Computer Vision For Food Quality: The Case of Injera

The use of Teff as an exclusive crop for making Injera, Ethiopian national staple, has changed overtime.Driven by the ever increasing price of Teff, producers have added other ingredients, of which some are good (maze and rice), while others are not. Hence, households opting for the industrial solution of Injera, are disturbed by the fact that hey can not figure out what exactly is contained in their Injera. Thousands of local producers and local shopkeepers work together to make fresh Injera available to millions around the country. However, consumers are finding it more and more difficult to find a safe Injera for purchase. This injera is usually sold unpacked, unlabeled and in an unsafe way through local shops. This being so, consumers face more and more health risks, all the more as it is impossible to evaluate the ingredients contained in the Injera they are buying There are two kinds of risks: (a) the local producers might try to reduce the cost by using cheap ingredients, including risky additives, and (b) the shops might sell expired Injera warmed up. We discuss here the growing food safety problem faced by millions of Injera consumers in Ethiopia, and the possibility of using AI to solve this problem.

Speaker bio: Wondimagegnehu is a master’s student in Information Science at Addis Ababa University. He is working on a master's thesis in learning an optimal representation of word structure for morphological complex languages under a constrained settings: limited training data and human supervision. He is interested in exploring research challenges in using AI on a social setting.