We proudly announce a new, remarkable achievement accomplished within the context of DIGI4ECO project!
The article, “A digital-twin strategy using robots for marine ecosystem monitoring” has been published at the “Ecological Informatics” Journal, by ELSEVIER!
The authors of the article are: Jacopo Aguzzi, Elias Chatzidouros, Damianos Chatzievangelou, Morane Clavel-Henry, Sascha Flogel, Nixon Bahamon, Michael Tangerlini, Laurenz Thomsen, Giacomo Picardi, Joan Navarro, Ivan Masmitja, Nathan J. Robinson, Tim Nattkemper, Sergio Stefanni, Jose Quintana, Ricard Camposi, Rafael García, Emanuela Fanelli, Marco Francescangeli, Luca Mirimin, Roberto Danovaro, Daniel Mihai Toma, Joaquín Del Rio-Fernandez, Enoc Martinez, Pol Banos, Oriol Prat, David Sarria, Matias Carandell, Jonathan White, Thomas Parissis, Stavroula Panagiotidou, Juliana Quevedo, Silvia Gallegati, Jordi Grinyo, Erik Simon-Lledo , Joan B. Company and Jennifer Doyle
Its respective DOI is the following: https://doi.org/10.1016/j.ecoinf.2025.103409
Partners involved:
- Institut de Ci`encies del Mar (ICM), CSIC
- Stazione Zoologica Anton Dohrn
- Engitec Systems International Limited
- GEOMAR Helmholtz Center for Ocean Research Kiel
- University of Gothenburg
- Universitat Politecnica de Catalunya (UPC) – SARTI Research Group
- Coronis Computing SL
- Polytechnic University of Marche
- Atlantic Technological University
- Marine Institute
- STRATAGEM Energy Ltd
The abstract and the Keywords of the publication can be found below.
ABSTRACT
Effective marine conservation and management require ecological monitoring in the form of intensive real-time data collection over large spatial scales. The combined use of fixed platforms (e.g., cabled observatories) and research vessels with platforms of different levels of teleoperated autonomy (e.g., remotely operated vehicles (ROVs) and autonomous underwater vehicles (AUVs) can contribute to the acquisition of large multiparametric biological and environmental data. If those data are spatially combined, sufficient spatial coverage can be achieved for ecological monitoring. A digital twin of the ocean (DTO) approach can then be used as a virtual representation of that monitored space, enabling multiparametric analyses of environmental patterns and processes affecting biodiversity and species distributions, as well as socioeconomic activities. Here, we propose a general architecture for a DTO centred on real-time data collection from local networks on fixed and mobile platforms, such as the physical twin observers (PTO), which is synergistically merged with platforms operating at large geographic scales. We describe a roadmap to achieve this DTO via 4 key steps: (1) acquisition of in situ data with a robotic network of platforms; (2) the application of AI in image processing for extracting biological data; (3) big data management with data bubbles; and (4) development of the resulting DTO framework for providing ecosystem monitoring via the computation of ecological indicators and socioecological modelling.
KEYWORDS
Marine monitoring; Robotic platforms; Data integration; Ecological indicators; Machine learning; Spatial modelling
You can reach the full article following this link: https://www.sciencedirect.com/science/article/pii/S1574954125004182?via%3Dihub