Project description
ML and GeoAI models to improve Copernicus surveillance
The Copernicus Security Service (CSS) plays a vital role in supporting the EU’s security, safety, law enforcement, and international commitments, with ongoing efforts from the European Commission to enhance its capabilities. The EU-funded AI4COPSEC project will leverage advanced machine learning (ML) and GeoAI models to enhance Copernicus products and services. Specifically, it will improve oil spill response, illegal fishing alerts, and develop new services for search-and-rescue operations and irregular migration detection. By using self-supervised deep learning, geomatics, and open-source intelligence (OSINT) data from multiple sources, the project aims to boost the timeliness and accuracy of information from both Earth observation (EO) and non-EO data. It will also focus on detecting anomalies in maritime traffic and improving small vessel detection.
Objective
The Copernicus Security Service (CSS) is instrumental to support the European Union’s security, safety, law enforcement, and international commitments with the European Commission advocating for its advancement. The AI4COPSEC project aims to demonstrate the potential of advanced ML and GeoAI models to provide relevant intelligence for enhancing existing Copernicus products and services such as oil spill response, illegal fishing alert and create new services intended to support Search-and–Rescue operations and irregular migration detection. The project will enhance CSS services through the usage of self-supervised deep learning models, geomatics and social media data (OSINT) extracted from heterogenous multi-sources data. AI4COPSEC is expected to have a transformative effect on the operational capabilities of EU security,surveillance and safety by leveraging advances to enhance the timeliness, accuracy, and relevance of information derived from EO and non-EO data sources, including the innovative use of thermal imagery for ship detection, the combination of satellite automatic identification system (AIS) data with structured data extracted from social media sources and the usage of in-situ environmental measurement derived from AIS data and IoT devices. This integration will lead to more effective and efficient security operations, environmental monitoring, and disaster response. AI4COPSEC is also set to detect anomalies and threat in the maritime traffic and advance ship detection capabilities, utilising high-resolution optical images and advanced segmentation algorithms to enhance the detection of small vessels independently of the type of material (metallic structures, wood, rubber...) a critical factor for a comprehensive maritime surveillance in line with the CSS and the EU's maritime security strategy (EUMSS).
Fields of science (EuroSciVoc)
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: The European Science Vocabulary.
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: The European Science Vocabulary.
- agricultural sciences agriculture, forestry, and fisheries fisheries
- natural sciences computer and information sciences internet internet of things
- engineering and technology mechanical engineering vehicle engineering aerospace engineering satellite technology
- agricultural sciences agriculture, forestry, and fisheries forestry
- social sciences law
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Keywords
Project’s keywords as indicated by the project coordinator. Not to be confused with the EuroSciVoc taxonomy (Fields of science)
Project’s keywords as indicated by the project coordinator. Not to be confused with the EuroSciVoc taxonomy (Fields of science)
Programme(s)
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
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HORIZON.2.4 - Digital, Industry and Space
MAIN PROGRAMME
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HORIZON.2.4.10 - Space, including Earth Observation
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Topic(s)
Calls for proposals are divided into topics. A topic defines a specific subject or area for which applicants can submit proposals. The description of a topic comprises its specific scope and the expected impact of the funded project.
Calls for proposals are divided into topics. A topic defines a specific subject or area for which applicants can submit proposals. The description of a topic comprises its specific scope and the expected impact of the funded project.
Funding Scheme
Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.
Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.
HORIZON-RIA - HORIZON Research and Innovation Actions
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Call for proposal
Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.
Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.
(opens in new window) HORIZON-CL4-2024-SPACE-01
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Net EU financial contribution. The sum of money that the participant receives, deducted by the EU contribution to its linked third party. It considers the distribution of the EU financial contribution between direct beneficiaries of the project and other types of participants, like third-party participants.
0164 OSLO
Norway
The total costs incurred by this organisation to participate in the project, including direct and indirect costs. This amount is a subset of the overall project budget.