ICT4SS - ICT FOR SMART SOCIETIES
Application of digital imaging on living organisms
Reference persons ENRICO MAGLI
External reference persons Dott. Benedetto Sicuro, Dipartimento di Scienze Veterinarie, UniversitÓ degli studi di Torino
Thesis type RESEARCH / EXPERIMENTAL
Description The future of aquaculture, that is the farming of aquatic organisms, is strongly related this its environmental impact on natural environment. In the international scientific community there is a great effort to control the possible negative effect of fish farms on natural systems, as rivers, lakes and sea.
The fish farms in Italy and in Europe are considered a potential sources of pollution and for monitoring the real effect of these farms some organisms, in particular bivalve mollusks, can be used as living monitoring organisms using digital imaging for investigate their movements in relation to alteration of environmental conditions.
Therefore, the idea of this research is to investigate the valve movements of these mollusks, in different environmental conditions and use them as a sort of living alarm system that in the future could be used near the fish farm (or wherever), in order to understand the potential application in aquaculture.
Sensors have been already used on bivalves, but we think that the use of digital imaging could improve the efficiency of this system, make it economically more convenient and in the future possibly connected to applications for smartphones, thus introducing a new concept of hybrid or bionic aquaculture, where organisms connected with different kind of sensors could improve the diffusion of environmentally sustainable aquaculture.
This research will be part of an European project of aquaculture that is focused on the biological interactions between fish farm and bivalves and the multidisciplinary approach of this project will make this research a challenging experience for students involved, in particular those with different scientific background.
Required skills Basic image processing and programming skills; knowledge of neural networks is desirable but not a prerequisite.
Deadline 11/01/2020 PROPONI LA TUA CANDIDATURA