Efnisyfirlit

• Cover
• Half Title
• Title Page
• Copyright Page
• Contents
• Preface
• Abbreviations
• Authors
• 1. Demystifying the Industrial IoT Paradigm
• 1.1 Primer
• 1.2 The IoT Adoption—Technology or Strategy Decision
• 1.3 Industrial IoT
• 1.4 IIoT Taxonomies
• 1.5 IoT Challenges in Agile Manufacturing
• 1.6 Drivers for IIoT Adoption
• 1.7 IIoT for Process Management
• 1.8 IIoT Protocols
• 1.9 Product Development and IoT
• 1.10 Industry 4.0, IIoT, and Related Developments
• 1.11 Conclusion
• References
• 2. The Internet of Things Applications
• 2.1 General
• 2.1.1 IoT Reference Model
• 2.1.1.1 Device-to-Device Communications
• 2.1.1.2 Device-to-Cloud Communications
• 2.1.1.3 Device-to-Gateway Communications
• 2.1.1.4 Back-End Data-Sharing Model
• 2.1.2 Current Areas of Industrial IoT adoption
• 2.1.2.1 Improving Energy Management
• 2.1.2.2 Increase Process Manufacturing Efficiency
• 2.1.2.3 Organizing Discreet Manufacturing
• 2.1.2.4 Safety in Mining Operations
• 2.1.2.5 Improving Agro Production
• 2.1.2.6 Environmental Compliance
• 2.1.2.7 Retailing and Consumer Analysis
• 2.2 Emerging Areas of IoT Adoption
• 2.2.1 Robotics-Driven Warehouses
• 2.2.2 Process Safety
• 2.2.3 Deep-Learning-Based Predictive Analytics
• 2.2.4 Machine Learning for Decision-Making
• 2.2.5 Connected Machines Assets
• 2.2.6 Inventory Traceability
• 2.2.7 Defective Product Identification
• 2.3 Worldwide IIoT Adoption Case Studies
• 2.3.1 Current and Future Areas of Domestic IoT Adoption
• 2.3.2 Cashless Transactions
• 2.3.3 Retail Industry
• 2.3.4 Home Automation
• 2.3.5 Energy Management
• 2.3.6 City Management
• 2.3.7 Logistics
• 2.3.8 Healthcare
• 2.3.9 Industrial
• 2.3.10 Environmental Monitoring
• 2.4 Conclusion
• References
• 3. Current Technologies
• 3.1 Introduction
• 3.1.1 Identification
• 3.1.2 Sensing
• 3.1.3 Communication
• 3.1.4 Computation
• 3.1.5 Services
• 3.1.6 Semantics
• 3.2 Cloud Deployment Models
• 3.3 Relevant Technologies
• 3.4 Small-Form Factor Computing
• 3.5 Web Services
• 3.6 Wireless Sensor Networks (WSN)
• 3.7 Virtual Sensors
• 3.8 Fog Computing
• 3.9 Artificial Intelligence (AI)
• 3.10 Virtual Reality
• 3.11 Big Data
• 3.12 Blockchain and Cryptography
• 3.13 Semantic Technologies
• 3.14 Fuzzy Logic
• 3.15 Next Generation Networks (NGN)
• 3.16 Future Internet
• 3.17 Nano-Networks
• 3.18 Single-Point Sensing
• 3.19 Future Advancements
• 3.20 Conclusion
• References
• 4. Business Models
• 4.1 Introduction
• 4.2 Business Model Framework
• 4.3 The IoT and Economics Context
• 4.4 The IoT Business Models
• 4.5 Case Studies
• 4.6 The IoT Business Model Based on IT
• 4.6.1 Freemium
• 4.6.2 Digital Add-On Enhancements
• 4.6.3 Razor and Blade and Digital Lock-In
• 4.6.4 Point of Sales (POS)
• 4.6.5 Direct Selling Business Model or Solution Provider Model using Intelligent Objects Self-Service
• 4.6.6 Pay Per Use Business Model
• 4.6.7 Digitally Charged Products Business Model
• 4.6.8 Data Sale
• 4.7 Challenges and Conclusion
