.6 Example IoT Systems 192

11.7 An IoT Data Model 194

11.8 The Problem of Data Ownership 194

11.9 Managing the Life of an IoT Device 195

11.10 Conclusion: Looking forward 195

12 Wireless Sensor Networks 197
David Y. Fong

12.1 Introduction 197

12.2 Characteristics of Wireless Sensor Networks 198

12.3 Distributed Computing 201

12.4 Parallel Computing 202

12.5 Self-Organizing Networks 205

12.6 Operating Systems for Sensor Networks 206

12.7 Web of Things (WoT) 207

12.8 Wireless Sensor Network Architecture 208

12.9 Modularizing the Wireless Sensor Nodes 209

12.10 Conclusion 210

13 Networking Protocols and Standards for Internet of Things 215
Tara Salman and Raj Jain

13.1 Introduction 215

13.2 IoT Data Link Protocols 218

13.3 Network Layer Routing Protocols 224

13.4 Network Layer Encapsulation Protocols 225

13.5 Session Layer Protocols 227

13.6 IoT Management Protocols 232

13.7 Security in IoT Protocols 233

13.8 IoT Challenges 234

13.9 Summary 235

14 IoT Architecture 239
Shyam Varan Nath

14.1 Introduction 239

14.2 Architectural Approaches 239

14.3 Business Markitecture 242

14.4 Functional Architecture 243

14.5 Application Architecture 243

14.6 Data and Analytics Architecture 246

14.7 Technology Architecture 246

14.8 Security and Governance 248

15 A Designer’s Guide to the Internet of Wearable Things 251
David Hindman and Peter Burnham

15.1 Introduction 251

15.2 Interface Glanceability 252

15.3 The Right Data at the Right Time 254

15.4 Consistency Across Channels 255

15.5 From Public to Personal 260

15.6 Nonvisual Ui 262

15.7 Emerging Patterns 264

15.8 Conclusion 265

16 Beacon Technology with IoT and Big Data 267
Nick Stein and Stephanie Urbanski

16.1 Introduction to Beacons 267

16.2 What is Beacon Technology 269

16.3 Beacon and BLE Interaction 270

16.4 Where Beacon Technology can be Applied/Used 271

16.5 Big Data and Beacons 273

16.6 San Francisco International Airport (Sfo) 274

16.7 Future Trends and Conclusion 280

17 SCADA Fundamentals and Applications in the IoT 283
Rich Hunzinger

17.1 Introduction 283

17.2 What Exactly is SCADA? 285

17.3 Why is SCADA the Right Foundation for an IoT Platform? 287

17.4 Case Study: Algae Lab Systems 290

17.5 The Future of SCADA and the Potential of the IoT 290

Part III DATA ANALYTICS TECHNOLOGIES 295

18 Data Analysis and Machine Learning Effort in Healthcare: Organization, Limitations, and Development of an Approach 297
Oleg Roderick, Nicholas Marko, David Sanchez and Arun Aryasomajula

