Effective enforcement and risk-based inspections supported by artificial intelligence (by Luca Megale)

The project focuses on setting up innovative risk-based food safety inspections with the support of artificial intelligence and machine learning. The scope is to plan more targeted inspections, reduce related costs (for operators and public authorities, including the health system) and support voluntary compliance, which are all central elements for effective and efficient enforcement.

Researcher: 

Luca Megale – (l.megale@lumsa.it)

University of Rome LUMSA