In today’s world, there is nothing permanent except change. We have seen the advent of the Fourth Industrial Revolution or Industry 4.0 over the last couple of years. Now is a perfect time to think about Industry 4.0 technology and leverage its advantages for the benefit of mankind. It cannot prevent the onset of pandemics; however, it can help and has helped prevent spread, educate, warn, and empower those on the ground to be aware of the situation, and noticeably lessen the impact. Industry 4.0 can fulfill the requirements of customized facemasks, gloves, and collect information for healthcare systems for proper controlling and treating of COVID-19 patients. Major technologies of Industry 4.0 are required to solve the problems of this virus. It is useful to provide day-to-day updates of an infected patient, area-wise, age-wise and state-wise with proper surveillance systems. We also believe that the proper implementation of these technologies would help to enhance education and communication regarding public health. These Industry 4.0 technologies could provide a lot of innovative ideas and solutions for fighting local and global medical emergencies. Today, we need to focus on technologies like mobile, cloud, analytics, robotics, AI/ML, 4G/5G, and high-speed internet; it has become possible to test several innovative approaches to pandemic response. The objective of this book is to bring together leading academic scientists, research scholars and professionals to exchange and share their experiences and research results in Industry 4.0 and Intelligent Business Analytics. This research-oriented book will provide a common platform to all researchers in this domain. It covers different verticals of industry and academics, which is an added advantage of this book.
Author(s): Soumi Dutta, Vinod Kumar Shukla, Shruti Nagpal, M. Niranjanamurthy
Series: Advances in Distributed Computing and Intelligent Data Analytics
Publisher: Nova Science Publishers
Year: 2022
Language: English
Pages: 360
City: New York
Contents
Preface
Part I. Industry 4.0 and Healthcare
Chapter 1
Human Computer Interface Trends in Healthcare: Industry 4.0 View
Abstract
Introduction
Human Computer Interaction
Core Components of Industry 4.0
Core Principles of Industry 4.0
Drivers and Challenges for Healthcare 4.0
Approach: Technologies of Industry 4.0 in Healthcare
Conclusion
References
Chapter 2
Role of Urban Control Centers
for City Planning and Monitoring
in a Pandemic Outbreak
Abstract
Introduction
Emergency-Prone Atmosphere of Cities
Metropolitan Data Management for Improved Responsivity
COVID-19 Endemic Perspective
Decision-Making Data during a Pandemic
Processing of Massive Data
Smart City Future Innitiatives
Conclusion
References
Chapter 3
Industry 4.0 for Promoting Health Inclusion in Emerging Markets: A Systematic Study of Narayana Healthcare, India
Abstract
Introduction
Health Care 1.0 to Health Care 4.0
Literature Review
Technology Integration in Health Care Sector in the Frame Work of Industry 4.0
Research Gap and Objectives of the Chapter
Business Model Filling the Institutional Voids
Implementation of Industry 4.0 for Health Inclusion
Scale Driven Model: The Road Ahead
Conclusion and Recommendations
References
Chapter 4
Bitcoin Mining and Its Utility in the Healthcare Sector
Abstract
Introduction
Bitcoin
Conceptual Model for Bitcoin Mining in Healthcare
The Bitcoin Blockchain
Attributes of Blockchain
How Blockchain Works
Bitcoin Mining
Bitcoin Operational Framework
How to Start Bitcoin Mining?
How does Bitcoin Mining Works?
