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.

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 Matevž 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