How can one monitor food fraud incidents around the world in almost real time? Can large-scale data analysis reveal patters related to the way that people modify food products, ingredients or packaging for economic gain? Is it possible to predict whether someone in the supply chain has substituted, misbranded, counterfeited, stolen or enhanced food in an unapproved way? In which ways can big data help us detect if there is increased probability of food fraud?
BigDataGrapes project answers these questions in a new post in Medium: “Can Big Data predict fraud?”
BigDataGrapes aims to help European companies in the wine and natural cosmetics industries become more competitive in the international markets. It specifically tries to help companies across the grapevine-powered value chain ride the big data wave, supporting business decisions with real time and cross-stream analysis of very large, diverse and multimodal data sources
