The internet of things and data analytics handbook
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 p...
Otros Autores: | |
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Formato: | Libro electrónico |
Idioma: | Inglés |
Publicado: |
Hoboken, New Jersey :
John Wiley & Sons
2017.
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Edición: | 1st ed |
Materias: | |
Ver en Biblioteca Universitat Ramon Llull: | https://discovery.url.edu/permalink/34CSUC_URL/1im36ta/alma991009849132206719 |
Tabla de Contenidos:
- --
- 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.