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Submit a ProposalThe New Advanced Society
 | Artificial Intelligence and Industrial Internet of Things Paradigm Edited by Sandeep Kumar Panda, Ramesh Kumar Mohapatra, Subharkanta Panda, and S. Balamurugan Series: Artificial Intelligence and Soft Computing for Industrial Transformation Copyright: 2022 | Status: Published ISBN: 9781119824473 | Hardcover | 473 pages | 185 illustrations Price: $225 USD  |
One Line Description
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.
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.
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.
Description
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.
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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.
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Author / Editor Details
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.
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.
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Table of Contents
Preface
Acknowledgments
1. Post Pandemic: The New Advanced Society
Sujata Priyambada Dash
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 Colleges Closures
1.2 Conclusions
References
2. Distributed Ledger Technology in the Construction Industry Using Corda
Sandeep Kumar Panda, Shanmukhi Priya Daliyet, Shagun S. Lokre and Vihas Naman
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
Soumya Prakash Otta and Subhrakanta Panda
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
Banhi Sanyal, Piyush R. Biswal, R.K. Mohapatra, Ratnakar Dash and Ankush Agarwalla
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
4.5.5 Pre-Trained Models
4.6 Discussion
4.7 Conclusion
References
5. Honeypot: A Trap for Attackers
Anjanna Matta, G. Sucharitha, Bandlamudi Greeshmanjali, Manji Prashanth Kumar and Mathi Naga Sarath Kumar
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 Aspect in Industrial-Based Internet of Things
Rohini Jha
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
D. Chandrasekhar Rao
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
Prashant Kumar Shrivastava, Ashish Chaturvedi, Megha Kamble and Megha Jain
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
Shounak Chakraborty, Nikumani Choudhury and Indrajit Kalita
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
Samdeep Kumar Panda
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
Md. Safiullah and Neha Parveen
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 Network Amrutanshu Panigrahi, Bibhuprasad Sahu, Satya Sobhan Panigrahi, Ajay Kumar Jena and Md. Sahil Khan
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
Shubhangi V. Urkude, Vijaykumar R. Urkude, S. Vairachilai and Sandeep Kumar Panda
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 the 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
Poonam Biswal, Monali Saha, Nishtha Jaiswal and Minakhi Rout
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
Abhishek Kumar Kashyap, Anish Pandey and Dayal R. Parhi
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
Vinutha D.C., Kavyashree S., Vijay C.P. and G.T. Raju
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
N. Yamuna, J. Antony Vijay and B. Gomathi
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
Sasmita Manjari Nayak and Minakhi Rout
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
Manoj Kumar, Pratibha Maurya and Rinki Verma
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
Back to Top
Preface
Acknowledgments
1. Post Pandemic: The New Advanced Society
Sujata Priyambada Dash
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 Colleges Closures
1.2 Conclusions
References
2. Distributed Ledger Technology in the Construction Industry Using Corda
Sandeep Kumar Panda, Shanmukhi Priya Daliyet, Shagun S. Lokre and Vihas Naman
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
Soumya Prakash Otta and Subhrakanta Panda
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
Banhi Sanyal, Piyush R. Biswal, R.K. Mohapatra, Ratnakar Dash and Ankush Agarwalla
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
4.5.5 Pre-Trained Models
4.6 Discussion
4.7 Conclusion
References
5. Honeypot: A Trap for Attackers
Anjanna Matta, G. Sucharitha, Bandlamudi Greeshmanjali, Manji Prashanth Kumar and Mathi Naga Sarath Kumar
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 Aspect in Industrial-Based Internet of Things
Rohini Jha
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
D. Chandrasekhar Rao
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
Prashant Kumar Shrivastava, Ashish Chaturvedi, Megha Kamble and Megha Jain
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
Shounak Chakraborty, Nikumani Choudhury and Indrajit Kalita
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
Samdeep Kumar Panda
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
Md. Safiullah and Neha Parveen
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 Network Amrutanshu Panigrahi, Bibhuprasad Sahu, Satya Sobhan Panigrahi, Ajay Kumar Jena and Md. Sahil Khan
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
Shubhangi V. Urkude, Vijaykumar R. Urkude, S. Vairachilai and Sandeep Kumar Panda
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 the 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
Poonam Biswal, Monali Saha, Nishtha Jaiswal and Minakhi Rout
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
Abhishek Kumar Kashyap, Anish Pandey and Dayal R. Parhi
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
Vinutha D.C., Kavyashree S., Vijay C.P. and G.T. Raju
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
N. Yamuna, J. Antony Vijay and B. Gomathi
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
Sasmita Manjari Nayak and Minakhi Rout
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
Manoj Kumar, Pratibha Maurya and Rinki Verma
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
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