Intelligent Systems and Methods to Combat Covid-19

✍ Scribed by Amit Joshi, Nilanjan Dey, K. C. Santosh

• Publisher: Springer Singapore
• Year: 2020
• Tongue: English
• Leaves: 98
• Series: SpringerBriefs in Computational Intelligence
• Category: Library

✦ Synopsis

This book discusses intelligent systems and methods to prevent further spread of COVID-19, including artificial intelligence, machine learning, computer vision, signal processing, pattern recognition, and robotics. It not only explores detection/screening of COVID-19 positive cases using one type of data, such as radiological imaging data, but also examines how data analytics-based tools can help predict/project future pandemics. In addition, it highlights various challenges and opportunities, like social distancing, and addresses issues such as data collection, privacy, and security, which affect the robustness of AI-driven tools. Also investigating data-analytics-based tools for projections using time series data, pattern analysis tools for unusual pattern discovery (anomaly detection) in image data, as well as AI-enabled robotics and its possible uses, the book will appeal to a broad readership, including academics, researchers and industry professionals.

✦ Table of Contents

Preface
Contents
About the Editors
Data Analytics: COVID-19 Prediction Using Multimodal Data
1 Introduction
2 Medical Perspectives
3 Related Works
4 Predictive Analytics
4.1 Predictive Analytics Models
4.2 Predictive Analytics Algorithms
5 Conclusion
References
COVID-19 Apps: Privacy and Security Concerns
1 Introduction
2 COVID-19 Apps
3 Advantages and Concerns of COVID-19 Apps
4 Discussions and Recommendations
5 Conclusions
References
Coronavirus Outbreak: Multi-Objective Prediction and Optimization
1 Introduction
2 Coronavirus: Symptoms, Prevention, Impingement
2.1 Impingement
3 Coronavirus Outbreak—Mathematical Perceptions
3.1 Constraints
3.2 Objectives and Measures Adopted
4 Constrained Multi-Objective Prediction and Optimization
5 Scope to Use Artificial Intelligence and Data Science
6 Conclusion
References
AI-Enabled Framework to Prevent COVID-19 from Further Spreading
1 Introduction
2 Background
3 Motivation and Contributions
4 A Novel Methodology
5 Results and Discussion
6 Conclusion
References
Artificial Intelligence-Enabled Robotic Drones for COVID-19 Outbreak
1 Introduction
2 Motivation and Contributions
3 Related Work on COVID-19 Outbreak
3.1 Robotic Technology
3.2 Drones Against COVID-19
3.3 AI-Enabled Intelligent Networks
3.4 5G: Coronavirus Outbreak
3.5 5G: COVID-19 Affected Africa
4 Conclusion
References
Understanding and Analysis of Enhanced COVID-19 Chest X-Ray Images
1 Introduction
2 Proposed Methodology
2.1 Illumination Estimation
2.2 Estimation of Reflectance
2.3 Validation of Enhanced Using Wavelet Energy (WE) Metric
3 Experiment Results and Comparative Analysis
4 Discussion and Conclusion
References
Deep Learning-Based COVID-19 Diagnosis and Trend Predictions
1 Introduction
2 Related Work
3 Deep Learning for COVID-19 Diagnosis
4 Prediction Model About COVID-19 Outbreak
5 Conclusions
References
COVID-19: Loose Ends
1 Introduction
2 Discussion of Parameters of COVID-19
3 Modeling Techniques for Different Phases of COVID-19
4 Role of AI, Robotics, and IOT
5 Summary
References
Social Distancing and Artificial Intelligence—Understanding the Duality in the Times of COVID-19
1 Introduction
2 Social Distancing and Its Relevance During the Spread of COVID-19
3 Artificial Intelligence in the Times of COVID-19
4 Impact of AI on Social Distancing
5 Case Studies Related to Application of Artificial Intelligence
5.1 Case Study 1
5.2 Case Study 2
5.3 Case Study 3
6 Conclusions
References
Post-COVID-19 and Business Analytics
1 Introduction
2 Advantages of Using the AI After the End of COVID-19 Crisis
3 Application of AI for Global Development in Post-COVID-19
4 An Experiment on Application of the AI on Forecasting Cryptocurrency
5 Challenges of Using the AI After the End of COVID-19 Crisis
6 Conclusion
Appendix: Actual and Predicted Values from ANN Models
References