Artificial intelligence as an upcoming technology in wastewater treatment: a comprehensive review. Issue 1 (1st January 2021)
- Record Type:
- Journal Article
- Title:
- Artificial intelligence as an upcoming technology in wastewater treatment: a comprehensive review. Issue 1 (1st January 2021)
- Main Title:
- Artificial intelligence as an upcoming technology in wastewater treatment: a comprehensive review
- Authors:
- Malviya, Arti
Jaspal, Dipika - Abstract:
- ABSTRACT: Artificial intelligence (AI) is nowadays an upcoming technology. It is a practice of simulating human intelligence for varied applications. When compared with the standard practices, AI is developing at a rapid rate. AI has proved its worth in several areas such as agriculture, automobile industry, banking and finance, space exploration, artificial creativity, etc. Owing to the efficiency, speed, and independence from human operations, AI is now entering the wastewater treatment sector. This technology has been used for monitoring the performance of the water treatment plants in terms of efficiency parameters, Biological Oxygen Demand (BOD) and Chemical Oxygen Demand (COD) determination, elimination of nitrogen and sulphur, prediction of turbidity and hardness, uptake of contaminants, etc., in the wastewater sector. Artificial Neural Networks (ANN), Fuzzy Logic Algorithms (FL), and Genetic Algorithms (GA) are the basic three models under AI predominantly used in the wastewater sector. Studies reveal that the determination coefficient values of 0.99 can be attained for COD, BOD, heavy metals and organics removal using ANN and hybrid intelligent systems. This review paper describes research with all the possible models of AI utilized in the water treatment which have enhanced the pollutant removal percentage accuracy of ranging from 84% to 90% and provided viewpoint on future directions of novel research, in the field with due focus on pollution remediation, costABSTRACT: Artificial intelligence (AI) is nowadays an upcoming technology. It is a practice of simulating human intelligence for varied applications. When compared with the standard practices, AI is developing at a rapid rate. AI has proved its worth in several areas such as agriculture, automobile industry, banking and finance, space exploration, artificial creativity, etc. Owing to the efficiency, speed, and independence from human operations, AI is now entering the wastewater treatment sector. This technology has been used for monitoring the performance of the water treatment plants in terms of efficiency parameters, Biological Oxygen Demand (BOD) and Chemical Oxygen Demand (COD) determination, elimination of nitrogen and sulphur, prediction of turbidity and hardness, uptake of contaminants, etc., in the wastewater sector. Artificial Neural Networks (ANN), Fuzzy Logic Algorithms (FL), and Genetic Algorithms (GA) are the basic three models under AI predominantly used in the wastewater sector. Studies reveal that the determination coefficient values of 0.99 can be attained for COD, BOD, heavy metals and organics removal using ANN and hybrid intelligent systems. This review paper describes research with all the possible models of AI utilized in the water treatment which have enhanced the pollutant removal percentage accuracy of ranging from 84% to 90% and provided viewpoint on future directions of novel research, in the field with due focus on pollution remediation, cost effectiveness, energy economy, and water management. GRAPHICAL ABSTRACT: UF0001 … (more)
- Is Part Of:
- Environmental technology reviews. Volume 10:Issue 1(2021)
- Journal:
- Environmental technology reviews
- Issue:
- Volume 10:Issue 1(2021)
- Issue Display:
- Volume 10, Issue 1 (2021)
- Year:
- 2021
- Volume:
- 10
- Issue:
- 1
- Issue Sort Value:
- 2021-0010-0001-0000
- Page Start:
- 177
- Page End:
- 187
- Publication Date:
- 2021-01-01
- Subjects:
- Wastewater treatment -- Artificial intelligence -- Artificial neural network -- Technology -- BOD -- Wastewater parameters
Environmental engineering -- Periodicals
Environmental protection -- Periodicals
628.05 - Journal URLs:
- http://www.tandfonline.com/toc/tetr20/current ↗
http://www.tandfonline.com/ ↗ - DOI:
- 10.1080/21622515.2021.1913242 ↗
- Languages:
- English
- ISSNs:
- 2162-2515
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 25097.xml