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Country: Greece


9 Projects, page 1 of 2
  • Funder: EC Project Code: 101121271
    Overall Budget: 4,260,540 EURFunder Contribution: 3,499,910 EUR

    CONNECTOR’s vision is to contribute to the European Integrated Border Management (EIBM) and to the EU Customs Action Plan by addressing the need of close cooperation between Customs, Border and Coast Guard Authorities within the current and upcoming challenging and demanding environment of borders’ control by further involving Customs to the Common Information Sharing Environment (CISE) network and Enhanced Common Information Sharing Environment (e-CISE) through the proposed Customs Extended Common Information Sharing Environment (CE-CISE). CONNECTOR aims for the first time to suggest an integrated, common and shared risk assessment approach for all Border Management Authorities, considering the pan-EU common risk indicators per end user group (Customs, Border and Coast Guards Authorities including FRONTEX), to ensure external EU border and secure EU citizens from cross-border crime and/or secure the seamless flow of travellers, as recommended in the multiannual strategic policy document . Thus, in this sense, CONNECTOR proposal, will design and develop the CONNECTOR system as an interoperable technical environment, ensuring close and practical cooperation and information exchange at all levels. The design and the development of the CONNECTOR system will be based on the analysis of current policy initiatives in EU level (directives, policy and staff documents, guidelines etc.) along with needs, gaps and future views of the end-user groups going beyond previous initiatives (ANDROMEDA, MARISA, EFFECTOR, etc.), complying with the Societal, Ethical and Legal (SoEL) requirements and regulations, following the SoEL-by-design principle. The CONNECTOR system will be validated in real operational environment, based on well-defined National, Cross-border and Transnational use cases defined commonly by Customs and Border and Coast Guards authorities, during three (3) long lasting trials (Demonstration and Testing) under standardised methodology.

  • Funder: EC Project Code: 101021673
    Overall Budget: 6,065,820 EURFunder Contribution: 4,997,560 EUR

    Maritime Domain Awareness is the combination of activities, events and threats in the maritime environment that could have impact on marine activities and EU territory. During the past decades, advances in Information and Communication Technologies have provided better means to monitor and analyse vessel activity. Today private and public source of data such the Automatic Identification System or space related data can be combined with Vessel Traffic Services, Vessel Traffic Management Systems and Vessel Traffic Monitoring & Information Systems data enabling the development of value added information resulted by the combination of such data. European waters are navigated daily by some 12,000 vessels, which share their positions to avoid collisions, generating a huge number of positional messages every month. It is important that this overabundance of information will not overwhelm the marine operator in charge for decision-making. The challenge is twofold: on one side encourage the exchange of heterogeneous data among administration valorising the CISE network currently in place, on the other exploit at the best these datasets by means of automated processing in a way to minimise false alert that might results by an incorrect processing or interpretation of the results. PROMENADE will improve solutions for the vessel tracking, behaviour analysis and automatic anomaly detection by means of the application Artificial Intelligence (AI) and Big Data (BD) technologies, and to promote collaborative exchange of information between maritime surveillance authorities, shortening the time to market and assuring the compliance with legal and ethical regulations. An open, service-based toolkit implementing “state of art” AI / BD techniques also benefiting of HPC (High Performance Computing) platform is the core activity of the project. The project’s developments will be demonstrated and evaluated in 3 operational scenarios and 1 simulated defined by Border Guards Authorities.

  • Funder: EC Project Code: 883374
    Overall Budget: 5,882,380 EURFunder Contribution: 4,999,530 EUR

    EFFECTOR aims to enhance maritime surveillance, improve decisions support, and foster collaboration of maritime stakeholders by implementing an Interoperability Framework and associated Data Fusion and Analytics services for Maritime Surveillance and Border Security that will allow faster detection of new events, better informed decision making, achievement of a joint understanding and undertaking of a situation across borders, allowing seamless cooperation between operating authorities and on-site intervention forces ensuring that all existing privacy and data protection rules are fully respected. Specifically, EFFECTOR will unlock the full capabilities of maritime surveillance systems and data sharing at tactical and strategic level by introducing applied solutions for enhanced border and external security, including the implementation of a multilayered data lake platform for end-to-end interoperability and data exploitation, the exchange of enhanced situational awareness pictures at different level with CISE and EUROSUR, the adoption of interoperability standards for exploiting data sources and systems currently underutilized in maritime environment and the demonstration of new concepts and tools for knowledge extraction, semantic representation, data fusion, analytics, and federated querying that can scale from local to regional and up to national and transnational level. The EFFECTOR solution will be tested, validated and demonstrated in real operational scenarios together with maritime authorities, End Users and practitioners in France, Portugal and Greece. The project will leverage on the developments, results and experience from current and previous research projects (EUCISE2020, MARISA, RANGER, PERSEUS, BLUEMASSMED), from National Procurement projects of CISE Nodes and Adaptors and on the CISE infrastructure of the End Users.

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  • Funder: EC Project Code: 833881
    Overall Budget: 6,009,590 EURFunder Contribution: 4,999,460 EUR

    The project aims to unlock the full potential of CISE, by validating in a long period of time CISE-compatible command, control and coordination systems from several Coast and Border Agencies. At the same time it is envisaged to further enhance, validate and demonstrate CISE by extending its scope for land borders and adapting relevant C2 solutions and associated services. This will be accomplished by extending the CISE data model based on the use cases and requirements and adapting state-of-the-art command & control systems for full compliancy with the enhanced model and CISE message exchange patterns. The project architecture will follow a hybrid scheme in order to allow the usage of the End User CISE Nodes/Gateways and at the same time to allow the testing and validation of the extended data model. The project will leverage on the developments, results and experience of the consortium from current and previous research projects (PERSEUS, CloseEye, MARISA, RANGER), from National Procurement projects of CISE Nodes and Adaptors and on the CISE infrastructure of the End Users.

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  • Funder: EC Project Code: 101121129
    Overall Budget: 5,998,860 EURFunder Contribution: 5,998,860 EUR

    The primary goal of SMAUG is to improve the underwater detection of threats in ports and their entrance routes, by means of a integrated system capable of providing data concerning threat analysis between 3 main elements: ports security infrastructure, advanced underwater detection systems and surveillance vessels. Underwater detection and location will be performed by four primary methods: i) acoustic detection, where a series of hydrophones will listen for sounds emitted by small underwater vehicles and will be processed by artificial intelligence methods, ii) rapid sonar hull scan, used to scan ships hulls and perform harbour floor scanning, iii) high resolution sonar inspection, to inspect objects in water with poor visibility and iv) collective autonomous location, where a swarm of autonomous underwater vehicles will act cooperatively. This will provide information to Artificial Intelligence modules which will improve the way detecting illicit and dangerous goods and/or of threats hidden below the water surface is currently done, taking into account sources such as Unmanned Surface Vehicle Systems, (USV), underswater remote operation vehicle (ROV), UAV (Aerial autonomous vehicle) and Port current information sources. The combination of these tools will allow SMAUG to prompt solutions capable of detecting possible threats to infrastructure or vessels, as well as identify vessels with concealed goods.


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