Project description
Digital twin technology for ecological monitoring
The rapid advancement of digital technologies such as digital twins, AI and machine learning has opened up promising avenues for ecological actions, including conservation, research and restoration. These technologies offer improved monitoring capabilities that can enhance our understanding of ecological processes and biodiversity. The EU-funded DIGI4ECO project aims to develop a digital twin-sustained 4D ecological monitoring system made by networks of robotic platforms, tailored for restoration efforts in fishery-depleted areas. Additionally, the project intends to enhance data flow safety, security and efficiency by developing innovative methodologies and providing toolsets to ensure data trustworthiness. Finally, DIGI4ECO aims to ensure accessibility of the data and demonstrate and enhance the effectiveness of its system.
Objective
To unlock and boost new discoveries that will be crucial to face climate change, and regulate human actives, which will be key for both environmental conservation and socio-economical activities. We aim to make all the past, current, and future biological and oceanographic data available to everybody. Therefore, we will use relevant sleeping data, by designing new tools and methodologies to use and process relevant data already collected for different institutions, which may come from physical and chemical sensors, or video cameras. We will also harmonize the data, promoting tools to make them the standard among researchers and data-generator actors, developing protocols and best practices, like standardization tools as PUCK among marine sensors and monitoring platforms, and unifying libraries and resources (e.g. FanthomNet or Emodnet). At the same time, we will ensure a secured, sustained and reliable data flows by developing auto correction/validation methodologies and by publishing a set of tools and pipelines to ensure the trustfulness of data. Moreover, we will be using economies of scale and enhanced standardization to conduct several pilot sea-basin scale monitoring tests using two strategies: (1) using existing relevant sleeping data form online and partner repositories, and (2) using new data collected during field test demonstrations. Here, we will develop tools to better support assessment: studying and identifying key indicators and mechanisms to extract them from the data will generate the appropriate guidelines for policymaker, researchers, and socioeconomic sectors. Making those tools, methodologies, and implementations open source for the researchers and public in general will boost their utilization and improvement, even after the conclusion of the present project. With these demonstration examples, the international collaboration, and open source resources, we aim to make our proposal by fact the standard gold to follow in the following years
Fields of science
- agricultural sciencesagriculture, forestry, and fisheriesfisheries
- engineering and technologyelectrical engineering, electronic engineering, information engineeringelectronic engineeringsensorsoptical sensors
- natural sciencesearth and related environmental sciencesatmospheric sciencesclimatologyclimatic changes
Keywords
Programme(s)
Funding Scheme
HORIZON-IA - HORIZON Innovation ActionsCoordinator
28006 Madrid
Spain