A Review on Machine Learning, Artificial Intelligence, and Smart Technology in Water Treatment and Monitoring
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Abstract
Artificial-intelligence methods and machine-learning models have demonstrated their ability to optimize, model, and automate critical water- and wastewater-treatment applications, natural-systems monitoring and management, and water-based agriculture such as hydroponics and aquaponics. In addition to providing computer-assisted aid to complex issues surrounding water chemistry and physical/biological processes, artificial intelligence and machine-learning (AI/ML) applications are anticipated to further optimize water-based applications and decrease capital expenses. This review offers a cross-section of peer reviewed, critical water-based applications that have been coupled with AI or ML, including…
Citation impact
318
total citations
- FWCI
- 23.23
- Percentile
- 100%
- References
- 137
Citations per year
Authors
3Topics & keywords
Topics
Keywords
- Computer science
- Automation
- Artificial intelligence
- Standardization
- Water quality
- Engineering
UN Sustainable Development Goals
- Clean water and sanitation
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