
IGP MIEL ASTURIAS
IGP MIEL ASTURIAS
1 Projects, page 1 of 1
Open Access Mandate for Publications and Research data assignment_turned_in Project2023 - 2026Partners:INTRASOFT International, THE LISBON COUNCIL, DIADIKASIA BUSINESS CONSULTANTS SA, ISEKI-Food Association, LGL +39 partnersINTRASOFT International,THE LISBON COUNCIL,DIADIKASIA BUSINESS CONSULTANTS SA,ISEKI-Food Association,LGL,TEKNOLOGIAN TUTKIMUSKESKUS VTT OY,JRC,HU,UBITECH LIMITED,A. ESPERSEN AS,HERMES AS,CONSEJERIA DE MEDIO RURAL Y COHESION TERRITORIAL DEL PRINCIPADO DE ASTURIAS,ASINCAR,Aprol Umbria,EURONEWS,University of Bayreuth,UCD,ASOCIACION PARA LA PROMOCION YGESTION IGP MIEL DE ASTURIAS,Directorate of Fisheries,INESC TEC,HAME VOCATIONAL INSTITUTE LTD,SLOVENE CONSUMERS ASSOCIATION,European Food Information Resource,UPC,UNIONE NAZIONALE CONSUMATORI,ADVID,SYNELIXIS,CERTH,METRO,DBC EUROPE,SmartAgroHub S.A.,MIGROS TICARET ANONIM SIRKETI,INRAE,CNR,BIOCOS,reframe.food,DECO,SINTEF AS,MRI,IGP MIEL ASTURIAS,BULGARIAN WINE EXPORT ASSOCIATION,Ministry of Trade, Industry and Fisheries,NTUA,University of Veterinary MedicineFunder: European Commission Project Code: 101084265Overall Budget: 9,744,010 EURFunder Contribution: 9,744,010 EURWATSON provides a methodological framework combined with a set of tools and systems that can detect and prevent fraudulent activities throughout the whole food chain thus accelerating the deployment of transparency solutions in the EU food systems. The proposed framework will improve sustainability of food chains by increasing food safety and reducing food fraud through systemic innovations that a) increase transparency in food supply chains through improved track-and-trace mechanisms containing accurate, time-relevant and untampered information for the food product throughout its whole journey, b) equip authorities and policy makers with data, knowledge and insights in order to have the complete situational awareness of the food chain and c) raise the consumer awareness on food safety and value, leading to the adoption of healthier lifestyles and the development of sustainable food ecosystems. WATSON implements an intelligence-based risk calculation approach to address the phenomenon of food fraud in a holistic way. The project includes three distinct pillars, namely, a) the identification of data gaps in the food chain, b) the provision of methods, processes and tools to detect and counter food fraud and c) the effective cross border collaboration of public authorities through accurate and trustworthy information sharing. WATSON will rely upon emerging technologies (AI, IoT, DLT, etc.) enabling transparency within supply chains through the development of a rigorous, traceability regime, and novel tools for rapid, non-invasive, on-the-spot analysis of food products. The results will be demonstrated in 6 use cases: a) prevention of counterfeit alcoholic beverages, b) preservation of the authenticity of PGI honey, c) on-site authenticity check and traceability of olive oil, d) the identification of possible manipulations at all stages of the meat chain, e) the improved traceability of high-value products in cereal and dairy chain, f) combat of salmon counterfeiting.
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