17:32, 06 February 2026

AI in Vladimir Is to Prevent Water Supply Failures

The system is designed to predict declining water quality and detect hidden problems before they turn into emergencies.

Researchers at the Murom Institute of Vladimir State University plan to deploy artificial intelligence to monitor the condition of water supply pipes in Murom. The approach is intended to forecast water-quality deterioration and identify hidden issues before they escalate into accidents, project leader Roman Romanov, a PhD in engineering and associate professor, said.

Pipes Filled With Sensors

The system is currently being tested on a single section of the water supply network to fine-tune data collection and processing.

“In the next stage, we plan to scale the monitoring system for centralized water supply across the entire city. There are also plans to expand to other regions, but that will require additional funding,” Romanov said.

He noted that most water supply networks today are heavily worn, which leads to declining water quality, leaks, and accidents. The idea behind the project is to install sensors throughout the network to collect data on pipe conditions. Neural networks then analyze this data, and based on their output, specialists generate forecasts and develop action plans.

“Intelligent data analysis makes it possible to take effective decisions when assessing the technical reliability of centralized water supply systems, as well as the quality of water delivered to the population,” the researcher said.

Four Sensors Per Measurement Point

According to Romanov, the intensity of corrosion processes in steel pipes is influenced by pH levels, oxygen concentration, and chemical composition. The sensors continuously measure key parameters in real time, including electrical conductivity, acidity (pH), hydrodynamic indicators, and temperature.

“At a single measurement point, it is sufficient to install four sensors. Critical changes in indicators — such as peak pressure or conductivity values — make it possible to localize sections where sanitary and technical conditions of the pipes are deteriorating. A key scientific challenge is determining optimal monitoring points, developing a hydrodynamic model, and identifying probabilistic characteristics of the observed section of the network,” Romanov said.

The project has received support from the Russian Science Foundation.

Earlier, we reported that in January 2026, Russian researchers from Perm National Research Polytechnic University and Volgograd State Agrarian University unveiled a universal robot designed for pipeline diagnostics and repair.

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