Reinforcement Learning for Adaptive Control of Advanced Oxidation Processes (AOPs) in Wastewater Treatment: A Digital Twin Approach.

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Created by Oluwafemi Bamidele

Apr 3, 2026 12:06 PM

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Project Details

8 items

Department

Chemistry, Physical Sciences, Chemistry

Research Field

Environmental Chemistry

Analytical Chemistry

Keywords

AI Machine Learning Environmental Monitoring

Collaboration Type

academic

Desired Skills

Python, Data Analysis, Lab Techniques

Duration

Medium-term (6-24 months)

Funding

Unfunded

Target Outcome

Journal Publication

Project Description 15 words

This project uses reinforcement learning and digital twin technology to optimize AOPs in wastewater treatment.

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Reinforcement Learning for Adaptive Control of Advanced Oxidation Processes (AOPs) in Wastewater Treatment: A Digital Twin Approach.

Project Details

Open Access Research Papers Free PDFs

Open Access Papers: (2023-2026)

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Reinforcement Learning for Adaptive Control of Advanced Oxidation Processes (AOPs) in Wastewater Treatment: A Digital Twin Approach.

Project Details

Open Access Research Papers Free PDFs

Open Access Papers: (2023-2026)

Team Members (1)

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Version History

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Task Details