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To improve our understanding of how marine ecosystems function, it is crucial to quantify their processes using proper spatio-temporal multiparametric monitoring techniques. Science and innovative technologies must play a central role in developing the Blue Growth in a sustainable manner, where advances in enabling technologies such as remote sensing, modelling, AI and autonomous systems, will enhance our capacity to monitor and predict, assess and manage ecosystems. The PLOME project proposes a spatially adaptive, non-invasive, modular platform of independent and wirelessly connected benthic stations and AUVs to intelligently observe, monitor and map marine ecosystems, during long-lasting periods with real-time supervision. The monitoring solution has a simple deployment and is easy-to-move from an experimental site to another, without any cable installation, for coastal and deep water environments. Stations provide continuous and intensive temporal observation, while AUVs can provide such intensive measurement at spatial level, when they undock for a mission from a station in which they previously recharged batteries and transmitted information. The PLOME project will demonstrate the proposed concept in two scenarios. The first one, involves testing independent capabilities in a real deep-sea scenario, while the second one entails a oneweek demonstration in shallow water, where an AUV will be operated from a docking station. This paper describes the Girona 1000 AUV from the Universitat de Girona that will be used for the deep tests , conducted at depths ranging from 200 to 400 meters. The AUV will be used in cooperation with two fixed stations developed by the Universitat Politècnica de Catalunya. Acoustic communications and ranges between the AUV and the stations will be used to coordinate the AUV’s work and to improve its navigation. Optical communications will be used to transmit data to the stations gathered from the AUV observations. The AUV will integrate a

This paper presents a software infrastructure based on Deep Learning aimed at identifying habitats of certain species of crustacean that colonize areas of the marine Mesopelagic zone. Determining their presense is done, in this case, from the detection of holes in the sand that form sets of burrow structures. Preliminar inferencing models are obtained from images captured in the North Sea by trawled UWTV (undewater TV) stations, offering quite significant detection success ratios

Visual odometry is usually integrated in the localization and control modules of underwater robots, combined with other data coming from diverse instruments and sensors, such as, Doppler Velocity Logs (DVL), pressure sensors or inertial units, to compute the vehicle motion and pose by means of death reckoning. Dead reckoning is subject to cumulative drift, and, in underwater scenarios is specially afected by the challenging structures, color textures and environmental conditions (currents, haze, water density, salinity, wind, etc...), increasing the need of specifc improvement or adjustment to this media. This article presents preliminary results of an evolution of the well known VISO2 stereo odometer, modifed in order to improve its performance when run online in marine scenarios, and from a moving Autonomous Underwater Vehicle (AUV) equipped with cameras pointing downwards to the sea bottom., Peer Reviewed

This paper presents a new methodology to pre-diagnose the state of post-surgical abdominal wounds based on visual information. The process consist of four major phases: a) building dense 3D reconstruction of the abdominal area around the wound, b) selecting an area close to the wound to fit a plane, c) calculating the distance from each point of the 3D model to the plane, d) analyzing this map of distances to infer if the wound is inflamed or not. This method needs to be wrapped in an application to be used by patients in order to save unnecessary visits to the medical center.

Actualmente, la sanidad pública está colapsada por la cantidad de gente que asiste a consultas médicas sin ser realmente necesario. En particular, los departamentos de cirugía reciben diariamente decenas de pacientes para el control y la curación de las heridas posquirúrgicas, donde la mayoría de ellos no presenta anomalías y se pueden tratar fácilmente de forma remota.