3Figure 3.1 Overall design.Figure 3.2 Kernel Function on non-linear SVM.Figure 3.3 Working of random forest algorithm.4 Chapter 4Figure 4.1 Home view of touch interaction.Figure 4.2 Cross language selection display for both doctor and patient.Figure 4.3 Categorical interactions initiated by doctor.Figure 4.4 Categorical interactions initiated by patient.Figure 4.5 A sample interactive interface in English.Figure 4.6 Figure 4.5’s interactions in Tamil.Figure 4.7 A sample interactive interface in English and Tamil.Figure 4.8 A sample case study for native language selection for patient and doc...Figure 4.9 Doctor interaction view of his/her language.Figure 4.10 Patient receives doctor’s interaction in native voice & reply throug...
5 Chapter 5Figure 5.1 Framework of proposed system.Figure 5.2 Flowchart of the proposed model.Figure 5.3 Snapshot of the home screen on the website.Figure 5.4 Snapshot of the ‘Registration Details’ page on the website.Figure 5.5 Snapshot of the ‘Patient’s Test Details’ page on the website.Figure 5.6 Snapshot of the ‘Sensor Readings’ page of a patient on the website.Figure 5.7 Snapshots of the screen of the phone application showing the differen...Figure 5.8 Snapshot from the phone application showing the Pulse Rate reading of...
6 Chapter 6Figure 6.1 General methodology of our proposed model.Figure 6.2 Algorithm of proposed framework.
7 Chapter 7Figure 7.1 Proposed system design and architecture model.Figure 7.2 Login window for Doctor/Nurse/Health official login from computer ter...Figure 7.3 Login window for Doctor/Nurse/Health official login from Android devi...Figure 7.4 Patient monitoring window from computer terminal.Figure 7.5 Patient monitoring window from Android tablet.Figure 7.6 Flowchart for patient clearance.Figure 7.7 Flowchart for relative clearance.Figure 7.8 Flowchart for pharmacy services clearance.Figure 7.9 Flowchart for researcher clearance.Figure 7.10 Flowchart for emergency services clearance.Figure 7.11 Flowchart for Doctor clearance.Figure 7.12 UI of unsuccessful login authentication.Figure 7.13 UI of unsuccessful OTP/MFA authentication.
8 Chapter 8Figure 8.1 Important physiologic roles of non-essential amino acids (NEAA) in hu...Figure 8.2 Overall block diagram of IOT-based health monitoring system.
9 Chapter 9Figure 9.1 Body area network [18].Figure 9.2 Various interconnection protocols in neighborhood area network.Figure 9.3 Various IoT networking devices.Figure 9.4 Smart medical network.Figure 9.5 Level of data security.Figure 9.6 Security constraints in medical IoT.Figure 9.7 Layers of healthcare security.Figure 9.8 Root of trust.Figure 9.9 Chain of trust.Figure 9.10 Architecture diagram of smart healthcare.Figure 9.11 Blockchain based IoT smart healtcare.
10 Chapter 10Figure 10.1 Overview of system architecture.Figure 10.2 Schematic diagram of the proposed system.Figure 10.3 An example of MQTT protocol use-case with different topics and clien...Figure 10.4 Quality of service (0) of MQTT.Figure 10.5 Quality of service (1) of MQTT.Figure 10.6 Quality of service (2) of MQTT.Figure 10.7 Raspberry Pi board (model RasPi B).Figure 10.8 Custard Pi 3A.Figure 10.9 Huba type 663 differential pressure transmitter.Figure 10.10 Flow chart of the publisher algorithm.Figure 10.11 Flow chart of the subscriber algorithm.Figure 10.12 Remote monitoring system for gas turbine engine using IoT.Figure 10.13 The experimental setup.Figure 10.14 Data from sensor 1.Figure 10.15 Data from sensor 2.Figure 10.16 Data from sensor 3.Figure 10.17 Data from sensor 4.Figure 10.18 Data from sensor 5.Figure 10.19 Data from sensor 6.Figure 10.20 Total energy consumed by each sensor with and without the proposed ...Figure 10.21 The overall energy consumption in the system with and without the p...Figure 10.22 Total bytes transmitted by RasPi with and without the proposed algo...Figure 10.23 Data storage with and without the proposed algorithm.Figure 10.24 Traceroute command in Linux.Figure 10.25 Traceroute command in Windows.Figure 10.26 Total number of transmitted bytes from the RasPi to the monitoring ...
