Aggregate Farming in the Cloud: The AFarCloud ECSEL projectShow others and affiliations
2020 (English)In: Microprocessors and microsystems, ISSN 0141-9331, E-ISSN 1872-9436, Vol. 78, article id 103218Article in journal (Refereed) Published
Abstract [en]
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. © 2020 The Author(s)
Place, publisher, year, edition, pages
Elsevier B.V. , 2020. Vol. 78, article id 103218
Keywords [en]
Autonomous and semi-autonomous vehicles, Autonomy and cooperation, Crop monitoring, Cyber-physical systems, Farming robots, Livestock management, Smart & precision farming, Aggregates, Agricultural robots, Animals, Cost effectiveness, Decision making, Embedded systems, Health risks, Productivity, Real time systems, Veterinary medicine, Wages, Animal health, Crop properties, Distributed platforms, Domain specific, Economic challenges, Farm management, Labor shortages, Real-time data mining, Data mining
National Category
Natural Sciences
Identifiers
URN: urn:nbn:se:ri:diva-46785DOI: 10.1016/j.micpro.2020.103218Scopus ID: 2-s2.0-85089063670OAI: oai:DiVA.org:ri-46785DiVA, id: diva2:1460647
Note
Funding details: Electronic Components and Systems for European Leadership, ECSEL, 783221; Funding text 1: 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] .
2020-08-242020-08-242023-05-16Bibliographically approved