Agricultural Informatics
Description
Agricultural Informatics: Automation Using the IoT and Machine Learning focuses on all these topics, including a few case studies, and they give a clear indication as to why these techniques should now be widely adopted by the agriculture and farming industries.
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Persons
Amitava Choudhury PhD is an assistant professor in the school of Computer Science, University of Petroleum & Energy Studies, Dehradun, India.
Arindam Biswas PhD is an assistant professor in School of Mines and Metallurgy at Kazi Nazrul University, Asansol, West Bengal, India.
Manish Prateek PhD is Professor and Dean, School of Computer Science, at the University of Petroleum and Energy Studies, Dehradun, India.
Amlan Chakrabarti PhD is a Full Professor in the A.K. Choudhury School of Information Technology at the University of Calcutta.
Content
Preface xiii
1 A Study on Various Machine Learning Algorithms and Their Role in Agriculture 1
Kalpana Rangra and Amitava Choudhury
1.1 Introduction 1
1.2 Conclusions 9
2 Smart Farming Using Machine Learning and IoT 13
Alo Sen, Rahul Roy and Satya Ranjan Dash
2.1 Introduction 14
2.2 Related Work 15
2.3 Problem Identification 22
2.4 Objective Behind the Integrated Agro-IoT System 23
2.5 Proposed Prototype of the Integrated Agro-IoT System 23
2.6 Hardware Component Requirement for the Integrated Agro-IoT System 26
2.7 Comparative Study Between Raspberry Pi vs Beaglebone Black 30
2.8 Conclusions 31
2.9 Future Work 32
3 Agricultural Informatics vis-à-vis Internet of Things (IoT): The Scenario, Applications and Academic Aspects--International Trend & Indian Possibilities 35
P.K. Paul
3.1 Introduction 36
3.2 Objectives 36
3.3 Methods 37
3.4 Agricultural Informatics: An Account 37
3.5 Agricultural Informatics & Technological Components: Basics & Emergence 40
3.6 IoT: Basics and Characteristics 41
3.7 IoT: The Applications & Agriculture Areas 43
3.8 Agricultural Informatics & IoT: The Scenario 45
3.9 IoT in Agriculture: Requirement, Issues & Challenges 49
3.10 Development, Economy and Growth: Agricultural Informatics Context 50
3.11 Academic Availability and Potentiality of IoT in Agricultural Informatics: International Scenario & Indian Possibilities 51
3.12 Suggestions 60
3.13 Conclusion 60
4 Application of Agricultural Drones and IoT to Understand Food Supply Chain During Post COVID-19 67
Pushan Kumar Dutta and Susanta Mitra
4.1 Introduction 68
4.2 Related Work 69
4.3 Smart Production With the Introduction of Drones and IoT 72
4.4 Agricultural Drones 75
4.5 IoT Acts as a Backbone in Addressing COVID-19 Problems in Agriculture 77
4.6 Conclusion 81
5 IoT and Machine Learning-Based Approaches for Real Time Environment Parameters Monitoring in Agriculture: An Empirical Review 89
Parijata Majumdar and Sanjoy Mitra
5.1 Introduction 90
5.2 Machine Learning (ML)-Based IoT Solution 90
5.3 Motivation of the Work 91
5.4 Literature Review of IoT-Based Weather and Irrigation Monitoring for Precision Agriculture 91
5.5 Literature Review of Machine Learning-Based Weather and Irrigation Monitoring for Precision Agriculture 92
5.6 Challenges 112
5.7 Conclusion and Future Work 113
6 Deep Neural Network-Based Multi-Class Image Classification for Plant Diseases 117
Alok Negi, Krishan Kumar and Prachi Chauhan
6.1 Introduction 117
6.2 Related Work 119
6.3 Proposed Work 121
6.4 Results and Evaluation 124
6.5 Conclusion 127
7 Deep Residual Neural Network for Plant Seedling Image Classification 131
Prachi Chauhan, Hardwari Lal Mandoria and Alok Negi
7.1 Introduction 131
7.2 Related Work 136
7.3 Proposed Work 139
7.4 Result and Evaluation 142
7.5 Conclusion 144
8 Development of IoT-Based Smart Security and Monitoring Devices for Agriculture 147
Himadri Nath Saha, Reek Roy, Monojit Chakraborty and Chiranmay Sarkar
8.1 Introduction 148
8.2 Background & Related Works 150
8.3 Proposed Model 155
8.4 Methodology 160
8.5 Performance Analysis 165
8.6 Future Research Direction 166
8.7 Conclusion 167
9 An Integrated Application of IoT-Based WSN in the Field of Indian Agriculture System Using Hybrid Optimization Technique and Machine Learning 171
Avishek Banerjee, Arnab Mitra and Arindam Biswas
9.1 Introduction 172
9.2 Literature Review 175
9.3 Proposed Hybrid Algorithms (GA-MWPSO) 177
9.4 Reliability Optimization and Coverage Optimization Model 179
9.5 Problem Description 181
9.6 Numerical Examples, Results and Discussion 182
9.7 Conclusion 183
10 Decryption and Design of a Multicopter Unmanned Aerial Vehicle (UAV) for Heavy Lift Agricultural Operations 189
Raghuvirsinh Pravinsinh Parmar
10.1 Introduction 190
10.2 History of Multicopter UAVs 192
10.3 Basic Components of Multicopter UAV 193
10.4 Working and Control Mechanism of Multicopter UAV 207
10.5 Design Calculations and Selection of Components 210
10.6 Conclusion 218
11 IoT-Enabled Agricultural System Application, Challenges and Security Issues 223
Himadri Nath Saha, Reek Roy, Monojit Chakraborty and Chiranmay Sarkar
11.1 Introduction 224
11.2 Background & Related Works 226
11.3 Challenges to Implement IoT-Enabled Systems 232
11.4 Security Issues and Measures 240
11.5 Future Research Direction 243
11.6 Conclusion 244
12 Plane Region Step Farming, Animal and Pest Attack Control Using Internet of Things 249
Sahadev Roy, Kaushal Mukherjee and Arindam Biswas
12.1 Introduction 250
12.2 Proposed Work 254
12.3 Irrigation Methodology 257
12.4 Sensor Connection Using Internet of Things 259
12.5 Placement of Sensor in the Field 263
12.6 Conclusion 267
References 268
Index 271
