{"product_id":"the-internet-of-things-isbn-9781119545262","title":"The Internet of Things","description":"\u003cp\u003e\u003cb\u003eProvides comprehensive coverage of the current state of IoT, focusing on data processing infrastructure and techniques\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eWritten 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.\u003c\/p\u003e \u003cp\u003e\u003ci\u003eThe Internet of Things: From Data to Insight\u003c\/i\u003e\u003c\/p\u003e \u003cul\u003e \u003cli\u003eProvides 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\u003c\/li\u003e \u003cli\u003eExplains how IoT technology is applied in practice and the benefits being delivered.\u003c\/li\u003e \u003cli\u003eAcquaints readers that are new to the area with concepts, components, technologies, and verticals related to and enabled by IoT\u003c\/li\u003e \u003cli\u003eGives IoT specialists a deeper insight into data and decision-making aspects as well as novel technologies and application areas\u003c\/li\u003e \u003cli\u003eAnalyzes and presents important emerging technologies for the IoT arena\u003c\/li\u003e \u003cli\u003eShows how different objects and devices can be connected to decision making processes at various levels of abstraction\u003c\/li\u003e \u003c\/ul\u003e \u003cp\u003e\u003ci\u003eThe Internet of Things: From Data to Insight\u003c\/i\u003e 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.\u003c\/p\u003e \u003cp\u003eAbout the Editors xi\u003c\/p\u003e \u003cp\u003eList of Contributors xiii\u003c\/p\u003e \u003cp\u003eAcknowledgments xvii\u003c\/p\u003e \u003cp\u003e\u003cb\u003e1 Introduction \u003c\/b\u003e\u003cb\u003e1\u003cbr\u003e\u003c\/b\u003e\u003ci\u003eJohn Davies and Carolina Fortuna\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e1.1 Stakeholders in IoT Ecosystems 3\u003c\/p\u003e \u003cp\u003e1.2 Human and IoT Sensing, Reasoning, and Actuation: An Analogy 4\u003c\/p\u003e \u003cp\u003e1.3 Replicability and Re-use in IoT 5\u003c\/p\u003e \u003cp\u003e1.4 Overview 6\u003c\/p\u003e \u003cp\u003eReferences 7\u003c\/p\u003e \u003cp\u003e\u003cb\u003e2 Connecting Devices: Access Networks \u003c\/b\u003e\u003cb\u003e9\u003cbr\u003e\u003c\/b\u003e\u003ci\u003ePaul Putland\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e2.1 Introduction 9\u003c\/p\u003e \u003cp\u003e2.2 Overview of Access Networks 10\u003c\/p\u003e \u003cp\u003e2.2.1 Existing Technologies are Able to Cover a Number of IoT Scenarios 10\u003c\/p\u003e \u003cp\u003e2.3 Low-Power Wide Area Network (LPWAN) 12\u003c\/p\u003e \u003cp\u003e2.3.1 Long-Range (LoRa) Low-Power Wide Area Network 14\u003c\/p\u003e \u003cp\u003e2.3.2 Sigfox Low-Power Wide Area Network 14\u003c\/p\u003e \u003cp\u003e2.3.3 Weightless Low-Power Wide Area Network 15\u003c\/p\u003e \u003cp\u003e2.4 Cellular Technologies 15\u003c\/p\u003e \u003cp\u003e2.4.1 Emerging 5G Cellular Technology 16\u003c\/p\u003e \u003cp\u003e2.5 Conclusion 18\u003c\/p\u003e \u003cp\u003eReferences 18\u003c\/p\u003e \u003cp\u003e\u003cb\u003e3 Edge