Hashing
Bitcoin Mining Hardware
Selecting Best Bitcoin Miners
Bitcoin Mining Software
Hashing Algorithms
Various Types of Algorithms
Conclusion
References
Chapter 5
Vocational Training and Integrative Technology in Neurodiverse Workforce
Abstract
Introduction
Theoretical Background
The Neurodiversity Paradigm
Principles
In Practice
Classification and Development of Neurodiverse Population
Autism Spectrum Disorder
Attention Deficit Hyperactivity Disorder (ADHD)
Applied Integrative Technology for Neurodiverse Individuals
Skill Acquisition, Life Skills, and Independency for Neurodiverse Workforce
Skill Acquisition
Life Skills
Independency
The Neurodiverse Workforce
Neurodiversity at Workplace
Strength-Based Approach
Challenges Around Neurodiversity and Work
Recruiting for Neurodiversity
References
Chapter 6
Use of Some Standard Mathematical Models in Physiology and Pathology
Abstract
Introduction
Objective of Mathematical Modelling
Role of Mathematical Models in the Study of Brain Injury Problems
Model I: Mathematical Model of Brain Injury Problem When the Cranium Is Subjected to an Angular Acceleration
Model 2: Mathematical Model of Brain Injury Problem When the Outermost Surface of the Cranium Is Subjected to a Time-Dependent Impulsive Force
Role of Mathematical Models in the Study of Blood Flow Through an Atherosclerotic Arterial Segment
Model 3: Mathematical Model of Multiple Stenoses in the Human Artery Taking H-B Model for Blood
Model 4: Mathematical Model of Multiple and Overlapped Stenoses in the Human Artery Taking Bingham Plastic Fluid Model for Blood
Model 5: Mathematical Model for Population Growth in India Using ODE
Model 6: Mathematical Model for Decaying of the Absorption of a Medicine in Human Rheological System with ODE
Model 7: Mathematical Model for the Spread of a Disease Growing or Decaying Exponentially
Conclusion
References
Chapter 7
Training Healthcare Professionals in Artificial Intelligence Augmented Services
Abstract
Introduction
The Need for Artificial Intelligence in Medical Practice
New Frontiers in Artificial Intelligence Augmented Healthcare
Streamlining Hospital Workflows
Administrative Tasks of Physicians
Clinical Decision-Making Support
Medical Imaging
Diagnostic Pathology
Precision Medicine
Population Medicine
Legal and Ethical Challenges
A Need to ‘Reboot’ Medical Education
AI in Medical Education: A Snapshot
Tighter Integration of Medical Education
Mitigating Apprehension
Conclusion
References
Part 2. Artificial Intelligence and Machine Learning in Healthcare
Chapter 8
Healthcare Sector and Use of Artificial Intelligence Technology in Modern Times
Abstract
Introduction
Artificial Intelligence in Healthcare
Conformity Concerns Occurring from Application of Artificial Intelligence to Medical Technologies
Conclusion
References
Chapter 9
Prediction of Cardiovascular Diseases Using Data Mining - Machine Learning and Deep Learning System
Abstract
Introduction
Literature Review
Heart
Structure of the Heart
Heart Wall
Chambers
Valves
Pericardium
Left Heart and Right Heart
Blood Circulation and Nerve Supply of the Heart
Development of the Heart
Types of Heart Diseases
Ischaemic
Valvular
Pericardial
Congenital
Arrhythmias
Failure
Tools and Machines Used for Diagnosis
General Examination
EchoCG
Imaging
Blood Test
Electrocardiogram (ECG)
Symptoms, Causes and Factors Which Are Likely to Cause a Risk
Symptoms
Causes
Risk Factors
Data Mining
Machine Learning
Naïve Bayes Algorithm
Decision Trees
Support Vector Machine Algorithm
Logistic Regression
Random Forest Classifier Algorithm
Deep Learning
Neural Networks
Proposed System through Machine Learning and Deep Learning
Parameters Used to Achieve the Output
Machine Learning Application Results Explained with Sample Outputs
ECG Deep Learning and Imaging
Conclusion
References
Chapter 10
Artificially Intelligent Queueing Modeling Approach to Analyzing and Improving Health Care Systems
Abstract
Introduction
Model Assumptions
Materials and Methods
Queueing Model
M/M/1 Model
Single Server Queueing Model
