-
Browse Book Series
- Adhesion and Adhesives: Fundamental and Applied Aspects
- Advances in Additive Manufacturing Technologies
- Advances in Antenna, Microwave and Communication Engineering
- Advances in Biofeedstocks and Biofuels
- Advances in Cyber Security
- Advances in Data Engineering and Machine Learning
- Advances in E-Mobility
- Advances in Hydrogen Production and Storage
- Advances in Intelligent and Scientific Computing (AISC)
- Advances in Learning Analytics for Intelligent Cloud-IoT Systems
- Advances in Membrane Processes
- Advances in Nanotechnology and Applications
- Advances in Natural Gas Engineering
- Advances in Pipes and Pipelines
- Advances in Production Engineering
- Advances in Solar Cell Materials and Storage
- Applied Functional Materials
- Artificial Intelligence and Soft Computing for Industrial Transformation
- Astrobiology Perspectives on Life in the Universe
- Bioprocessing in Food Science
- Computational Intelligence and Biomedical Engineering
- Concise Introductions to AI and Data Science
- Cyber Systems and Quantum Engineering
- Decentralized Systems and Next-Generation Internet
- Diatoms: Biology and Applications
- Digital Convergence in Engineering Systems
- Emerging Trends in Medicinal and Pharmaceutical Chemistry
- Engineering Systems Design for Sustainable Development
- Fintech in a Sustainable Digital Society
- Industry 5.0 Transformation Applications
- Infectious and Rare Diseases
- Innovations in Materials and Manufacturing
- Machine Learning in Biomedical Science and Healthcare Informatics
- Materials Degradation and Failure
- Mathematics and Computer Science
- Next-Generation Computing and Communication Engineering
- Performability Engineering Series
- Rotating Machinery Fundamentals and Advances
- Studies in Computational Intelligence and Smart Technologies
- Sustainable Computing and Optimization
Browse Subject Areas
For Authors
Submit a ProposalMachine Learning Approaches for Convergence of IoT and Blockchain
 | Edited by Krishna Kant Singh, Akansha Singh and Sanjay Sharma
Copyright: 2021 | Status: Published ISBN: 9781119761747 | Hardcover | 248 pages | 67 illustrations Price: $195 USD  |
One Line Description
The unique aspect of this book is that its focus is the convergence of machine learning, IoT, and blockchain in a single publication.
Audience
The target audience of this book is professionals and researchers (artificial intelligence specialists, systems engineers, information technologists) in the fields of machine learning, IoT, and blockchain technology.
The target audience of this book is professionals and researchers (artificial intelligence specialists, systems engineers, information technologists) in the fields of machine learning, IoT, and blockchain technology.
Description
Blockchain technology and the Internet of Things (IoT) are two of the most impactful trends to have emerged in the field of machine learning. Although there are a number of books available solely on the subjects of machine learning, IoT and blockchain technology, no such book has been available which focuses on machine learning techniques for IoT and blockchain convergence until now. Thus, this book is unique in terms of the topics it covers. Designed as an essential guide for all academicians, researchers, and those in industry who are working in related fields, this book will provide insights into the convergence of blockchain technology and the IoT with machine learning.
Highlights of the book include:
• Examines many industries such as agriculture, manufacturing, food production,
healthcare, the military, and IT
• Security of the Internet of Things using blockchain and AI
• Developing smart cities and transportation systems using machine learning and IoT
Back to Top
Blockchain technology and the Internet of Things (IoT) are two of the most impactful trends to have emerged in the field of machine learning. Although there are a number of books available solely on the subjects of machine learning, IoT and blockchain technology, no such book has been available which focuses on machine learning techniques for IoT and blockchain convergence until now. Thus, this book is unique in terms of the topics it covers. Designed as an essential guide for all academicians, researchers, and those in industry who are working in related fields, this book will provide insights into the convergence of blockchain technology and the IoT with machine learning.
Highlights of the book include:
• Examines many industries such as agriculture, manufacturing, food production,
healthcare, the military, and IT
• Security of the Internet of Things using blockchain and AI
• Developing smart cities and transportation systems using machine learning and IoT
Back to Top
Author / Editor Details
Krishna Kant Singh, PhD is an associate professor in the Faculty of Engineering & Technology, Jain (Deemed-to-be University), Bengaluru, India. Dr. Singh has acquired BTech, MTech, and PhD (IIT Roorkee) in the area of machine learning and remote sensing. He has authored more than 50 technical books and research papers in international conferences and SCIE journals.
Krishna Kant Singh, PhD is an associate professor in the Faculty of Engineering & Technology, Jain (Deemed-to-be University), Bengaluru, India. Dr. Singh has acquired BTech, MTech, and PhD (IIT Roorkee) in the area of machine learning and remote sensing. He has authored more than 50 technical books and research papers in international conferences and SCIE journals.
