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Full Description
Environmental Monitoring with AI and IoT: Smart Systems for a Sustainable Future aims to provide a comprehensive understanding of how modern technologies like Artificial Intelligence (AI) and the Internet of Things (IoT) revolutionize environmental monitoring. It bridges the gap between traditional environmental assessment methods and advanced, technology-driven approaches to enhance efficiency, accuracy, and scalability.
The book emphasizes the practical application of AI and IoT in addressing pressing environmental challenges, such as air, water, and soil quality monitoring, while aligning with sustainability goals. The scope of this book is vast, covering both foundational concepts and advanced methodologies in environmental monitoring. It includes essential topics like sensor technologies, AI techniques for data analysis, IoT communication protocols, and ethical considerations in environmental monitoring. Real-world case studies and practical examples make the content relatable and actionable. It is supported by instructor-friendly materials, such as digital resources and a detailed teaching guide, making it suitable for both traditional and blended learning environments.
Students, instructors, and professionals will benefit from the insights into creating and deploying smart environmental systems capable of addressing diverse challenges, from urban air quality management to disaster prediction and response. Students will find the content highly accessible and aligned with academic and industrial requirements, while instructors will appreciate its structured approach to teaching these cutting-edge topics.
Contents
Part I: Fundamental Concepts. 1. Introduction to Environmental Monitoring. 2. Environmental Parameters and Their Measurement. 3. Foundations of AI and IoT for Environmental Applications. 4. Role of AI in Environmental Monitoring and Supporting Technologies. Part II: Core Technologies and Methodologies. 5. Sensor Technologies in Environmental Monitoring. 6. IoT Infrastructure and Communication Protocols. 7. AI Techniques for Environmental Data Analysis. 8. Data Management and Analytics. 9. Global Case Studies from Underrepresented Regions. Part III: Applications and Practical Insights. 10. Air Quality Monitoring Systems. 11. Water Quality Monitoring Systems. 12. Soil Health and Agricultural Applications. 13. Disaster Monitoring and Climate Analysis. Part IV: Broader Perspectives and Challenges. 14. Ethics and Social Implications. 15. Emerging Trends and Future Technologies. 16. Policy and Governance. 17. Some Benefits and Tips. 18. Challenges in AI Environmental Projects. 19. Digital Twin Technology in Environmental Applications. 20. Expanded Section: GIS and Remote Sensing Essentials. 21. Uncertainty Analysis in AI for Environmental Research. 22. Practical Hands-on Tutorials (Examples). 23. Concluding Perspectives.