Computing \u003c\/b\u003e\u003cb\u003e21\u003cbr\u003e\u003c\/b\u003e\u003ci\u003eMohammad Hossein Zoualfaghari, Simon Beddus, and Salman Taherizadeh\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e3.1 Introduction 21\u003c\/p\u003e \u003cp\u003e3.2 Edge Computing Fundamentals 22\u003c\/p\u003e \u003cp\u003e3.2.1 Edge Compute Strategies 22\u003c\/p\u003e \u003cp\u003e3.2.2 Network Connectivity 25\u003c\/p\u003e \u003cp\u003e3.3 Edge Computing Architecture 25\u003c\/p\u003e \u003cp\u003e3.3.1 Device Overview 25\u003c\/p\u003e \u003cp\u003e3.3.2 Edge Application Modules 26\u003c\/p\u003e \u003cp\u003e3.3.3 IoT Runtime Environment 26\u003c\/p\u003e \u003cp\u003e3.3.4 Device Management 27\u003c\/p\u003e \u003cp\u003e3.3.5 Secure Runtime Environment 27\u003c\/p\u003e \u003cp\u003e3.4 Implementing Edge Computing Solutions 28\u003c\/p\u003e \u003cp\u003e3.4.1 Starter Configuration 28\u003c\/p\u003e \u003cp\u003e3.4.2 Developer Tools 28\u003c\/p\u003e \u003cp\u003e3.4.3 Edge Computing Frameworks 29\u003c\/p\u003e \u003cp\u003e3.5 Zero-Touch Device On-boarding 30\u003c\/p\u003e \u003cp\u003e3.6 Applying Edge Computing 32\u003c\/p\u003e \u003cp\u003e3.7 Conclusions 33\u003c\/p\u003e \u003cp\u003eReferences 33\u003c\/p\u003e \u003cp\u003e\u003cb\u003e4 Data Platforms: Interoperability and Insight \u003c\/b\u003e\u003cb\u003e37\u003cbr\u003e\u003c\/b\u003e\u003ci\u003eJohn Davies and Mike Fisher\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e4.1 Introduction 37\u003c\/p\u003e \u003cp\u003e4.2 IoT Ecosystems 38\u003c\/p\u003e \u003cp\u003e4.3 Context 40\u003c\/p\u003e \u003cp\u003e4.4 Aspects of Interoperability 41\u003c\/p\u003e \u003cp\u003e4.4.1 Discovery 41\u003c\/p\u003e \u003cp\u003e4.4.2 Access Control 43\u003c\/p\u003e \u003cp\u003e4.4.3 Data Access 44\u003c\/p\u003e \u003cp\u003e4.5 Conclusion 48\u003c\/p\u003e \u003cp\u003eReferences 49\u003c\/p\u003e \u003cp\u003e\u003cb\u003e5 Streaming Data Processing for IoT \u003c\/b\u003e\u003cb\u003e51\u003cbr\u003e\u003c\/b\u003e\u003ci\u003eCarolina Fortuna and Timotej Gale\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e5.1 Introduction 51\u003c\/p\u003e \u003cp\u003e5.2 Fundamentals 52\u003c\/p\u003e \u003cp\u003e5.2.1 Compression 52\u003c\/p\u003e \u003cp\u003e5.2.2 Dimensionality Reduction 52\u003c\/p\u003e \u003cp\u003e5.2.3 Summarization 53\u003c\/p\u003e \u003cp\u003e5.2.4 Learning and Mining 53\u003c\/p\u003e \u003cp\u003e5.2.5 Visualization 53\u003c\/p\u003e \u003cp\u003e5.3 Architectures and Languages 54\u003c\/p\u003e \u003cp\u003e5.4 Stream Analytics and Spectrum Sensing 56\u003c\/p\u003e \u003cp\u003e5.4.1 Real-Time Notifications 57\u003c\/p\u003e \u003cp\u003e5.4.2 Statistical Reporting 57\u003c\/p\u003e \u003cp\u003e5.4.3 Custom Applications 58\u003c\/p\u003e \u003cp\u003e5.5 Summary 59\u003c\/p\u003e \u003cp\u003eReferences 60\u003c\/p\u003e \u003cp\u003e\u003cb\u003e6 Applied Machine Vision and IoT \u003c\/b\u003e\u003cb\u003e63\u003cbr\u003e\u003c\/b\u003e\u003ci\u003eV. Garc\u003c\/i\u003e\u003ci\u003eía, N. S\u003c\/i\u003e\u003ci\u003eánchez, J.A. Rodrigo, J.M. Men\u003c\/i\u003e\u003ci\u003eéndez, and