Projects
The key oobjective of the SILVANUS project is the release of a climate resilient forest management platform to prevent and suppress forest fire. 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 to efficiently monitor forest resources, to evaluate biodiversity, to generate more accurate fire risk indicators, and promote safety regulations among the local population affected by wildfire through awareness campaigns.
The overarching aim of the X-ALFY project is to provide advanced AI-based eXtended reality tools for Forestry 5.0, addressing three different yet complementary application areas: Teaching, Learning and Environmental Awareness. These applications are in turn instrumental for the rapid acceptance and a wide adoption of the upcoming Forestry 5.0 transformation. The project also addresses key exploitation aspects, including the provision of an exhaustive market analysis and a business plan towards monetisation of the proposed technology.
X-ALFY
The objective of the LASIE project was to design and develop a novel framework to assist forensic analysts in their investigations. The envisaged framework was based on automated technology for advanced data processing supported by an important human component in critical decision making stages, as well as, legal and ethical aspects. The framework consisted of tools to automatically manipulate, analyse and fuse vast amounts of heterogeneous data acquired from different sources including CCTV surveillance content, confiscated desktops and hard disks, mobile devices, Internet, social networks, handwritten and calligraphic documents.
The MAGNETO project developed solutions and tools that leverage sophisticated knowledge representation, advanced semantic reasoning and augmented intelligence. These advancements provided LEAs with enhanced capabilities for crime analysis, prevention and investigation. The project’s ultimate goal was to deliver the MAGNETO platform, which will empower LEAs to seamlessly integrate diverse and extensive data sources. By doing so, they can uncover hidden relationships among data items and identify trends related to the evolution of security incidents.
The objective of the EU-funded project DEFENDER was to model Critical Energy Infrastructures as distributed Cyber-Physical Systems for managing the potential reciprocal effects of cyber and physical threats (ii) deploy a novel security governance model, which leverages on lifecycle assessment for cost-effective security management over the time (iii) bring people at centre stage by empowering them as virtual sensors for threat detection, as first level emergency responders to attacks, or by considering workforce as potential threats.