Artificial Intelligence (AI) represents a collection of tools and methodologies that have the potential to revolutionise various aspects of human activity. Earth observation (EO) data, including satellite and in-situ, are essential in a number of high impact applications, ranging from security and energy to agriculture and health. In this paper, we present the AI4Copernicus framework for bridging the two domains within the European context to enable data-centred innovation. In order to achieve this goal, AI4Copernicus has developed and enriches the European AI-on-demand platform with a number of application bootstrapping services and tools to accelerate uptake and innovation, whilst it provides integration over AI-on-Demand services and the Copernicus ecosystem, targeting the highly successful Data and Information Access Service (DIAS) Cloud platforms. More specifically, by employing procedures for onboarding and validating models and tools, and by utilising a host of meticulously reviewed and supervised open calls-enabled projects, and containerisation best-practices, AI4Copernicus deployed and made available several products on DIAS platforms. Moreover, these products and resources have been made available on the AI-on-Demand platform catalogue for discovery, use and further development. The AI4Copernicus framework is being used by a number of business-driven projects and SMEs spanning several application domains. This article provides an overview of the European AI and EO context as well as the AI4Copernicus technological framework and tools offered. Further, we present real world use-cases as well as a community-centred evaluation of our framework based on usage and feedback received from several projects.

European AI and EO convergence via a novel community-driven framework for data-intensive innovation / Troumpoukis, Antonis; Klampanos, Iraklis; Pantazi, Despina-Athanasia; Albughdadi, Mohanad; Baousis, Vasileios; Barrilero, Omar; Bojor, Alexandra; Branco, Pedro; Bruzzone, Lorenzo; Chietera, Andreina; Fournand, Philippe; Hall, Richard; Lazzarini, Michele; Luna, Adrian; Nousias, Alexandros; Perentis, Christos; Petrakis, George; Punjani, Dharmen; Robl, David; Stamoulis, George; Tsalapati, Eleni; Urbanaviciute, Indre; Weikmann, Giulio; Ziouvelou, Xenia; Ziolkowski, Marcin; Koubarakis, Manolis; Karkaletsis, Vangelis. - In: FUTURE GENERATION COMPUTER SYSTEMS. - ISSN 0167-739X. - 160:(2024), pp. 505-521. [10.1016/J.FUTURE.2024.06.013]

European AI and EO convergence via a novel community-driven framework for data-intensive innovation

Bruzzone, Lorenzo;Perentis, Christos;Weikmann, Giulio;
2024-01-01

Abstract

Artificial Intelligence (AI) represents a collection of tools and methodologies that have the potential to revolutionise various aspects of human activity. Earth observation (EO) data, including satellite and in-situ, are essential in a number of high impact applications, ranging from security and energy to agriculture and health. In this paper, we present the AI4Copernicus framework for bridging the two domains within the European context to enable data-centred innovation. In order to achieve this goal, AI4Copernicus has developed and enriches the European AI-on-demand platform with a number of application bootstrapping services and tools to accelerate uptake and innovation, whilst it provides integration over AI-on-Demand services and the Copernicus ecosystem, targeting the highly successful Data and Information Access Service (DIAS) Cloud platforms. More specifically, by employing procedures for onboarding and validating models and tools, and by utilising a host of meticulously reviewed and supervised open calls-enabled projects, and containerisation best-practices, AI4Copernicus deployed and made available several products on DIAS platforms. Moreover, these products and resources have been made available on the AI-on-Demand platform catalogue for discovery, use and further development. The AI4Copernicus framework is being used by a number of business-driven projects and SMEs spanning several application domains. This article provides an overview of the European AI and EO context as well as the AI4Copernicus technological framework and tools offered. Further, we present real world use-cases as well as a community-centred evaluation of our framework based on usage and feedback received from several projects.
2024
Troumpoukis, Antonis; Klampanos, Iraklis; Pantazi, Despina-Athanasia; Albughdadi, Mohanad; Baousis, Vasileios; Barrilero, Omar; Bojor, Alexandra; Bran...espandi
European AI and EO convergence via a novel community-driven framework for data-intensive innovation / Troumpoukis, Antonis; Klampanos, Iraklis; Pantazi, Despina-Athanasia; Albughdadi, Mohanad; Baousis, Vasileios; Barrilero, Omar; Bojor, Alexandra; Branco, Pedro; Bruzzone, Lorenzo; Chietera, Andreina; Fournand, Philippe; Hall, Richard; Lazzarini, Michele; Luna, Adrian; Nousias, Alexandros; Perentis, Christos; Petrakis, George; Punjani, Dharmen; Robl, David; Stamoulis, George; Tsalapati, Eleni; Urbanaviciute, Indre; Weikmann, Giulio; Ziouvelou, Xenia; Ziolkowski, Marcin; Koubarakis, Manolis; Karkaletsis, Vangelis. - In: FUTURE GENERATION COMPUTER SYSTEMS. - ISSN 0167-739X. - 160:(2024), pp. 505-521. [10.1016/J.FUTURE.2024.06.013]
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11572/464712
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