Intelligent Systems and Methods to Combat Covid-19

Description

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. 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