Enhancing Earth Observation capabilities of the Eratosthenes Centre of Excellence on Disaster Risk Reduction through Artificial Intelligence

Informazioni relative al progetto

AI-OBSERVER

ID dell’accordo di sovvenzione: 101079468

DOI

10.3030/101079468

Progetto chiuso

Data della firma CE 3 Agosto 2022

Data di avvio 1 Ottobre 2022

Data di completamento 30 Settembre 2025

Finanziato da

• Widening participation and spreading excellence

Costo totale

€ 1 489 379,25

Contributo UE

€ 1 489 379,00

Coordinato da

ERATOSTHENES CENTRE OF EXCELLENCE
Cyprus

CORDIS fornisce collegamenti ai risultati finali pubblici e alle pubblicazioni dei progetti ORIZZONTE.

I link ai risultati e alle pubblicazioni dei progetti del 7° PQ, così come i link ad alcuni tipi di risultati specifici come dataset e software, sono recuperati dinamicamente da .OpenAIRE .

Risultati finali

Websites, patent fillings, videos etc. (1)

AI-OBSERVER project’s website and logo

The AI-OBSERVER website, equipped with a security area, will be developed and maintained by CLK in close collaboration with the coordinator, with the participation of all partners. It will provide an overview of the project, promote project’s objectives, dissemination activities, e-newsletters, and results to wider audiences. A project logo will also be created by CLK.

Documents, reports (4)

Dissemination and exploitation plan

A report that will present the guidelines for he dissemination and exploitation activities of the project, and will include a set of Key Performance Indicators (KPIs) to assess the achievement of the goals set previously.

Current and emerging trends on AI for EO related research

A state-of-the-art review to identify the most recent advancements in the field of AI for EO and the best practices worldwide for the integration of AI with the research area of Disaster Risk Reduction of the ECoE. Upcoming synergies between AI and EO experts through European and International Space programmes and Agencies, such as ESA, NASA, DLR, and the Copernicus Programme, will be also included.

Quality Assurance plan

A plan for the quality assurance procedure implemented by the Quality Assurance team, consisting of experts in the fields of EO and AI, i.e. Prof. D. Hadjimitsis (ECoE), Dr A. Pagani (DFKI), and Prof. F. Del Frate (UNITOV), for all project deliverables.

Risk assessment and contingency plan

A report, that will include all the potential risks and the respective mitigation actions, will be developed at the project start (M3), and will be frequently updated, throughout the project’s duration, to accommodate all immerging issues, as their occurrence likelihood and/ or impact severity might change.

Data Management Plan (1)

Data Management Plan

A report that will describes the data management life cycle for the data to be collected, processed and/or generated by the project. The DMP will include information on the handling of research data during and after the end of the project; the data that will be collected, processed and/or generated; the methodology that will be applied; the data accessibility, curation and preservation (including after the end of the project).

Pubblicazioni

Peer reviewed articles (4)

A generalized machine learning approach for cost-effective monitoring of irrigation suitability: A demonstration case in El Fahs aquifer (Tunisia)

Autori: Constantinos F. Panagiotou, Charalampos Konstantinou, Anis Chekirbane
Pubblicato in: Groundwater for Sustainable Development, Numero 27, 2024, ISSN 2352-801X
Editore: Elsevier BV
DOI: 10.1016/J.GSD.2024.101324

A Review of Open Remote Sensing Data with GIS, AI, and UAV Support for Shoreline Detection and Coastal Erosion Monitoring

Autori: Demetris Christofi, Christodoulos Mettas, Evagoras Evagorou, Neophytos Stylianou, Marinos Eliades, Christos Theocharidis, Antonis Chatzipavlis, Thomas Hasiotis, Diofantos Hadjimitsis
Pubblicato in: Applied Sciences, Numero 15, 2025, ISSN 2076-3417
Editore: MDPI AG
DOI: 10.3390/APP15094771

Measuring the performance of ant colony optimization algorithms for the dynamic traveling salesman problem

Autori: Michalis Mavrovouniotis*, Maria N. Anastasiadou, Diofantos Hadjimitsis
Pubblicato in: Algorithms, 2023, ISSN 1999-4893
Editore: MDPI Open Access Publishing
DOI: 10.3390/a16120545

