Muutke küpsiste eelistusi

Machine Learning Approaches for Convergence of IoT and Blockchain [Kõva köide]

Edited by (KIET Group of Institutions, Ghaziabad, India), Edited by (Jaipur, Rajasthan, India), Edited by (Amity University, Noida, India)
  • Formaat: Hardback, 256 pages, kõrgus x laius x paksus: 10x10x10 mm, kaal: 454 g
  • Ilmumisaeg: 24-Aug-2021
  • Kirjastus: Wiley-Scrivener
  • ISBN-10: 1119761743
  • ISBN-13: 9781119761747
Teised raamatud teemal:
Machine Learning Approaches for Convergence of IoT and BlockchainSuurem pilt
  • Formaat: Hardback, 256 pages, kõrgus x laius x paksus: 10x10x10 mm, kaal: 454 g
  • Ilmumisaeg: 24-Aug-2021
  • Kirjastus: Wiley-Scrivener
  • ISBN-10: 1119761743
  • ISBN-13: 9781119761747
Teised raamatud teemal:
Püsilink: https://www.kriso.ee/db/9781119761747.html
Märksõnad:
MACHINE LEARNING APPROACHES FOR CONVERGENCE OF IOT AND BLOCKCHAIN The unique aspect of this book is that its focus is the convergence of machine learning, IoT, and blockchain in a single publication.

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

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.
Preface xi
1 Blockchain and Internet of Things Across Industries 1(34)
Ananya Rakhra
Raghav Gupta
Akansha Singh
1.1 Introduction
1(2)
1.2 Insight About Industry
3(5)
1.2.1 Agriculture Industry
5(1)
1.2.2 Manufacturing Industry
5(1)
1.2.3 Food Production Industry
6(1)
1.2.4 Healthcare Industry
7(1)
1.2.5 Military
7(1)
1.2.6 IT Industry
8(1)
1.3 What is Blockchain?
8(3)
1.4 What is IoT?
11(3)
1.5 Combining IoT and Blockchain
14(11)
1.5.1 Agriculture Industry
15(2)
1.5.2 Manufacturing Industry
17(1)
1.5.3 Food Processing Industry
18(2)
1.5.4 Healthcare Industry
20(1)
1.5.5 Military
21(3)
1.5.6 Information Technology Industry
24(1)
1.6 Observing Economic Growth and Technology's Impact
25(3)
1.7 Applications of IoT and Blockchain Beyond Industries
28(4)
1.8 Conclusion
32(1)
References
33(2)
2 Layered Safety Model for IoT Services Through Blockchain 35(22)
Anju Malik
Bharti Sharma
2.1 Introduction
36(3)
2.1.1 IoT Factors Impacting Security
38(1)
2.2 IoT Applications
39(1)
2.3 IoT Model With Communication Parameters
40(1)
2.3.1 RFID (Radio Frequency Identification)
40(1)
2.3.2 WSH (Wireless Sensor Network)
40(1)
2.3.3 Middleware (Software and Hardware)
40(1)
2.3.4 Computing Service (Cloud)
41(1)
2.3.5 IoT Software
41(1)
2.4 Security and Privacy in IoT Services
41(3)
2.5 Blockchain Usages in IoT
44(1)
2.6 Blockchain Model With Cryptography
44(2)
2.6.1 Variations of Blockchain
45(1)
2.7 Solution to IoT Through Blockchain
46(4)
2.8 Conclusion
50(1)
References
51(6)
3 Internet of Things Security Using AI and Blockchain 57(36)
Raghav Gupta
Ananya Rakhra
Akansha Singh
3.1 Introduction
58(1)
3.2 IoT and Its Application
59(2)
3.3 Most Popular IoT and Their Uses
61(2)
3.4 Use of IoT in Security
63(1)
