Predictive maintenance of radio station


The following project is born in collaboration with Dgroove Srl as part of a bigger predictive maintenance study for Ray Way SpA.
In general predictive maintenance exploits mathematical models to know in advance when a failure is more likely to occur. In this way, it is possible to reduce maintenance times and costs while maintaining high standards of safety and reliability.

The related work describes the development of an algorithm to quantify the relationship between the variables monitored at the Radio Station of Ravina, Trento.
This analysis is used to define an accurate choice of features in view of an Artificial intelligence model training.