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Application of Artificial Intelligence in Wastewater Treatment [electronic resource] / edited by Shikha Gulati.

Contributor(s): Material type: TextPublisher: Cham : Springer Nature Switzerland : Imprint: Springer, 2024Edition: 1st ed. 2024Description: XIX, 319 p. 89 illus., 81 illus. in color. online resourceContent type:
  • text
Media type:
  • computer
Carrier type:
  • online resource
ISBN:
  • 9783031694332
Subject(s):
Additional physical formats: Printed edition:: No title; Printed edition:: No title; Printed edition:: No titleLOC classification:
  • GB651-2998
Online resources:
Contents:
Introduction -- Overview of AI Application in diverse fields -- Fundamentals of Artificial Intelligence in wastewater treatment -- Potential of AI optimization in wastewater treatment processes -- Real Time Analysis for Smart Sensor -- Automated Water Control System in Wastewater Treatment plants -- Predictive Modeling for Pollutant removal: Machine learning -- Algorithms for Predictive Analysis -- Case Studies and Success Stories of AI Implementation in Wastewater Treatment -- Environmental Sustainability, Compliance & Life Cycle -- Assessment of AI-Integrated Systems -- Emerging AI Technologies in Wastewater Treatment -- Regulatory framework and standards for adapting AI Systems, Interplay between AI and Environmental policies -- Recommendations for implementation of AI, Steps toward industry wide Adoption -- Conclusions and future prospects of AI in wastewater treatment.
In: Springer Nature eBookSummary: This book offers a comprehensive exploration of the integration of artificial intelligence (AI) techniques in addressing challenges and optimizing processes within wastewater treatment. The coverage of the book spans a spectrum of applications, including AI-driven monitoring and control systems, predictive modeling for pollutant removal, and the development of smart sensor networks for real-time data analysis in wastewater treatment plants. By amalgamating AI methodologies with wastewater treatment processes, the book provides insights into enhancing efficiency, reducing costs, and mitigating environmental impacts. In the current research scenario, the theme of the book is highly pertinent as it responds to the pressing need for sustainable and efficient wastewater treatment solutions. The book defines the theme by elucidating how AI technologies, such as machine learning algorithms and data analytics, can revolutionize wastewater treatment processes by enabling proactive decision-making, optimizing resource allocation, and predicting potential system failures. This intersection of AI and wastewater treatment not only addresses operational challenges but also contributes to the broader goal of achieving environmentally conscious and economically viable solutions.
Item type: List(s) this item appears in: Titluri cărți electronice Springer Nature 2025 (10631 titluri)
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Introduction -- Overview of AI Application in diverse fields -- Fundamentals of Artificial Intelligence in wastewater treatment -- Potential of AI optimization in wastewater treatment processes -- Real Time Analysis for Smart Sensor -- Automated Water Control System in Wastewater Treatment plants -- Predictive Modeling for Pollutant removal: Machine learning -- Algorithms for Predictive Analysis -- Case Studies and Success Stories of AI Implementation in Wastewater Treatment -- Environmental Sustainability, Compliance & Life Cycle -- Assessment of AI-Integrated Systems -- Emerging AI Technologies in Wastewater Treatment -- Regulatory framework and standards for adapting AI Systems, Interplay between AI and Environmental policies -- Recommendations for implementation of AI, Steps toward industry wide Adoption -- Conclusions and future prospects of AI in wastewater treatment.

This book offers a comprehensive exploration of the integration of artificial intelligence (AI) techniques in addressing challenges and optimizing processes within wastewater treatment. The coverage of the book spans a spectrum of applications, including AI-driven monitoring and control systems, predictive modeling for pollutant removal, and the development of smart sensor networks for real-time data analysis in wastewater treatment plants. By amalgamating AI methodologies with wastewater treatment processes, the book provides insights into enhancing efficiency, reducing costs, and mitigating environmental impacts. In the current research scenario, the theme of the book is highly pertinent as it responds to the pressing need for sustainable and efficient wastewater treatment solutions. The book defines the theme by elucidating how AI technologies, such as machine learning algorithms and data analytics, can revolutionize wastewater treatment processes by enabling proactive decision-making, optimizing resource allocation, and predicting potential system failures. This intersection of AI and wastewater treatment not only addresses operational challenges but also contributes to the broader goal of achieving environmentally conscious and economically viable solutions.

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