J. Lalueza\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e6.1 Introduction: Machine Vision and the Proliferation of Smart Internet of Things Driven Environments 63\u003c\/p\u003e \u003cp\u003e6.2 Machine Vision Fundamentals 65\u003c\/p\u003e \u003cp\u003e6.3 Overview of Relevant Work: Current Trends in Machine Vision in IoT 67\u003c\/p\u003e \u003cp\u003e6.3.1 Improved Perception for IoT 67\u003c\/p\u003e \u003cp\u003e6.3.2 Improved Interpretation and Learning for IoT 68\u003c\/p\u003e \u003cp\u003e6.4 A Generic Deep Learning Framework for Improved Situation Awareness 69\u003c\/p\u003e \u003cp\u003e6.5 Evaluating the Impact of Deep Learning in Different IoT Related Verticals 70\u003c\/p\u003e \u003cp\u003e6.5.1 Sensing Critical Infrastructures Using Cognitive Drone-Based Systems 70\u003c\/p\u003e \u003cp\u003e6.5.2 Sensing Public Spaces Using Smart Embedded Systems 71\u003c\/p\u003e \u003cp\u003e6.5.3 Preventive Maintenance Service Comparison Based on Drone High-Definition Images 72\u003c\/p\u003e \u003cp\u003e6.6 Best Practice 74\u003c\/p\u003e \u003cp\u003e6.7 Summary 75\u003c\/p\u003e \u003cp\u003eReferences 75\u003c\/p\u003e \u003cp\u003e\u003cb\u003e7 Data Representation and Reasoning \u003c\/b\u003e\u003cb\u003e79\u003cbr\u003e\u003c\/b\u003e\u003ci\u003eMaria Maleshkova and Nicolas Seydoux\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e7.1 Introduction 79\u003c\/p\u003e \u003cp\u003e7.2 Fundamentals 80\u003c\/p\u003e \u003cp\u003e7.3 Semantic IoT and Semantic WoT (SWoT) 81\u003c\/p\u003e \u003cp\u003e7.4 Semantics for IoT Integration 82\u003c\/p\u003e \u003cp\u003e7.4.1 IoT Ontologies and IoT-O 83\u003c\/p\u003e \u003cp\u003e7.4.2 The Digital Twin Approach 85\u003c\/p\u003e \u003cp\u003e7.5 Use Case 87\u003c\/p\u003e \u003cp\u003e7.6 Summary 88\u003c\/p\u003e \u003cp\u003eReferences 89\u003c\/p\u003e \u003cp\u003e\u003cb\u003e8 Crowdsourcing and Human-in-the-Loop for IoT \u003c\/b\u003e\u003cb\u003e91\u003cbr\u003e\u003c\/b\u003e\u003ci\u003eLuis-Daniel Ib\u003c\/i\u003e\u003ci\u003eáñez, Neal Reeves, and Elena Simperl\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e8.1 Introduction 91\u003c\/p\u003e \u003cp\u003e8.2 Crowdsourcing 92\u003c\/p\u003e \u003cp\u003e8.3 Human-in-the-Loop 95\u003c\/p\u003e \u003cp\u003e8.4 Spatial Crowdsourcing 97\u003c\/p\u003e \u003cp\u003e8.5 Participatory Sensing 99\u003c\/p\u003e \u003cp\u003e8.6 Conclusion 100\u003c\/p\u003e \u003cp\u003eReferences 101\u003c\/p\u003e \u003cp\u003e\u003cb\u003e9 IoT Security: Experience is an Expensive Teacher \u003c\/b\u003e\u003cb\u003e107\u003cbr\u003e\u003c\/b\u003e\u003ci\u003ePaul Kearney\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e9.1 Introduction 107\u003c\/p\u003e \u003cp\u003e9.2 Why is IoT Security Different from IT Security? 108\u003c\/p\u003e \u003cp\u003e9.3 What is Being Done to Address IoT Security Challenges? 