Artificial Intelligence for Air Quality Monitoring and Prediction
eBook - ePub

Artificial Intelligence for Air Quality Monitoring and Prediction

  1. 301 pages
  2. English
  3. ePUB (mobile friendly)
  4. Available on iOS & Android
eBook - ePub

Artificial Intelligence for Air Quality Monitoring and Prediction

About this book

This book is a comprehensive overview of advancements in artificial intelligence (AI) and how it can be applied in the field of air quality management. It explains the linkage between conventional approaches used in air quality monitoring and AI techniques such as data collection and preprocessing, deep learning, machine vision, natural language processing, and ensemble methods. The integration of climate models and AI enables readers to understand the relationship between air quality and climate change. Different case studies demonstrate the application of various air monitoring and prediction methodologies and their effectiveness in addressing real-world air quality challenges.

Features

  • A thorough coverage of air quality monitoring and prediction techniques.
  • In-depth evaluation of cutting-edge AI techniques such as machine learning and deep learning.
  • Diverse global perspectives and approaches in air quality monitoring and prediction.
  • Practical insights and real-world case studies from different monitoring and prediction techniques.
  • Future directions and emerging trends in AI-driven air quality monitoring.

This is a great resource for professionals, researchers, and students interested in air quality management and control in the fields of environmental science and engineering, atmospheric science and meteorology, data science, and AI.

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Yes, you can access Artificial Intelligence for Air Quality Monitoring and Prediction by Amit Awasthi,Kanhu Charan Pattnayak,Gaurav Dhiman,Pushp Raj Tiwari in PDF and/or ePUB format, as well as other popular books in Technology & Engineering & Artificial Intelligence (AI) & Semantics. We have over one million books available in our catalogue for you to explore.

Table of contents

  1. Cover
  2. Half-Title Page
  3. Series Page
  4. Title Page
  5. Copyright Page
  6. Table of Contents
  7. Preface
  8. List of Contributors
  9. About the Editors
  10. 1 Air Quality Monitoring (AQM) and Prediction: Transitioning from Conventional to AI Techniques
  11. 2 Temporal Variations of Sulfur Dioxide Levels across India: A Biennial Assessment (2020–2021)
  12. 3 The Effectiveness of Machine Learning Techniques in Enhancing Air Quality Prediction
  13. 4 Enhancing Environmental Resilience: Precision in Air Quality Monitoring through AI-Driven Real-Time Systems
  14. 5 Forecasting Air Pollution with Artificial Intelligence: Recent Advancements at Global Scale and Future Perspectives
  15. 6 Integrating AI into Air Quality Monitoring: Precision and Progress
  16. 7 Application of AI-Based Tools in Air Pollution Study
  17. 8 Study of Extreme Weather Events in the Central Himalayan Region through Machine Learning and Artificial Intelligence: A Case Study
  18. 9 Machine Learning Applications in Air Quality Management and Policies
  19. 10 A Glimpse into Tomorrow’s Air: Leveraging PM 2.5 with FP Prophet as a Forecasting Model
  20. 11 Air Quality Forecast Using Machine Learning Algorithms
  21. 12 Deep Learning Approaches in Air Quality Prediction
  22. 13 Incorporation of AI with Conventional Monitoring Systems
  23. 14 A Comparative Evaluation of AI-Based Methods and Traditional Approaches for Air Quality Monitoring: Analyzing Pros and Cons
  24. 15 Machine Learning-Driven Hydrogen Yield Prediction for Sustainable Environment
  25. Index