Development of AI based applications to support insect breeding experiments for the circular economy.
External reference persons The thesis is in collaboration with the University of Turin (Dipartimento di Scienze Agrarie, Forestali e Alimentari) through Dr. Sara Bellezza Oddon
Research Groups SYSTEMS BIOLOGY GROUP
Thesis type RESEARCH / EXPERIMENTAL
Description Since insects can grow on a wide range of organic waste, the interest in insect breeding as an integral part of the circular economy model has gained increasing attention in recent years. In particular, the black soldier fly (Hermetia illucens) is one of the most bred species given its adaptability, its efficiency in the conversion of waste, and the simple management of its life cycle compared to the other insect species. In parallel with the commercial development of this sector, research is also dedicated, through experimental trials, to provide scientific evidence that allows a production standardization. During the experimental trials, one of the problems encountered derives from the need to have a large number of larvae (at least 500 individuals/box; 5 boxes per treatment). Normally, for each trial, at least 4 treatments are tested. Therefore, the total number of larvae to be counted is often overcome 10.000. At the moment, the count is done manually and this, considering the high number of larvae involved, is time-consuming and could lead to “human error”.
This thesis aims at using cutting-edge image processing algorithms coupled with artificial intelligence to realize a mobile application able to precisely count larvae in a picture thus supporting researchers allowing them to reduce the work and improve accuracy.
Required skills Advanced programming skills (preferably python and mobile development). Basic image processing and machine learning knowledge would help.
Deadline 13/03/2022 PROPONI LA TUA CANDIDATURA