AI, Edge and IoT-based Smart Agriculture

Description

AI, Edge, and IoT Smart Agriculture integrates applications of IoT, edge computing, and data analytics for sustainable agricultural development and introduces Edge of Thing-based data analytics and IoT for predictability of crop, soil, and plant disease occurrence for improved sustainability and increased profitability. The book also addresses precision irrigation, precision horticulture, greenhouse IoT, livestock monitoring, IoT ecosystem for agriculture, mobile robot for precision agriculture, energy monitoring, storage management, and smart farming. The book provides an overarching focus on sustainable environment and sustainable economic development through smart and e-agriculture.

Providing a medium for the exchange of expertise and inspiration, contributions from both smart agriculture and data mining researchers around the world provide foundational insights. The book provides practical application opportunities for the resolution of real-world problems, including contributions from the data mining, data analytics, Edge of Things, and cloud research communities working in the farming production sector. The book offers broad coverage of the concepts, themes, and instruments of this important and evolving area of IOT-based agriculture, Edge of Things and cloud-based farming, Greenhouse IOT, mobile agriculture, sustainable agriculture, and big data analytics in agriculture toward smart farming.

Integrates sustainable agriculture, Greenhouse IOT, precision agriculture, crops monitoring, crops controlling to prediction, livestock monitoring, and farm management
Presents data mining techniques for precision agriculture, including weather prediction, plant disease prediction, and decision support for crop and soil selection
Promotes the importance and uses in managing the agro ecosystem for food security
Emphasizes low energy usage options for low cost and environmental sustainability

Front Cover 2
AI, Edge and IoT-based Smart Agriculture 5
Copyright 6
Contents 7
Contributors 23
Section 1: IoT and edge foundations and framework 29
- Chapter 1: Internet of things (IoT) and data analytics in smart agriculture: Benefits and challenges 31
  - 1. Introduction 31
    - 1.1. Understanding AI 32
  - 2. IoT ecosystem in agriculture 33
    - 2.1. Management techniques/systems (IoT and big data) 33
    - 2.2. Smart information systems (SIS) in agriculture 34
  - 3. Benefits of IoT in agriculture 35
    - 3.1. Remote sensing as a major tool in agriculture 35
    - 3.2. Weather forecasting as a prime IoT in agriculture 36

Front Cover 2
AI, Edge and IoT-based Smart Agriculture 5
Copyright 6
Contents 7
Contributors 23
Section 1: IoT and edge foundations and framework 29
- Chapter 1: Internet of things (IoT) and data analytics in smart agriculture: Benefits and challenges 31
  - 1. Introduction 31
    - 1.1. Understanding AI 32
  - 2. IoT ecosystem in agriculture 33
    - 2.1. Management techniques/systems (IoT and big data) 33
    - 2.2. Smart information systems (SIS) in agriculture 34
  - 3. Benefits of IoT in agriculture 35
    - 3.1. Remote sensing as a major tool in agriculture 35
    - 3.2. Weather forecasting as a prime IoT in agriculture 36
    - 3.3. Agriculture drones 36
    - 3.4. Crop monitoring 36
    - 3.5. Smart irrigation 37
    - 3.6. Greenhouse monitoring and automation system 37
  - 4. Open issues and key challenges in the adoption of IoT in agriculture 38
    - 4.1. Reliability 38
    - 4.2. Data privacy protection and issues of ownership 38
    - 4.3. Autonomy foreseeability and causation 39
    - 4.4. Control 39
    - 4.5. Opaque research and development 40
  - 5. Legal issues in regulating AI in agriculture 40
    - 5.1. Torts and contracts 40
    - 5.2. Crimes 41
    - 5.5. Environmental laws 41
    - 5.3. Law relating to accidents, health, and safety 41
    - 5.4. Accidents and negligence 41
  - 6. Conclusion 42
  - References 42
- Chapter 2: Edge computing-Foundations and applications 45
  - 2. Edge computing 45
  - 1. Introduction 45
  - 3. Applications of edge computing 50
    - 3.1. Future trends of edge computing 54
  - 4. Conclusions 54
  - References 56
- Chapter 3: IoT-based fuzzy logic-controlled novel and multilingual mobile application for hydroponic farming 59
  - 1. Introduction 59
  - 2. Literature review 60
  - 3. Methodology 61
  - 4. Proposed method 62
  - 5. Results and discussion 67
  - References 69
  - 6. Conclusion 69
- Chapter 4: Functional framework for IoT-based agricultural system 71
  - 1. Introduction 71
    - 1.1. Overview of the cases 72
    - 1.2. Challenges, opportunities, and use of IoT applications in agriculture 73
      - 1.2.1. Challenges 73
        
