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ID: 783221

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Lopez Santidrian, M. LourdesParticipanteLana Serrano, SaraParticipanteCastillejo Parrilla, PedroParticipanteRubio Cifuentes, GregorioParticipanteRodriguez Molina, JesusParticipanteBeltran Martinez, Maria VictoriaParticipanteLucas Martinez, NestorParticipanteMartinez Ortega, Jose FernanInvestigador principalHernandez Diaz, VicenteParticipanteSan Emeterio De La Parte, MarioParticipanteMuriel Elduayen, MartaParticipanteWang, YitingParticipante

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Aggregate Farming in the Cloud

Investigadores/as: WANG, YITING (Participante); MURIEL ELDUAYEN, MARTA (Participante); SAN EMETERIO DE LA PARTE, MARIO (Participante); HERNANDEZ DIAZ, VICENTE (Participante); Martinez Ortega, Jose Fernan (Investigador principal (IP)); LUCAS MARTINEZ, NESTOR (Participante); BELTRAN MARTINEZ, MARIA VICTORIA (Participante); RODRIGUEZ MOLINA, JESUS (Participante); Rubio Cifuentes, Gregorio (Participante); CASTILLEJO PARRILLA, PEDRO (Participante); Lana Serrano, Sara (Participante); LOPEZ SANTIDRIAN, M. LOURDES (Participante)

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Resumen

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. Furthermore, reliable detection, accurate identification and proper quantification of pathogens and other factors affecting both plant and animal health, are critical to be kept under control in order to reduce economic expenditures, trade disruptions and even human health risks. AFarCloud will provide a distributed platform for autonomous farming that will allow the integration and cooperation of agriculture Cyber Physical Systems in real-time in order to increase efficiency, productivity, animal health, food quality and reduce farm labour costs. This platform will be integrated with farm management software and will support monitoring and decision-making solutions based on big data and real time data mining techniques. The AFarCloud project also aims to make farming robots accessible to more users by enabling farming vehicles to work in a cooperative mesh, thus opening up new applications and ensuring re-usability, as heterogeneous standard vehicles can combine their capabilities in order to lift farmer revenue and reduce labour costs. The achievements from AFarCloud will be demonstrated in 3 holistic demonstrators (Finland, Spain and Italy), including cropping and livestock management scenarios and 8 local demonstrators (Latvia, Sweden, Spain and Czech Republic) in order to test specific functionalities and validate project results in relevant environments located in different European regions. AFarCloud outcomes will strengthen 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. (Most relevant results)

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