Artificial intelligence of health-enabled spaces

Chapter 1: IoT and Machine Learning- Based Smart Healthcare System for Monitoring Patients Chapter 2: Detection and Diagnosis of COVID- 19 from Chest X- Ray Images Using Deep Learning Chapter 3: Analysing the Stages of Diabetic Retinopathy Using Deep Learning Techniques Chapter 4: COVID- 19 Detection Based on Deep Learning Feature Extraction and AdaBoost Ensemble Classifier Chapter 5: Deep Learning and Transfer Learning Models for Detection of COVID- 19 Chapter 6: Industry 4.0 Challenges and Applications in the Healthcare Industry with Emerging Technologies Chapter 7: Cyber- Security Countermeasures and Vulnerabilities to Prevent Social-Engineering Attacks Chapter 8: Development of a COVID- 19 Tracking System Chapter 9: An Overview of Autonomous Perception for a Robotic Arm Chapter 10: Artificial Intelligence- Based Methods for SARS- CoV- 2 Detection with CRISPR Systems

The primary objective of this book is to concentrate on the advancement and examination of artificial intelligence (AI) model applications in various fields of study. The book includes AI-based deep learning models, fuzzy and hybrid intelligent systems, and intrinsic explainable models. This smart health-oriented book explores several domains where AI applications are considered, such as electrical engineering, biomedical engineering, environmental engineering, computer engineering, education, cyber security, chemistry, pharmacy, molecular biology, and tourism. This book is dedicated to addressing the major challenges in fighting diseases and psychological issues using AI. The aim of the book is hence to focus on both the design and implementation aspects of AI-based approaches in the proposed health-related solutions.