Artificial Intelligence and Industrial Internet of Things Paradigm
Buch, Englisch, 512 Seiten, Format (B × H): 160 mm x 234 mm, Gewicht: 826 g
ISBN: 978-1-119-82447-3
Verlag: Wiley
THE NEW ADVANCED SOCIETY
Included in this book are the fundamentals of Society 5.0, artificial intelligence, and the industrial Internet of Things, featuring their working principles and application in different sectors.
A 360-degree view of the different dimensions of the digital revolution is presented in this book, including the various industries transforming industrial manufacturing, the security and challenges ahead, and the far-reaching implications for society and the economy. The main objective of this edited book is to cover the impact that the new advanced society has on several platforms such as smart manufacturing systems, where artificial intelligence can be integrated with existing systems to make them smart, new business models and strategies, where anything and everything is possible through the internet and cloud, smart food chain systems, where food products can be delivered to any corner of the world at any time and in any situation, smart transport systems in which robots and self-driven cars are taking the lead, advances in security systems to assure people of their privacy and safety, and smart healthcare systems, where biochips can be incorporated into the human body to predict deadly diseases at early stages. Finally, it can be understood that the social reformation of Society 5.0 will lead to a society where every person leads an active and healthy life.
Audience
The targeted audience for this book includes research scholars and industry engineers in artificial intelligence and information technology, engineering students, cybersecurity experts, government research agencies and policymakers, business leaders, and entrepreneurs.
Sandeep Kumar Panda, PhD is an associate professor in the Department of Data Science and Artificial Intelligence at IcfaiTech (Faculty of Science and Technology), ICFAI Foundation for Higher Education, Hyderabad. His research areas include artificial intelligence, IoT, blockchain technology, cloud computing, cryptography, computational intelligence, and software engineering.
Ramesh Kumar Mohapatra, PhD is an assistant professor in the Department of Computer Science and Engineering, National Institute of Technology, Rourkela, Odisha, India. His research interests include optical character recognition, document image analysis, video processing, secure computing, and machine learning.
Subhrakanta Panda, PhD is an assistant professor in the Department of Computer Science and Information Systems, BITS-PILANI, Hyderabad Campus, Jawahar Nagar, Hyderabad, India. His research interests include social network analysis, cloud computing, security testing, and blockchain.
S. Balamurugan, PhD is the Director of Research and Development, Intelligent Research Consultancy Services (iRCS), Coimbatore, Tamilnadu, India. He is also Director of the Albert Einstein Engineering and Research Labs (AEER Labs), as well as Vice-Chairman, Renewable Energy Society of India (RESI), India. He has published 45 books, 200+ international journals/ conferences, and 35 patents.
Autoren/Hrsg.
Fachgebiete
Weitere Infos & Material
Preface xvii
Acknowledgments xxiii
1 Post Pandemic: The New Advanced Society 1
Sujata Priyambada Dash
1.1 Introduction 1
1.1.1 Themes 2
1.1.1.1 Theme: Areas of Management 2
1.1.1.2 Theme: Financial Institutions Cyber Crime 3
1.1.1.3 Theme: Economic Notion 4
1.1.1.4 Theme: Human Depression 6
1.1.1.5 Theme: Migrant Labor 7
1.1.1.6 Theme: Digital Transformation (DT) of Educational Institutions 9
1.1.1.7 School and Colleges Closures 11
1.2 Conclusions 12
References 12
2 Distributed Ledger Technology in the Construction Industry Using Corda 15
Sandeep Kumar Panda, Shanmukhi Priya Daliyet, Shagun S. Lokre and Vihas Naman
2.1 Introduction 16
2.2 Prerequisites 16
2.2.1 DLT vs Blockchain 17
2.3 Key Points of Corda 18
2.3.1 Some Salient Features of Corda 20
2.3.2 States 20
2.3.3 Contract 22
2.3.3.1 Create and Assign Task (CAT) Contract 22
2.3.3.2 Request for Cash (RT) Contract 23