3.5 What is AI?
64(1)
3.6 Applications of AI
65(1)
3.7 AI and Security
66(2)
3.8 Advantages of AI
68(1)
3.9 Timeline of Blockchain
69(1)
3.10 Types of Blockchain
70(2)
3.11 Working of Blockchain
72(2)
3.12 Advantages of Blockchain Technology
74(1)
3.13 Using Blockchain Technology With IoT
74(2)
3.14 IoT Security Using AI and Blockchain
76(2)
3.15 AI Integrated IoT Home Monitoring System
78(1)
3.16 Smart Homes With the Concept of Blockchain and AI
79(2)
3.17 Smart Sensors
81(1)
3.18 Authentication Using Blockchain
82(1)
3.19 Banking Transactions Using Blockchain
83(1)
3.20 Security Camera
84(1)
3.21 Other Ways to Fight Cyber Attacks
85(3)
3.22 Statistics on Cyber Attacks
88(2)
3.23 Conclusion
90(1)
References
90(3)
4 Amalgamation of IoT, ML, and Blockchain in the Healthcare Regime 93(16)
Pratik Kumar
Piyush Yadav
Rajeev Agrawal
Krishna Kant Singh
4.1 Introduction
93(2)
4.2 What is Internet of Things?
95(5)
4.2.1 Internet of Medical Things
97(1)
4.2.2 Challenges of the IoMT
97(2)
4.2.3 Use of IoT in Alzheimer Disease
99(1)
4.3 Machine Learning
100(4)
4.3.1 Case 1: Multilayer Perceptron Network
101(1)
4.3.2 Case 2: Vector Support Machine
102(1)
4.3.3 Applications of the Deep Learning in the Healthcare Sector
103(1)
4.4 Role of the Blockchain in the Healthcare Field
104(2)
4.4.1 What is Blockchain Technology?
104(1)
4.4.2 Paradigm Shift in the Security of Healthcare Data Through Blockchain
105(1)
4.5 Conclusion
106(1)
References
106(3)
5 Application of Machine Learning and IoT for Smart Cities 109(20)
Nilanjana Pradhan
Ajay Shankar Singh
Shrddha Sagar
Akansha Singh
Ahmed A. Elngar
5.1 Functionality of Image Analytics
110(2)
5.2 Issues Related to Security and Privacy in IoT
112(2)
5.3 Machine Learning Algorithms and Blockchain Methodologies
114(7)
5.3.1 Intrusion Detection System
116(2)
5.3.2 Deep Learning and Machine Learning Models
118(1)
5.3.3 Artificial Neural Networks
118(1)
5.3.4 Hybrid Approaches
119(1)
5.3.5 Review and Taxonomy of Machine Learning
120(1)
5.4 Machine Learning Open Source Tools for Big Data
121(2)
5.5 Approaches and Challenges of Machine Learning Algorithms in Big Data
123(4)
5.6 Conclusion
127(1)
References
127(2)
6 Machine Learning Applications for IoT Healthcare 129(16)
Neha Agarwal
Pushpa Singh
Narendra Singh
Krishna Kant Singh
Rohit Jain
6.1 Introduction
130(1)
6.2 Machine Learning
130(5)
6.2.1 Types of Machine Learning Techniques
131(1)
6.2.1.1 Unsupervised Learning
131(1)
6.2.1.2 Supervised Learning
131(1)
6.2.1.3 Semi-Supervised Learning
132(1)
6.2.1.4 Reinforcement Learning
132(1)
6.2.2 Applications of Machine Learning
132(3)
6.2.2.1 Prognosis
132(2)
6.2.2.2 Diagnosis
134(1)
6.3 IoT in Healthcare
135(3)
6.3.1 IoT Architecture for Healthcare System
135(3)
6.3.1.1 Physical and Data Link Layer
136(1)
6.3.1.2 Network Layer
137(1)
6.3.1.3 Transport Layer
137(1)
6.3.1.4 Application Layer
137(1)
6.4 Machine Learning and IoT
138(2)
6.4.1 Application of ML and IoT in Healthcare
138(14)
6.4.1.1 Smart Diagnostic Care
138(1)