        1.2.1.1. Software complexity 73
        
        1.2.1.3. Technical skill requirement 74
        
        1.2.1.2. Security 74
        
        1.2.1.4. Lack of supporting infrastructure 75
      - 1.3. Opportunities allied with the solicitation of IoT in agriculture 75
        
        1.3.1. Low-power wireless sensor (LPS) 75
        
        1.3.4. Remote control management 76
        
        1.3.2. Better connectivity 76
        
        1.3.3. Operational efficiency 76
      - 1.4. The architecture of a smart farm monitoring system 76
      - 1.5. Energy-saving technologies 80
      - 1.6. Security mechanisms 80
      - 1.8. Precision farming 81
      - 1.7. Advantages of IoT in agriculture system 81
        
        1.7.1. Climate conditions or agility 81
      - 1.10. Data analytics 82
      - 1.9. Smart greenhouse 82
      - 1.11. Agricultural drones 83
      - 1.12. Limitations of the existing proposed model 84
    - 2. Methodology 84
      - 2.1. Block diagram of proposed model 84
      - 2.2. Flow diagram of controlling process of motor using sensors 85
      - 2.3. IoT with transmitter and receiver wireless sensor model 86
    - 3. Experimental results and discussion 87
      - 3.1. Experimental work 87
      - 3.2. Thingspeak cloud server 89
    - 4. Results 90
      - 4.1. Measurements at 14:30 when soil is dry 90
      - 4.2. Measurements on May 14, 2020; time varies when soil is wet 91
      - 4.3. Measurement in night, when soil is dry 92
      - 4.4. Measurement in night, when soil is wet 92
    - 5. Discussion 93
    - References 94
    - 6. Conclusion and future scope 94
      - 6.1. Future scope 94
  - Chapter 5: Functional framework for edge-based agricultural system 99
    - 1. Introduction 99
    - 2. Relevant technologies 101
    - 3. Edge computing in agricultural sectors 101
      - 3.1. Role of edge computing in multiple facets of agriculture 104
        
        3.1.1. Smart farming 104
        
        3.1.2. Aquafarming 104
        
        3.1.3. Livestock 106
        
        3.1.4. Dairy farming 106
        
        3.1.5. Hydroponics 106
      - 4. Edge computing framework design in agriculture 106
        
        4.1. Communication 108
        
        4.1.4. SigFox 108
        
        4.1.2. Message Queue-Telemetry Transport Protocol (MQTT) 108
        
        4.1.5. Zigbee 108
        
        4.1.3. Radio Frequency Identification (RFID) 108
        
        4.1.6. WiFi 108
        
        4.1.1. Low range wide area network protocol (LoraWan) 108
        
        4.1.7. Bluetooth 109
        
        4.1.8. Worldwide Interoperability for Microwave Access (WiMAX) 109
        
        4.1.9. Routing Protocol for Low-Power and Lossy Networks (RPL) 109
        
        4.2. Processing/computation 109
        
        4.3. Analytics 110
        
        4.4. Storage 111
        
        4.4.3. Cloud 112
        
        4.4.1. Local 112
        
        4.4.2. Edge/Cloudlet 112
        
        4.5. Actuation 112
        
        4.6. Sensing 112
      - 5. Edge computing implementation 113
        
        5.1. Hardware implementation 115
        
        5.2. Data communication technologies 116
        
        5.3. Data processing implementation 117
        
        5.4. Experimental set-up of edge-based agricultural system 120
        
        5.4.1. Edge node 1 120
        
        5.4.2. Edge node 2 121
        
        5.4.4. Cloud server 122
        
        5.4.3. Edge server 122
        
        6. Conclusion 122
        
        References 124
      - Chapter 6: Precision agriculture: Weather forecasting for future farming 129
        
