On 25 and 26 January, Italferr, Infrastructure Hub of the FS Group, took part in "Innovation to Impact", the closing event of the sixth edition of the Open Italy Elis programme, at MAXXI Museum in Rome, where the main players of Italian industry shared and discussed with the entire ecosystem, with a view to impact that generates value.
OPEN ITALY was born within the ELIS consortium, a co-creation laboratory in which large companies, start-ups and young talents collaborate for the development of concrete innovation projects. It is an opportunity to work together on the development of new solutions, promoting the culture of open innovation.
In this scenario Italferr developed, during the 2022 edition, two Proof of Concepts (PoCs) focused respectively on the digitization of construction management processes and on the predictive monitoring of containment works such as cortical cladding.
DIGISITE is the project developed with the start-up Mela Works to digitize the activities that the Works Management carries out on site through work tools capable of optimizing time and resources. An application to collect data in a flexible and fast way, thus optimizing information flows. The tool also allows you to compile predefined reports, draw up the customized work journal on the Italferr format and apply signatures in real time.
The collaboration with the start-up Modelway, on the other hand, led to the creation of RAIL (Relax, Artificial Intelligence is Looking), the project designed to define a new approach for the continuous supervision of hydrogeological risk mitigation works in the railway sector, through machine learning algorithms and virtual sensors. The system developed in the context of the PoC allows the automatic recognition of the containment works, i.e. ropes, nets and nails, through computer vision algorithms and is able to identify any anomalies and predict critical events. Through image analysis, the Artificial Intelligence algorithm is also able to map the elements of the protection structure and monitor the entire life cycle, with a view to predictive maintenance.