The New Advanced Society: Artificial Intelligence and Industrial Internet of Things Paradigm
- Length: 512 pages
- Edition: 1
- Language: English
- Publisher: Wiley-Scrivener
- Publication Date: 2022-04-05
- ISBN-10: 1119824478
- ISBN-13: 9781119824473
- Sales Rank: #0 (See Top 100 Books)
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.
Cover Half-Title Page Series Page Title Page Copyright Page Dedication Contents Preface Acknowledgments 1 Post Pandemic: The New Advanced Society 1.1 Introduction 1.1.1 Themes 1.1.1.1 Theme: Areas of Management 1.1.1.2 Theme: Financial Institutions Cyber Crime 1.1.1.3 Theme: Economic Notion 1.1.1.4 Theme: Human Depression 1.1.1.5 Theme: Migrant Labor 1.1.1.6 Theme: Digital Transformation (DT) of Educational Institutions 1.1.1.7 School and College Closures 1.2 Conclusions References 2 Distributed Ledger Technology in the Construction Industry Using Corda 2.1 Introduction 2.2 Prerequisites 2.2.1 DLT vs Blockchain 2.3 Key Points of Corda 2.3.1 Some Salient Features of Corda 2.3.2 States 2.3.3 Contract 2.3.3.1 Create and Assign Task (CAT) Contract 2.3.3.2 Request for Cash (RT) Contract 2.3.3.3 Transfer of Cash (TT) Contract 2.3.3.4 Updation of the Task (UOT) Contract 2.3.4 Flows 2.3.4.1 Flow Associated With CAT Contract 2.3.4.2 Flow Associated With RT Contract 2.3.4.3 Flow Associated With TT Contract 2.3.4.4 Flow Associated With UOT Contract 2.4 Implementation 2.4.1 System Overview 2.4.2 Working Flowchart 2.4.3 Experimental Demonstration 2.5 Future Work 2.6 Conclusion References 3 Identity and Access Management for Internet of Things Cloud 3.1 Introduction 3.2 Internet of Things (IoT) Security 3.2.1 IoT Security Overview 3.2.2 IoT Security Requirements 3.2.3 Securing the IoT Infrastructure 3.3 IoT Cloud 3.3.1 Cloudification of IoT 3.3.2 Commercial IoT Clouds 3.3.3 IAM of IoT Clouds 3.4 IoT Cloud Related Developments 3.5 Proposed Method for IoT Cloud IAM 3.5.1 Distributed Ledger Approach for IoT Security 3.5.2 Blockchain for IoT Security Solution 3.5.3 Proposed Distributed Ledger-Based IoT Cloud IAM 3.6 Conclusion References 4 Automated TSR Using DNN Approach for Intelligent Vehicles 4.1 Introduction 4.2 Literature Survey 4.3 Neural Network (NN) 4.4 Methodology 4.4.1 System Architecture 4.4.2 Database 4.5 Experiments and Results 4.5.1 FFNN 4.5.2 RNN 4.5.3 CNN 4.5.4 CNN 4.6 Discussion 4.7 Conclusion References 5 Honeypot: A Trap for Attackers 5.1 Introduction 5.1.1 Research Honeypots 5.1.2 Production Honeypots 5.2 Method 5.2.1 Low-Interaction Honeypots 5.2.2 Medium-Interaction Honeypots 5.2.3 High-Interaction Honeypots 5.3 Cryptanalysis 5.3.1 System Architecture 5.3.2 Possible Attacks on Honeypot 5.3.3 Advantages of Honeypots 5.3.4 Disadvantages of Honeypots 5.4 Conclusions References 6 Examining Security Aspects in Industrial-Based Internet of Things 6.1 Introduction 6.2 Process Frame of IoT Before Security 6.2.1 Cyber Attack 6.2.2 Security Assessment in IoT 6.2.2.1 Security in Perception and Network Frame 6.3 Attacks and Security Assessments in IIoT 6.3.1 IoT Security Techniques Analysis Based on its Merits 6.4 Conclusion References 7 A Cooperative Navigation for Multi-Robots in Unknown Environments Using Hybrid Jaya-DE Algorithm 7.1 Introduction 7.2 Related Works 7.3 Problem Formulation 7.4 Multi-Robot Navigation Employing Hybrid Jaya-DE Algorithm 7.4.1 Basic Jaya Algorithm 7.5 Hybrid Jaya-DE 7.5.1 Mutation 7.5.2 Crossover 7.5.3 Selection 7.6 Simulation Analysis and