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

Project Information

Smart Droplets

Grant agreement ID: 101070496

DOI

10.3030/101070496

Project closed

EC signature date 14 June 2022

Start date 1 September 2022

End date 28 February 2026

Funded under

• Digital, Industry and Space

Total cost

€ 3 175 475,25

EU contribution

€ 2 998 370,00

Coordinated by

GEOPONIKO PANEPISTIMION ATHINON
Greece

CORDIS provides links to public deliverables and publications of HORIZON projects.

Links to deliverables and publications from FP7 projects, as well as links to some specific result types such as dataset and software, are dynamically retrieved from OpenAIRE .

Deliverables

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

Publications

Peer reviewed articles (6)

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

Author(s): Hilmy Baja, Michiel G.J. Kallenberg, Herman N.C. Berghuijs, Ioannis N. Athanasiadis
Published in: Computers and Electronics in Agriculture, Issue 237, 2025, ISSN 0168-1699
Publisher: Elsevier BV
DOI: 10.1016/J.COMPAG.2025.110554

Interoperable agricultural digital twins with reinforcement learning intelligence

Author(s): Michiel Kallenberg, Hilmy Baja, Mihailo Ilić, Aleksandar Tomčić, Milenko Tošić, Ioannis Athanasiadis
Published in: Smart Agricultural Technology, Issue 12, 2025, ISSN 2772-3755
Publisher: Elsevier BV
DOI: 10.1016/J.ATECH.2025.101412

Causality and Explainability for Trustworthy Integrated Pest Management

Author(s): Ilias Tsoumas, Vasileios Sitokonstantinou, Georgios Giannarakis, Evagelia Lampiri, Christos Athanassiou, Gustau Camps-Valls, Charalampos Kontoes, Ioannis Athanasiadis
Published in: Workshop on Tackling Climate Change with Machine Learning, NeurIPS2023, 2023, ISSN 1049-5258
Publisher: Cornell University / arXiv.
DOI: 10.48550/ARXIV.2312.04343

Domain adaptation with transfer learning for pasture digital twins

Author(s): Pylianidis, C.; Kallenberg, M.G.J.; Athanasiadis, I.N.
Published in: Crossref, 2024, ISSN 2634-4602
Publisher: Cambridge University Press
DOI: 10.1017/EDS.2024.6

Nitrogen management with reinforcement learning and crop growth models

Author(s): Michiel G.J. Kallenberg, Hiske Overweg, Ron van Bree and Ioannis N. Athanasiadis
Published in: Environmental Data Science, 2023, ISSN 2634-4602
Publisher: 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

Author(s): Hilmy Baja, Michiel Kallenberg, Ioannis N. Athanasiadis
Published in: Proceedings of the AAAI Conference on Artificial Intelligence, Issue 39, 2025, ISSN 2374-3468
Publisher: 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

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

Learning Long-Term Crop Management Strategies with CyclesGym

Author(s): Turchetta, Matteo; Corinzia, Luca; Sussex, Scott; Burton, Amanda; Herrera, Juan; Athanasiadis, Ioannis N.; Buhmann, Joachim M.; Krause, Andreas
Published in: ISBN: 9781713871088, 2022

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

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

Leveraging Behavior Trees for Hybrid Autonomous Navigation in Seasonal Agricultural Environments

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