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Internet of Things and Data Analytics Handbook, 1. udgave
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Internet of Things and Data Analytics Handbook Vital Source e-bog

Hwaiyu Geng
(2016)
John Wiley & Sons
1.613,00 kr.
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Internet of Things and Data Analytics Handbook, 1. udgave

Internet of Things and Data Analytics Handbook

Hwaiyu Geng
(2017)
Sprog: Engelsk
John Wiley & Sons, Incorporated
1.662,00 kr.
Print on demand. Leveringstid vil være ca 2-3 uger.

Detaljer om varen

  • 1. Udgave
  • Vital Source searchable e-book (Reflowable pages)
  • Udgiver: John Wiley & Sons (December 2016)
  • ISBN: 9781119173625
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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Detaljer om varen

  • 1. Udgave
  • Hardback: 816 sider
  • Udgiver: John Wiley & Sons, Incorporated (Januar 2017)
  • ISBN: 9781119173649

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).
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
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