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Artificial Intelligence and Modeling for Water Sustainability

Global Challenges

Alaa El Din Mahmoud editor Manal Fawzy editor Nadeem Ahmad Khan editor

Format:Paperback

Publisher:Taylor & Francis Ltd

Publishing:19th Dec '24

£46.99

This title is due to be published on 19th December, and will be despatched as soon as possible.

This paperback is available in another edition too:

Artificial Intelligence and Modeling for Water Sustainability cover

Artificial intelligence and the use of computational methods to extract information from data are providing adequate tools to monitor and predict water pollutants and water quality issues faster and more accurately. Smart sensors and machine learning models help detect and monitor dispersion and leakage of pollutants before they reach groundwater. With contributions from experts in academia and industries, who give a unified treatment of AI methods and their applications in water science, this book help governments, industries, and homeowners not only address water pollution problems more quickly and efficiently, but also gain better insight into the implementation of more effective remedial measures.

FEATURES

  • Provides cutting-edge AI applications in water sector.
  • Highlights the environmental models used by experts in different countries.
  • Discusses various types of models using AI and its tools for achieving sustainable development in water and groundwater.
  • Includes case studies and recent research directions for environmental issues in water sector.
  • Addresses future aspects and innovation in AI field related to watersustainability.

This book will appeal to scientists, researchers, and undergraduate and graduate students majoring in environmental or computer science and industry professionals in water science and engineering, environmental management, and governmental sectors. It showcases artificial intelligence applications in detecting environmental issues, with an emphasis on the mitigation and conservation of water and underground resources.

ISBN: 9781032197074

Dimensions: unknown

Weight: 453g

292 pages