Wastewater Modeling

This book provides an efficient and low-cost solution for remediation of wastewater. The book focuses on physico-chemical treatment via advanced oxidation process, adsorption, its management and recovery of valuable chemicals. It discusses treatment and recovery process for the range of pollutants including BTX, PCB, PCDDs, proteins, phenols, antibiotics, complex organic compounds and metals.

This volume is dedicated to water as the most important source of life.

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.