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Transforming Agriculture through robotics, AI, and augmented reality

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AGRO-WELL

Agricultural Robotics and Augmented Reality for Workplace Enhancement and Labor Linkage

AGRO-WELL follows a highly interdisciplinary approach to enhance knowledge for technological transitions towards an environmentally, economically, and socially sustainable agricultural sector. It brings together leading scientists from a multitude of OSH-related disciplines, various regions across Europe, key technology providers and farmer representatives.

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The project will assess farmer needs and explore ways to increase awareness with respect to smart farming. AGRO-WELL builds on five technologies to leverage the potential of robotics, augmented reality, and artificial intelligence to enhance working conditions and farm safety, enable faster and better-informed farm management decisions, and reduce the environmental impact of four different farming systems. Potential effects of the technologies will be multidimensionally assessed. To support market uptake, AGRO-WELL will design and explore the viability of business models based on novel technologies that are predominantly focused on improving OSH. To support other promising technologies, AGRO-WELL will incorporate an open technology competition enabled by cascade funding. All project results will be synthesized in effective dissemination strategies and meaningful policy recommendations to foster promising technological solutions and sustainable business models.

Cutting-Edge Research

Trustworthy Collaborations

Expertise in European Projects

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Project coordination

 

Technical University of Munich
Professor Johannes Sauer
Dr. Fabian Frick


Contact Emails

 

agro-well.pur@mgt.tum.de
fabian.frick@tum.de

Key facts

 

Call: HORIZON-CL6-2024-GOVERNANCE-01
Type of action: Horizon Europe Research and Innovation Actions
Duration: November 2024 - October 2029 (60 months)
Consortium: 13 partners across 7 countries
Coordinator: Technical University of Munich
Total budget: €4,998,670 

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The AGRO-WELL project has received funding from the European Union’s Horizon Europe research and innovation programme under grant agreement No 101182923.

Funded by the European Union. Views and opinions expressed are however those of the author(s) only and do not necessarily reflect those of the European Union or the European Research Executive Agency (REA). Neither the European Union nor the granting authority can be held responsible for them.

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