Objectives
To tackle the current environmental challenges, the new SOSFood (Sustainability Optimization for Secure Food Systems) project funded under Horizon Europe programme will accelerate the green transition of EU food systems by using the great potential of artificial intelligence technologies.
The main objective in the span of 48 months is to support all stakeholders of the food chain to make well-informed decisions with a holistic approach, enabling more productive, inclusive, sustainable, and resilient food systems.
Despite various efforts to address such aspects as reducing waste, promoting eco-friendly farming and local food products, improving unhealthy diets in the population, optimizing manufacturing and distribution, etc., none have fully grasped the global scale of the issue. Additionally, existing strategies have often been too complex or inaccessible to make significant impacts.
SOSFood seeks to change the situation by bringing together a diverse consortium of experts from the private and public sectors, academia, research, and industries, including consumers and producers. They will collaborate aiming to establish a multi-actor network that promotes transparency and data sharing; map the food system with a multidimensional strategy; co-design tailored decision-making tools that empower every stakeholder in the food chain.
To ensure the effectiveness and viability of the project, the project will undergo validation in three case studies at regional, metropolis, and national levels in Galicia, Athens, and Lithuania, respectively.
SOSFood officially kicked-off on March 1st, 2024, in Santiago de Compostela, Spain, bringing together all 17 partners from across Europe. Besides the event hosting country, the Netherlands, Italy, Portugal, Lithuania, Greece, France, and Belgium are in the project’s multidisciplinary consortium. For further information about the project, please visit our website.
The added value of data will be a key factor in the new international research project funded by the 'Horizon Europe' program, with which the EU strengthens its strategy to address the crisis in the agri-food sector with with new analysis methods and algorithms developed by the project. According to estimates from the Food and Agriculture Organization (FAO) of the United Nations, "by 2050, it will be necessary to produce 60% more food to feed a global population of 9.3 billion people" […]. Achieving this with traditional agriculture would impose a heavy burden on our natural resources. Thus, we have no choice but to embark on a more ecological revolution" […].
Softeam Role in the project:
Softeam will manage the project DataLake in particular for our three case studies in three different European scenarios: Galicia (representing a regional scope); Athens (a metropolitan scope); and Lithuania (a national scope),
Key facts and figures
Project acronym
SOSFood
Full title
Sustainability Optimization for Secure Food Systems
Project number
101134894
Funding source
Horizon Europe, call HORIZON-CL6-2023-GOVERNANCE-01
Coordinator
Universidade de Vigo (UVIGO), Spain
Start date
1 February 2024
End date
31 January 2028
Duration
48 months
Total budget / EU contribution
EUR 3,954,196.25
Web Site: sosfood-project.eu
Start Date: 1st January 2024
End Date: 31st December 2027
In response to the current environmental emergency, SOSFood uses data exploitation and AI-based technologies to build a holistic and comprehensive picture of the EU food system. The project develops tailored predictive tools to support well-informed decisions for all stakeholders of the food chain, following a multi-factorial, multi-actor and multi-scale approach. The consortium brings together experts from the private and public sectors, academia, and food system representatives, including consumers, producers and industries.
SOSFood aims to help industries improve the sustainability of food production, treatment and waste management, and to help consumers make better dietary decisions by increasing information on the eco-healthy fingerprint of food products.
Provide a holistic and comprehensive image of the EU food system.
Develop AI-based predictive tools to support decision-making across the food chain.
Build a consolidated food data space focused on sustainability and health.
Help industries improve sustainability in production, treatment and waste management.
Help consumers make more informed, eco-healthy dietary choices.
Validate tools through pilot case studies in Galicia (Spain), Lithuania and Athens Metropolis (Greece).
The consortium includes 17 participants (16 partners plus 1 affiliated entity) from 8 countries.
No. Short name Organisation Country
1 UVIGO Universidade de Vigo (Coordinator) Spain
2 USC Universidade de Santiago de Compostela Spain
3SRU Stichting Radboud Universiteit Netherlands
4 UNIFE Universita degli Studi di Ferrara Italy
4.1 UCSC Universita Cattolica del Sacro Cuore (Affiliated Entity) Italy
5 UNL Universidade Nova de Lisboa Portugal
6 DIH DATAlife DIH DATAlife, European Digital Innovation Hub
Spain
7 AFL Agrifood Lithuania DIH Lithuania
8 SAH Smart Agro Hub Anonymi Etairia Greece
9 SOFTEAM Softeam France
10 JIBE JIBE company BV Netherlands
11 CTA Contactica SL Spain
12 CUEVAS Ignacio de las Cuevas SA (Grupo Cuevas) Spain
13 VKA Vikonda Grupe, UAB Lithuania
14 JOTIS Yiotis Anonimos Emporiki and Viomixaniki Etaireia Greece
15 EURO COOP Communaute Europeenne des Cooperatives de Consommateurs Belgium
16 AGADER Axencia Galega de Desenvolvemento Rural Spain
Full descriptions of each partner are available on the official Participants page.
SOSFood publishes project news, event recaps and press releases on its official website. The launch press release and the full news archive are linked below.
SOSFood project launches to transform EU food systems with AI innovation (launch press release)
Website: https://sosfood-project.eu/
Objectives: https://sosfood-project.eu/objectives/
Results: https://sosfood-project.eu/results/
Contacts: https://sosfood-project.eu/contacts/
Zenodo community: https://zenodo.org/communities/sosfood/
This project has received funding from the European Union's Horizon Europe research and innovation programme under Grant Agreement No. 101134894. Views and opinions expressed are those of the author(s) only and do not necessarily reflect those of the European Union or the European Research Executive Agency (REA). Neither the European Union nor the granting authority can be held responsible for them.