Multi-Server Queuing Model
Service Time
Busy Period
Idle Period
Artificial Intelligence
Artificial Neural Network Approach
Queuing Model Analysis
Supervised and Unsupervised Learning
Supervised Training
Unsupervised Training
Training Set
Test Set
Prediction of Results
Validation
Conclusion
References
Chapter 11
Clientele Perception and Trust on Artificial Intelligence Integrated Health Services
Abstract
Introduction
Background and Theories
AI Integrated Health Services
Ethical Principles
Trust and Perception
Methodology
Data Analysis
Results
Preliminary Survey: Trust Rating
Qualitative Analysis: Clientele Perceptions
Awareness and Knowledge of AI Health Services
Perception on AI-Assisted Diagnosis and Treatment
Perception on Independent AI Diagnosis and Treatment
Perception on AI-Integrated Hospital Systems
Conclusion and Recommendation
Appendix
References
Chapter 12
Leveraging Deep Learning: Early Detection and Prediction of Brain Disorders
Abstract
Introduction
Introduction to Deep Learning
Fundamentals of Deep Learning
Neural Networks
Artificial Intelligence (AI)
Machine Learning
Deep Learning in Neurology
Application of Machine Learning and Deep Learning in the Detection and Prediction of Various Brain Disorders
Applications in Medical Domain
Medical Image Classification
Medical Image Segmentation
Classification of Brain Disorders and Functional Connectivity
Data Reconstruction Techniques
Image Reconstruction
Signal Enhancement
Cross-Modality Image Synthesis
Proposed Framework for Early Detection and Prediction of Neurological Disorder
Software Requirements
Parameters Used to Achieve the Output
Machine Learning Application Results
Random Forest Classifier
Deep Learning Example
Clinical Significance
Future Trends
Discussion
Conclusion
References
Part 3. COVID-19, Healthcare and Technology
Chapter 13
COVID-19 Pandemic: Recovery and Death Ratio Analysis Based on Latitude Using Correlation and ANOVA
Abstract
Introduction
Background
COVID-19 Pandemic
ANOVA
Research Methodology
Result and Discussion
Conclusion
References
Chapter 14
Pillars of a Corruption Free Economically Strong Healthcare Industry during COVID-19: Artificial Intelligence and Global Connectivity
Abstract
Introduction
Literature Review
Objectives
Hypothesis
Research Methodology
Analysis and Findings
GDP-AI (Index): Artificial Intelligence Usage and Gross Domestic Product
Global Connectivity Index (GCI) and Corruption Perception Index (CPI)
Healthcare Free from Corruption Index (GCI_CPI_HCI)
Conclusion
Practical Implications
References
Chapter 15
Analyzing COVID-19 and Other Pandemics through Human-Computer Interaction
Abstract
Introduction
Challenges Posed by Pandemics
Role of HCI In Pandemics
Severe Acute Respiratory Syndrome (SARS) -2003
(H1N1) Influenza -2009
Ebola Virus Disease (EVD) – 2013
COVID 19 -2019
Result
Conclusion
References
Chapter 16
Electronic Health Records and Challenges in Human Computer Interaction
Abstract
Introduction
Challenges of Electronic Health Records
Addressing the Challenges
Display of Information
Overload of Cognition
Poor Navigation
Conflict with the Workflow
Functionality Support
Conclusion
References
Chapter 17
A Novel Model to Anticipate Transparency in COVID-19 Records of India Using Blockchain
Abstract
Introduction
Background
Proposed Blockchain Based Model
to Anticipate Transparency
Result and Discussion
Conclusion
References
Chapter 18
Applications and Implementation of Contactless Hand Sanitizer Using Proximity Sensor
Abstract
Introduction
Use and Importance of Technology during Pandemic Time
Need and Consumption of Sanitizer Worldwide
Hardware Requirement
Infrared Sensor
TIP32C or BD140 Transistor
1k Resistor
18650 Double Battery Holder
6V Water Pump
Aquarium Tube
18650 Batteries
Coffee Jar
Circuit Diagram: Sensor Based Contactless Hand Sanitizer
Placement of the Circuit
Testing of Infrared Proximity Sensor
Result and Understanding
Conclusion
References
About the Editors
About the Contributors
Index
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