Machine learning approaches for convergence of IoT and blockchain
Otros Autores: | , , |
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Formato: | Libro electrónico |
Idioma: | Inglés |
Publicado: |
Hoboken, New Jersey :
Wiley-Scrivener
[2021]
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Materias: | |
Ver en Biblioteca Universitat Ramon Llull: | https://discovery.url.edu/permalink/34CSUC_URL/1im36ta/alma991009631652406719 |
Tabla de Contenidos:
- Cover
- Half-Title Page
- Series Page
- Title Page
- Copyright Page
- Contents
- Preface
- 1 Blockchain and Internet of Things Across Industries
- 1.1 Introduction
- 1.2 Insight About Industry
- 1.2.1 Agriculture Industry
- 1.2.2 Manufacturing Industry
- 1.2.3 Food Production Industry
- 1.2.4 Healthcare Industry
- 1.2.5 Military
- 1.2.6 IT Industry
- 1.3 What is Blockchain?
- 1.4 What is IoT?
- 1.5 Combining IoT and Blockchain
- 1.5.1 Agriculture Industry
- 1.5.2 Manufacturing Industry
- 1.5.3 Food Processing Industry
- 1.5.4 Healthcare Industry
- 1.5.5 Military
- 1.5.6 Information Technology Industry
- 1.6 Observing Economic Growth and Technology's Impact
- 1.7 Applications of IoT and Blockchain Beyond Industries
- 1.8 Conclusion
- References
- 2 Layered Safety Model for IoT Services Through Blockchain
- 2.1 Introduction
- 2.1.1 IoT Factors Impacting Security
- 2.2 IoT Applications
- 2.3 IoT Model With Communication Parameters
- 2.3.1 RFID (Radio Frequency Identification)
- 2.3.2 WSH (Wireless Sensor Network)
- 2.3.3 Middleware (Software and Hardware)
- 2.3.4 Computing Service (Cloud)
- 2.3.5 IoT Software
- 2.4 Security and Privacy in IoT Services
- 2.5 Blockchain Usages in IoT
- 2.6 Blockchain Model With Cryptography
- 2.6.1 Variations of Blockchain
- 2.7 Solution to IoT Through Blockchain
- 2.8 Conclusion
- References
- 3 Internet of Things Security Using AI and Blockchain
- 3.1 Introduction
- 3.2 IoT and Its Application
- 3.3 Most Popular IoT and Their Uses
- 3.4 Use of IoT in Security
- 3.5 What is AI?
- 3.6 Applications of AI
- 3.7 AI and Security
- 3.8 Advantages of AI
- 3.9 Timeline of Blockchain
- 3.10 Types of Blockchain
- 3.11 Working of Blockchain
- 3.12 Advantages of Blockchain Technology
- 3.13 Using Blockchain Technology With IoT
- 3.14 IoT Security Using AI and Blockchain.
- 3.15 AI Integrated IoT Home Monitoring System
- 3.16 Smart Homes With the Concept of Blockchain and AI
- 3.17 Smart Sensors
- 3.18 Authentication Using Blockchain
- 3.19 Banking Transactions Using Blockchain
- 3.20 Security Camera
- 3.21 Other Ways to Fight Cyber Attacks
- 3.22 Statistics on Cyber Attacks
- 3.23 Conclusion
- References
- 4 Amalgamation of IoT, ML, and Blockchain in the Healthcare Regime
- 4.1 Introduction
- 4.2 What is Internet of Things?
- 4.2.1 Internet of Medical Things
- 4.2.2 Challenges of the IoMT
- 4.2.3 Use of IoT in Alzheimer Disease
- 4.3 Machine Learning
- 4.3.1 Case 1: Multilayer Perceptron Network
- 4.3.2 Case 2: Vector Support Machine
- 4.3.3 Applications of the Deep Learning in the Healthcare Sector
- 4.4 Role of the Blockchain in the Healthcare Field
- 4.4.1 What is Blockchain Technology?
