In the battle against the COVID-19 pandemic, the integration of Internet of Things (IoT) technologies has played a pivotal role in reshaping public health and healthcare delivery. Interconnected devices have demonstrated their capacity to collect, transmit, and analyze data, significantly impacting various aspects of pandemic management.
COVID-19 - Monitoring with IoT Devices is a comprehensive guide to measuring the impact of COVID-19 infection and monitoring outbreak metrics. Beginning with an introduction to SARS-CoV-2 and its symptoms, the book presents chapters on machine learning (supervised and unsupervised algorithms) and techniques to predict COVID-19 outcomes. The book concludes with the role of IoT technology in detecting COVID-19 infections within a community, showcasing different computing models applicable to specific use-cases.
Covers a data-driven approach to COVID-19 monitoring by explaining methods for data collection, prediction, and analysis.
Includes specific recommendations for machine learning algorithms designed for COVID-19 monitoring.
Easy-to-read structured chapters suitable for novices in computer science and biomedical engineering.
COVID-19 - Monitoring with IoT Devices provides a valuable resource for understanding the role of IoT technology in managing and mitigating the impact of COVID-19, and developing adequate infection control policies. It also showcases the potential of IoT for future research and applications in the healthcare sector. This book is intended for a diverse readership, including academicians, industry professionals, researchers, and healthcare practitioners.
COVID-19 - Monitoring with IoT Devices is a comprehensive guide to measuring the impact of COVID-19 infection and monitoring outbreak metrics. Beginning with an introduction to SARS-CoV-2 and its symptoms, the book presents chapters on machine learning (supervised and unsupervised algorithms) and techniques to predict COVID-19 outcomes. The book concludes with the role of IoT technology in detecting COVID-19 infections within a community, showcasing different computing models applicable to specific use-cases.
Key Features:
Explores the pivotal role of IoT technology in the fight against the COVID-19 pandemic.Covers a data-driven approach to COVID-19 monitoring by explaining methods for data collection, prediction, and analysis.
Includes specific recommendations for machine learning algorithms designed for COVID-19 monitoring.
Easy-to-read structured chapters suitable for novices in computer science and biomedical engineering.
COVID-19 - Monitoring with IoT Devices provides a valuable resource for understanding the role of IoT technology in managing and mitigating the impact of COVID-19, and developing adequate infection control policies. It also showcases the potential of IoT for future research and applications in the healthcare sector. This book is intended for a diverse readership, including academicians, industry professionals, researchers, and healthcare practitioners.
Table of Contents
- Contents
- Foreword I
- Foreword Ii
- Preface
1.1. Introduction
1.2. Symptoms
1.3. Measures
1.3.1. Demographic Information
1.3.2. Depressive Symptoms
1.3.3. Emotional Health
1.4. Potential Impact
1.4.1. Using Machine Learning
1.4.2. Using IoT Devices
1.5. Overview of the Book
- Conclusion
- References
2.1. Introduction
2.2. Supervised Learning Algorithms
2.2.1. Support Vector Machine
2.2.2. Artificial Neural Network
2.2.3. Naive Bayes Method
2.2.4. K-Nearest Neighbor
2.2.5. Decision Support System
2.2.6. One Rule (Oner)
2.2.7. Zero Rule (Zeror)
2.3. Linear Regression
2.3.1. Random Forest
2.3.2. Gradient Boosted Regression Tree
2.3.3. Perception Back-Propogation
2.4. Drawbacks
2.5. Future Directions
- Conclusion
- References
3.1. Introduction
3.2. Semi-Supervised Algorithms in Healthcare
3.2.1. Linear Regression
3.2.2. Multiple Regression
3.2.3. Logistic Regression
3.3. Drawbacks
- Conclusion
- References
4.1. Introduction
4.2. Clustering
4.3. Drawbacks
- Conclusion
- References
5.1. Introduction
5.2. Architecture
5.3. Role of IoT in Covid-19
5.3.1. IoT - Healthcare
5.3.2. Role of Iot-Transportation in Covid-19
5.3.3. Role of Iot-Entertainment During Covid-19
5.3.4. Role of Iot-Retail
5.3.5. Role of Iot-Education During Covid-19
5.4. Role of Cloud
5.5. Challenges
5.5.1. Awareness
5.5.2. Accesibility
5.5.3. Human Power Crisis
5.6. Affordability
5.7. Accountability
5.8. Drawbacks
5.9. Future Directions
5.9.1. Edge Architecture in H-Iot
5.9.2. Cryptography With Computing in H-Iot
5.9.3. Blockchain Based H-Iot
5.9.4. Machine Learning in H-Iot
5.9.5. Digital Twin in H-Iot
5.9.6. Unified Network Integration Framework
5.9.7. Context Aware Accessibility
5.9.8. Edge and Fog Computing
5.9.9. Sensors and Actuator Integration in H-Iot
- Conclusion
- References
- Subject Index
Author
- Ambika Nagaraj
