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.
1. Title of Book - p. Cover 2. Cover image - p. Cover 3. Title page - p. ii 4. Table of Contents - p. iii 5. Copyright - p. iii 6. Contributors - p. xxi 7. Section 1: IoT and edge foundations and framework - p. xxvi 8. Chapter 1. Internet of things (IoT) and data analytics in smart agriculture: Benefits and challenges - p. 3 9. Chapter 2. Edge computing–Foundations and applications - p. 23 10. Chapter 3. IoT-based fuzzy logic-controlled novel and multilingual mobile application for hydroponic farming - p. 31 11. Chapter 4. Functional framework for IoT-based agricultural system - p. 43 12. Chapter 5. Functional framework for edge-based agricultural system - p. 74 13. Chapter 6. Precision agriculture: Weather forecasting for future farming - p. 101 14. Section 2: IoT use cases in smart farming and smart agriculture - p. 121 15. Chapter 7. Crop management system using IoT - p. 125 16. Chapter 8. Smart irrigation and crop security in agriculture using IoT - p. 143 17. Chapter 9. The Internet of Things in agriculture for sustainable rural development - p. 157 18. Chapter 10. Internet of Things (IoT) in agriculture toward urban greening - p. 171 19. Chapter 11. Smart e-agriculture monitoring systems - p. 183 20. Chapter 12. Smart agriculture using renewable energy and AI-powered IoT - p. 205 21. Chapter 13. Smart irrigation-based behavioral study of Moringa plant for growth monitoring in subtropical desert climatic condition - p. 227 22. Chapter 14. Surveying smart farming for smart cities - p. 241 23. Section 3: Edge computing use cases in smart farming and smart agriculture - p. 262 24. Chapter 15. Farm automation - p. 265 25. Chapter 16. A fog computing-based IoT framework for prediction of crop disease using big data analytics - p. 287 26. Chapter 17. Agribots: A gateway to the next revolution in agriculture - p. 301 27. Section 4: Sensor network use cases in smart farming and smart agriculture - p. 311 28. Chapter 18. SAW: A real-time surveillance system at an agricultural warehouse using IoT - p. 315 29. Chapter 19. The predictive model to maintain pH levels in hydroponic systems - p. 329 30. Chapter 20. A crop-monitoring system using wireless sensor networking - p. 345 31. Chapter 21. Integration of RFID and sensors in agriculture using IOT - p. 361 32. Section 5: AI and data analytics in agriculture - p. 372 33. Chapter 22. Prediction of crop yield and pest-disease infestation - p. 375 34. Chapter 23. Machine learning-based remote monitoring and predictive analytics system for crop and livestock - p. 403 35. Chapter 24. Exploring performance and predictive analytics of agriculture data - p. 409 36. Chapter 25. Climate condition monitoring and automated systems - p. 437 37. Chapter 26. Decision-making system for crop selection based on soil - p. 449 38. Chapter 27. Cyberespionage: Socioeconomic implications on sustainable food security - p. 477 39. Chapter 28. Internet of Things on sustainable aquaculture system - p. 495 40. Chapter 29. IoT-based monitoring system for freshwater fish farming: Analysis and design - p. 505 41. Chapter 30. Transforming IoT in aquaculture: A cloud solution - p. 517 42. Chapter 31. Toward the design of an intelligent system for enhancing salt water shrimp production using fuzzy logic - p. 533 43. Index - p. 543
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.
1. Title of Book - p. Cover 2. Cover image - p. Cover 3. Title page - p. ii 4. Table of Contents - p. iii 5. Copyright - p. iii 6. Contributors - p. xxi 7. Section 1: IoT and edge foundations and framework - p. xxvi 8. Chapter 1. Internet of things (IoT) and data analytics in smart agriculture: Benefits and challenges - p. 3 9. Chapter 2. Edge computing–Foundations and applications - p. 23 10. Chapter 3. IoT-based fuzzy logic-controlled novel and multilingual mobile application for hydroponic farming - p. 31 11. Chapter 4. Functional framework for IoT-based agricultural system - p. 43 12. Chapter 5. Functional framework for edge-based agricultural system - p. 74 13. Chapter 6. Precision agriculture: Weather forecasting for future farming - p. 101 14. Section 2: IoT use cases in smart farming and smart agriculture - p. 121 15. Chapter 7. Crop management system using IoT - p. 125 16. Chapter 8. Smart irrigation and crop security in agriculture using IoT - p. 143 17. Chapter 9. The Internet of Things in agriculture for sustainable rural development - p. 157 18. Chapter 10. Internet of Things (IoT) in agriculture toward urban greening - p. 171 19. Chapter 11. Smart e-agriculture monitoring systems - p. 183 20. Chapter 12. Smart agriculture using renewable energy and AI-powered IoT - p. 205 21. Chapter 13. Smart irrigation-based behavioral study of Moringa plant for growth monitoring in subtropical desert climatic condition - p. 227 22. Chapter 14. Surveying smart farming for smart cities - p. 241 23. Section 3: Edge computing use cases in smart farming and smart agriculture - p. 262 24. Chapter 15. Farm automation - p. 265 25. Chapter 16. A fog computing-based IoT framework for prediction of crop disease using big data analytics - p. 287 26. Chapter 17. Agribots: A gateway to the next revolution in agriculture - p. 301 27. Section 4: Sensor network use cases in smart farming and smart agriculture - p. 311 28. Chapter 18. SAW: A real-time surveillance system at an agricultural warehouse using IoT - p. 315 29. Chapter 19. The predictive model to maintain pH levels in hydroponic systems - p. 329 30. Chapter 20. A crop-monitoring system using wireless sensor networking - p. 345 31. Chapter 21. Integration of RFID and sensors in agriculture using IOT - p. 361 32. Section 5: AI and data analytics in agriculture - p. 372 33. Chapter 22. Prediction of crop yield and pest-disease infestation - p. 375 34. Chapter 23. Machine learning-based remote monitoring and predictive analytics system for crop and livestock - p. 403 35. Chapter 24. Exploring performance and predictive analytics of agriculture data - p. 409 36. Chapter 25. Climate condition monitoring and automated systems - p. 437 37. Chapter 26. Decision-making system for crop selection based on soil - p. 449 38. Chapter 27. Cyberespionage: Socioeconomic implications on sustainable food security - p. 477 39. Chapter 28. Internet of Things on sustainable aquaculture system - p. 495 40. Chapter 29. IoT-based monitoring system for freshwater fish farming: Analysis and design - p. 505 41. Chapter 30. Transforming IoT in aquaculture: A cloud solution - p. 517 42. Chapter 31. Toward the design of an intelligent system for enhancing salt water shrimp production using fuzzy logic - p. 533 43. Index - p. 543
