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D3.2 Maritime Use Case: Initial Evaluation and Validation Report

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    "description": "<p>This report summarises the results of the preliminary evaluation of the components developed for the Maritime Use</p>\n\n<p>Case that will be integrated and tested in a final experimentation at sea toward the end of the Project INFORE.</p>\n\n<p>The Maritime Use Case consists in developing and deploying a hybrid sensor network for ship target detection,</p>\n\n<p>localization and classification. Sensor data for the global scale and the local scale surveillance scenario, resulting in</p>\n\n<p>an extreme scale data stream, will be integrated in a maritime situation awareness platform to perform high level</p>\n\n<p>fusion tasks and target behavioural analysis in order to detect behavioural anomalies of vessels with respect to the</p>\n\n<p>normal traffic in the area of interest. The developed platform will be integrated/using the INFORE architecture,</p>\n\n<p>utilizing its capabilities to analyse extreme scale streamed data.</p>\n\n<p>The evaluation is performed using a set of key performance indices (KPIs) defined for the single components of the</p>\n\n<p>system and for the system as a whole, including human factors. The data used in the evaluation process are historical</p>\n\n<p>data available at the beginning of the Project INFORE or generated by simulating surveillance scenarios.</p>\n\n<p>The tested components include i) the CMRE coordinated sea surface robotic sensor network for target detection and</p>\n\n<p>localization by acoustic data, the target detection and classification systems for satellite data and for thermal and RGB</p>\n\n<p>video camera data, and the MarineTraffic situation awareness platform algorithms for complex event detection.</p>\n\n<p>The results of the evaluation are in general in line with the expectations. The coordinated robotic sensor network</p>\n\n<p>outperforms the base network without coordination, the classification from satellite data and camera data performs</p>\n\n<p>with classification accuracy around or greater than 90% and around 80%, respectively. The complex event classifier</p>\n\n<p>system has analogous performance with accuracy achieving, in some cases, values greater than 90%.</p>\n\n<p>The report provides a complete description of each component, including theoretical details, the evaluation of the</p>\n\n<p>components and finally a preliminary plan of the final experiment at sea to evaluate the Maritime Use Case as a whole.</p>\n\n<p>Future work before the final experiment includes implementation of the control and cooperation software on board</p>\n\n<p>the surface robot vehicles and further test of the classification algorithms for satellite and camera data and for complex</p>\n\n<p>events. Furthermore, the detailed plan, including logistic aspects, of the final experiment at sea will be started soon</p>\n\n<p>this year and finalized next year.</p>", 
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        "title": "Interactive Extreme-Scale Analytics and Forecasting", 
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