WP2: Data Processing and Analysis
- Type: Research
- Start Date: 01 June 2018
- End Date: 31 December 2019
- WP Leader: On AIR
- Abstract: The objective of WP2 is the study and the characterization of methods of processing and analysis of meteorological and marine data, integrated with hull models of tourist boats. This in order to quantify the current or expected degree of risk/comfort of a position or a route and to select the best compatible alternatives. These methods will operate on a unified data structure able to manage the different spatial and temporal layers and resolutions specific of the weather data that are made available.
T2.1 - Access methods for sea-meteorological data. To implement the above objectives, the weather information made available by WP1 will be integrated, so that they will be interoperable and aligned, using a shared format (GRIB or NetCDF). A single access method will allow to extract the expected weather conditions for a certain geographical point at a certain time, interpolating between the available data in a transparent way, in order to decouple the management of the weather data from the individual analysis functions.
T2.2 - Classification and modeling of boat types. The tourist boats will be classified in order to establish, for each class, an adequate and relevant objective function, related to the weather and sea data and to the structural characteristics of the boat (e.g. length, displacement).
T2.3 - Quantification of the risk/comfort level of navigation. Starting from the combination of forecasted weather data and boat models, numerical calculation methods will be analyzed to quantify the degree of risk and comfort of expected navigation, in order to identify critical situations in different contexts.
T2.4 - Generation of operational suggestions. Different optimization methods will be set up in order to prevent the critical situations for the boats and to propose feasible alternatives. Particular emphasis will be placed on the management of access to port facilities, using high-resolution data, and the prediction of any drift due to failure, using specific models related to wind and currents.
Deliverable D.2: Characterization report of data analysis algorithms and automatic generation of operational suggestions for navigation.