Internet of Things and Machine Learning in Agriculture

Contents
Preface
Acknowledgments
Chapter 1
Smart Farming Enabling Technologies: A Systematic Review
	Abstract
	Introduction
	Review of Artificial Intelligence
	Review of IoT
	Components of Smart Farming
	Applications of Artificial Intelligence  and IoT in Smart Farming
	Conclusion
	References
Chapter 2
Internet of Things Platform  for Smart Farming
	Abstract
	1. Agriculture
	2. Agriculture Process
	3. Challenges in Traditional Agriculture
	4. Technological Development in Agriculture
	5. How Is the Internet of Things?
	6. IoT Helpful to Agriculture
	7. Role of IoT in Farming
	8. Applications
	9. The IoT Technology
	10. Challenges Faced in the Agricultural  Sector by IoT
	11. How Beneficial IoT Technique  in the Agricultural Sector?
	12. Disadvantages of IoT in Agriculture
	13. Impact of IoT on Agriculture
	14. Future of IoT in Agriculture
	References
Chapter 3
Internet of Things for  Smart Farming
	Abstract
	1. Introduction
	2. Literature Survey
	3. IoT Ecosystem
		3.1. Advantages of IoT
		3.2. Disadvantages of IoT
	4. IoT in Agriculture
	5. Structure of IoT in Agriculture
		5.1. Sensor Layer
		5.2. Transport Layer
		5.3. Application Layer
	6. How IoT Can Be Used for Smart Farming
	7. Methodology
		7.1. Proposed Model
	8. Limitations
	9. Future Scope
	Conclusion
	References
Chapter 4
A Comprehensive Review on Intelligent Systems for Mitigating Pests and Diseases in Agriculture
	Abstract
	1. Introduction
	2. Intelligent Technologies Applied in Agriculture
		2.1. Machine Learning
			2.1.1. Supervised Learning
			2.1.2. Unsupervised Learning
		2.2. Deep Learning
		2.3. Internet of Things
	3. Literature Review
	4. Disease Prediction
		4.1. Leaf Disease Prediction
		4.2. Weed Identification
	Conclusion
	References
Chapter 5
Plant Disease Detection Using  Image Sensors: A Step towards Precision Agriculture
	Abstract
	Introduction
	Various Image Sensors
		RGB Image Sensors
		Thermal Sensors
		Hyperspectral and Multispectral Image Sensors
	Combination of Different Imaging Methods
	Future Prospects
	Acknowledgments
	References
Chapter 6
Recent Trends in Agriculture Using IoT, Challenges and Opportunities
	Abstract
	Introduction
	Internet of Things
	Agriculture Based IoT
	Sensor Network Based on Agriculture
	Applications of Various Sectors
	Conclusion
	References
Chapter 7
Early Detection of Infection/Disease in Agriculture
	Abstract
	Introduction
	Literature Survey
	Proposed Work
	Analysis
	Conclusion
	References
Chapter 8
Application of Agriculture Using IoT: Future Perspective for Smart Cities Management 5.0
	Abstract
	1. Introduction
		1.1. Water Crisis in the World
		1.2. Global Warming and Its Impact on Agriculture
		1.3. Need for Water Conservation
		1.4. Smart Irrigation Devices
		1.5. IoT and Smart Irrigation
		1.6. Use of AI and ML in Agriculture
		1.7. Sensor-Based Irrigation and its Significance
		1.8. Existing Smart Irrigation Systems in the Market
	2. Literature Review
	3. Components Used
		3.1. Arduino System
		3.2. Sensors Used in Our Research Work
			3.2.1. Soil Moisture Sensor
			3.2.2. Temperature and Humidity Sensor
			3.2.3. Rainfall Sensor
	4. Proposed System
	5. Android Mobile Applications  for Smart Irrigation
		5.1. Main Page
		5.2. Snapshot of Working Model (ICs and Working model)
	6. Novelty
	7. Future Research Work
	8. Limitations
	Conclusion
	References
Chapter 9
The Internet of Things (IoT) for Sustainable Agriculture
	Abstract
	Introduction
	ICT in Agriculture
	Internet of a Thing (IoT) in Agriculture  and Allied Sector
	Geo-Spatial Technology
	Summary and Conclusion
	References
Chapter 10
IoT Based Data Collection and Data Analytics Decision Making  for Precision Farming
	Abstract
	Introduction
	Existing Technological Intervention  in Agriculture
	Farming Data Collection with IoT
		Better Regulation
		Cost Management and Spend Decrease
		Data Management
		Increased Product Quality and Amount
		Increased Business Efficiency
	The Proposed Method
	Automated Decision Making  with Data Analytics
		Finding Popular Pest Data, for Instance 0x001 [African Bug]
		Pest Classification
		Pest Detection
	Conclusion
	References
About the Editors
Index
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