11 Chapter 12Figure 12.1 Views of AI [10].Figure 12.2 Different types of artificial intelligence.Figure 12.3 Intelligent agent.Figure 12.4 Various disciplines of AI [15, 16].Figure 12.5 The relation between AI, ML, and DL.Figure 12.6 Industry 4.0 [19].Figure 12.7 Types of industrial revolutions.Figure 12.8 Role of ML in Industry 4.0.Figure 12.9 Challenges in Industry 4.0 [29, 30].Figure 12.10 Other Industries that adopt new trends.
12 Chapter 13Figure 13.1 Preliminary screening of COVID-19 patients.
13 Chapter 14Figure 14.1 Flow chart—symptoms of COVID-19 and predictive measures.Figure 14.2 Linear regression model.Figure 14.3 Adequacy model.Figure 14.4 Stationarity analysis.Figure 14.5 Auto correlation functional values—time and lag.Figure 14.6 Partial autocorrelation.Figure 14.7 Time plot of daily COVID-19 new cases in the world during 22-Jan 22-...Figure 14.8 Time plot of daily COVID-19 new deaths in the world during 22-Jan-20...Figure 14.9 Plots of ACF values for daily COVID-19-new cases in the world.Figure 14.10 Plots of PACF values for daily COVID-19 new cases in the world.Figure 14.11 Plots of ACF values for daily COVID-19 deaths in the world.Figure 14.12 Plots of PACF values for daily COVID-19 new new deaths in the world...Figure 14.13 Time plot of new cases across the globe during 22 Jan-2020 to 31-Ma...Figure 14.14 Time plot of second differencing for new cases and deaths in the wo...Figure 14.15 Plots of ACF values of second differencing of daily new cases in th...Figure 14.16 Plots of PACF values of second differencing of daily new cases in t...Figure 14.17 Plots of ACF values of second differencing of daily new deaths in t...Figure 14.18 Plots of PACF values of second differencing of daily new deaths in ...Figure 14.19 Plotting of ACF and PACF values for estimated residuals of daily ne...Figure 14.20 Plotting of ACF and PACF values for estimated residuals of daily ne...Figure 14.21 Normal P–P plot of estimated residual daily new cases.Figure 14.22 Normal P–P plot of estimated of residuals of daily new deaths.Figure 14.23 Forecast graph of daily new cases in the world.Figure 14.24 Forecast graph of daily new deaths in the world.Figure 14.25 Scatter plot of daily new cases vs daily COVID-19 new deaths.Figure 14.26 Normal P–P plot of estimated residuals.
List of Tables
1 Chapter 1Table 1.1 Defined epileptic state in transient EEG signal.Table 1.2 Brainwaves frequency characteristics.Table 1.3 EEG signal mathematical transform with feature.Table 1.4 EEG signal seizures proposed HANNSVM system result.Table 1.5 Initially defined epileptic states.Table 1.6 Feature sets that resulted in the highest prediction accuracy for pati...Table 1.7 Feature sets that resulted in the highest prediction accuracy for each...
2 Chapter 2Table 2.1 Very recent articles focusing on applications of fuzzy set theory in h...Table 2.2 Abbreviations with descriptions.
3 Chapter 3Table 3.1 Classification results for COVID-19 data set.Table 3.2 Weights of different criteria.Table 3.3 Performance scores and rank by SMART.Table 3.4 Presentation determined by WPM.Table 3.5 Presentation determines by TOPSIS.
4 Chapter 9Table 9.1 Protocols used for interconnection in medical IoT.
5 Chapter 10Table 10.1 A list of all parameters used in this study.
6 Chapter 13Table 13.1 Country-wise statistical table for affected area.Table 13.2 AI-assisted diagnosis of COVID-19 and drug discovery.
7 Chapter 14Table 14.1 Auto correlation of second differenced daily new cases.Table 14.2 Partial auto correlation of second differenced daily new cases.Table 14.3 Autocorrelation with second differenced values are obtained by transf...Table 14.4 Partial auto correlation
