This dataset is part of the AIMS project (Artificial Intelligence to Monitor our Seas), which has the vision to develop and validate novel Artificial Intelligence (AI) algorithms to unlock the true potential of remote monitoring and enable a faster transition to a climate neutral society and economy: the AI algorithms will leverage the advantages of usual monitoring methodologies of the features of waves and offshore wind, and eventually overcome their intrinsic limitations. The value and resolution of sparse measurements of satellites and unevenly-distributed in-situ instruments will be increased, hence leading to a significant reduction of the cost and execution time of data collection, ultimately making knowledge wider and more accessible. This dataset in particular ir related to collection of a moored Directional Wave Spectra Drifter (DWSD) buoy network deployed offshore of Livorno as part of the AIMS project. The campaign aimed to create an experimental 3 x 3 buoy grid, positioned at 1.5 km intervals, to study wave dynamics in a confined area and evaluate the accuracy of numerical wave models. Each buoy, equipped with GPS and real-time data transmission via satellite, recorded wave and meteo-marine parameters at three-hour intervals over approximately five months. The data, though partially affected by buoy losses, provide a high-resolution view of wave behaviour and serve as a valuable resource for wave energy studies and forecasting models. This report includes detailed descriptions of the dataset and its structure, offering insights into data quality, operational challenges, and guidelines for future campaigns.

AIMS: Artificial Intelligence to Monitor our Seas is funded by the European Union - NextGeneration EU within the PRIN 2022 PNRR program (D.D.1409 del 14/09/2022 Ministero dell’Università e della Ricerca). This document reflects only the authors’ view, and the Commission and Ministry cannot be considered responsible for any use that may be made of the information it contains.