Intro
Preface
Contents
About the Editors
Intelligent Systems in Agriculture
An Efficient Approach for Plant Leaf Species Identification Based on SVM and SMO and Performance Improvement
1 Introduction
2 Methodology
3 Spider Monkey Optimization Algorithm (SMO)
3.1 Population Initiation
3.2 Local Leader Phase (LLP)
3.3 Global Leader Phase (GLP)
4 Support Vector Machine
5 Simulation Results
6 Conclusion
References
Smart IoT-Based Pesticides Recommendation System for Rice Diseases
1 Introduction
2 Literature Survey
3 Methodology

3.1 Materials and Methodology
4 Results
4.1 Evaluation Metrics
4.2 Sensors Results and Readings
5 Conclusion
References
Classification of Tomato Leaf Diseases: A Comparison of Different Optimizers
1 Introduction
2 Related Work
3 Methodology
4 Results and Discussion
5 Conclusion
References
Optimization of Rainfall Intensities Classification Based on Artificial Intelligence Using Recurrent Neural Network
1 Introduction
1.1 Data and Methodology
1.2 MSG Data and Radar Data
1.3 Selection of Input Parameters
1.4 RNN Model

1.5 Choice of RNN Architecture
2 Application and Classification Results
2.1 Application to a Scene
2.2 Application to All Scenes
3 Conclusion
References
Tomato Plant Leaf Disease Detection Using Inception V3
1 Introduction
2 Related Research
3 Workflow for Tomato Plant Disease Detection
3.1 Inception V3
3.2 Dataset Description
3.3 Intermediate Results of Model Training
4 Conclusion
References
Astute Farm Monitoring Using WSN and AI-A Solution for Optimally Monitoring Environmental Conditions
1 Introduction
2 Literature Review
3 Proposed Work

3.1 Proposed System
3.2 Components Used in Proposed System
3.3 System Modules
4 Result and Discussion
4.1 Dataset Description and Experimental Setup
4.2 Evaluation Metrics
4.3 Result Analysis
5 Conclusion
References
Intelligent Systems in Internet of Things and Cloud Computing
A Comprehensive Literature Review of Artificial Intelligent Practices in the Field of Penetration Testing
1 Introduction
2 Existing Automated Penetration Testing Models
3 Results and Discussion
4 Future Directions
5 Conclusions
References

IoT-Cloud-Enabled Smart Framework for Real-World Applications
1 Introduction
1.1 Motivation for the Proposed Framework
2 Related Work
3 Proposed IoT-Cloud-Enabled Smart Framework for Real-World Applications
3.1 Sensor Connectivity and Network Phase
3.2 Gateway and Network Phase
3.3 Cloud Computing Phase
3.4 IoT-Cloud Applications Phase
4 Use Case Scenario (Air Quality Monitoring)
5 Various Real-World IoT-Cloud Applications
5.1 Smart Health Care
5.2 Smart Agriculture
5.3 Smart Home
5.4 Smart Environment Monitoring