- 4.4.2 Paradigm Shift in the Security of Healthcare Data Through Blockchain
- 4.5 Conclusion
- References
- 5 Application of Machine Learning and IoT for Smart Cities
- 5.1 Functionality of Image Analytics
- 5.2 Issues Related to Security and Privacy in IoT
- 5.3 Machine Learning Algorithms and Blockchain Methodologies
- 5.3.1 Intrusion Detection System
- 5.3.2 Deep Learning and Machine Learning Models
- 5.3.3 Artificial Neural Networks
- 5.3.4 Hybrid Approaches
- 5.3.5 Review and Taxonomy of Machine Learning
- 5.4 Machine Learning Open Source Tools for Big Data
- 5.5 Approaches and Challenges of Machine Learning Algorithms in Big Data
- 5.6 Conclusion
- References
- 6 Machine Learning Applications for IoT Healthcare
- 6.1 Introduction
- 6.2 Machine Learning
- 6.2.1 Types of Machine Learning Techniques
- 6.2.2 Applications of Machine Learning
- 6.3 IoT in Healthcare
- 6.3.1 IoT Architecture for Healthcare System
- 6.4 Machine Learning and IoT.
- 6.4.1 Application of ML and IoT in Healthcare
- 6.5 Conclusion
- References
- 7 Blockchain for Vehicular Ad Hoc Network and Intelligent Transportation System: A Comprehensive Study
- 7.1 Introduction
- 7.2 Related Work
- 7.3 Connected Vehicles and Intelligent Transportation System
- 7.3.1 VANET
- 7.3.2 Blockchain Technology and VANET
- 7.4 An ITS-Oriented Blockchain Model
- 7.5 Need of Blockchain
- 7.5.1 Food Track and Trace
- 7.5.2 Electric Vehicle Recharging
- 7.5.3 Smart City and Smart Vehicles
- 7.6 Implementation of Blockchain Supported Intelligent Vehicles
- 7.7 Conclusion
- 7.8 Future Scope
- References
- 8 Applications of Image Processing in Teleradiology for the Medical Data Analysis and Transfer Based on IOT
- 8.1 Introduction
- 8.2 Pre-Processing
- 8.2.1 Principle of Diffusion Filtering
- 8.3 Improved FCM Based on Crow Search Optimization
- 8.4 Prediction-Based Lossless Compression Model
- 8.5 Results and Discussion
- 8.6 Conclusion
- Acknowledgment
- References
- 9 Innovative Ideas to Build Smart Cities with the Help of Machine and Deep Learning and IoT
- 9.1 Introduction
- 9.2 Related Work
- 9.3 What Makes Smart Cities Smart?
- 9.3.1 Intense Traffic Management
- 9.3.2 Smart Parking
- 9.3.3 Smart Waste Administration
- 9.3.4 Smart Policing
- 9.3.5 Shrewd Lighting
- 9.3.6 Smart Power
- 9.4 In Healthcare System
- 9.5 In Homes
- 9.6 In Aviation
- 9.7 In Solving Social Problems
- 9.8 Uses of AI-People
- 9.8.1 Google Maps
- 9.8.2 Ridesharing
- 9.8.3 Voice-to-Text
- 9.8.4 Individual Assistant
- 9.9 Difficulties and Profit
- 9.10 Innovations in Smart Cities
- 9.11 Beyond Humans Focus
- 9.12 Illustrative Arrangement
- 9.13 Smart Cities with No Differentiation
- 9.14 Smart City and AI
- 9.15 Further Associated Technologies
- 9.15.1 Model Identification
- 9.15.2 Picture Recognition.
- 9.15.3 IoT
- 9.15.4 Big Data
- 9.15.5 Deep Learning
- 9.16 Challenges and Issues
- 9.16.1 Profound Learning Models
- 9.16.2 Deep Learning Paradigms
- 9.16.3 Confidentiality
- 9.16.4 Information Synthesis
- 9.16.5 Distributed Intelligence
- 9.16.6 Restrictions of Deep Learning
- 9.17 Conclusion and Future Scope
- References
- Index
- EULA.