110\u003c\/p\u003e \u003cp\u003e9.3.1 Governments 110\u003c\/p\u003e \u003cp\u003e9.3.2 Standards Bodies 111\u003c\/p\u003e \u003cp\u003e9.3.3 Industry Groups 112\u003c\/p\u003e \u003cp\u003e9.4 Picking the Low-Hanging Fruit 113\u003c\/p\u003e \u003cp\u003e9.4.1 Basic Hygiene Factors 113\u003c\/p\u003e \u003cp\u003e9.4.2 Methodologies and Compliance Frameworks 115\u003c\/p\u003e \u003cp\u003e9.4.3 Labeling Schemes and Consumer Advice 116\u003c\/p\u003e \u003cp\u003e9.5 Summary 117\u003c\/p\u003e \u003cp\u003eReferences 118\u003c\/p\u003e \u003cp\u003e\u003cb\u003e10 IoT Data Privacy \u003c\/b\u003e\u003cb\u003e121\u003cbr\u003e\u003c\/b\u003e\u003ci\u003eNorihiro Okui, Vanessa Bracamonte, Shinsaku Kiyomoto, and Alistair Duke\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e10.1 Introduction 121\u003c\/p\u003e \u003cp\u003e10.2 Basic Concepts in IoT Data Privacy 122\u003c\/p\u003e \u003cp\u003e10.2.1 What is Personal Data? 122\u003c\/p\u003e \u003cp\u003e10.2.2 General Requirements for Data Privacy 123\u003c\/p\u003e \u003cp\u003e10.2.3 Personal Data and IoT 124\u003c\/p\u003e \u003cp\u003e10.2.4 Existing Privacy Preservation Approaches 126\u003c\/p\u003e \u003cp\u003e10.2.5 Toward a Standards-Based Approach in Support of PIMS Business Models 128\u003c\/p\u003e \u003cp\u003e10.3 A Data Handling Framework Based on Consent Information and Privacy Preferences 129\u003c\/p\u003e \u003cp\u003e10.3.1 A Data Handling Framework 129\u003c\/p\u003e \u003cp\u003e10.3.2 Privacy Preference Manager (PPM) 130\u003c\/p\u003e \u003cp\u003e10.3.3 Implementation of the Framework 131\u003c\/p\u003e \u003cp\u003e10.4 Standardization for a User-Centric Data Handling Architecture 132\u003c\/p\u003e \u003cp\u003e10.4.1 Introduction to oneM2M 132\u003c\/p\u003e \u003cp\u003e10.4.2 PPM in oneM2M 133\u003c\/p\u003e \u003cp\u003e10.5 Example Use Cases 133\u003c\/p\u003e \u003cp\u003e10.5.1 Services Based on Home Energy Data 133\u003c\/p\u003e \u003cp\u003e10.5.2 HEMS Service 133\u003c\/p\u003e \u003cp\u003e10.5.3 Delivery Service 134\u003c\/p\u003e \u003cp\u003e10.6 Conclusions 137\u003c\/p\u003e \u003cp\u003eReferences 137\u003c\/p\u003e \u003cp\u003e\u003cb\u003e11 Blockchain: Enabling Trust on the Internet of Things \u003c\/b\u003e\u003cb\u003e141\u003cbr\u003e\u003c\/b\u003e\u003ci\u003eGiampaolo Fiorentino, Carmelita Occhipinti, Antonello Corsi, Evandro Moro, John Davies, and Alistair Duke\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e11.1 Introduction 141\u003c\/p\u003e \u003cp\u003e11.2 Distributed Ledger Technologies and the Blockchain 143\u003c\/p\u003e \u003cp\u003e11.2.1 Distributed Ledger Technology Overview 143\u003c\/p\u003e \u003cp\u003e11.2.2 Basic Concepts and Architecture 145\u003c\/p\u003e \u003cp\u003e11.2.2.1 Consensus Algorithm 148\u003c\/p\u003e \u003cp\u003e11.2.3 When to Deploy DLT 149\u003c\/p\u003e \u003cp\u003e11.3 The Ledger of Things: Blockchain and IoT 150\u003c\/p\u003e \u003cp\u003e11.4 Benefits and Challenges 150\u003c\/p\u003e \u003cp\u003e11.5 Blockchain Use Cases 152\u003c\/p\u003e \u003cp\u003e11.6 Conclusion 154\u003c\/p\u003e \u003cp\u003eReferences 