Challenge description

Water is a daily necessary resource for life, health, economic development and the ecosystem all over the world. Although water is still a relatively cheap and accessible commodity in Europe, drinking water discharges still represent significant losses to the environment, especially during increasingly frequent drought periods. On the other hand, faecal wastewater leaks are also undesirable, as they can further destroy infrastructure and pollute the environment. Public utility companies strive to eliminate spills and control their pipeline system as soon as possible, but with the increasing diversification, the control of such systems is a difficult task.

Medius is challenging EESTech Challenge participants here!

Teams will have the task of detecting potential water leakage before it occurs, using the data we measure on the micro turbines and the principles of machine learning. Faster and more efficient detection of potential water discharges can drastically help reduce drinking water losses.

With the help of pre-prepared data, the participants of the challenge will be challenged with task of develop an algorithm that will try to automatically detect water spills. As its input, the algorithm will obtain measurable quantities of micro turbines in the form of time series, process them and try to predict or. detect water outflow.