Objective
GATES will develop a serious game-based training platform, in order to train professionals across the agricultural value chain on the use of Smart Farming Technologies (SFT), thus allowing deploying its full economic and environmental potential in European agriculture.
The positive impact on the adoption of Smart Farming Technologies (SFT) in crop farming has been well established for the last 10 years. In fact, many SFT are available at present time, but farmers find it difficult to grasp which are the technologies that can be used and furthermore, which are the productivity and environmental benefits brought by their adoption. Likewise, SFT companies face barriers in the commercialization of their equipment due to the lack of knowledge and training of the farmer community.
GATES provides the farmer community, agronomical students, extension services and the SFT industry sales force an easy to use and understand gaming experience that will allow a first approach to the concept of SFT, their uses, available equipment and simulation on the adoption of such technologies.
GATES will develop a near-to-market (TRL7) serious game-based training platform that, through the use of a range of gaming technologies (3D scenarios, interactive storytelling, modeling and data), will train professionals and other stakeholders in the value chain in the use of SFT. GATES will develop a cross-platform (Desktop/Mobile/Web) serious gaming available for Android, iOS and Windows featuring online and offline synchronized modes.
GATES will represent a successful example on the use of serious gaming as a training tool, applicable on formal and informal educational settings, on a complex and multidisciplinary subject such as SFT, benefitting from serious gaming capabilities such as virtual environments and worlds, personalized tutorial tools, competition between peers, wide personalization to real life and simulated case scenarios, etc.
Fields of science
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques.
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques.
- engineering and technologyelectrical engineering, electronic engineering, information engineeringinformation engineeringtelecommunicationsradio technologyradar
- agricultural sciencesagriculture, forestry, and fisheriesagriculture
- engineering and technologyelectrical engineering, electronic engineering, information engineeringelectronic engineeringrobotics
- engineering and technologyenvironmental engineeringenergy and fuels
- natural sciencescomputer and information sciencesinternetworld wide web
Programme(s)
Funding Scheme
IA - Innovation actionCoordinator
118 55 ATHINA
Greece