18.1 Introduction 297

18.2 Data Science Problems in Healthcare 298

18.3 Qualifications and Personnel in Data Science 306

18.4 Data Acquisition and Transformation 310

18.5 Basic Principles of Machine Learning 316

18.6 Case Study: Prediction of Rare Events on Nonspecific Data 321

18.7 Final Remarks 324

19 Data Analytics and Predictive Analytics in the Era of Big Data 329
Amy Shi-Nash and David R. Hardoon

19.1 Data Analytics and Predictive Analytics 329

19.2 Big Data and Impact to Analytics 334

19.3 Conclusion 343

20 Strategy Development and Big Data Analytics 347
Neil Fraser

20.1 Introduction 347

20.2 Maximizing the Influence of Internal Inputs for Strategy Development 348

20.3 A Higher Education Case Study 352

20.4 Maximizing the Influence of External Inputs for Strategy Development 356

20.5 Conclusion 363

21 Risk Modeling and Data Science 365
Joshua Frank

21.1 Introduction 365

21.2 What is Risk Modeling 365

21.3 The Role of Data Science in Risk Management 366

21.4 How to Prepare and Validate Risk Model 367

21.5 Tips and Lessons Learned 374

21.6 Future Trends and Conclusion 380

22 Hadoop Technology 383
Scott Shaw

22.1 Introduction 383

22.2 What is Hadoop Technology and Application? 384

22.3 Why Hadoop? 386

22.4 Hadoop Architecture 388

22.5 HDFS: What and how to use it 391

22.6 YARN: What and how to use it 392

22.7 Mapreduce: What and how to use it 394

22.8 Apache: what and how to use it 395

22.9 Future Trend and Conclusion 396

23 Security of IoT Data: Context, Depth, and Breadth Across Hadoop 399
Pratik Verma

23.1 Introduction 399

23.2 IoT Data in Hadoop 402

23.3 Security in IoT Platforms Built on Hadoop 402

23.4 Architectural Considerations for Implementing Security in Hadoop 403

23.5 Breadth of Control 403

23.6 Context for Security 404

23.7 Security Policies and Rules Based on Pxp Architecture 404

23.8 Conclusion 405

Part Iv SMART EVERYTHING 407

24 Connected Vehicle 409
Adrian Pearmine

24.1 Introduction 409

24.2 Connected, Automated, and Autonomous Vehicle Technologies 410

24.3 Connected Vehicles from the Department of Transportation Perspective 413

24.4 Policy Issues Around DSRC 414

24.5 Alternative forms of V2X Communications 414

24.6 DOT Connected Vehicle Applications 415

24.7 Other Connected Vehicle Applications 418

24.8 Migration Path from Connected and Automated to Fully Autonomous Vehicles 419

24.9 Autonomous Vehicle Adoption Predictions 419

24.10 Market Growth for Connected and Autonomous Vehicle Technology 422

24.11 Connected Vehicles in the Smart City 423

24.12 Issues not Discussed in this Chapter 423

24.13 Conclusion 425

25 In-Vehicle Health and Wellness: An Insider Story 427
Pramita Mitra, Craig Simonds, Yifan Chen and Gary Strumolo

25.1 Introduction 427

25.2 Health and Wellness Enabler Technologies inside the Car 429

25.3 Health and Wellness as Automotive Features 435

25.4 Top Challenges for Health and Wellness 440

25.5 Summary and Future Directions 444

26 Industrial Internet 447
David Bartlett

26.1 Introduction (History, Why, and Benefits) 447

26.2 Definitions of Components and Fundamentals of Industrial Internet 448

26.3 Application in Healthcare 450

26.4 Application in Energy 451

26.5 Application in Transport/Aviation and Others 453

26.6 Conclusion and Future Development 454

27 Smart City Architecture and Planning: Evolving Systems through IoT 457
Dominique Davison and Ashley Z. Hand

27.1 Introduction 457

27.2 Cities and the Advent of Open Data 459

27.3 Buildings in Smarter Cities 460

27.4 The Trifecta of Technology 461

27.5 Emerging Solutions: Understanding Systems 462

27.6 Conclusion 464

28 Nonrevenue Water 467
Kenneth Thompson, Brian Skeens and Jennifer Liggett

28.1 Introduction and Background 467

28.2 NRW Anatomy 467

28.3 Economy and Conservation 468

28.4 Best Practice Standard Water Balance 469

28.5 NRW Control and Audit 469

28.6 Lessons Learned 472

28.7 Case Studies 473

28.8 The Future of Nonrevenue Water Reduction 479

28.9 Conclusion 479

29 IoT and Smart Infrastructure 481
George Lu and Y.J. Yang

29.1 Introduction 481

29.2 Engineering Decisions 482

29.3 Conclusion 492

30 Internet of Things and Smart Grid Standardization 495
Girish Ghatikar

30.1 Introduction and Background 495

30.2 Digital Energy Accelerated by the Internet of Things 497

30.3 Smart Grid Power Systems and Standards 500

30.4 Leveraging IoTs and Smart Grid Standards 503

30.5 Conclusions and Recommendations 510

31 IoT Revolution in Oil and Gas Industry 513
Satyam Priyadarshy

31.1 Introduction 513

31.2 What is IoT Revolution in Oil and Gas Industry? 515

31.3 Case Study 516

31.4 Conclusion 519

32 Modernizing the Mining Industry with the Internet of Things 521
Rafael Laskier

32.1 Introduction 521

32.2 How IoT will Impact the Mining Industry 523

32.3 Case Study 535

32.4 Conclusion 541

33 Internet of Things (IoT)-Based Cyber–Physical Frameworks for Advanced Manufacturing and Medicine 545
J. Cecil

33.1 Introduction 545

33.2 Manufacturing and Medical Application Contexts 546

33.3 Overview of IoT-Based Cyber–Physical Framework 548

33.4 Case Studies in Manufacturing and Medicine 548

33.5 Conclusion: Challenges, Road Map for the Future 556

Part V IoT/DATA ANALYTICS CASE STUDIES 563

34 Defragmenting Intelligent Transportation: A Practical Case Study 565
Alan Carlton, Rafael Cepeda and Tim Gammons

34.1 Introduction 565

34.2 The Transport Industry and Some Lessons from the Past 566

34.3 The Transport Industry: a Long Road Traveled 567

34.4 The Transpoprt Industry: Current Status and Outlook 570

34.5 Use Case: oneTRANSPORT—a Solution to Today’s Transport Fragmentation 572

34.6 oneTRANSPORT: Business Model 575

34.7 Conclusion 578

35 Connected and Autonomous Vehicles 581
Levent Guvenc, Bilin Aksun Guvenc and Mumin Tolga Emirler

35.1 Brief History of Automated and Connected Driving 581

35.2 Automated Driving Technology 583

35.3 Connected Vehicle Technology and the Cv Pilots 587

35.4 Automated Truck Convoys 589

35.5 On-Demand Automated Shuttles for a Smart City 590

35.6 A Unified Design Approach 591

35.7 Acronym and Description 592

36 Transit Hub: A Smart Decision Support System for Public Transit Operations 597
Shashank Shekhar, Fangzhou Sun, Abhishek Dubey, Aniruddha Gokhale, Himanshu Neema, Martin Lehofer and Dan Freudberg

