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.

ALLIANCE represents a paradigm shift in the Food Supply Chain Systems’ management for the combat against Food Fraud, distinguishing from the traditionally approaches that leverage monolithic digitalized logistic solutions and standalone FSC interoperability protocols. ALLIANCE aims to provide a holistic framework that safeguards data integrity and veracity, enhances traceability and transparency and reinforces interoperability in quality labelled supply chain of organic, PDO, PGI, and GI food, through innovative technology solutions and validated approaches (such as distributed ledger technologies supported by IoT sensing devices, providing extensible anchors to interoperability protocols and use of in-situ portable rapid testing devices to detect adulteration and verify food origin and authenticity) and fosters evidence-based decision making through AI and ML for preventative interventions and actionable planning. The proposed framework will improve social and economic sustainability of quality labelled food supply chains by ensuring quality & authenticity, increasing food safety, while also considering climatic and environmental impacts of food products. The technologies to be employed in this project will be described and demonstrated in detail to reach higher technology readiness levels (TRLs) and enable smooth and rapid adoption by all stakeholders.

The agri-food industry faces numerous challenges dealing with societal, public health, individual nutrition and environmental, food waste and overall food system sustainability challenges. Imbalances and disconnected food markets are generating undesirable trade-offs between the food supply, the consumption patterns, quality of nutrition and the environment. Interoperability and data sharing across agri-food supply networks is limited. Data can revolutionise the food industry and foster its contribution to inclusive and sustainable food systems. Data can be used to assist these stakeholders in making informed decisions on how to operate in a more sustainable and inclusive manner. In this way, they increase the efficiency of the food industry through the optimisation of relevant operations and the reduction of waste, promoting transparency and demonstrate their commitment to ethical and sustainable production. FoodDataQuest will develop ground-breaking data-driven solutions based on an integrated methodological framework that explores new types of private and public data sources, data from “unconventional players” and non-competitive data and leverages data sharing mechanisms in order to provide the EU food chain stakeholders with increased insights and enhance the transition towards sustainable healthy diets. The proposed framework will include guidelines and data collection strategies, to drive the food system transformation towards inclusive, sustainable, healthy diets within the boundaries of legal and policy frameworks. FoodDataQuest will co-create and test advanced data-driven solutions based on AI and ML algorithms, following a multi-actor approach that will serve as a lighthouse that positively impacts a fair, healthy and environmentally friendly food system. Last, FoodDataQuest will engage citizens into industry's data-driven innovations balancing between data openness and protection of private and sensitive data of multiple stakeholders.