Performance Evaluation of Jaya-DE Algorithm 7.7 Total Navigation Path Deviation (TNPD) 7.8 Average Unexplored Goal Distance (AUGD) 7.9 Conclusion References 8 Categorization Model for Parkinson’s Disease Occurrence and Severity Prediction 8.1 Introduction 8.2 Applications 8.2.1 Machine Learning in PD Diagnosis 8.2.2 Challenges of PD Detection 8.2.3 Structuring of UPDRS Score 8.3 Methodology 8.3.1 Overview of Data Driven Intelligence 8.3.2 Comparison Between Deep Learning and Traditional Machine 8.3.3 Deep Learning for PD Diagnosis 8.3.4 Convolution Neural Network for PD Diagnosis 8.4 Proposed Models 8.4.1 Classification of Patient and Healthy Controls 8.4.2 Severity Score Classification 8.5 Results and Discussion 8.5.1 Performance Measures 8.5.2 Graphical Results 8.6 Conclusion References 9 AI-Based Smart Agriculture Monitoring Using Ground-Based and Remotely Sensed Images 9.1 Introduction 9.2 Automatic Land-Cover Classification Techniques Using Remotely Sensed Images 9.3 Deep Learning-Based Agriculture Monitoring 9.4 Adaptive Approaches for Multi-Modal Classification 9.4.1 Unsupervised DA 9.4.2 Semi-Supervised DA 9.4.3 Active Learning-Based DA 9.5 System Model 9.6 IEEE 802.15.4 9.6.1 802.15.4 MAC 9.6.2 DSME MAC 9.6.3 TSCH MAC 9.7 Analysis of IEEE 802.15.4 for Smart Agriculture 9.7.1 Effect of Device Specification 9.7.1.1 Low-Power 9.7.2 Effect of MAC Protocols 9.8 Experimental Results 9.9 Conclusion & Future Directions References 10 Car Buying Criteria Evaluation Using Machine Learning Approach 10.1 Introduction 10.2 Literature Survey 10.3 Proposed Method 10.4 Dataset 10.5 Exploratory Data Analysis 10.6 Splitting of Data Into Training Data and Test Data 10.7 Pre-Processing 10.8 Training of Our Models 10.8.1 Gaussian Naïve Bayes 10.8.2 Decision Tree Classifier 10.8.3 Tuning the Model 10.8.4 Karnough Nearest Neighbor Classifier 10.8.5 Tuning the Model 10.8.6 Neural Network 10.8.7 Tuning the Model 10.9 Result Analysis 10.9.1 Confusion Matrix 10.9.2 Gaussian Naïve Bayes 10.9.3 Decision Tree Classifier 10.9.4 Karnough Nearest Neighbor Classifier 10.9.5 Neural Network 10.9.6 Accuracy Scores 10.10 Conclusion and Future Work References 11 Big Data, Artificial Intelligence and Machine Learning: A Paradigm Shift in Election Campaigns 11.1 Introduction 11.2 Big Data Reveals the Voters’ Preference 11.2.1 Use of Software Applications in Election Campaigns 11.2.1.1 Team Joe App 11.2.1.2 Trump 2020 11.2.1.3 Modi App 11.3 Deep Fakes and Election Campaigns 11.3.1 Deep Fake in Delhi Elections 11.4 Social Media Bots 11.5 Future of Artificial Intelligence and Machine Learning in Election Campaigns References 12 Impact of Optimized Segment Routing in Software Defined Networks 12.1 Introduction 12.2 Software-Defined Network 12.3 SDN Architecture 12.4 Segment Routing 12.5 Segment Routing in SDN 12.6 Traffic Engineering in SDN 12.7 Segment Routing Protocol 12.8 Simulation and Result 12.9 Conclusion and Future Work References 13 An Investigation into COVID-19 Pandemic in India 13.1 Introduction 13.1.1 Symptoms of COVID-19 13.1.2 Precautionary Measures 13.1.3 Ways of Spreading the Coronavirus 13.2 Literature Survey 13.3 Technologies Used to Fight COVID-19 13.3.1 Robots 13.3.2 Drone Technology 13.3.3 Crowd Surveillance 13.3.4 Spraying the Disinfectant 13.3.5 Sanitizing the Contaminated Areas 13.3.6 Monitoring Temperature Using Thermal Camera 13.3.7 Delivering Essential Things 13.3.8 Public Announcement in the Infected Areas 13.4 