36.1 Introduction 597

36.2 Challenges 600

36.3 Integrated Sensors 600

36.4 Transit Hub System with Mobile Apps and Smart Kiosks 601

36.5 Conclusion 610

37 Smart Home Services Using the Internet of Things 613
Gene Wang and Danielle Song

37.1 Introduction 613

37.2 What Matters? 613

37.3 IoT for the Masses 614

37.4 Lifestyle Security Examples 615

37.5 Market Size 617

37.6 Characteristics of an Ideal System 619

37.7 IoT Technology 624

37.8 Conclusion 630

38 Emotional Insights via Wearables 631
Gawain Morrison

38.1 Introduction 631

38.2 Measuring Emotions: What are they? 632

38.3 Measuring Emotions: How does it Work? 632

38.4 Leaders in Emotional Understanding 633

38.5 The Physiology of Emotion 635

38.6 Why Bother Measuring Emotions? 636

38.7 Use Case 1 636

38.8 Use Case 2 637

38.9 Use Case 3 640

38.10 Conclusion 640

39 A Single Platform Approach for the Management of Emergency in Complex Environments such as Large Events, Digital Cities, and Networked Regions 643
Francesco Valdevies

39.1 Introduction 643

39.2 Resilient City: Selex Es Safety and Security Approach 645

39.3 City Operating System: People, Place, and Organization Protection 646

39.4 Cyber Security: Knowledge Protection 650

39.5 Intelligence 651

39.6 A Scalable Solution for Large Events, Digital Cities, and Networked Regions 652

39.7 Selex ES Relevant Experiences in Security and Safety Management in Complex Situations 652

39.8 Conclusion 657

40 Structural Health Monitoring 665
George Lu and Y.j. Yang

40.1 Introduction 665

40.2 Requirement 666

40.3 Engineering Decisions 667

40.4 Implementation 669

40.5 Conclusion 671

41 Home Healthcare and Remote Patient Monitoring 675
Karthi Jeyabalan

41.1 Introduction 675

41.2 What the Case Study is About 676

41.3 Who are the Parties in the Case Study 677

41.4 Limitation, Business Case, and Technology Approach 678

41.5 Setup and Workflow Plan 678

41.6 What are the Success Stories in the Case Study 679

41.7 What Lessons Learned to be Improved 681

Part Vi  Cloud, Legal, Innovation, and Business Models 683

42 Internet of Things and Cloud Computing 685
James Osborne

42.1 Introduction 685

42.2 What is Cloud Computing? 687

42.3 Cloud Computing and IoT 688

42.4 Common IoT Application Scenarios 690

42.5 Cloud Security and IoT 693

42.6 Cloud Computing and Makers 695

42.7 An Example Scenario 696

42.8 Conclusion 697

43 Privacy and Security Legal Issues 699
Francoise Gilbert

43.1 Unique Characteristics 699

43.2 Privacy Issues 701

43.3 Data Minimization 704

43.4 Deidentification 708

43.5 Data Security 710

43.6 Profiling Issues 714

43.7 Research and Analytics 715

43.8 IoT and DA Abroad 716

44 IoT and Innovation 719
William Kao

44.1 Introduction 719

44.2 What is Innovation? 719

44.3 Why is Innovation Important? Drivers and Benefits 724

44.4 How: the Innovation Process 725

44.5 Who does the Innovation? Good Innovator Skills 727

44.6 When: in a Product Cycle when does Innovation Takes Part? 729

44.7 Where: Innovation Areas in IoT 730

44.8 Conclusion 732

45 Internet of Things Business Models 735
Hubert C.Y. Chan

45.1 Introduction 735

45.2 IoT Business Model Framework Review 736

45.3 Framework Development 740

45.4 Case Studies 743

45.5 Discussion and Summary 755

45.6 Limitations and Future Research 756

Index 759

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Author Information

Hwaiyu Geng, P.E., is a consultant with Amica Research (www.AmicaResearch.org, Palo Alto, California), promoting green planning, design, and construction projects. He has had over 40 years of manufacturing and management experience, working with Westinghouse, Applied Materials, Hewlett Packard, and Intel on multi-million high-tech projects. He has written and presented numerous technical papers at international conferences.  Mr. Geng, a patent holder, is also the editor/author of Data Center Handbook (Wiley, 2015).

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