ANTONIO Project // ERA-NET ICT-AGRI-FOOD project
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ANTONIO
ICT-AGRI-FOOD Project

Welcome to ANTONIO ERA-NET ICT-AGRI-FOOD project

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ANTONIO project develops a unifying framework to combine different sensor modalities, methods for creating accurate maps to facilitate operations on a narrow scale with a smaller environment footprint, artificial intelligence algorithms for data processing and decision support, and applications to make relevant information easily visible to the farmer.​

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PARTNERS

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Aristotle University of Thessaloniki

Politecnico di Bari​

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Aristotle University of Thessaloniki (AUTH)
​Laboratory for Alternative Energy Sources in Agriculture (AUTH-AESA) [Greece]​​

National Research Council of Italy​

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​​Institute of Intelligent Industrial Technologies and Systems for Advanced Manufacturing - National Research Council of Italy (STIIMA) [Italy]

AgriCirle

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AgriCircle (AC) [Switzerland]

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Politecnico di Bari, Department of Mechanics, Mathematics and Management​ (POLIBA) [Italy]​

Fraunhofer IAIS

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Fraunhofer Institute for Intelligent Analysis and Information Systems IAIS​​ (FRA) [Germany]

The framework of ANTONIO project is demonstrated in the field through the integration onboard of unmanned ground and aerial robots and it is implemented to be compatible with AgriCircle’s farm management information system (FMIS), which enables map-based control of many application devices & displayed via standard tablet PCs.

Overall goal of ANTONIO project

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The overall goal of ANTONIO project is the development and implementation of multi-sensor systems and s ensor processing algorithms to enable agri-robots to perform plant phenotyping and precision agriculture tasks, such as precise local application of pesticides/fertilizers and yield estimation. 
The envisaged idea is based on an integrated sensor network, including mobile sensors mounted on board of ground robots and drones. Information coming from the fixed sensing devices will flag “attention spots” in the crop for further local investigation by the robotic platforms.
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ANTONIO

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This project has received funding from the European Union's Horizon 2020 research and innovation programme ​under grant agreement no 862665 ICT-AGRI-FOOD. 

Funded by:
  • GSRT, Greece
  • MIPAAF, Italy
  • BMBF, Germany
  • FOAG, Switzerland

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