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Status and future trends in wastewater management strategies using artificial intelligence and machine learning techniques.
Baskar, Gurunathan; Nashath Omer, Soghra; Saravanan, Panchamoorthy; Rajeshkannan, R; Saravanan, V; Rajasimman, M; Shanmugam, Venkatkumar.
Affiliation
  • Baskar G; Department of Biotechnology, St. Joseph's College of Engineering, Chennai, 600119. India; School of Engineering, Lebanese American University, Byblos, 1102 2801, Lebanon. Electronic address: basg2004@gmail.com.
  • Nashath Omer S; School of Bio-Sciences and Technology, Vellore Institute of Technology, Vellore, 632014, Tamil Nadu, India.
  • Saravanan P; Department of Petrochemical Technology, UCE - BIT Campus, Anna University, Tiruchirappalli, Tamil Nadu, 620024, India.
  • Rajeshkannan R; Department of Chemical Engineering, Annamalai University, Chidambaram, Tamil Nadu, 608002, India.
  • Saravanan V; Department of Chemical Engineering, Annamalai University, Chidambaram, Tamil Nadu, 608002, India.
  • Rajasimman M; Department of Chemical Engineering, Annamalai University, Chidambaram, Tamil Nadu, 608002, India.
  • Shanmugam V; School of Bio-Sciences and Technology, Vellore Institute of Technology, Vellore, 632014, Tamil Nadu, India. Electronic address: venkatkumars@vit.ac.in.
Chemosphere ; 362: 142477, 2024 Aug.
Article in En | MEDLINE | ID: mdl-38844107
ABSTRACT
The two main things needed to fulfill the world's impending need for water in the face of the widespread water crisis are collecting water and recycling. To do this, the present study has placed a greater focus on water management strategies used in a variety of contexts areas. To distribute water effectively, save it, and satisfy water quality requirements for a variety of uses, it is imperative to apply intelligent water management mechanisms while keeping in mind the population density index. The present review unveiled the latest trends in water and wastewater recycling, utilizing several Artificial Intelligence (AI) and machine learning (ML) techniques for distribution, rainfall collection, and control of irrigation models. The data collected for these purposes are unique and comes in different forms. An efficient water management system could be developed with the use of AI, Deep Learning (DL), and the Internet of Things (IoT) structure. This study has investigated several water management methodologies using AI, DL and IoT with case studies and sample statistical assessment, to provide an efficient framework for water management.
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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Artificial Intelligence / Wastewater / Machine Learning Language: En Journal: Chemosphere Year: 2024 Document type: Article

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Artificial Intelligence / Wastewater / Machine Learning Language: En Journal: Chemosphere Year: 2024 Document type: Article