        1. Introduction 129
        
        1.1. Terminologies employed in precision agriculture 131
        
        1.1.1. Application map 131
        
        1.1.5. Global positioning systems (GPS) 132
        
        1.1.8. Management zone 132
        
        1.1.11. Precision farming 132
        
        1.1.3. Georeferencing 132
        
        1.1.6. Grid sampling 132
        
        1.1.9. ``On-the-go´´ sensing 132
        
        1.1.12. Remote sensing 132
        
        1.1.4. Geographical information systems (GIS) 132
        
        1.1.7. Kriging 132
        
        1.1.10. Pixel 132
        
        1.1.2. Class post mapping 132
        
        1.1.13. Scouting 133
        
        1.1.16. Variable rate technology (VRT) 133
        
        1.1.14. Smoothing 133
        
        1.1.17. Yield map 133
        
        1.1.15. Spatial resolution 133
        
        1.1.18. Yield monitor 133
        
        1.2. Connection between precision agriculture and traditional agriculture 133
        
        1.2.1. Information 133
        
        1.2.2. Technology 134
        
        1.2.3. Decision support 134
        
        2. Weather and climate 134
        
        2.1. Weather 135
        
        2.2. Climate 136
        
        2.2.4. Humid climate 136
        
        2.2.2. Arid climate 136
        
        2.2.3. Mediterranean climate 136
        
        2.2.1. Tropical climate 136
        
        2.2.5. Arctic climate 137
        
        2.2.6. Highland climate 137
        
        3. Agricultural implications of climate change 137
        
        3.1. Reducing the burden of agriculture on climate change 138
        
        3.2. Exploring the climate change influence as an influential element in agricultural productivity 139
        
        4. Modern tools and techniques for precision agriculture 141
        
        4.2. Sensor technology 142
        
        4.3. Unmanned aerial vehicles (UAVs) 142
        
        4.1. Internet of Things (IoT) 142
        
        4.5. Robots 143
        
        4.6. Smartphone 143
        
        4.4. Unmanned ground vehicles (UGVs) 143
        
        4.7. Autoguidance equipment (AGE) 143
        
        4.8. Variable rate technology 144
        
        4.9. Grid sampling 144
        
        5. Conclusion 144
        
        References 145
        
        Section 2: IoT use cases in smart farming and smart agriculture 151
        
        Chapter 7: Crop management system using IoT 153
        
        1. Introduction 153
        
        2. Background and related works 155
        
        3. Proposed model 157
        
        4. Methodology 160
        
        5. Performance analysis 165
        
        6. Future research direction 165
        
        7. Conclusion 167
        
        References 168
        
        Chapter 8: Smart irrigation and crop security in agriculture using IoT 171
        
        1. Introduction 171
        
        1.1. Overview 172
        
        1.2. Applications 172
        
        1.3. Motivation 173
        
        1.4. Objectives 173
        
        2. Methodology 173
        
        2.1. Basic building blocks of an IoT device 174
        
        2.1.1. Components used 174
        
        2.1.2. Node MCU 174
        
        2.1.3. PIR motion sensor 175
        
        2.1.4. Buzzer 175
        
        2.1.5. Raspberry Pi camera 177
        
        3. Algorithms 177
        
        3.1. Design flow 178
        
        4. Implementation 179
        
        4.1. System process 180
        
        6. Conclusion and future scope 182
        
        5. Testing and results 182
        
        References 183
        
        Chapter 9: The Internet of Things in agriculture for sustainable rural development 185
        
