Commercial fisheries increasingly are incorporating electronic monitoring (EM) into existing fishery-dependent data collection programs. Across the United States, seven fisheries in the Northeast (Atlantic herring and mackerel, and groundfish), West Coast (Groundfish, Pacific whiting), Alaska (fixed gear groundfish and Pacific halibut), and Highly Migratory Species (Atlantic Bluefin tuna) are using EM for catch accounting and/or compliance with catch retention requirements. Machine vision learning applications, based on image-training datasets, global positioning systems (GPS), and sensors, could substantially reduce data collection and processing costs for existing and future EM programs. Remotely collected data (video images, GPS, sensors) could be used for collecting data such as gear, time and area of effort, length and weight measurements, and species composition of catch and catch disposition, to support the science and management of fisheries. It is critical to examine how these new data streams can be integrated with traditional observer and other fishery-dependent data to support catch monitoring and fish stock assessments.
The objective of this symposium is to provide the current status of EM and automated data (video and sensor) processing, and how these efforts can be improved in future fisheries-dependent data collection. This symposium will bring together electronic technology experts to examine advanced technologies (camera and sensor systems) and automated data processing onboard commercial fishing vessels. It will also assemble experts and stakeholders to discuss how data collected remotely can be used in stock assessments and catch monitoring.
This symposium builds on a 2015 AFS symposium, “Implementing Electronic Monitoring and Reporting in U.S. Fisheries” and the Second National Electronic Monitoring Workshop in 2016. This symposium also compliments a similar session in 2017, focused on fishery-independent technologies, “Integrating Acoustic and Optical Technologies for Next Generation Fisheries and Ecosystem Surveys.”