Risk-Based Food Fraud Decision Support Module
The Risk-Based Food-Fraud Decision Support Module uses a state-of-the-art methodology to quantitatively assess food fraud risk in complex food systems, through a software application named the Food Fraud Risk Engine. The Engine uses various techniques to gather information about a particular supply chain, such as screening food fraud databases, analysing socioeconomic drivers, collecting climatic and agricultural data, and using expert elicitation methods. Additionally, real-time Internet of Things (IoT) data are collected from various sensors. All this information is synthesised and processed comprehensively to evaluate food fraud vulnerability factors. Specifically, the Engine is fed periodically with real-time data to update the fraud risk indicators of each node (e.g., harvesting, transportation, storage) composing the stages of a supply chain. Thereafter, the underlying probabilistic model integrates the risks stemming from the individual nodes to evaluate the food chain's overall risk. When the overall risk factor exceeds a pre-defined threshold value, the Decision Support System sends an alarm alerting pertinent authorities to potential food fraud activities. The main added value of this Engine for the end user is the ability to proactively detect and quantify food fraud risks in real time across the entire supply chain, enabling timely and evidence-based interventions. The outputs can inform policy decisions, compliance strategies, and operational controls through evidence-based, real-time risk insights.
WATSON
Completed | 2023-2026
- Main funding source
- Horizon Europe (EU Research and Innovation Programme)
- Geographical location
- Ireland, France, Italy, Greece, Finland, Denmark, Other, Portugal, Germany, Luxembourg, Spain, Cyprus, Belgium, Slovenia, Austria, Hungary, Bulgaria