In the span of 48 months, SOSFood aims to design, develop and validate data-driven AI-based tools that can help all actors along the food supply chain to make evidence-based sustainable decisions, through the identification of those causal factors conditioning the sustainability of their activities and offering specific suggestions for its improvement.

  • Co-create a multi-actor and social innovation approach aiming to
  • Analyze the needs and expectations of all food system stakeholders to improve sustainability;
  • Explore the existing private data sharing system in the food supply chain;
  • Ensure the solutions proposed will adapt to each stakeholder;
  • Design a framework to measure and weight impacts of the food system on sustainability dimensions, using
  • Methods and metrics approaches for the interaction among the defined systems;
  • New factors and interactions derived from applying AI for a dynamic multimodal impact analysis.

  • Develop new predictive and clustering analysis methods based on machine learning (ML) able to identify and predict the evolution of those relevant factors with a significant impact on the sustainability of each actor of the food system, and develop new digital twins to predict and optimize the relevant sustainability indicators from a multi-stakeholder perspective.
  • Develop and implement data-driven decision-making tools for nutritional and sustainable food systems as a complement to the data spaces available to food system actors.
  • Validate the innovation of the project through different agri-food systems representing the disparities of the European territories and demonstration of further applicability in other communities.
  • Maximize the impact of the project through dissemination, communication and exploitation activities.