Big data solutions for big farming challenges

Vast volumes of data from satellites in space, drones in the air and sensors on the ground will be harnessed by a pioneering EU-funded project that promises to revolutionise farming, land use, agricultural sustainability and food security.

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Countries
Countries
  Algeria
  Argentina
  Australia
  Austria
  Bangladesh
  Belarus
  Belgium
  Benin
  Bolivia
  Bosnia and Herzegovina
  Brazil
  Bulgaria
  Burkina Faso
  Cambodia
  Cameroon
  Canada
  Cape Verde
  Chile
  China
  Colombia
  Costa Rica
  Croatia
  Cyprus
  Czechia
  Denmark
  Ecuador
  Egypt
  Estonia
  Ethiopia
  Faroe Islands
  Finland
  France
  French Polynesia
  Georgia


 

Published: 19 September 2018  
Related theme(s) and subtheme(s)
Agriculture & foodAgriculture  |  Food safety & health risks
Bioeconomy
EnvironmentEarth Observation  |  Ecosystems, incl. land, inland waters, marine  |  Land management  |  Sustainable development
Innovation
Research policyHorizon 2020
SMEs
Countries involved in the project described in the article
Austria  |  Czechia  |  France  |  Germany  |  Greece  |  Spain  |  Switzerland
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Big data solutions for big farming challenges

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© scharfsinn86 #161252993, 2018 fotolia.com

Big data offers enormous opportunities for improved and more sustainable agriculture.

The EU-funded EUXDAT initiative will use the technological infrastructure needed by farmers, scientists and public authorities to take advantage of its potential.

The EUXDAT e-infrastructure will serve as a cloud and high-performance computing front end through which a multitude of data, analytics and computational resources can be accessed to monitor soil and crop health, optimise resource consumption, increase agricultural yields and sustainably manage land.

The project – led by digital services network Atos in Spain and involving industrial and research partners across Europe – will showcase its solutions through three pilot applications focused on sustainable agriculture and development. These will highlight how farmers and decision-makers can use real-time actionable intelligence by combining and analysing Earth observation data from satellites, meteorological information from robotic sensors in fields, and images from unmanned aerial vehicles.

Deep-learning algorithms being developed by the EUXDAT team would, for instance, enable robotic agricultural machines to intervene in fields where needed, re-establishing nutritional balance in the soil, eliminating weeds or restoring crop health. This targeted approach would reduce the need for environmentally harmful pesticides and fertilisers.

The project team will also investigate monitoring, predictive analytics and machine-learning solutions to improve energy efficiency and water use in agriculture. Furthermore, it will investigate ways to harness 3D imaging technologies to better manage the placement and distribution of crops, prevent soil erosion and mitigate nutrient run-off that has a devastating impact on aquatic ecosystems.

By working closely with scientific and agricultural communities and building solutions on top of existing technologies, the EUXDAT consortium aims to ensure its e-infrastructure will be cost-effective and commercially viable, opening pathways for end-users to develop their own innovative applications to drive sustainable agriculture and development.

Project details

  • Project acronym: EUXDAT
  • Participants: Spain (Coordinator), France, Germany, Czechia, Greece, Austria, Switzerland
  • Project N°: 777549
  • Total costs: € 2 999 062,50
  • EU contribution: € 2 999 062,50
  • Duration: November 2017 to October 2020

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