154\u003c\/p\u003e \u003cp\u003e\u003cb\u003e12 Healthcare \u003c\/b\u003e\u003cb\u003e159\u003cbr\u003e\u003c\/b\u003e\u003ci\u003eDuarte Gon\u003c\/i\u003e\u003ci\u003eçalves-Ferreira, Joana Ferreira, Bruno Oliveira, Ricardo Cruz-Correia, and Pedro Pereira Rodrigues\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e12.1 Internet of Things in Healthcare Settings 159\u003c\/p\u003e \u003cp\u003e12.1.1 Monitoring Patient Status in Hospitals 160\u003c\/p\u003e \u003cp\u003e12.1.2 IoT from Healthcare to Everyday Life 160\u003c\/p\u003e \u003cp\u003e12.1.3 Systems Interoperability 161\u003c\/p\u003e \u003cp\u003e12.2 BigEHR: A Federated Repository for a Holistic Lifelong Health Record 163\u003c\/p\u003e \u003cp\u003e12.2.1 Why a Federated Design? 164\u003c\/p\u003e \u003cp\u003e12.2.2 System Architecture 164\u003c\/p\u003e \u003cp\u003e12.3 Gathering IoT Health-Related Data 165\u003c\/p\u003e \u003cp\u003e12.3.1 From Inside the Hospitals 166\u003c\/p\u003e \u003cp\u003e12.3.2 Feeding Data from Outside Sources 166\u003c\/p\u003e \u003cp\u003e12.4 Extracting Meaningful Information from IoT Data 167\u003c\/p\u003e \u003cp\u003e12.4.1 Privacy Concerns 167\u003c\/p\u003e \u003cp\u003e12.4.2 Distributed Reasoning 167\u003c\/p\u003e \u003cp\u003e12.5 Outlook 168\u003c\/p\u003e \u003cp\u003eAcknowledgments 169\u003c\/p\u003e \u003cp\u003eReferences 169\u003c\/p\u003e \u003cp\u003e\u003cb\u003e13 Smart Energy \u003c\/b\u003e\u003cb\u003e173\u003cbr\u003e\u003c\/b\u003e\u003ci\u003eArtemis Voulkidis, Theodore Zahariadis, Konstantinos Kalaboukas, Francesca Santori, and Matevž Vu\u003c\/i\u003e\u003ci\u003ečnik\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e13.1 Introduction 173\u003c\/p\u003e \u003cp\u003e13.2 Use Case Description 175\u003c\/p\u003e \u003cp\u003e13.2.1 The Role of 5G in the Smart Grid IoT Context 177\u003c\/p\u003e \u003cp\u003e13.3 Reference Architecture 178\u003c\/p\u003e \u003cp\u003e13.4 Use Case Validation 182\u003c\/p\u003e \u003cp\u003e13.4.1 AMI-Based Continuous Power Quality Assessment System 183\u003c\/p\u003e \u003cp\u003e13.5 Conclusion 187\u003c\/p\u003e \u003cp\u003eAcknowledgment 187\u003c\/p\u003e \u003cp\u003eReferences 187\u003c\/p\u003e \u003cp\u003e\u003cb\u003e14 Road Transport and Air Quality \u003c\/b\u003e\u003cb\u003e189\u003cbr\u003e\u003c\/b\u003e\u003ci\u003eCharles Carter and Chris Rushton\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e14.1 Introduction 189\u003c\/p\u003e \u003cp\u003e14.2 The Air Pollution Challenge 191\u003c\/p\u003e \u003cp\u003e14.3 Road Traffic Air Pollution Reduction Strategies 193\u003c\/p\u003e \u003cp\u003e14.4 Monitoring Air Pollution Using IoT 194\u003c\/p\u003e \u003cp\u003e14.5 Use Case: Reducing Emissions Through an IoT-Based Advanced Traffic Management System 196\u003c\/p\u003e \u003cp\u003e14.6 Limitations of Average Speed Air Quality Modeling 201\u003c\/p\u003e \u003cp\u003e14.7 Future Roadmap and Summary 202\u003c\/p\u003e \u003cp\u003eReferences 203\u003c\/p\u003e \u003cp\u003e\u003cb\u003e15 Conclusion \u003c\/b\u003e\u003cb\u003e207\u003cbr\u003e\u003c\/b\u003e\u003ci\u003eJohn Davies and Carolina Fortuna\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e15.1 Origins and Evolution 207\u003c\/p\u003e \u003cp\u003e15.2 Why Now? 207\u003c\/p\u003e \u003cp\u003e15.2.1 Falling Costs and Miniaturization 208\u003c\/p\u003e \u003cp\u003e15.2.2 Societal Challenges and Resource Efficiency 208\u003c\/p\u003e \u003cp\u003e15.2.3 Information Sharing Comes of Age 208\u003c\/p\u003e \u003cp\u003e15.2.4 Managing Complexity 208\u003c\/p\u003e \u003cp\u003e15.2.5 Technological Readiness 208\u003c\/p\u003e \u003cp\u003e15.3 Maximizing the Value of Data 209\u003c\/p\u003e \u003cp\u003e15.4 Commercial Opportunities 209\u003c\/p\u003e \u003cp\u003e15.5 A Glimpse of the Future 210\u003c\/p\u003e \u003cp\u003eReferences 212\u003c\/p\u003e \u003cp\u003eIndex 213\u003c\/p\u003e  \u003cp\u003e\u003cb\u003eEDITED BY\u003c\/b\u003e \u003c\/p\u003e\u003cp\u003e\u003cb\u003eJOHN DAVIES, P\u003csmall\u003eH\u003c\/small\u003eD,\u003c\/b\u003e is Chief Researcher in BT's Research \u0026amp; 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. \u003c\/p\u003e\u003cp\u003e\u003cb\u003eCAROLINA FORTUNA, P\u003csmall\u003eH\u003c\/small\u003eD,\u003c\/b\u003e 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.   \u003c\/p\u003e\u003cp\u003e\u003cb\u003ePROVIDES COMPREHENSIVE COVERAGE OF THE CURRENT STATE OF IoT, FOCUSING ON DATA PROCESSING INFRASTRUCTURE AND TECHNIQUES\u003c\/b\u003e \u003c\/p\u003e\u003cp\u003eWritten 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. \u003c\/p\u003e\u003cp\u003e\u003ci\u003eThe Internet of Things: From Data to Insight\u003c\/i\u003e \u003c\/p\u003e\u003cul\u003e \u003cli\u003eProvides 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\u003c\/li\u003e \u003cli\u003eExplains how IoT technology is applied in practice and the benefits being delivered\u003c\/li\u003e \u003cli\u003eAcquaints readers that are new to the area with concepts, components, technologies, and verticals related to and enabled by IoT\u003c\/li\u003e \u003cli\u003eGives IoT specialists a deeper insight into data and decision-making aspects as well as novel technologies and application areas\u003c\/li\u003e \u003cli\u003eAnalyzes and presents important emerging technologies for the IoT arena\u003c\/li\u003e \u003cli\u003eShows how different objects and devices can be connected to decision making processes at various levels of abstraction??\u003c\/li\u003e \u003c\/ul\u003e \u003cp\u003e\u003ci\u003eThe Internet of Things: From Data to Insight\u003c\/i\u003e 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.\u003c\/p\u003e","brand":"Wiley","offers":[{"title":"Default Title","offer_id":47990268559589,"sku":"NP9781119545262","price":137.95,"currency_code":"USD","in_stock":false}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/1842\/7735\/files\/9781119545262.jpg?v=1761787133","url":"https:\/\/k12savings.com\/es\/products\/the-internet-of-things-isbn-9781119545262","provider":"K12savings","version":"1.0","type":"link"}