Akansha Singh, PhD is an associate professor in the Department of Computer Science Engineering in Amity University, Noida, India. Dr. Singh has acquired BTech, MTech, and PhD (IIT Roorkee) in the area of neural networks and remote sensing. She has authored more than 40 technical books and research papers in international conferences and SCIE journals. Her area of interest includes mobile computing, artificial intelligence, machine learning, digital image processing.
Sanjay Kumar Sharma, PhD is professor and Head in the Department of Electronics and Communication Engineering at KIET Group of Institutions. Dr. Sanjay Sharma has a total of 24 years of teaching and research experience. He has more than 45 publications in journals and international conferences.
Back to Top
Table of Contents
Preface
1. Blockchain and Internet of Things Across Industries
Ananya Rakhra, Raghav Gupta and Akansha Singh
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
Anju Malik and Bharti Sharma
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
Raghav Gupta, Ananya Rakhra and Akansha Singh
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
4. Amalgamation of IoT, ML, and Blockchain in the Healthcare Regime
Pratik Kumar, Piyush Yadav, Rajeev Agrawal and Krishna Kant Singh
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
Nilanjana Pradhan, Ajay Shankar Singh, Shrddha Sagar, Akansha Singh and Ahmed A. Elngar
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
Neha Agarwal, Pushpa Singh, Narendra Singh, Krishna Kant Singh and Rohit Jain
6.1 Introduction
6.2 Machine Learning
6.2.1 Types of Machine Learning Techniques
6.2.1.1 Unsupervised Learning
6.2.1.2 Supervised Learning
6.2.1.3 Semi-Supervised Learning
6.2.1.4 Reinforcement Learning
6.2.2 Applications of Machine Learning
6.2.2.1 Prognosis
6.2.2.2 Diagnosis
6.3 IoT in Healthcare
6.3.1 IoT Architecture for Healthcare System
6.3.1.1 Physical and Data Link Layer
6.3.1.2 Network Layer
6.3.1.3 Transport Layer
6.3.1.4 Application Layer
6.4 Machine Learning and IoT
6.4.1 Application of ML and IoT in Healthcare
6.4.1.1 Smart Diagnostic Care
6.4.1.2 Medical Staff and Inventory Tracking
6.4.1.3 Personal Care
6.4.1.4 Healthcare Monitoring Device
6.4.1.5 Chronic Disease Management
6.5 Conclusion
References
7. Blockchain for Vehicular Ad Hoc Network and Intelligent Transportation System: A Comprehensive Study
Raghav Sharma, Anirudhi Thanvi, Shatakshi Singh, Manish Kumar and Sunil Kumar Jangir
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
S. N. Kumar, A. Lenin Fred, L. R. Jonisha Miriam, Parasuraman Padmanabhan, Balázs Gulyás and Ajay Kumar H.
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
ShylajaVinaykumar Karatangi, Reshu Agarwal, Krishna Kant Singh and Ivan Izonin
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
Back to Top
Preface
1. Blockchain and Internet of Things Across Industries
Ananya Rakhra, Raghav Gupta and Akansha Singh
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
Anju Malik and Bharti Sharma
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
Raghav Gupta, Ananya Rakhra and Akansha Singh
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
4. Amalgamation of IoT, ML, and Blockchain in the Healthcare Regime
Pratik Kumar, Piyush Yadav, Rajeev Agrawal and Krishna Kant Singh
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
Nilanjana Pradhan, Ajay Shankar Singh, Shrddha Sagar, Akansha Singh and Ahmed A. Elngar
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
Neha Agarwal, Pushpa Singh, Narendra Singh, Krishna Kant Singh and Rohit Jain
6.1 Introduction
6.2 Machine Learning
6.2.1 Types of Machine Learning Techniques
6.2.1.1 Unsupervised Learning
6.2.1.2 Supervised Learning
6.2.1.3 Semi-Supervised Learning
6.2.1.4 Reinforcement Learning
6.2.2 Applications of Machine Learning
6.2.2.1 Prognosis
6.2.2.2 Diagnosis
6.3 IoT in Healthcare
6.3.1 IoT Architecture for Healthcare System
6.3.1.1 Physical and Data Link Layer
6.3.1.2 Network Layer
6.3.1.3 Transport Layer
6.3.1.4 Application Layer
6.4 Machine Learning and IoT
6.4.1 Application of ML and IoT in Healthcare
6.4.1.1 Smart Diagnostic Care
6.4.1.2 Medical Staff and Inventory Tracking
6.4.1.3 Personal Care
6.4.1.4 Healthcare Monitoring Device
6.4.1.5 Chronic Disease Management
6.5 Conclusion
References
7. Blockchain for Vehicular Ad Hoc Network and Intelligent Transportation System: A Comprehensive Study
Raghav Sharma, Anirudhi Thanvi, Shatakshi Singh, Manish Kumar and Sunil Kumar Jangir
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
S. N. Kumar, A. Lenin Fred, L. R. Jonisha Miriam, Parasuraman Padmanabhan, Balázs Gulyás and Ajay Kumar H.
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
ShylajaVinaykumar Karatangi, Reshu Agarwal, Krishna Kant Singh and Ivan Izonin
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
Back to Top