This book presents state-of-the-art optimization algorithms followed by Internet of Things (IoT) fundamentals. The applications of machine learning and IoT are explored, with topics including optimization, algorithms and machine learning in image processing and IoT.
Applications of Optimization and Machine Learning in Image Processing and IoT is a complete reference source, providing the latest research findings and solutions for optimization and machine learning algorithms. The chapters examine and discuss the fields of machine learning,
IoT and image processing.
Author(s): Dr. Nidhi Gupta
Publisher: CRC Press
Year: 2023
Language: English
Pages: 236
Cover
Half Title
Title
Copyright
Dedication
Contents
Preface
Acknowledgments
About the Editor
List of Contributors
Chapter 1 ◾ State-of-the-Art on Evolved Optimization Approaches for Damage Detection in Steel Bridges
1.1 Introduction
1.2 Optimization Model
1.3 Optimization Phases
1.4 Conclusions
References
Chapter 2 ◾ loT and Its Advancement
2.1 Introduction
2.2 Protocols of Cloud Computing
2.3 Conclusion
References
Chapter 3 ◾ Optimal Configuration of IOT Cluster with Full Connectivity with Minimum Transmission Power Using SA and BO Algorithms
3.1 Introduction
3.2 Wireless Sensor Networks
3.3 Investigated Optimization Algorithms
3.4 Results and Discussions
3.5 Conclusions
References
Chapter 4 ◾ IoT Optimization for Smart Cities and Mobility in Smart Cities
4.1 Introduction
4.2 Smart Cities
4.3 Smart Mobility for the Smart City
4.4 Conclusion
References
Chapter 5 ◾ Application of the Internet of Things in E-Waste Management
5.1 Introduction
5.2 Internet of Things
5.3 Electronic Waste Management Using IoT
5.4 Regulatory Environment for IoT-Based E-Waste Management System
5.5 Conclusions
References
Chapter 6 ◾ Power of IoT in Smart Healthcare Systems
6.1 Introduction
6.2 Architecture of Smart Healthcare Using IoT
6.3 Related Work
6.4 IoT-Based Healthcare Devices
6.5 Challenges for IoT in Smart Healthcare Systems
6.6 Conclusion
References
Chapter 7 ◾ Verification Scheme for Malicious Routing in the Internet of Things
7.1 Introduction
7.2 Security Issues in IoT
7.3 Proposed Framework for Malicious Routing
7.4 Results and Discussion
7.5 Conclusion and Future Scope
References
Chapter 8 ◾ Agricultural Applications Using Artificial Intelligence and Computer Vision Technologies
8.1 Introduction
8.2 Computer Vision
8.3 Convolutional Neural Network Architecture
8.4 Analysis of Computer Vision Technology in Agriculture
8.5 Conclusion
References
Chapter 9 ◾ Artificial Intelligence-Based Smart Identification System Using Herbal Images: Decision Making Using Various Machine Learning Models
9.1 Introduction
9.2 Prior Art
9.3 Machine Learning: Expanding Horizons
9.4 Creation of Image Database
9.5 Feature Extraction
9.6 Data Augmentation
9.7 Classification Techniques Using Machine Learning Models
9.8 Validation of Developed Model
9.9 Transfer Learning
9.10 Conclusion and Future Prospects
References
Chapter 10 ◾ CNN-Based Fire Prediction Using Fractional Order Optical Flow and Smoke Features
10.1 Introduction
10.2 Methodology
10.3 Estimation of Fractional Order Optical Flow
10.4 Extraction of Smoke Motion Active Region from Color Map
10.5 Experiments, Results and Discussion
10.6 Conclusion and Future Work
Acknowledgments
References
Chapter 11 ◾ Early Prediction of Cardiac Diseases Using Ensemble Learning Techniques: A Machine Learning Technique to Deal with Heart Disease Problems
11.1 Introduction
11.2 Related Work
11.3 Methodology
11.4 Experiments and Results
11.5 Conclusion
References
Index
