The SILVANUS proposal, promoted by Z&P and its 49 partners from the European Union, Brazil, Indonesia, and Australia coordinated by the Università Telematica Pegaso, will be funded by the European Commission under the Horizon 2020 programme between 2021 and 2024.

SILVANUS – Integrated Technological and Information Platform for Wildfire envisages delivering an environmentally sustainable and climate-resilient forest management platform to prevent, suppress and withstand forest fires. SILVANUS relies on environmental, technical and social sciences experts to support regional and national authorities responsible for wildfire management in their respective countries. SILVANUS scientists and research engineers will aid the civil protection authorities in efficiently monitoring forest resources, evaluating biodiversity, generating more accurate fire risk indicators, and promoting safety regulations among the local population affected by wildfire through awareness campaigns.

SILVANUS aims to offer a new technological solution to improve three phases of forest fire management, namely:

 

  • Phase A: Prevention and Preparedness activities. These activities aim to evaluate fire danger indexes continuously, train and prepare firefighters for events with the use of augmented reality and virtual reality tools, increase public awareness to wildfire and create new strategies for fire prevention;

 

  • Phase B: Detection and Response activities. This phase will develop an AI-based mechanism to quickly detect forest fire considering various factors (e.g., weather, wind, etc.) in order to optimise wildfire containment by first responders;

 

  • Phase C: Restoration and Adaptation. The last phase will be built on recent innovations in simulation models, aiming to develop a Decision Support System (DSS) that will find the optimal approach to restore an area affected by a wildfire to its pre-fire condition, considering both flora and fauna.

The main innovations brought by the project are the following:

  • development and integration of advanced semantic technologies to systematically formalise the knowledge of forest administration and resource utilization;

 

  • integration of a big-data processing framework capable of analysing heterogeneous data sources, including earth observation resources, climate models and weather data, continuous onboard computation of multispectral video streams;

 

  • integration of a series of sensors and actuator technologies using innovative wireless communication infrastructures through the coordination of unmanned aerial vehicles (UAVs) and unmanned ground vehicles (UGVs).

Documentation