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Application of artificial intelligen...
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Gulati, Shikha.
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Application of artificial intelligence in wastewater treatment
紀錄類型:
書目-電子資源 : Monograph/item
正題名/作者:
Application of artificial intelligence in wastewater treatment/ edited by Shikha Gulati.
其他作者:
Gulati, Shikha.
出版者:
Cham :Springer Nature Switzerland : : 2024.,
面頁冊數:
xix, 319 p. :ill. (some col.), digital ;24 cm.
內容註:
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.
Contained By:
Springer Nature eBook
標題:
Sewage - Purification -
電子資源:
https://doi.org/10.1007/978-3-031-69433-2
ISBN:
9783031694332
Application of artificial intelligence in wastewater treatment
Application of artificial intelligence in wastewater treatment
[electronic resource] /edited by Shikha Gulati. - Cham :Springer Nature Switzerland :2024. - xix, 319 p. :ill. (some col.), digital ;24 cm.
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.
ISBN: 9783031694332
Standard No.: 10.1007/978-3-031-69433-2doiSubjects--Topical Terms:
3724094
Sewage
--Purification
LC Class. No.: TD745
Dewey Class. No.: 628.3028563
Application of artificial intelligence in wastewater treatment
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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.
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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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