Russian Engineers Develop AI System for Industrial Water Treatment
The platform combines a digital twin, smart sensors, and neural networks to analyze and automatically regulate treatment processes.
Engineers at the Moscow Aviation Institute have unveiled a pilot version of software designed for intelligent water treatment at factories, municipal utilities, and agricultural enterprises, the university’s press service said.
According to project participant and MAI graduate Valeria Salimgareeva, the system integrates modeling tools, artificial intelligence, sensor networks, and automated control of aeration processes within treatment facilities.
The solution can be deployed at existing wastewater treatment plants or used in the design of new ones. It improves the removal of heavy metals, organic contaminants, and bacteria while maintaining the required acidity level.
Digital Twin and Smart Process Control
The project unfolds in several stages. The first involves creating a digital twin of a treatment facility during the design phase. The software predicts water flow dynamics and contaminant distribution, enabling engineers to select the most effective configuration of equipment and filtration systems.
The second stage focuses on automated control. Installed sensors monitor key water parameters in real time, including acidity, turbidity, flow rate, and temperature. AI algorithms analyze the collected data and automatically adjust equipment settings, allowing the system to respond instantly to changes in water composition.
According to the developers, the technology reduces design costs by 30–40 percent. Independent experts estimate that implementing the system in production could optimize treatment operations by 25–30 percent.
The team plans to launch a cloud-based platform for remote management and a mobile app for operators. Future upgrades will also include integration with enterprise resource management systems to simplify reporting.
