Smart Farming can be seen as the use of sensing technology and digitalization in agriculture to atomize, guide and optimize management and agricultural activities for crops and livestock production through the wide analysis and capitalization of collected information and data.
Precision agriculture (PA) is an important aspect of smart farming and can be defined as a management strategy that gathers, processes and analyzes temporal, spatial and individual data and combines it with other information to support management decisions according to estimated variability for improved resource use efficiency, productivity, quality, profitability and sustainability of agricultural production.
In practice PA typically, but not necessarily, relies heavily on new technologies and digitalization. Especially positioning systems, sensor technologies, automation, robotics and digitized auxiliary data like elevation models, weather data, soil unit mapping and satellite data.
The main challenge for EU agriculture will be its ability to ensure a high level of production while improving the protection of natural resources
Decisions on pesticides, such as the directive 2009/128/EC or the last changes in the CAP Greening resolutions show the will of the European Community to change for a more environment-friendly agriculture, while keeping high levels of production. PA can answer these two issues by providing a way to reduce the use of agricultural inputs: a competitiveness gain (less inputs for the same production level) and an environmental gain (less fuel and crop protection agents).
Our program aims at answering these issues, through the following specific objectives by:
Our project closely involves business partners from various areas of the Smart Farming industry and local authorities. Thanks to this cooperation, we are able to help define the immediate future of the industry and better train students for the reality of the job market. The hands-on experience gained working directly with international leaders of the Smart Farming industry gives students who participate in our program a distinct advantage in the workforce.
Our Smart Farming program is focused on using new technology in Crop Production. The purpose of this project is to raising students’ awareness of new technologies and teach them how to use them in order to meet industry need for these skills. Going from sensors to robotics by way of information processing, we aim to help students develop the transdisciplinary skills needed to work in Precision Agriculture.
In this project, we have tried to identify complementary expertise at each partner institution, to cover the different key points of PA. Each partner will therefore bring its very specific knowledge and experience in a specialization useful for this project: teledetection, GIS, robotics, mechatronics, plant science, etc. Each partner has been identified for its particular expertise and the added-value that he/she would bring to the project and its content:
UTAD Portugal is a specialist in GIS, Teledetection and e-learning. Their principal studies deal with southern crops (viticulture).
NMBU Norway focuses particularly on robotics and their application in crops.
SLU Sweden deals with sensors and image analysis, particularly on northern crop systems.
University of Helsinki, Finland, focuses on the automation, systems technology and modelling, applied to northern crop systems.
University of Liège – Gembloux Agrobiotech, Belgium will offer a broad range of skills with modelling and geo-statistics, mechatronics and remote sensing. They are specialists on Central Europe crop systems.
Perrotis College, Greece deals with remote sensing and computerized farm machinery applied to southern crops such as viticulture and olive trees.
ISA Lille – Yncréa Hauts-de-France has expertise in crop systems, robotics and GIS. It also has a solid experience in innovative teaching methods (co-design projects and active learning).
The principle teaching modalities are:
Students will be evaluated through their project work.
The principle objectives and subject areas are:
