The Internet of Things

PROVIDES COMPREHENSIVE COVERAGE OF THE CURRENT STATE OF IOT, FOCUSING ON DATA PROCESSING INFRASTRUCTURE AND TECHNIQUES

Written by experts in the field, this book addresses the IoT technology stack, from connectivity through data platforms to end-user case studies, and considers the tradeoffs between business needs and data security and privacy throughout. There is a particular emphasis on data processing technologies that enable the extraction of actionable insights from data to inform improved decision making. These include artificial intelligence techniques such as stream processing, deep learning and knowledge graphs, as well as data interoperability and the key aspects of privacy, security and trust. Additional aspects covered include: creating and supporting IoT ecosystems; edge computing; data mining of sensor datasets; and crowd-sourcing, amongst others. The book also presents several sections featuring use cases across a range of application areas such as smart energy, transportation, smart factories, and more. The book concludes with a chapter on key considerations when deploying IoT technologies in the enterprise, followed by a brief review of future research directions and challenges.

The Internet of Things: From Data to Insight

* Provides a comprehensive overview of the Internet of Things technology stack with focus on data driven aspects from data modelling and processing to presentation for decision making
* Explains how IoT technology is applied in practice and the benefits being delivered.
* Acquaints readers that are new to the area with concepts, components, technologies, and verticals related to and enabled by IoT
* Gives IoT specialists a deeper insight into data and decision-making aspects as well as novel technologies and application areas
* Analyzes and presents important emerging technologies for the IoT arena
* Shows how different objects and devices can be connected to decision making processes at various levels of abstraction

The Internet of Things: From Data to Insight will appeal to a wide audience, including IT and network specialists seeking a broad and complete understanding of IoT, CIOs and CIO teams, researchers in IoT and related fields, final year undergraduates, graduate students, post-graduates, and IT and science media professionals.

EDITED BYJOHN DAVIES, PHD, is Chief Researcher in BT's Research & Innovation Department, UK, where he leads a team focused on Internet of Things technologies. He is a Fellow of the British Computer Society and a Chartered Engineer as well as a Visiting Professor at the Open University and has published over 100 scientific articles. CAROLINA FORTUNA, PHD, is a Research Fellow at the Jo??ef Stefan Institute, Slovenia. She received her PhD in Computer Science in 2013, was a postdoctoral research associate at Ghent University, 2014-2015 and a Visitor at Stanford University in 2017. She has authored over 60 peer reviewed papers, technically led EU-funded research projects and is a consultant to industry. About the Editors xi

List of Contributors xiii

Acknowledgments xvii

1 INTRODUCTION 1

John Davies and Carolina Fortuna

1.1 Stakeholders in IoT Ecosystems 3

1.2 Human and IoT Sensing, Reasoning, and Actuation: An Analogy 4

1.3 Replicability and Re-use in IoT 5

1.4 Overview 6

References 7

2 CONNECTING DEVICES: ACCESS NETWORKS 9

Paul Putland

2.1 Introduction 9

2.2 Overview of Access Networks 10

2.2.1 Existing Technologies are Able to Cover a Number of IoT Scenarios 10

2.3 Low-Power Wide Area Network (LPWAN) 12

2.3.1 Long-Range (LoRa) Low-Power Wide Area Network 14

2.3.2 Sigfox Low-Power Wide Area Network 14

2.3.3 Weightless Low-Power Wide Area Network 15

2.4 Cellular Technologies 15

2.4.1 Emerging 5G Cellular Technology 16

2.5 Conclusion 18

References 18

3 EDGE COMPUTING 21

Mohammad Hossein Zoualfaghari, Simon Beddus, and Salman Taherizadeh

3.1 Introduction 21

3.2 Edge Computing Fundamentals 22

3.2.1 Edge Compute Strategies 22

3.2.2 Network Connectivity 25

3.3 Edge Computing Architecture 25

3.3.1 Device Overview 25

3.3.2 Edge Application Modules 26

3.3.3 IoT Runtime Environment 26

3.3.4 Device Management 27

3.3.5 Secure Runtime Environment 27

3.4 Implementing Edge Computing Solutions 28

3.4.1 Starter Configuration 28

3.4.2 Developer Tools 28

3.4.3 Edge Computing Frameworks 29

3.5 Zero-Touch Device On-boarding 30

3.6 Applying Edge Computing 32

3.7 Conclusions 33

References 33

4 DATA PLATFORMS: INTEROPERABILITY AND INSIGHT 37

John Davies and Mike Fisher

4.1 Introduction 37

4.2 IoT Ecosystems 38

4.3 Context 40

4.4 Aspects of Interoperability 41

4.4.1 Discovery 41

4.4.2 Access Control 43

4.4.3 Data Access 44

4.5 Conclusion 48

References 49

5 STREAMING DATA PROCESSING FOR IOT 51

Carolina Fortuna and Timotej Gale

5.1 Introduction 51

5.2 Fundamentals 52

5.2.1 Compression 52

5.2.2 Dimensionality Reduction 52

5.2.3 Summarization 53

5.2.4 Learning and Mining 53

5.2.5 Visualization 53

5.3 Architectures and Languages 54

5.4 Stream Analytics and Spectrum Sensing 56

5.4.1 Real-Time Notifications 57

5.4.2 Statistical Reporting 57

5.4.3 Custom Applications 58

5.5 Summary 59

References 60

6 APPLIED MACHINE VISION AND IOT 63

V. García, N. Sánchez, J.A. Rodrigo, J.M. Menéndez, and J. Lalueza

6.1 Introduction: Machine Vision and the Proliferation of Smart Internet of Things Driven Environments 63

6.2 Machine Vision Fundamentals 65

6.3 Overview of Relevant Work: Current Trends in Machine Vision in IoT 67

6.3.1 Improved Perception for IoT 67

6.3.2 Improved Interpretation and Learning for IoT 68

6.4 A Generic Deep Learning Framework for Improved Situation Awareness 69

6.5 Evaluating the Impact of Deep Learning in Different IoT Related Verticals 70

6.5.1 Sensing Critical Infrastructures Using Cognitive Drone-Based Systems 70

6.5.2 Sensing Public Spaces Using Smart Embedded Systems 71

6.5.3 Preventive Maintenance Service Comparison Based on Drone High-Definition Images 72

6.6 Best Practice 74

6.7 Summary 75

References 75

7 DATA REPRESENTATION AND REASONING 79

Maria Maleshkova and Nicolas Seydoux

7.1 Introduction 79

7.2 Fundamentals 80

7.3 Semantic IoT and Semantic WoT (SWoT) 81

7.4 Semantics for IoT Integration 82

7.4.1 IoT Ontologies and IoT-O 83

7.4.2 The Digital Twin Approach 85

7.5 Use Case 87

7.6 Summary 88

References 89

8 CROWDSOURCING AND HUMAN-IN-THE-LOOP FOR IOT 91

Luis-Daniel Ibáñez, Neal Reeves, and Elena Simperl

8.1 Introduction 91

8.2 Crowdsourcing 92

8.3 Human-in-the-Loop 95

8.4 Spatial Crowdsourcing 97

8.5 Participatory Sensing 99

8.6 Conclusion 100

References 101

9 IOT SECURITY: EXPERIENCE IS AN EXPENSIVE TEACHER 107

Paul Kearney

9.1 Introduction 107

9.2 Why is IoT Security Different from IT Security? 108

9.3 What is Being Done to Address IoT Security Challenges? 110

9.3.1 Governments 110