6.4.1.2 Medical Staff and Inventory Tracking
139(1)
6.4.1.3 Personal Care
139(1)
6.4.1.4 Healthcare Monitoring Device
139(1)
6.4.1.5 Chronic Disease Management
139(1)
6.5 Conclusion
140(1)
References
140(5)
7 Blockchain for Vehicular Ad Hoc Network and Intelligent Transportation System: A Comprehensive Study 145(30)
Raghav Sharma
Anirudhi Thanvi
Shatakshi Singh
Manish Kumar
Sunil Kumar Jangir
7.1 Introduction
146(3)
7.2 Related Work
149(3)
7.3 Connected Vehicles and Intelligent Transportation System
152(3)
7.3.1 VANET
153(1)
7.3.2 Blockchain Technology and VANET
153(2)
7.4 An ITS-Oriented Blockchain Model
155(1)
7.5 Need of Blockchain
156(8)
7.5.1 Food Track and Trace
159(1)
7.5.2 Electric Vehicle Recharging
160(1)
7.5.3 Smart City and Smart Vehicles
161(3)
7.6 Implementation of Blockchain Supported Intelligent Vehicles
164(1)
7.7 Conclusion
165(1)
7.8 Future Scope
166(1)
References
167(8)
8 Applications of Image Processing in Teleradiology for the Medical Data Analysis and Transfer Based on IoT 175(30)
S.N. Kumar
A. Lenin Fred
L.R. Jonisha Miriam
Parasuraman Padmanabhan
Balazs Gulyas
Ajay Kumar H.
8.1 Introduction
176(2)
8.2 Pre-Processing
178(5)
8.2.1 Principle of Diffusion Filtering
178(5)
8.3 Improved FCM Based on Crow Search Optimization
183(1)
8.4 Prediction-Based Lossless Compression Model
184(4)
8.5 Results and Discussion
188(14)
8.6 Conclusion
202(1)
Acknowledgment
202(1)
References
203(2)
9 Innovative Ideas to Build Smart Cities with the Help of Machine and Deep Learning and IoT 205(28)
Shylaja Vinaykumar Karatangi
Reshu Agarwal
Krishna Kant Singh
Ivan Izonin
9.1 Introduction
206(1)
9.2 Related Work
207(1)
9.3 What Makes Smart Cities Smart?
208(4)
9.3.1 Intense Traffic Management
208(1)
9.3.2 Smart Parking
209(1)
9.3.3 Smart Waste Administration
210(1)
9.3.4 Smart Policing
211(1)
9.3.5 Shrewd Lighting
211(1)
9.3.6 Smart Power
211(1)
9.4 In Healthcare System
212(1)
9.5 In Homes
213(1)
9.6 In Aviation
213(1)
9.7 In Solving Social Problems
213(1)
9.8 Uses of AI-People
214(1)
9.8.1 Google Maps
214(1)
9.8.2 Ridesharing
214(1)
9.8.3 Voice-to-Text
215(1)
9.8.4 Individual Assistant
215(1)
9.9 Difficulties and Profit
215(1)
9.10 Innovations in Smart Cities
216(1)
9.11 Beyond Humans Focus
217(1)
9.12 Illustrative Arrangement
217(1)
9.13 Smart Cities with No Differentiation
218(1)
9.14 Smart City and AI
219(2)
9.15 Further Associated Technologies
221(3)
9.15.1 Model Identification
221(1)
9.15.2 Picture Recognition
221(1)
9.15.3 IoT
222(1)
9.15.4 Big Data
223(1)
9.15.5 Deep Learning
223(1)
9.16 Challenges and Issues
224(4)
9.16.1 Profound Learning Models
224(1)
9.16.2 Deep Learning Paradigms
225(1)
9.16.3 Confidentiality
226(1)
9.16.4 Information Synthesis
226(1)
9.16.5 Distributed Intelligence
227(1)
9.16.6 Restrictions of Deep Learning
228(1)
9.17 Conclusion and Future Scope
228(1)
References
229(4)
Index 233
Krishna Kant Singh 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 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.