دورية أكاديمية
Status and future trends in wastewater management strategies using artificial intelligence and machine learning techniques.
| العنوان: | Status and future trends in wastewater management strategies using artificial intelligence and machine learning techniques. |
|---|---|
| المؤلفون: | Baskar, Gurunathan, Nashath Omer, Soghra, Saravanan, Panchamoorthy, Rajeshkannan, R, Saravanan, V, Rajasimman, M, Shanmugam, Venkatkumar |
| المصدر: | Chemosphere ; ISSN:1879-1298 ; Volume:362 |
| بيانات النشر: | Elsevier Science |
| سنة النشر: | 2024 |
| المجموعة: | PubMed Central (PMC) |
| مصطلحات موضوعية: | Artificial intelligence, Deep learning, Internet of things, Machine learning, Sampling, Water management |
| الوصف: | 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. |
| نوع الوثيقة: | article in journal/newspaper |
| اللغة: | English |
| العلاقة: | https://doi.org/10.1016/j.chemosphere.2024.142477Test; https://pubmed.ncbi.nlm.nih.gov/38844107Test |
| DOI: | 10.1016/j.chemosphere.2024.142477 |
| الإتاحة: | https://doi.org/10.1016/j.chemosphere.2024.142477Test https://pubmed.ncbi.nlm.nih.gov/38844107Test |
| حقوق: | Copyright © 2024 Elsevier Ltd. All rights reserved. |
| رقم الانضمام: | edsbas.F56668EE |
| قاعدة البيانات: | BASE |
| DOI: | 10.1016/j.chemosphere.2024.142477 |
|---|