• References
• 5. Smart Manufacturing
• 5.1 Introduction
• 5.2 Manufacturing Concerns
• 5.2.1 Compliances
• 5.2.2 Right Product Mix
• 5.2.3 Skill Gap
• 5.2.4 Shop Floor Productivity
• 5.2.5 Energy Monitoring
• 5.2.6 Operational Efficiency of Machines
• 5.3 Industry 4.0 and Related Models
• 5.4 Smart Manufacturing
• 5.4.1 Smart Design
• 5.4.2 Smart Machines
• 5.4.3 Monitoring
• 5.4.4 Control
• 5.4.5 Dynamic and On-Demand Scheduling
• 5.4.6 Collaboration
• 5.4.7 Digitized Products
• 5.4.8 The IoT-Driven Process
• 5.4.9 The IoT and People
• 5.4.10 Scalable IT Systems
• 5.4.11 Financial Feasibility
• 5.4.12 Autonomous Functioning Driven by Machine Data
• 5.5 Smart Manufacturing: Indian Case Study
• 5.6 Conclusion
• References
• 6. Energy Consumption
• 6.1 Introduction
• 6.2 Energy Management Practices
• 6.3 The IoT for Energy Management
• 6.4 Industrial Case Study
• 6.5 Conclusion
• References
• Bibliography
• 7. Logistics Optimization
• 7.1 Introduction
• 7.2 Challenges in Logistics
• 7.3 Logistics Costs
• 7.4 Autonomous Logistics
• 7.5 The IoT-Enabled Activity-Based Costing
• 7.6 The IoT and Inventory Consolidation
• 7.7 The IoT and Consigned Inventory
• 7.8 Case Study: Industrial Logistics
• 7.9 Conclusion
• References
• 8. Distribution Channel Management
• 8.1 Introduction
• 8.2 The IoT Applications in Retail Distribution
• 8.3 Field Research
• 8.3.1 Consumer White Goods
• 8.3.2 Super Mart Items
• 8.3.3 Food Items
• 8.3.4 Fashion
• 8.3.5 Logistics
• 8.3.6 Energy Management
• 8.3.7 In-Store Technology
• 8.4 The IoT Case Studies in Retail
• 8.5 Costa Coffee
• 8.6 Conclusion
• References
• 9. Green Manufacturing
• 9.1 Introduction
• 9.2 Framework for Green Manufacturing
• 9.3 Case Study
• 9.4 Collaborative IoT for Advanced Manufacturing
• 9.5 Green IoT
• 9.6 Conclusions
• References
• 10. User Perceptions
• 10.1 Introduction
• 10.2 The IoT-UPM (User Perceptions Model)
• 10.3 The IoT Technology Acceptance Model
• 10.4 The IoT Maturity Model
• 10.4.1 Traditional IT Systems
• 10.4.2 People
• 10.4.3 Connected Assets
• 10.4.4 Digital Products
• 10.4.5 Financial Feasibility
• 10.5 Insights Based on a Field Survey
• 10.6 Conclusion
• References
• 11. The Future of the Internet of Things
• 11.1 Introduction
• 11.2 Hybrid Technologies
• 11.3 Futuristic Manufacturing Value Chains
• 11.4 Futuristic Consumer IoT
• 11.5 Emerging Trends
• 11.5.1 Operating Platforms
• 11.5.2 Standards
• 11.5.3 Distributed Stream Computing
• 11.5.4 Operating Systems
• 11.5.5 Hardware
• 11.5.6 Networks
• 11.5.7 Analytics
• 11.5.8 Wider Scope
• 11.5.9 Security
• 11.5.10 Identity Management
• 11.6 Future Development
• 11.7 Conclusion
• References
• 12. Governance, Security, and Privacy
• 12.1 Introduction
• 12.2 Classification
• 12.3 Types of the IoT Attacks
• 12.4 Current Protocols and Challenges
• 12.5 Network Level Security
• 12.6 Authorization and Authentication
• 12.7 Privacy in the IoT
• 12.8 Governance Issues
• 12.9 Conclusion
• References
• Index