Forecasts? Sentinel is the new platform for predictive maintenance and consumption optimization of remotely managed air conditioning machines.

Born from the union of the know-how of Priamria and FR Engineering relating to HVAC systems and the in-depth knowledge of statistical techniques in collaboration also with the University of Padua and also from the opportunity given by the European Regional Development Fund 2014-2020 through the Por FESR project .

The aim is the theoretical research of automated technologies, based on machine learning algorithms aimed at organizing the after-sales service effectively and efficiently and optimizing the operational functioning of a refrigerating machine via remote management. The reference manufacturing sector of the project is the manufacture of machinery/equipment for refrigeration and air conditioning.

The ultimate goal of the proposed algorithms is to support and automate strategic actions that minimize the defects of refrigerating machines, maximize their reliability and reduce energy consumption at the same time.

The heart of the project's innovation lies both in the predictive nature of the algorithms and in the making them intelligently available to automatic systems.

The algorithms will be incorporated into a vertical type web-based application which will be proposed to manufacturing industries producing machines/equipment for refrigeration and air conditioning and to companies providing after-sales assistance services .

The benefits are many: predictive maintenance uses condition monitoring tools and techniques to monitor equipment performance during normal operation; discover and trace any anomalies, identifying them with the aim of solving the flaws before they generate failures; reduce unplanned downtime by up to 30%; schedule multiple service visits at the same time.