This book deals with a different research area of cognitive IoT and explains how machine learning algorithms can be applied for cognitive IoT. It deals with applications of cognitive IoT in this pandemic (COVID-19), applications for student performance evaluation, applications for human healthcare for chronic disease prediction, use of wearable sensors and review regarding their energy optimization and how cognitive IoT helps in farming through rainfall prediction and prediction of lake levels.
Features:
Describes how cognitive IoT is helpful for chronic disease prediction and processing of data gathered from healthcare devices Explains different sensors available for health monitoring Explores application of cognitive IoT in COVID-19 analysis Discusses pertinent and efficient farming applications for sustaining agricultural growth Reviews smart educational aspects such as student response, performance, and behavior and instructor response, performance, and behavior
This book aims at researchers, professionals and graduate students in Computer Science and Engineering, Computer Applications and Electronics Engineering, and Wireless Communications and Networking.
| Preface |
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xi | |
| Acknowledgement |
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xiii | |
| Author's Biography |
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xv | |
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1 Cognitive Internet of Things and Its Impact on Human Life |
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1 | (10) |
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1.1 Introduction to Cognitive Internet of Things |
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1 | (3) |
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4 | (1) |
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5 | (1) |
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1.4 Cognitive IoT and Covid-19 Pandemic |
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6 | (1) |
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1.5 Global Applications of Cognitive IoT |
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7 | (1) |
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8 | (3) |
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9 | (2) |
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2 Cognitive Internet of Things: Smart Student Evaluation |
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11 | (12) |
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2.1 Education and Internet of Things |
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11 | (3) |
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2.1.1 IoT and Education Institution |
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12 | (2) |
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2.2 Machine Learning Classifiers for Smart Education |
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14 | (3) |
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14 | (3) |
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2.3 Implementation Using MATLAB Tool |
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17 | (1) |
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2.3.1 Dataset Used and Curve Fitting Tool |
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17 | (1) |
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2.3.2 Classification Learner Tool |
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18 | (1) |
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18 | (5) |
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2.4.1 Global Application (Watson) |
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20 | (1) |
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20 | (3) |
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3 Cognitive Internet of Things: Chronic Disease Prediction |
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23 | (18) |
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3.1 Chronic Disease and Human Health |
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23 | (3) |
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3.1.1 Chronic Disease Monitoring |
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24 | (2) |
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3.2 Disease Prediction and Machine Learning |
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26 | (2) |
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3.2.1 Bottlenecks and Prediction Model |
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26 | (1) |
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3.2.2 Naive Bayes Machine Learning Classifier |
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27 | (1) |
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3.3 Heart Disease Prediction Using Matlab Tool |
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28 | (9) |
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28 | (1) |
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3.3.2 Classifiers and Accuracy |
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29 | (8) |
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37 | (4) |
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38 | (3) |
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4 Challenges in Internet of Things: Energy-Efficient Wearables |
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41 | (42) |
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4.1 Wearable Internet of Things |
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41 | (6) |
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4.1.1 Wireless Body Area Network |
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41 | (1) |
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42 | (1) |
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42 | (3) |
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45 | (2) |
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4.2 Issues and Challenges in WBAN |
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47 | (2) |
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49 | (2) |
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4.4 WBAN and Earlier Study |
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51 | (25) |
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4.4.1 What Is Not Being Done? |
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76 | (1) |
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76 | (1) |
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4.6 Limitations and Future Scope |
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77 | (6) |
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77 | (6) |
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5 Cognitive Internet of Things: Rainfall Prediction for Effective Farming |
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83 | (10) |
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5.1 Farming and Cognitive Internet of Things |
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83 | (2) |
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5.1.1 Gross Domestic Product and Agriculture |
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84 | (1) |
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5.2 Machine Learning Model for Rainfall Prediction |
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85 | (3) |
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5.2.1 Decision Tree Classifier |
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85 | (1) |
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5.2.2 Support Vector Machine |
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85 | (2) |
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87 | (1) |
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5.3 Practical Approach (Matlab Tool Box) |
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88 | (2) |
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90 | (3) |
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90 | (3) |
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6 Cognitive Internet of Things: Lake Level Prediction to Prevent Drought |
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93 | (10) |
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6.1 Data Forecasting and Boundaries |
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93 | (2) |
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94 | (1) |
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6.2 Ensemble Prediction Model |
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95 | (5) |
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97 | (1) |
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98 | (1) |
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6.2.3 Ensemble Model Is Better Than Single Classifier |
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99 | (1) |
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6.3 Validation of Prediction Model |
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100 | (1) |
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100 | (3) |
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101 | (2) |
| Appendix: MATLAB Implementation of Different Classifiers |
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103 | (10) |
| Index |
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113 | |
Dr J P Patra is a Professor at Shri Shankaracharya Institute of Professional Management and Technology, Raipur, under Chhattisgarh Swami Vivekanand Technical University, Bhilai, India. He has more than 17 years of experience in research, teaching in the areas of Artificial Intelligence, Analysis and Design of Algorithms, Cryptography, and Network Security. He was acclaimed for being the author of books such as Analysis and Design of Algorithms and Performance Improvement of a Dynamic System Using Soft Computing Approaches, and has published more than 51 papers in SCOPUS, Web of Science, and UGC-CARE listed journals. He has published and granted Indian/Australian patents. He has contributed to book chapters, published by Elsevier, Springer, and IGI Global. He is associated with AICTE-IDEA LAB, IIT Bombay, and IIT Kharagpur as a coordinator. He is on the editorial board and reviewer board of four leading international journals. In addition, he is on the Technical Committee Board for several international conferences. He is having a Life Membership of professional bodies such as CSI, ISTE, and QCFI, and he has also served the post of Chairman of the Raipur Chapter for the Computer Society of India, which is Indias largest professional body for computer professionals. He has served in various positions in different engineering colleges as Associate Professor and Head. Currently, he is working with SSIPMT, Raipur, as Professor and Head of the Department of Computer Science and Engineering.
Mr Gurudatta Verma is Assistant Professor at Shri Shankaracharya Institute of Professional Management and Technology, Raipur, under Chhattisgarh Swami Vivekanand Technical University, Bhilai, India. He has more than 12 years of experience in research, teaching in the areas of parallel processing and machine learning. He has published more than 15 papers in SCOPUS, Web of Science, and UGC-CARE listed journals. He has published and granted Indian/Australian patents. He has contributed to book chapters published by Elsevier, Springer, and IGI Global.
