Real time detection of freeswimming sea lice

e-Lice

Project duration: September 2023 – December 2024

Objective

Modern technology, such as artificial intelligence and machine learning, can play a role in the work of identifying solutions to reduce the salmon lice challenge in Norwegian salmon farming. In the e-Lice project, advanced underwater sensors and artificial intelligence will be used to detect salmon lice in the water column.

The purpose of the project "e-Lice" is to develop an early warning system based on images of salmon lice in the water column. This will be achieved by using an optical sensor with built-in artificial intelligence for data processing. The system will be used to identify, classify and quantify different life stages of salmon lice in real time. Data aimed at the end user will be visualized on an e-dashboard. In this way, end users will gain access to an early warning system that enables the implementation of mitigating measures to reduce the risk of lice infection.

The optical sensor to be used in the project is an Underwater Vision Profiler 6 (UVP6) (Picheral et al., 2022). This is an in-situ image processing unit used to study plankton and other particles in water. The sensor is equipped with a high-resolution camera that takes images of plankton and particles as they pass through a field illuminated by a laser diode. The images are then analyzed for identification and quantification of different species/particles using a dedicated image processing unit based on artificial intelligence.

e-Lice concept rig — We deploy a UVP6 at a farming site with the industry partner in the project, Nova Sea. Here a figure showing a vertical mooring where several UVP6 are attached.

If the project succeeds in developing an early warning system for free-swimming salmon lice, this will have great value for the aquaculture industry. Such a system will make it possible to quickly implement preventive and/or mitigating measures, which can contribute to a significant reduction in lice infestations. Locally, knowledge of when and where salmon lice blooms can be expected will help farmers in decisions about which preventive strategies to apply at different sites and with what intensity. A reference group and a user group have been established for the project.

Funding: FHF project 901871 Partners: Veso AquaLab, Kongsberg Discovery, NIVA, Hydroptic, MP Consulting and Nova Sea.

### Reference

Picheral, M., Catalano, C., Brousseau, D., Claustre, H., Coppola, L., Leymarie, E., Coindat, J., Dias, F., Fevre, S., Guidi, L., Irisson, J.O., Legendre, L., Lombard, F., Mortier, L., Penkerch, C., Rogge, A., Schmechtig, C., Thibault, S., Tixier, T., Waite, A. and Stemmann, L. (2022), The Underwater Vision Profiler 6: an imaging sensor of particle size spectra and plankton, for autonomous and cabled platforms. Limnol Oceanogr Methods, 20: 115-129. https://doi.org/10.1002/lom3.10475