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Artificial Intelligence for Air Quality Monitoring and Prediction (AI Applications in Earth Science)

By: Amit Awasthi (Edited by) , Gaurav Dhiman (Edited by) , Kanhu Charan Pattnayak (Edited by) , Pushp Raj Tiwari (Edited by)

Manufacture on Demand

Ksh 30,400.00

Format: Hardback or Cased Book

ISBN-10: 1032683791

ISBN-13: 9781032683799

Collection / Series: AI Applications in Earth Science

Collection Type: Publisher collection

Publisher: Taylor & Francis Ltd

Imprint: CRC Press

Country of Manufacture: GB

Country of Publication: GB

Publication Date: Oct 2nd, 2024

Publication Status: Active

Product extent: 301 Pages

Weight: 453.00 grams

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  • Description

  • Reviews

This book is a comprehensive overview of advancements in artificial intelligence (AI) and how it can be applied in air quality management. It explains the linkage between conventional approaches used in air quality monitoring with AI techniques such as data collection, preprocessing, deep learning, machine vision, ensemble methods, and more.

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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