Accelerating the achievement of EU Green Deal Goals for pesticide and fertilizer reduction through AI, data and robotic technologies.

Informazioni relative al progetto

Smart Droplets

ID dell’accordo di sovvenzione: 101070496

DOI

10.3030/101070496

Progetto chiuso

Data della firma CE 14 Giugno 2022

Data di avvio 1 Settembre 2022

Data di completamento 28 Febbraio 2026

Finanziato da

• Digital, Industry and Space

Costo totale

€ 3 175 475,25

Contributo UE

€ 2 998 370,00

Coordinato da

GEOPONIKO PANEPISTIMION ATHINON
Greece

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

Documents, reports (7)

Dissemination, communication and exploitation plan and reports v2

The main reference for communication activities with guidelines for partners to disseminate and exploit results Also includes an action plan on the planned liaisons with complementary AI Data and Robotics initiatives

Dissemination, communication and exploitation plan and reports v3

The main reference for communication activities, with guidelines for partners to disseminate and exploit results. Also includes an action plan on the planned liaisons with complementary AI, Data and Robotics initiatives.

Dissemination, communication and exploitation plan and reports v1

The main reference for communication activities with guidelines for partners to disseminate and exploit results Also includes an action plan on the planned liaisons with complementary AI Data and Robotics initiatives

Smart Droplets Academy - Program, Timeline & Activities v1

Work plan on training activities includes the production of learning kits and recorded video content

Reference Architectures and Resources Mapping

Report on reference architectures, common resources and prospective links with other AI, Data and Robotics projects and initiatives

Industry Needs & Requirements Analysis v2

Assessment report on industry needs, incl. mapping of requirements and metrics/ KPIs that relate to the use case implementation. Output of T2.1, T2.2.

Industry Needs & Requirements Analysis v1

Assessment report on industry needs, incl. mapping of requirements and metrics/ KPIs that relate to the use case implementation. Output of T2.1, T2.2

Pubblicazioni

Peer reviewed articles (4)

Adaptive fertilizer management for optimizing nitrogen use efficiency with constrained reinforcement learning

Autori: Hilmy Baja, Michiel G.J. Kallenberg, Herman N.C. Berghuijs, Ioannis N. Athanasiadis
Pubblicato in: Computers and Electronics in Agriculture, Numero 237, 2025, ISSN 0168-1699
Editore: Elsevier BV
DOI: 10.1016/J.COMPAG.2025.110554

Interoperable agricultural digital twins with reinforcement learning intelligence

Autori: Michiel Kallenberg, Hilmy Baja, Mihailo Ilić, Aleksandar Tomčić, Milenko Tošić, Ioannis Athanasiadis
Pubblicato in: Smart Agricultural Technology, Numero 12, 2025, ISSN 2772-3755
Editore: Elsevier BV
DOI: 10.1016/J.ATECH.2025.101412

Nitrogen management with reinforcement learning and crop growth models

Autori: Michiel G.J. Kallenberg, Hiske Overweg, Ron van Bree and Ioannis N. Athanasiadis
Pubblicato in: Environmental Data Science, 2023, ISSN 2634-4602
Editore: Cambridge University Press.
DOI: 10.1017/eds.2023.28

To Measure or Not: A Cost-Sensitive, Selective Measuring Environment for Agricultural Management Decisions with Reinforcement Learning

Autori: Hilmy Baja, Michiel Kallenberg, Ioannis N. Athanasiadis
Pubblicato in: Proceedings of the AAAI Conference on Artificial Intelligence, Numero 39, 2025, ISSN 2374-3468
Editore: Association for the Advancement of Artificial Intelligence (AAAI)
DOI: 10.1609/AAAI.V39I27.34999

Conference proceedings (4)

Integrating processed-based models and machine learning for crop yield prediction

Autori: Michiel G.J. Kallenberg, Bernardo Maestrini, Ron van Bree, Paul Ravensbergen, Christos Pylianidis, Frits van Evert, Ioannis N. Athanasiadis
Pubblicato in: Workshop on Synergy of Scientific and Machine Learning Modeling, International Conference on Machine Learning, 2023, ISSN 2331-8422
Editore: ArXiv.org
DOI: 10.48550/arXiv.2307.13466

Learning Long-Term Crop Management Strategies with CyclesGym

Autori: Turchetta, Matteo; Corinzia, Luca; Sussex, Scott; Burton, Amanda; Herrera, Juan; Athanasiadis, Ioannis N.; Buhmann, Joachim M.; Krause, Andreas
Pubblicato in: ISBN: 9781713871088, 2022

Interoperability as an Enabler for Digital Twin Based Decision Making in Smart Agriculture

Autori: M. Ilić; M. Tošić; A. Tomčić
Pubblicato in: 2025 48th ICT and Electronics Convention (MIPRO), 2025
Editore: IEEE (in cooperation with MIPRO — Croatian Society MIPRO, Rijeka/Opatija, Croatia)

Leveraging Behavior Trees for Hybrid Autonomous Navigation in Seasonal Agricultural Environments

Autori: Juan Francisco Rascón, Pau Reverté, Xavier Ruiz, Mateus S. Moura, Daniel Serrano, Carlos Rizzo
Pubblicato in: 2024 7th Iberian Robotics Conference (ROBOT), 2024
Editore: IEEE
DOI: 10.1109/ROBOT61475.2024.10797423