Thesis subject
Data driven food fraud vulnerability assessment using Artificial Intelligence (MSc)
Food fraud is a significant issue that threatens the safety and integrity of food products available on the market. Research has revealed that food fraud affects a wide range of products, with fraudulent activities ranging from intentional adulteration of food to falsification of documentation. Identifying vulnerabilities in the food supply chain and determining which products and fraud types require assessment are critical steps to safeguarding food quality and safety. This MSc project aims to use artificial intelligence to develop a data-driven approach for assessing food fraud vulnerability in the main food supply chains such as honey supply chain. The goal is to predict the level of vulnerability, potential food fraud types and adulterants at each stage of the supply chain.