2.3.3.3 Transfer of Cash (TT) Contract 24
2.3.3.4 Updation of the Task (UOT) Contract 24
2.3.4 Flows 25
2.3.4.1 Flow Associated With CAT Contract 25
2.3.4.2 Flow Associated With RT Contract 26
2.3.4.3 Flow Associated With TT Contract 26
2.3.4.4 Flow Associated With UOT Contract 26
2.4 Implementation 26
2.4.1 System Overview 27
2.4.2 Working Flowchart 28
2.4.3 Experimental Demonstration 29
2.5 Future Work 35
2.6 Conclusion 36
References 37
3 Identity and Access Management for Internet of Things Cloud 43
Soumya Prakash Otta and Subhrakanta Panda
3.1 Introduction 44
3.2 Internet of Things (IoT) Security 45
3.2.1 IoT Security Overview 45
3.2.2 IoT Security Requirements 46
3.2.3 Securing the IoT Infrastructure 49
3.3 IoT Cloud 49
3.3.1 Cloudification of IoT 50
3.3.2 Commercial IoT Clouds 52
3.3.3 IAM of IoT Clouds 54
3.4 IoT Cloud Related Developments 55
3.5 Proposed Method for IoT Cloud IAM 58
3.5.1 Distributed Ledger Approach for IoT Security 59
3.5.2 Blockchain for IoT Security Solution 60
3.5.3 Proposed Distributed Ledger-Based IoT Cloud IAM 62
3.6 Conclusion 64
References 65
4 Automated TSR Using DNN Approach for Intelligent Vehicles 67
Banhi Sanyal, Piyush R. Biswal, R.K. Mohapatra, Ratnakar Dash and Ankush Agarwalla
4.1 Introduction 68
4.2 Literature Survey 69
4.3 Neural Network (NN) 70
4.4 Methodology 71
4.4.1 System Architecture 71
4.4.2 Database 71
4.5 Experiments and Results 71
4.5.1 FFNN 74
4.5.2 RNN 76
4.5.3 CNN 76
4.5.4 CNN 76
4.5.5 Pre-Trained Models 79
4.6 Discussion 79
4.7 Conclusion 80
References 88
5 Honeypot: A Trap for Attackers 91
Anjanna Matta, G. Sucharitha, Bandlamudi Greeshmanjali, Manji Prashanth Kumar and Mathi Naga Sarath Kumar
5.1 Introduction 92
5.1.1 Research Honeypots 93
5.1.2 Production Honeypots 93
5.2 Method 94
5.2.1 Low-Interaction Honeypots 94
5.2.2 Medium-Interaction Honeypots 95
5.2.3 High-Interaction Honeypots 95
5.3 Cryptanalysis 96
5.3.1 System Architecture 96
5.3.2 Possible Attacks on Honeypot 97
5.3.3 Advantages of Honeypots 98
5.3.4 Disadvantages of Honeypots 99
5.4 Conclusions 99
References 100
6 Examining Security Aspect in Industrial-Based Internet of Things 103
Rohini Jha
6.1 Introduction 104
6.2 Process Frame of IoT Before Security 105
6.2.1 Cyber Attack 107
6.2.2 Security Assessment in IoT 107
6.2.2.1 Security in Perception and Network Frame 108
6.3 Attacks and Security Assessments in IIoT 111
6.3.1 IoT Security Techniques Analysis Based on its Merits 111
6.4 Conclusion 116
References 119
7 A Cooperative Navigation for Multi-Robots in Unknown Environments Using Hybrid Jaya-DE Algorithm 123
D. Chandrasekhar Rao
7.1 Introduction 124
7.2 Related Works 126
7.3 Problem Formulation 130
7.4 Multi-Robot Navigation Employing Hybrid Jaya-DE Algorithm 134
7.4.1 Basic Jaya Algorithm 134
7.5 Hybrid Jaya-DE 136
7.5.1 Mutation 136
7.5.2 Crossover 136
7.5.3 Selection 137
7.6 Simulation Analysis and Performance Evaluation of Jaya-DE Algorithm 139
7.7 Total Navigation Path Deviation (TNPD) 147
7.8 Average Unexplored Goal Distance (AUGD) 148
7.9 Conclusion 159
References 159
8 Categorization Model for Parkinson’s Disease Occurrence and Severity Prediction 163
Prashant Kumar Shrivastava, Ashish Chaturvedi, Megha Kamble and Megha Jain
8.1 Introduction 164
8.2 Applications 166
8.2.1 Machine Learning in PD Diagnosis 166
8.2.2 Challenges of PD Detection 169
8.2.3 Structuring of UPDRS Score 170
8.3 Methodology 173
8.3.1 Overview of Data Driven Intelligence 173
8.3.2 Comparison Between Deep Learning and Traditional Machine 175
8.3.3 Deep Learning for PD Diagnosis 176
8.3.4 Convolution Neural Network for PD Diagnosis 176
8.4 Proposed Models 178
8.4.1 Classification of Patient and Healthy Controls 178
8.4.2 Severity Score Classification 181
8.5 Results and Discussion 184
8.5.1 Performance Measures 185
8.5.2 Graphical Results 187
8.6 Conclusion 187
References 187
9 AI-Based Smart Agriculture Monitoring Using Ground-Based and Remotely Sensed Images 191
Shounak Chakraborty, Nikumani Choudhury and Indrajit Kalita
9.1 Introduction 192
9.2 Automatic Land-Cover Classification Techniques Using Remotely Sensed Images 194
9.3 Deep Learning-Based Agriculture Monitoring 196
9.4 Adaptive Approaches fo