Measuring the Performance of Ant Colony Optimization Algorithms for the Dynamic Traveling Salesman Problem

Autori: Michalis Mavrovouniotis, Maria N. Anastasiadou, Diofantos Hadjimitsis
Pubblicato in: Algorithms, Numero 16, 2025, ISSN 1999-4893
Editore: MDPI AG
DOI: 10.3390/A16120545

Conference proceedings (7)

Enhancing disaster risk reduction through artificial intelligence: capitalizing on the capacity building activities of the AI-OBSERVER twinning project

Autori: Marios Tzouvaras, Michalis Mavrovouniotis, Renos Votsis, Kyriaki Fotiou, Eleftheria Kalogirou, Thomaida Polydorou, Gerd Reis, Fabio Del Frate, Lorenzo Giuliano Papale, Giorgia Guerrisi, Diofantos Hadjimitsis
Pubblicato in: Tenth International Conference on Remote Sensing and Geoinformation of the Environment (RSCy2024), 2024
Editore: SPIE
DOI: 10.1117/12.3037135

Empirical Analysis of Oil Spill Detection Methods

Autori: Eleftheria Kalogirou, Michalis Mavrovouniotis, Marios Tzouvaras, Christodoulos Mettas, Evagoras Evagorou, Diofantos Hadjimitsis
Pubblicato in: IGARSS 2024 - 2024 IEEE International Geoscience and Remote Sensing Symposium, 2024
Editore: IEEE
DOI: 10.1109/IGARSS53475.2024.10642731

Enhancing Earth Observation Capabilities of the Eratosthenes Centre of Excellence on Disaster Risk Reduction Through Artificial Intelligence: Introducing the AI-OBSERVER Project

Autori: Marios Tzouvaras, Gerd Reis, Fabio Del Frate, Haris Zacharatos, Diofantos Hadjimitsis
Pubblicato in: IGARSS 2024 - 2024 IEEE International Geoscience and Remote Sensing Symposium, 2024
Editore: IEEE
DOI: 10.1109/IGARSS53475.2024.10640751

Enhancing Earth Observation Capabilities of the ERATOSTHENES Centre of Excellence on Disaster Risk Reduction through Artificial Intelligence: The AI-OBSERVER Horizon Europe Twinning Project

Autori: Marios Tzouvaras*, Kyriacos Themistocleous, Kyriacos Neocleous, Gerd Reis, Fabio Del Frate, Giovanni Schiavon, Haris Zacharatos, Eleftheria Kouppari and Diofantos G. Hadjimitsis
Pubblicato in: Ninth International Conference on Remote Sensing and Geoinformation of Environment (RSCy2023), 2023, ISBN 978-9963-697-44-1
Editore: RSCy2023-SPIE

Estimation of crop yield using deep learning for precision agriculture

Autori: Stelios P. Neophytides, Giorgia Guerissi, Michalis Mavrovouniotis, Marios Tzouvaras, Fabio Del Frate, Diofantos G. Hadjimitsis
Pubblicato in: Tenth International Conference on Remote Sensing and Geoinformation of the Environment (RSCy2024), 2024
Editore: SPIE
DOI: 10.1117/12.3037319

Prediction of Groundwater Salinization Using Particle Swarm Optimization for Neural Network Training

Autori: Stelios P. Neophytides, Michalis Mavrovouniotis, Constantinos F. Panagiotou, Marinos Eliades, Anis Chekirbane, Diofantos Hadjimitsis
Pubblicato in: IGARSS 2024 - 2024 IEEE International Geoscience and Remote Sensing Symposium, 2024
Editore: IEEE
DOI: 10.1109/IGARSS53475.2024.10641861

An Empirical Study of Regression Algorithms for Soil Organic Matter Prediction

Autori: Eleni Neofytou, Stelios P. Neophytides, Michalis Mavrovouniotis, Marinos Eliades, Christiana Papoutsa, Diofantos G. Hadjimitsis
Pubblicato in: IGARSS 2024 - 2024 IEEE International Geoscience and Remote Sensing Symposium, 2024
Editore: IEEE
DOI: 10.1109/IGARSS53475.2024.10642115