Emerging Technologies for Combatting Pandemics

This book focuses on both the design and implementation of AI-based approaches for systems that aid in monitoring and combating pandemics such as occurred with COVID-19. These systems are based on the Internet of Medical Things (IoMT), using sensor networks and other advanced technologies. The book examines different aspects of AI and IoMT.

Dr. M. Rubaiyat Hossain Mondal is a Professor in the Institute of Information and Communication Technology (IICT) at Bangladesh University of Engineering and Technology (BUET), Bangladesh. Dr. Utku Kose is an Associate Professor in Suleyman Demirel University, Turkey. Dr. Surya Prasath is a mathematician with expertise in the application areas of image processing and computer vision. Dr. Prajoy Podder is a researcher at the Institute of Information and Communication Technology, Bangladesh University of Engineering and Technology. Dr. Subrato Bharati is a researcher at the Institute of Information and Communication Technology, Bangladesh University of Engineering and Technology. Dr. Joarder Kamruzzaman is a Professor at the School of Engineering, Information Technology and Physical Sciences, Federation University, Australia.

Foreword. Preface. Acknowledgments. About the Editors. List of Contributors. 1 Artificial Intelligence Leveraged Internet of Medical Things and Continuous Health Monitoring and Combating Pandemics within the Internet of Medical Things Framework. 2 Assessing the Economic Impact of COVID-19. 3 Assessing the Economic Impact of COVID-19 on the Implications of the Internet of Things Adoption on Small and Medium Enterprise Business's Sustainability. 4 Impact of COVID-19: Insights from Key Sectors of the Indian Economy. 5 Future Scope of Artificial Intelligence in Healthcare for COVID-19. 6 Patient Recovery and Tracing Repercussions for COVID-19 in Discharged Patients. 7 The Impact of COVID-19 on the Maritime Economy: A Study on Bangladesh. 8 Intelligent Optimization and Computational Learning Techniques for Mitigating Pandemics. 9 Various Deep Learning Methodologies for COVID-19 Diagnosis. 10 Hybridization of Decision Tree Algorithm Using Sequencing Predictive Model for COVID-19. 11 CoVICU: A Smart Model for Predicting the Intensive Care Unit Stay of COVID-19 Patients Using Machine Learning Techniques. 12 Long Short-Term Memory-Based Recurrent Neural Network Model for COVID-19 Prediction in Different States of India. 13 Dengue in the Presence of COVID-19: Evaluation of Tree-Based Classifiers Using Stratified K- Fold on Dengue Dataset. Index.