Dry Weather Adaptations in Wastewater Treatment: Innovative Control Strategies for Effective Organic and Nitrogen Elimination

¹ Department of Computer Science Engineering, New Horizon College of Engineering, Bangalore, Karnataka, India.
² Lovely Professional University, Phagwara, India.
³ Department of AI&ML, GRIET, Bachupally, Hyderabad, Telangana, India.
⁴ Lloyd Institute of Engineering & Technology, Knowledge Park II, Greater Noida, Uttar Pradesh, India.
⁵ Medical Laboratory Technology Department, College of Medical Technology, The Islamic University, Najaf, Iraq
⁶ Lloyd Institute of Management and Technology, Greater Noida, Uttar Pradesh, India - 201306
⁷ Department of Science and Humanities, MLR Institute of Technology, Hyderabad, Telangana, India.

^* Corresponding author: skumars1803@gmail.com

Abstract

Through a meta-heuristic framework, this study examines various wastewater treatment methods in detail and proposes a novel application of genetic algorithms (GAs) in plant optimization. ASM models are adapted to include ion speciation and pairing models, and microplastics (MPs) are challenged, indicating the need for further research. An integrated model accounts for carbon, nitrogen, phosphorus, oxygen, and hydrogen, emphasizing pH’s crucial role in biological treatment processes by examining microbial growth rates and organic compound removal. By applying natural selection and evolutionary processes, GAs are investigated as an optimization tool for plants, improving gene sequence structures and, by extension, treatment processes. The importance of this is particularly evident when dealing with non-standard numerical solutions and algebraic calculations. A robust and adaptable wastewater treatment strategy that accommodates variable weather conditions is provided by the study, which illustrates GAs, their stopping conditions, and the selection process for fitness functions.