Aggregate Farming in the Cloud: The AFarCloud ECSEL project: The AFarCloud ECSEL project
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2020-10
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Abstract
Farming is facing many economic challenges in terms of productivity and cost-effectiveness. Labor shortage partly due to depopulation of rural areas, especially in Europe, is another challenge. Domain specific problems such as accurate monitoring of soil and crop properties and animal health are key factors for minimizing economical risks, and not risking human health. The ECSEL AFarCloud (Aggregate Farming in the Cloud) project 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 labor costs. Moreover, such a platform can be integrated with farm management software to support monitoring and decision-making solutions based on big data and real-time data mining techniques.
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Publisher Copyright: © 2020 The Author(s)
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Cyber-physical systems , Smart & precision farming , Livestock management , Crop monitoring , Autonomy and cooperation , Autonomous and semi-autonomous vehicles , Farming robots , Cyber-physical systems , Smart & precision farming , Livestock management , Crop monitoring , Autonomy and cooperation , Autonomous and semi-autonomous vehicles , Farming robots , Software , Hardware and Architecture , Computer Networks and Communications , Artificial Intelligence , SDG 2 - Zero Hunger , Project ID , info:eu-repo/grantAgreement/EC/H2020/783221/EU/Aggregate Farming in the Cloud/AFarCloud , info:eu-repo/grantAgreement/EC/H2020/783221/EU/Aggregate Farming in the Cloud/AFarCloud , Funding Info , A special thanks to all the AFarCloud consortium people that have worked on the AFarCloud proposal on which this paper is based on. The AFarCloud project is funded from the ECSEL Joint Undertaking under grant agreement n◦783221, and from several National funding agencies. It is worth noting some ECSEL projects that have provided background and/or reusable results taken into account in AFarCloud: MegaM@rt2 [34], SafeCOP [35], and AQUAS [36]. , A special thanks to all the AFarCloud consortium people that have worked on the AFarCloud proposal on which this paper is based on. The AFarCloud project is funded from the ECSEL Joint Undertaking under grant agreement n◦783221, and from several National funding agencies. It is worth noting some ECSEL projects that have provided background and/or reusable results taken into account in AFarCloud: MegaM@rt2 [34], SafeCOP [35], and AQUAS [36].
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Castillejo , P , Johansen , G , Cürüklü , B , Bilbao-Arechabala , S , Fresco , R , Martinez-Rodriguez , B , Pomante , L , Rusu , C , Martínez-Ortega , J-F , Centofanti , C , Hakojärvi , M , Santic , M & Häggman , J 2020 , ' Aggregate Farming in the Cloud: The AFarCloud ECSEL project : The AFarCloud ECSEL project ' , Microprocessors and Microsystems , vol. 78 , 103218 , pp. 103218 . https://doi.org/10.1016/j.micpro.2020.103218