        1. Introduction 185
        
        1.2. Present scenario 186
        
        1.2.1. National perspective 187
        
        1.2.2. International perspective 187
        
        1.1. Literature survey 186
        
        2. Background details 188
        
        2.1. Internet of Things 188
        
        2.1.1. History of the IoT 188
        
        2.1.2. IoT devices 189
        
        2.2. IoT in agriculture for rural development 190
        
        2.2.1. Significance in agriculture 190
        
        2.2.2. Benefits of IoT in agriculture 191
        
        2.2.3. Applications of IoT in agriculture 191
        
        3. IoT in agriculture: Use cases 192
        
        4. Case studies: IoT-based agriculture for sustainable rural development 193
        
        4.1. Slashing water consumption in avocado 193
        
        4.2. Smart dairy farming 194
        
        5. Impact of IoT on food sustainability and socioeconomic uplift 194
        
        5.1. Food sustainability 194
        
        5.2. Socioeconomic uplift 195
        
        6. Challenges and opportunities 195
        
        6.1. Unstable Internet connection in farms 195
        
        6.3. Costly hardware 196
        
        6.2. Disrupted connectivity to cloud servers 196
        
        7. Conclusion 196
        
        References 197
        
        Chapter 10: Internet of Things (IoT) in agriculture toward urban greening 199
        
        1. Introduction 199
        
        2. IOT architectures 200
        
        2.1. Definitions of IoT 200
        
        2.3. Architecture of IoT 201
        
        2.2. G-IoT 201
        
        3. G-IOT application 202
        
        3.1. Green tags 202
        
        3.2. Green sensing networks 203
        
        3.3. Green Internet technologies 203
        
        4. IOT applications 203
        
        4.3. Smart data collection 205
        
        4.1. Smart industrial plants and machine-to-machine communications 205
        
        4.2. Smart plant monitoring 205
        
        4.6. Smart social networks 206
        
        4.4. Smart sensing 206
        
        4.7. Smart agriculture 206
        
        4.5. Smart sports 206
        
        4.8. Smart waste 206
        
        4.9. Smart environment 207
        
        4.10. Smart grid 207
        
        5. G-IOT challenges and opportunities 207
        
        5.1. Green infrastructure 207
        
        5.2. Green spectrum management 207
        
        5.3. Green communication 208
        
        5.4. Green security and management 208
        
        6. Conclusion 208
        
        References 209
        
        Chapter 11: Smart e-agriculture monitoring systems 211
        
        1. Introduction 211
        
        2. Need for smart e-monitoring system for agriculture 212
        
        3. System architecture 212
        
        3.1. WSN-based architecture 213
        
        3.2. IoT-Cloud based architecture 214
        
        4. IoT and data analytics in agriculture 218
        
        4.3. Data processing 219
        
        4.1. Devices deployed 219
        
        4.4. Data analytics 219
        
        4.2. Data acquisition 219
        
        5. Different types of solutions available 221
        
        5.1. Botanicalls 221
        
        5.2. Parrot flower power 221
        
        5.6. Edyn 222
        
        5.4. Open garden 222
        
        5.5. Automated hydroponics: Bitponics 222
        
        5.3. HarvestGeek 222
        
        5.7. Koubachi 223
        
        6. Research challenges 223
        
        7. Case study on IoT-based monitoring systems 224
        
        7.1. Case study 1: IoT-based greenhouse crop production 224
        
        7.2. Case study 2: IoT-based plant disease prediction 225
        
        7.3. Case study 3: IoT-based vineyard monitoring 226
        
        7.4. Case study 4: IoT-based irrigation management 226
        
        8. Open research issues 227
        
        9. Conclusion 227
        
        References 228
        
        Chapter 12: Smart agriculture using renewable energy and AI-powered IoT 233
        
        1. Introduction 233
        
        2. Background and related work 234
        
        2.1. VAWT 234
        
        2.2. Data analytics platform 235
        
        2.3. IoT devices 237
        
        2.3.3. Sensors 237
        
        2.3.1. Single board computer 237
        
        2.3.4. Smartphone application 237
        
        2.3.2. Microcontrollers 237
        
        3. Concept 237
        
        3.1. Suburban set-up 238
        
        3.2. Rural set-up 239

Author's affiliation

Joel J.P.C. Rodrigues: Instituto de Telecomunicações, Universidade d

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