Teem Fish

Teem Fish

Electronic Monitoring: A Key Tool For Commercial Fisheries

Despite being a source of healthy seafood and employing millions of people, the fishing industry continues to face issues ranging from IUU fishing, through climate change, by-catch, discards and overfishing. Electronic monitoring is seen as one route to gathering data needed to address these challenges.

It is now being recognised that one way towards a more sustainable, thriving industry is to gather fishery/fleet information on targeted catch, by-catch, any at-sea discarding, fluctuating catch per unit effort (CPUE), total fishing effort and general compliance with regulations.

In September 2021, Canadian fisheries monitoring firm Teem Fish was acquired by Snap Group LP, which owns Snap IT, a camera and AI firm in New Zealand. We spoke to Teem Fish about the importance of electronic monitoring (EM) and the next steps for the system.

A federally designated fisheries monitoring provider in Canada and the USA, Teem Fish combines advanced technology with fisheries expertise to deliver EM programmes and systems, helping fishermen with the monitoring requirements of their jobs and creating an affordable way to scale the use of electronic data capture to ensure the ongoing viability of global fish stocks.

‘People have been putting cameras on boats since the early 2000s,’ said Teem Fish CEO Amanda Barney

Work began in 2011 as part of the charity Ecotrust Canada, which developed an EM system for a single commercial fishery before launching more pilot projects. As the EM programme grew in 2017 and 2018, Teem Fish was established in 2019 and is now owned by Snap Group LP.

‘EM can help not only the fishing industry but also industry regulators, consumers and communities by collecting data in a more efficient, affordable way,’ explained Amanda Barney, CEO of Teem Fish.

‘One important challenge for the fishing industry is data deserts – huge gaps in data sets. EM can help fill these gaps and paint a clear picture of what is happening on the water.’

Teem Fish CEO Amanda Barney

Teem Fish’s system – a central, custom-built computer attached to sensors and video cameras – monitors vessels and records information in real time such as a vessel’s location and movement and the species that it’s catching. GPS information is collected, while sensors for parameters such as hydraulic pressure are in place.

Radio frequency tags embedded in gear, a radio frequency tag scanner and other sensors can determine the exact timing of fishing effort for some fisheries. Teem Fish’s system can also run AI algorithms on-vessel to identify on video when fishing begins and ends, with sensors in place as backup. All data is removed physically from the vessel or compressed and transmitted to a cloud pipeline.

It’s then processed and watched by a video analyst, who collects any information required by a regulatory industry. The eventual goal is to use AI on-vessel to reduce overall video file capture and create data processing and analysis efficiencies.

‘Each fishery has unique monitoring requirements,’ Amanda Barney said

‘Each fishery has unique monitoring requirements, but in general programmes and EM systems allow us to monitor for the presence or absence of a particular behaviour or event,’ Amanda Barney said.

‘We could be looking for discards, or a particular species so we can identify it and estimate its weight. We may investigate marine mammal or seabird interactions, or where a vessel is fishing and when, the type of gear that is being used and how long that gear is in the water for. Or we may look at the number of vessels in a particular area – are there fifteen boats that fish in the same place or are they spread out? Any number of data points might be required by a regulator, industry or third party (research group, certification programme or processor),’ she said, commenting that from a logistical point of view, it’s time-consuming to review EM data and footage and quickly find the necessary information.

‘We want to eventually incorporate AI into the video review process as well, as it allows for more efficient review of all captured video.  It can also reduce the video files that need to be collected and/or stored long-term and enable us to select and package certain bits of information so we don’t need to send out an entire data set.’

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