*Register here*

SMMR are hosting OLSPS for a talk on “Innovative software solution for the accurate and efficient capture and reporting of fisheries data”.

The Webinar will take place on 5 April 2023 from 1-2pm with a 30 minute talk, followed by a Q&A.

In recent years two technologies have emerged to monitor commercial fishing activities. These technologies are a) electronic logbooks (eLogs) for the electronic reporting (ER) of compliance reports, and b) electronic monitoring (EM), which refers to the use of Closed Circuit Television (CCTV) in order to record fishing activities on the vessels. While both ER and EM technologies are found to be very effective in their task, they still suffer from several significant shortcomings. EM technology is mainly hampered by the huge amount of video footage it produces, which makes the processing of its data very tedious and labour-intensive process. Electronic logbooks on the other hand, while capable of recording many data types with great detail, suffer from a possible lack of accountability, since a lot of data must be entered manually and certain entries cannot be verified, leaving room for misreporting.

In order to make the scanning of EM videos more practical and focused, OLSPS has developed a conceptual integration model between eLogs and EM cameras, which has maned iEMR – Integrated Electronic Monitoring and Reporting. This solution allows images recorded by cameras to be viewed and stored on the Olrac Dynamic Data Logger (OlracDDL) dashboard and to use the vessel date and time of activity as a common key that allows images taken by the cameras to be easily matched to data recorded and reported by the Olrac eLog. Examples of activities that are important to keep track of are discarding events, excessive catches, bycatch, and marine life interactions. The ability to match recorded images to relevant eLog records means that clear discrepancies between what the skipper reports and the actual visuals can be easily identified and scrutinized.

OLSPS is also experimenting with the integration of user-activated and supervised, AI-based, image processing technology into their iEMR solution which will reduce further the time of video scanning.