How does using ML or AI helps improving Real-Time Optimization of Dosing for water treatment plants?
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Using ML or AI can improve real-time optimization of dosing for water treatment plants in several ways. Firstly, ML models can be developed to optimize the chemical dosing procedure based on input parameters such as water quality and desired output parameters . These models can continuously train and improve over time, leading to optimal dosing of chemicals to meet water quality standards . Secondly, AI frameworks can be used to predict water levels in tunnels and detect security threats in wastewater treatment plants . By utilizing deep-learning models and recurrent neural networks, these frameworks can accurately predict water levels and classify anomalies, allowing for proactive measures to prevent overflows and cyberattacks . Lastly, ML and AI can be employed to create intelligent dosing systems that automatically monitor water quality, recommend optimal dosages, and control dosing processes . These systems use image recognition, algorithms, and self-learning capabilities to improve water qualification rates and reduce dosing costs .
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11 Dec 2022 | The provided paper does not mention ML or AI specifically for real-time optimization of dosing in water treatment plants. |
11 Dec 2022 | The provided paper does not mention ML or AI specifically for real-time optimization of dosing in water treatment plants. |
| The provided paper discusses the use of intelligent control techniques, including artificial intelligence and neural networks, for water treatment systems. However, it does not specifically mention real-time optimization of dosing for water treatment plants. | |
| The provided paper does not mention anything about real-time optimization of dosing for water treatment plants. | |
| The provided paper does not mention anything about real-time optimization of dosing for water treatment plants. |
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