Spanish technology company Satlink has been authorised by the National Oceanic and Atmospheric Administration (NOAA) to supply its electronic monitoring (EM) system to the US fishing fleet.
The federal agency in charge of managing fish stocks in the United States’ exclusive economic zone, NOAA has endorsed the reliability of Satlink’s solution, based on its experience in managing more than 250 installations in the Atlantic, Indian and Pacific Oceans.
Specifically, Satlink will be able to supply its on-board electronic activity monitoring solution for the 2022 fishing season to those vessels operating under the Northeast Multispecies Fishery Management Plan, gaining weight in the international market for this type of system capable of uninterrupted monitoring of vessel activity.
‘Our R&D capacity and more than eight years of experience and participation in numerous international electronic monitoring projects of different sizes and for all types of fleets, have allowed us to obtain authorisation to commercialise our solution in a market as regulated as the United States,’ said Pablo Torralbo, director of Satlink’s Electronic Monitoring division.
‘This is a very important endorsement to consolidate our leadership as a supplier of fisheries management systems and as a technological benchmark for the sustainability of the oceans and better management of fishery resources.]
Satlink’s SeaTube is based on a system of high-definition cameras and sensors that monitor fishing activity to check compliance with best fishing practices and responsible activity on board. Among its most recent projects to implement this system are those developed with the governments of the Solomon Islands, Micronesia and Seychelles, countries with economies highly dependent on fishing. In the case of the Pacific Ocean, Satlink leads this market with the monitoring and analysis of more than 110 vessels of fleets from nine countries.
Satlink also has a team of R&D engineers focused exclusively on the development of applications in the field of Artificial Intelligence (Machine Learning) that will enable an assisted analysis of video and sensor data of fishing activity, recognising fishing periods as well as identifying fish and other relevant parameters.
