The NetMoA project is aimed at providing regularly updated information to network operators about critical situations (anthropic activities and growth of trees) occurring in proximity of their infrastructures, to improve the protection of their assets and to reduce the cost of current surveys.

NetMoA will use both Sentinel data and VHR data to detect and characterize various risk situation that can affect the integrity of the infrastructures and the continuity of the related service. NetMoA will exploit EO processing algorithms and various AI techniques to process and integrate different types of satellite data to provide regular updated analyses about the environment surrounding the various infrastructures. Possible service adaptations to include specific features for different types of infrastructures will be tackled progressively.

NetMoA service will provide customers with the following benefits:

Reduction of network damages and service interruptions;
Cost savings on the aerial/helicopter/vehicle surveys, by limiting them when and where it is really needed;
Shorter intervention time and optimization of field workforce operations;
Faster and more cost-effectively planning of new infrastructures.

The second phase of NetMoA development aims to realize the evolution of the prototype monitoring service developed under Copernicus Incubation. to better respond to the information needs of large infrastructure operators (such as electricity, transport, energy, telecommunications) that must monitor, protect and manage networks that unfold for several tens of thousands of linear kilometers and that are subject to interference from human activities vegetation and natural disasters.

This project envisages the purchase and the use of a workstation with high data processing capacity, equipped with a high-performance NVIDIA professional GPU, specifically designed for data processing through artificial intelligence and deep learning. The project implements a workflow with a more complex logic decision tree that combines algorithms for data processing with more stringent multi-temporal analyses and various AI techniques.

The results of the new processing chain will be extensively tested, also through in-situ surveys, in test areas selected with end-customers to validate the project outcome.

The project also includes the promotion of the service to potential customers abroad to start testing the market potential outside Italy.