GroVision is a software for controlling and monitoring the farm site. It gives fish farmers the ability to optimise the feeding process and minimise feed wastage with the help of cameras, sensors and a remotely controlled feeding system.


GroVision has several qualities that make it an excellent software for controlling and monitoring fish farms. One of its key advantages is the ability to track feed wastage, leading to minimized feed wastage and improved production efficiency. Another key advantage is the ability to create custom camera views with all cameras on the farm site. Finally, GroVision can view logged data from various types of sensors used in fish farms.

Track Feed Wastage

GroVision also offers the ability to scan images for feed. This can assist on-site feeders or feed centrals with feed optimization and control of the feeding system. The GroVision software can observe if pellets descend below the main body of the fish, which indicates that the appetite is satisfied. This feature results in minimized feed wastage and seabed pollution, as well as improved production efficiency.

Custom Camera Views

One of the key advantages of GroVision is the ability to create custom camera views with all cameras on the farm site. This allows operators to get a complete view of the farm and monitor all areas from a single interface. By integrating feeding system data and controls on the camera images, operators can quickly identify and address any issues with the feeding system. This feature allows for optimal control of the feeding system and improved production efficiency.

Read Sensor Data

The GroVision software is designed to view logged data from various types of sensors used in fish farms. Built on big-data technology, the software is capable of handling vast amounts of data with ease. With this software, you can view trends in the readouts from e.g. the GroSensor and monitor values in real-time.

GroVision can also be used to log and monitor multiple sensors, including Dissolved Oxygen, Temperature, Salinity, pH, Turbidity, Algae, sea current, and weather.


GroVision is a highly flexible software that can be used to monitor and control all existing feed systems hardware in the market. It can also host and control several farming sites simultaneously, allowing users to efficiently manage multiple locations from a single interface. Additionally, the software can easily export data to other software, making it an ideal solution for businesses that require a high level of flexibility and customization. 

Easy to Use

One of the most important qualities of GroVision is its ease of use. With a straightforward and uncomplicated user interface, operators can easily navigate the software and quickly access the information they need. This ease of use is critical for businesses that require a reliable and efficient platform that can help them streamline their operations and increase productivity.

We are here to
guide you

Do you have questions, speculations or want to
chat about possibilities, get in touch.

Kristian Andreasen

Head of Sales

Faroe Islands

Robbie Duncanson

Sales (UK & Ireland)


Our clients say

Our goal is to reduce CO2 emissions with 50% by 2030. By diverting to landline power-supply for our feeding barges, we can reduce oil consumption and thereby emissions from our farm sites.

Jón Purkhús
Manager, Bakkafrost Faroe Islands

GroAqua delivered all the technical equipment for our farmsite in Sandsvág, Faroe Islands. They delivered the feeding barge, camera system, feeding system, internet, sensors and landline.

Hans Jákup Mikkelsen
Managing Director, Mowi Faroe Islands

GroAqua has a lot of experience in building feeding barges for areas with unpredictable weather and challenging seas. With a hybrid barge from GroAqua, we are taking big steps toward more sustainable farming.

Gauti Geirsson
CEO, Háafell

Product Range


GroVision is the software for controlling and monitoring the farm site with the compatible hardware, such as the GroFeeder, GroSensor and GroCamera.


The FeedTracker software is vision-based and scans images from subsea cameras for feed. Using Machine Learning it can automatically control the feeding system.