The Internet of Things in Public Utilities: a case from the Digital Zone for Mosvodokanal

What is the task Mosvodokanal? Provide people with clean, hot and cold water at home with normal pressure. And if something went wrong, then quickly intervene and return the water to its channel (in the literal sense).

For this company, it is important to know what happens to the water in the pipeline: whether it flows or does not flow and whether it flows where necessary. If not, then somewhere soon - yes, although it should not. In general, the essence you caught.

Therefore, Mosvodokanal turned to the Digital Zone company, which has developed an automated information system (AIS) for detecting damaged sections of a water supply system (RWEL) based on the Internet of Things .

The Digital Zone (DZ) company develops information systems, web platforms and services (business intelligence, assessment of installed systems, technical support, etc.).

How did Mosvodokanal live

On Mosvodokanal already had AIS Piduv. It was needed for the rapid identification of large spouts on the water supply network of the capital. Analyzing changes in the totality of hydraulic indicators (first of all, pressure in control points), she monitored the operation of pumping units. At the same time, it was possible to regulate changes in water consumption only by turning the additional pump sensors on or off.

Simply put, the system was at the level of primary automation. It was a screen with a complete infrastructure, that is, a map of the aqueduct with marked pumping stations (like the metro scheme). When a breakthrough occurred somewhere, the operator looked at the screen and, analyzing the pressure change indicators, determined the approximate location of the accident and decided which valves to shut off, where to increase or decrease the engine power, etc.

It is important to understand that the automatic component recorded the fact of breakage and its location with an accuracy of a microdistrict. The operator must, in any case, send the crew to the scene of the accident and fix the damage.

From calls of grandmothers a la "Oh, granddaughter, we have hot water from asphalt flowing here" sometimes was more confusing because they were heard earlier and the address was accurate.

What led the water company to DZ?

Of course, Mosvodokanal wanted more. At some point, they changed the principle of regulating the supply of water to a new one. It consisted in maintaining pressure at current points with the help of frequency power regulators of pumping units. With this approach, the current AIS RPC and completely lost its relevance, since now regulators could control the pressure drawdown automatically and did not allow the pressure on the spout to fall so that this area was displayed in the AIS.

Mosvodokanal turned to DZ in order to upgrade the existing AIS GTC. He asked for a system that could identify an emergency case faster and more accurately , displayed it on a map and did not require waiting for phone calls from affected residents.

Prior to this, Mosvodokanal also introduced a system for collecting information from multiparameter sensors. Now it was recorded not only the pressure, but also the water consumption in this area and the noise level.

What was ultimately required from DZ?

A new algorithm that increases the sensitivity of the old AIS: it must detect damage with varying degrees of outflow (that is, before the water starts to beat the fountain from the bowels of the earth) and display the location of the accident as locally as possible.

How could DZ create it?

Based on hydraulic and acoustic indicators from the sensors installed by Mosvodokanal, but subject to automatic maintenance of pressure at the test points.

What was the result? Overall picture

The new AIS OPUV with the use of IoT technology is a monitoring system with an algorithm for reading and analyzing data from multiparameter sensors, as well as an emulation system for analyzing the behavior of the water supply network under various scenarios.

The algorithm was based on a mathematical model for predicting and comparing data in real time. Ideally, water flows through the water supply system along a given route (S) with a given pressure (P) for a certain period of time (τ), that is, there is a cyclical action. This cycle was described by programmers.

This forecasting model is a benchmark.

And then the program reads the indicators from the sensors and compares with the standard.

Outwardly, almost nothing has changed in terms of the interface, but at the program level, IT professionals have conjured again. They draw additional layers on the map to make it easier for the dispatcher to keep track of what is happening.

As a result, the system issues informational messages about detected deviations in the behavior of the water supply network, shows a section of a potential malfunction and all information that can help in deciding on further actions.

Life Mosvodokanal after change

For clarity, we present the results in the comparative table.
Indicators / AISAIS OPUV
MGUP "Mosvodokanal"
Number of sensorsabout 5 pieces / 10 kmabout 40 pieces / 10 km
Fault detection time20 minutes5 minutes
LocalizationWithin the microdistrict1-3 square meters. km

The technology was introduced in 2012. By speeding up the reading and processing of data, the system has reduced the costs of the city budget in emergency situations by 10-15%.


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