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Related Experiment Videos

Tackling environmental challenges in pollution controls using artificial intelligence: A review.

Zhiping Ye1, Jiaqian Yang1, Na Zhong1

  • 1College of Environment, Zhejiang University of Technology, Hangzhou 310014, PR China.

The Science of the Total Environment
|March 19, 2021
PubMed
Summary
This summary is machine-generated.

Artificial intelligence (AI) offers advanced prediction and control for environmental pollution. This review details AI applications in wastewater treatment, pollution monitoring, and solid waste management, highlighting benefits and challenges.

Keywords:
Artificial neural networkEarly-warningEnvironmental pollutantsIntelligent controlSoft measurement

Related Experiment Videos

Area of Science:

  • Environmental Science
  • Computer Science
  • Chemical Engineering

Background:

  • Environmental pollution control relies on understanding complex chemical and biological processes.
  • Traditional methods face challenges in accurately predicting and managing pollutants.

Purpose of the Study:

  • To review the advancements in artificial intelligence (AI) technologies for environmental pollution control.
  • To overview the characteristics, advantages, and limitations of various AI methods in environmental applications.

Main Methods:

  • Review of artificial neural networks (ANNs) for wastewater treatment and pollutant prediction.
  • Evaluation of fuzzy logic for intelligent control of wastewater treatment processes.
  • Application of AI-aided soft-sensors for parameter estimation.
  • Analysis of AI methods for pollution monitoring and early-warning systems.
  • AI modeling for solid waste generation, recycling, and reduction.

Main Results:

  • AI methods, including single and hybrid approaches, show significant potential in pollutant removal prediction and optimization.
  • Hybrid AI methods offer synergistic effects but can be computationally intensive.
  • AI effectively aids in on-line/off-line parameter estimation and the design of monitoring systems.
  • AI models demonstrate utility in predicting solid waste generation and optimizing recycling processes.

Conclusions:

  • AI technologies are crucial for enhancing environmental pollution control strategies.
  • Further research is needed to address the computational challenges and optimize AI model deployment in environmental fields.