9.3.2 Standards Bodies 111

9.3.3 Industry Groups 112

9.4 Picking the Low-Hanging Fruit 113

9.4.1 Basic Hygiene Factors 113

9.4.2 Methodologies and Compliance Frameworks 115

9.4.3 Labeling Schemes and Consumer Advice 116

9.5 Summary 117

References 118

10 IOT DATA PRIVACY 121

Norihiro Okui, Vanessa Bracamonte, Shinsaku Kiyomoto, and Alistair Duke

10.1 Introduction 121

10.2 Basic Concepts in IoT Data Privacy 122

10.2.1 What is Personal Data? 122

10.2.2 General Requirements for Data Privacy 123

10.2.3 Personal Data and IoT 124

10.2.4 Existing Privacy Preservation Approaches 126

10.2.5 Toward a Standards-Based Approach in Support of PIMS Business Models 128

10.3 A Data Handling Framework Based on Consent Information and Privacy Preferences 129

10.3.1 A Data Handling Framework 129

10.3.2 Privacy Preference Manager (PPM) 130

10.3.3 Implementation of the Framework 131

10.4 Standardization for a User-Centric Data Handling Architecture 132

10.4.1 Introduction to oneM2M 132

10.4.2 PPM in oneM2M 133

10.5 Example Use Cases 133

10.5.1 Services Based on Home Energy Data 133

10.5.2 HEMS Service 133

10.5.3 Delivery Service 134

10.6 Conclusions 137

References 137

11 BLOCKCHAIN: ENABLING TRUST ON THE INTERNET OF THINGS 141

Giampaolo Fiorentino, Carmelita Occhipinti, Antonello Corsi, Evandro Moro, John Davies, and Alistair Duke

11.1 Introduction 141

11.2 Distributed Ledger Technologies and the Blockchain 143

11.2.1 Distributed Ledger Technology Overview 143

11.2.2 Basic Concepts and Architecture 145

11.2.2.1 Consensus Algorithm 148

11.2.3 When to Deploy DLT 149

11.3 The Ledger of Things: Blockchain and IoT 150

11.4 Benefits and Challenges 150

11.5 Blockchain Use Cases 152

11.6 Conclusion 154

References 154

12 HEALTHCARE 159

Duarte Gonçalves-Ferreira, Joana Ferreira, Bruno Oliveira, Ricardo Cruz-Correia, and Pedro Pereira Rodrigues

12.1 Internet of Things in Healthcare Settings 159

12.1.1 Monitoring Patient Status in Hospitals 160

12.1.2 IoT from Healthcare to Everyday Life 160

12.1.3 Systems Interoperability 161

12.2 BigEHR: A Federated Repository for a Holistic Lifelong Health Record 163

12.2.1 Why a Federated Design? 164

12.2.2 System Architecture 164

12.3 Gathering IoT Health-Related Data 165

12.3.1 From Inside the Hospitals 166

12.3.2 Feeding Data from Outside Sources 166

12.4 Extracting Meaningful Information from IoT Data 167

12.4.1 Privacy Concerns 167

12.4.2 Distributed Reasoning 167

12.5 Outlook 168

Acknowledgments 169

References 169

13 SMART ENERGY 173

Artemis Voulkidis, Theodore Zahariadis, Konstantinos Kalaboukas, Francesca Santori, and Matev? Vučnik

13.1 Introduction 173

13.2 Use Case Description 175

13.2.1 The Role of 5G in the Smart Grid IoT Context 177

13.3 Reference Architecture 178

13.4 Use Case Validation 182

13.4.1 AMI-Based Continuous Power Quality Assessment System 183

13.5 Conclusion 187

Acknowledgment 187

References 187

14 ROAD TRANSPORT AND AIR QUALITY 189

Charles Carter and Chris Rushton

14.1 Introduction 189

14.2 The Air Pollution Challenge 191

14.3 Road Traffic Air Pollution Reduction Strategies 193

14.4 Monitoring Air Pollution Using IoT 194

14.5 Use Case: Reducing Emissions Through an IoT-Based Advanced Traffic Management System 196

14.6 Limitations of Average Speed Air Quality Modeling 201

14.7 Future Roadmap and Summary 202

References 203

15 CONCLUSION 207

John Davies and Carolina Fortuna

15.1 Origins and Evolution 207

15.2 Why Now? 207

15.2.1 Falling Costs and Miniaturization 208

15.2.2 Societal Challenges and Resource Efficiency 208

15.2.3 Information Sharing Comes of Age 208

15.2.4 Managing Complexity 208

15.2.5 Technological Readiness 208

15.3 Maximizing the Value of Data 209

15.4 Commercial Opportunities 209

15.5 A Glimpse of the Future 210

References 212

Index 213