Impact of COVID-19 on Business 13.4.1 Impact on Financial Markets 13.4.2 Impact on Supply Side 13.4.3 Impact on Demand Side 13.4.4 Impact on International Trade 13.5 Impact of COVID-19 on Indian Economy 13.6 Data and Result Analysis 13.7 Conclusion and Future Scope References 14 Skin Cancer Classification: Analysis of Different CNN Models via Classification Accuracy 14.1 Introduction 14.2 Literature Survey 14.3 Methodology 14.3.1 Dataset Preparation 14.3.2 Dataset Loading and Data Pre-Processing 14.3.3 Creating Models 14.4 Models Used 14.5 Simulation Results 14.5.1 Changing Size of MaxPool2D(n,n) 14.5.2 Changing Size of AveragePool2D(n,n) 14.5.3 Changing Number of con2d(32n–64n) Layers 14.5.4 Changing Number of con2d-32*n Layers 14.5.5 ROC Curves and MSE Curves 14.6 Conclusion References 15 Route Mapping of Multiple Humanoid Robots Using Firefly-Based Artificial Potential Field Algorithm in a Cluttered Terrain 15.1 Introduction 15.2 Design of Proposed Algorithm 15.2.1 Mechanism of Artificial Potential Field 15.2.1.1 Potential Field Generated by Attractive Force of Goal 15.2.1.2 Potential Field Generated by Repulsive Force of Obstacle 15.2.2 Mechanism of Firefly Algorithm 15.2.2.1 Architecture of Optimization Problem Based on Firefly Algorithm 15.2.3 Dining Philosopher Controller 15.3 Hybridization Process of Proposed Algorithm 15.4 Execution of Proposed Algorithm in Multiple Humanoid Robots 15.5 Comparison 15.6 Conclusion References 16 Innovative Practices in Education Systems Using Artificial Intelligence for Advanced Society 16.1 Introduction 16.2 Literature Survey 16.2.1 AI in Auto-Grading 16.2.2 AI in Smart Content 16.2.3 AI in Auto Analysis on Student’s Grade 16.2.4 AI Extends Free Intelligent Tutoring 16.2.5 AI in Predicting Student Admission and Drop-Out Rate 16.3 Proposed System 16.3.1 Data Collection Module 16.3.2 Data Pre-Processing Module 16.3.3 Clustering Module 16.3.4 Partner Selection Module 16.4 Results 16.5 Future Enhancements 16.6 Conclusion References 17 PSO-Based Hybrid Weighted k-Nearest Neighbor Algorithm for Workload Prediction in Cloud Infrastructures 17.1 Introduction 17.2 Literature Survey 17.2.1 Machine Learning 17.3 Proposed System 17.3.1 Load Aware Cloud Computing Model 17.3.2 Wavelet Neural Network 17.3.3 Evaluation Using LOOCV Model 17.3.4 k-Nearest Neighbor (k-NN) Algorithm 17.3.5 Particle Swarm Optimization (PSO) Algorithm 17.3.6 HWkNN Optimization Algorithm Based on PSO 17.3.7 PSO-Based HWkNN (PHWkNN) Load Prediction Algorithm 17.4 Experimental Results 17.5 Conclusion References 18 An Extensive Survey on the Prediction of Bankruptcy 18.1 Introduction 18.2 Literature Survey 18.2.1 Data Pre-Processing 18.2.1.1 Balancing of Imbalanced Dataset 18.2.1.2 Outlier Data Handling 18.2.2 Classifiers 18.2.3 Ensemble Models 18.3 System Architecture and Simulation Results 18.4 Conclusion References 19 Future of Indian Agriculture Using AI and Machine Learning Tools and Techniques 19.1 Introduction 19.2 Overview of AI and Machine Learning 19.3 Review of Literature 19.4 Application of AI & Machine Learning in Agriculture 19.5 Current Scenario and Emerging Trends of AI and ML in Indian Agriculture Sector 19.6 Opportunities for Agricultural Operations in India 19.7 Conclusion References Index Also of Interest Check out these published and forthcoming titles in the “Artificial Intelligence and SoftComputing for Industrial Transformation
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