Perspectives on Artificial Intelligence and Internet of Things for Sustainable Environment addresses urgent environmental issues stemming from urbanization, deforestation, and pollution by harnessing the power of artificial intelligence and the Internet of Things. This book offers readers crucial insights into how AI can be integrated with IoT, providing the knowledge necessary for leveraging these technologies to foster a sustainable future. In addition to theoretical knowledge, this book serves as a practical guide, offering tailored practices for AI and IoT integration. Case studies provide hands-on experience, empowering readers to make informed decisions on selecting and applying various AI and IoT frameworks for environmental sustainability.
1. Introduction - p. xxiii 2. Part 1. Foundations - p. P1 3. Chapter 1. Fundamentals of the Internet of Things (IoT) for environmental monitoring - p. 3 4. Chapter 2. Basics of image and signal processing applied to the processing and analysis of environmental data - p. 55 5. Chapter 3. Basics of deep learning enabling smart ecosystems - p. 69 6. Part 2. AI techniques and distributed computing - p. P2 7. Chapter 4. Deep learning methods for image recognition and classification in smart environmental systems - p. 89 8. Chapter 5. Federated Learning and Edge Computing: Revolutionizing Smart Environments - p. 111 9. Chapter 6. Connected intelligence for ecofriendly precision agriculture: Tides and tactics - p. 129 10. Part 3. Applications and case studies - p. P3 11. Chapter 7. AI-powered smart grids with edge computing in renewable energy - p. 169 12. Chapter 8. Weather prediction using machine learning algorithms: A comparative analysis of multiple models - p. 185 13. Chapter 9. AI-IOT for sustainable farming decisions - p. 203 14. Chapter 10. AI for the real-time air pollution monitoring and control - p. 225 15. Chapter 11. Collaborative edge-cloud computing for sustainable waste management - p. 241 16. Chapter 12. Ocean waste monitoring using IoT enabled oceanographic analysis - p. 265 17. Chapter 13. IoT-driven ensemble framework for climate change monitoring and cyclone disaster management - p. 283 18. Chapter 14. A dynamic real-time soil moisture identification system with interpolation capabilities for improved crop yield and water conservation - p. 313 19. Part 4. Challenges and future directions - p. P4 20. Chapter 15. Ethical and societal challenges of AI and IoT for sustainable development - p. 343 21. Chapter 16. Outlook on current challenges and future directions - p. 377 22. Glossary - p. 403 23. Index - p. 405
Perspectives on Artificial Intelligence and Internet of Things for Sustainable Environment addresses urgent environmental issues stemming from urbanization, deforestation, and pollution by harnessing the power of artificial intelligence and the Internet of Things. This book offers readers crucial insights into how AI can be integrated with IoT, providing the knowledge necessary for leveraging these technologies to foster a sustainable future. In addition to theoretical knowledge, this book serves as a practical guide, offering tailored practices for AI and IoT integration. Case studies provide hands-on experience, empowering readers to make informed decisions on selecting and applying various AI and IoT frameworks for environmental sustainability.
1. Introduction - p. xxiii 2. Part 1. Foundations - p. P1 3. Chapter 1. Fundamentals of the Internet of Things (IoT) for environmental monitoring - p. 3 4. Chapter 2. Basics of image and signal processing applied to the processing and analysis of environmental data - p. 55 5. Chapter 3. Basics of deep learning enabling smart ecosystems - p. 69 6. Part 2. AI techniques and distributed computing - p. P2 7. Chapter 4. Deep learning methods for image recognition and classification in smart environmental systems - p. 89 8. Chapter 5. Federated Learning and Edge Computing: Revolutionizing Smart Environments - p. 111 9. Chapter 6. Connected intelligence for ecofriendly precision agriculture: Tides and tactics - p. 129 10. Part 3. Applications and case studies - p. P3 11. Chapter 7. AI-powered smart grids with edge computing in renewable energy - p. 169 12. Chapter 8. Weather prediction using machine learning algorithms: A comparative analysis of multiple models - p. 185 13. Chapter 9. AI-IOT for sustainable farming decisions - p. 203 14. Chapter 10. AI for the real-time air pollution monitoring and control - p. 225 15. Chapter 11. Collaborative edge-cloud computing for sustainable waste management - p. 241 16. Chapter 12. Ocean waste monitoring using IoT enabled oceanographic analysis - p. 265 17. Chapter 13. IoT-driven ensemble framework for climate change monitoring and cyclone disaster management - p. 283 18. Chapter 14. A dynamic real-time soil moisture identification system with interpolation capabilities for improved crop yield and water conservation - p. 313 19. Part 4. Challenges and future directions - p. P4 20. Chapter 15. Ethical and societal challenges of AI and IoT for sustainable development - p. 343 21. Chapter 16. Outlook on current challenges and future directions - p. 377 22. Glossary - p. 403 23. Index - p. 405
