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. This book emphasizes the practical application of AI and IoT in addressing pressing environmental challenges, such as air, water, and soil quality monitoring, while aligning…mehr
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. This 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. 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.
Sneha Gautam is an Associate Professor in the Division of Civil Engineering at Karunya Institute of Technology and Sciences, Coimbatore, India. He has received numerous awards, including the Young Scientist Award 2023. He also serves as an Editor, Associate Editor, Editorial Board Member, and Guest Editor for several high-impact journals. With over 146 articles in leading journals, he has developed a global network of collaborators, and his research has been featured in prominent media outlets. Chafai Azri is a prominent researcher specializing in environmental science, with a focus on air quality, pollution, and ecological health risks. His work has significantly contributed to understanding the dynamics of atmospheric pollutants and their implications for human health, particularly in the context of Tunisia. His collaborations with international institutions, such as Cairo University and Georg-August-Universitat Göttingen, further highlight his commitment to advancing research in environmental sciences on a global scale. Through his extensive body of work, Azri continues to address critical environmental issues, contributing to the broader understanding of pollution and its effects on both ecosystems and human health. Md. Badiuzzaman Khan is the Head of the Department of Environmental Science at Bangladesh Agricultural University (BAU). His research focuses on atmospheric aerosols, environmental chemistry, and pollution monitoring. Dr. Khan has contributed to over 16 international journal publications and has been recognized with several awards, including the Outstanding Reviewer Award from the Journal of Environmental Chemical Engineering in 2016. He is also a member of various professional organizations, such as the Science and Engineering Institute and the Indian Association for Air Pollution Control.
Inhaltsangabe
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
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
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