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A holistic frameWork with Anticounterfeit and inTelligence-based technologieS that will assist food chain stakehOlders in rapidly identifying and preveNting the spread of fraudulent practices.

Project description

Preventing food fraud through digital and intelligence-based technologies

The EU-funded WATSON project will develop a set of tools and systems that can detect and prevent fraudulent practices across the entire food supply chain. It will increase transparency through improved track-and-trace mechanisms containing accurate, time-relevant and untampered information on the food product throughout its whole journey. The project will also raise consumer awareness about food safety and value, leading to the adoption of healthier lifestyles and the development of sustainable food ecosystems. Moreover, it will demonstrate the solutions in six different use cases across a number of key food supply chains, covering important commodity groups in the European food system (e.g. wine, olive oil, honey, meat, fish, cereal and dairy).

Objective

WATSON 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.

Keywords

Coordinator

UNIVERSITY COLLEGE DUBLIN, NATIONAL UNIVERSITY OF IRELAND, DUBLIN
Net EU contribution
€ 713 500,00
Address
BELFIELD
4 Dublin
Ireland

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Region
Ireland Eastern and Midland Dublin
Activity type
Higher or Secondary Education Establishments
Links
Total cost
€ 713 500,00

Participants (43)

Partners (5)