Project information

Name
783221 AFarCloud
Period
Sep 2018 - Aug 2021
Call
ECSEL-JU 2017
Total Partners
60
Members in Project
40
Website
No website
EU Funding
9,35 M Euro

Farming is facing many economic challenges in terms of productivity and cost-effectiveness, as well as an increasing labour shortage partly due to depopulation of rural areas. Reliable detection, accurate identification and proper quantification of pathogens affecting both plant and animal health, must be kept under control to reduce unnecessary costs, trade disruptions and even human health risks. AFarCloud addresses the urgent need for a holistic and systematic approach. It will provide a distributed platform for autonomous farming, which will allow the integration and coop...

Farming is facing many economic challenges in terms of productivity and cost-effectiveness, as well as an increasing labour shortage partly due to depopulation of rural areas. Reliable detection, accurate identification and proper quantification of pathogens affecting both plant and animal health, must be kept under control to reduce unnecessary costs, trade disruptions and even human health risks. AFarCloud addresses the urgent need for a holistic and systematic approach. It will provide a distributed platform for autonomous farming, which will allow the integration and cooperation of Cyber Physical Systems in real-time for increased agriculture efficiency, productivity, animal health, food quality and reduced farm labour costs. This platform will be integrated with farm management software and will support monitoring and decision-making, based on big data and real time data mining techniques. AFarCloud also aims to make farming robots accessible to more users by enabling farming vehicles to work in a cooperative mesh, opening up new applications and ensuring re-usability, as various standard vehicles can combine their capabilities in order to boost farming efficiency. The achievements from AFarCloud will be showcased in early laboratory trials and holistic demonstrators, including cropping and livestock management scenarios. Local demonstrators and validate project results in relevant environments located in different European regions. AFarCloud outcomes will strenghten partners' market position, boosting their innovation capacity and addressing industrial needs both at EU and international levels. The consortium represents the whole ICT-based farming solutions’ value chain, including all key actors needed for the development, demonstration and future market uptake of the precision farming framework targeted in the project.

Project leader

Name
José-Fernán Martínez-Ortega
Organisation
Universidad Politécnica, Madrid
Country
Spain

Project partners