Outbreaks of salmon lice in fish farms are a main cause for stress, reduced growth and death in commercial fish farming. Such attacks have been estimated to account for losses in billions of NOKs each year in Norwegian farms. Even a minor reduction in outbreaks would result in high profitability gains.
NCE Seafood Innovation Cluster is currently developing the AquaCloud concept were data from various sources is collected and will be made available for research and innovation. One of the initiatives is focusing on the prediction of salmon lice outbreaks based on historical data. This is a data source that will be considered int his project. A pilot involving IBM Watson is part of their initiative, and will be one option to look into.
The topic for the project work and master thesis is to investigate how outbreaks of salmon lice attacks can be predicted based on available historical data (from various sensors, manual count of number of lice, measurements of food consumption and growth, etc.). In addition, the analysis of videos showing fish behaviour should be considered. Collaboration with companies developing drones for collecting data in fish farms could be considered.
The thesis will be done at the Telenor-NTNU AI-Lab with connections to the EXPOSED Aquaculture SFI, in which NTNU IDI is a partner, (dealing with monitoring and decision support systems), and NCE Seafood Innovation Cluster.
Supervisor: Kerstin Bach and Agnar Aamodt, IDI, NTNU
Co-supervisors: Sigmund Akselsen, Telenor og Gunnar Senneseth, Sintef Ocean