M.A.R.E.

Machine Learning Applied to Marine Ecosystem Research via AUV's.

Abstract.

There are still gaps in the observation of biological, ecological, chemical, and geological parameters. The purpose of M.A.R.E. is to develop a new integrated system for measuring essential ocean variables (EOV) using sensors throughout the entire water column. M.A.R.E. will develop, integrate, validate, test, and demonstrate a new integrated system for marine environment observation, incorporating data collected from various platforms.

Project Phases:

  • Definition of requirements to establish the technical specifications of the modules and their integration into the M.A.R.E. platform.
  • Integration of multiple modules (AUV + Docking Station + Lander + Hub Buoy + Ground Control Station) into the M.A.R.E. platform using an innovative approach
  • Development of a new network to enable consistent, interoperable, and common communication and network integration of the modules.
  • Laboratory calibration/testing of the modules to assess their performance and functionality.
  • Testing in controlled scenarios, through joint operations involving multiple modules (AUV-Docking Station, Lander-Hub Buoy, Hub Buoy-GCS).


The proposed activities aim to provide in situ demonstrations of the modules across a wide range of environmental contexts and relevant applications. The data flow management will ensure an integrated and enhanced understanding of possible variables and models for assessing marine environmental quality, enabling greater scientific knowledge and research capabilities.

Funded by the European Union – NextGenerationEU

Project implemented within the framework of the National Recovery and Resilience Plan (NRP).

RAISE – Robotics and AI for Socio-economic Empowerment

Project code: RAISE_2023_031

Project cost: € 972.317.00

Project funding: € 699,432.05

Project duration: 18 months (01/03/2024 – 31/08/2025)