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Full Description
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.
Contents
CHAPTER-1 COGNITIVE IOT AND ITS IMPACT ON HUMAN LIFE
Abstract
1.1 Introduction to Cognitive IoT
1.2 Internet of Things
1.3 AI and IoT
1.4 Cognitive IoT and Covid19 Pandemic
1.5 Global Applications of Cognitive IoT
1.6 Conclusion
References
CHAPTER-2 COGNITIVE IOT: SMART STUDENT EVALUATION
Abstract
2.1 Education and IoT
2.2 Machine learning classifiers for Smart Education
2.3 Implementation using Matlab Tool
2.4 Summary
References
CHAPTER-3 COGNITIVE IOT: CHRONIC DISEASE PREDICTION
Abstract
3.1 Chronic Disease and Human Health
3.2. Disease prediction and Machine Learning
3.3 Heart Disease Prediction using MatLab Tool
3.4 Summary
References
CHAPTER-4 CHALLENGES IN IOT: ENERGY EFFICIENT WEARABLES
Abstract
4.1. Wearable IoT
4.2 Issues and Challenges in WBAN
4.3 Localization in WBAN
4.4. WBAN and Earlier Study
4.5. Applications
4.6. Limitations and Future Scope
References
CHAPTER-5 COGNITIVE IOT: RAINFALL PREDICTION FOR EFFECTIVE FARMING
Abstract
5.1 Farming and Cognitive IoT
5.2 Machine Learning Model for Rainfall Prediction
5.3 Practical Approach (Matlab Tool Box)
5.4 Summary
References
CHAPTER-6 COGNITIVE IOT: LAKE LEVEL PREDICTION TO PREVENT DROUGHT
Abstract
6.1 Data forecasting and Boundaries
6.2 Ensemble Prediction Model
6.3 Validation of Prediction Model
6.4 Summary
References
