Smart-AKIS – European Agricultural Knowledge and Innovation Systems (AKIS) towards innovation-driven research in Smart Machines and Systems, H2020-ISIB-2014-1


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The main objective of the Smart-AKIS Thematic Network is to foster the effective exchange between all relevant actors in the value chain, communicate and disseminate direct applicable solutions to close the research and innovation divide for the use of Smart Machines and Systems (SFTs) in crop, livestock and forestry production in Europe. Smart-AKIS will use a “Multi Actor Approach”, including in the partnership researchers, extension services, farmers organizations and industrial partners. Through covering a wide range of the European AKIS typologies, Smart-AKIS will leverage on their differences in order to better capture their innovation capacities and processes in the field of SFTs.

Smart-AKIS will collect existing knowledge and best practices related to SFT and will facilitate the use of results through the production of easily accessible end-user material under the EIP-Agri common format. The project will also: i) integrate the technological and socio-economic aspects involved in the innovation processes, by assessing farmers needs and interests, the factors affecting adoption and the identification of best practices; ii) enable researchers, extensions services and practitioners to assess SFT solutions, including online assessment; iii) foster interactive collaboration, through the use of open innovation methods in multi-actor workshops; iv) facilitate communication and knowledge sharing and exchange through the use of an ad-hoc designed interactive Platform.

Smart-AKIS will establish a direct communication with the EIP-Agri to maximize the impact of the project activities and the stakeholder mobilization achieved. The project will serve many future OGs as it lies across the primary sector. The Smart- AKIS Platform will be compatible with the EIP-SP in order to ensure long term accessibility of results.

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commission-cl The project leading to this application has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 696294.