We want to ask a direct question: when you look at the data coming out of your current fish monitoring setup, do you trust it completely? Not just the count. The species breakdown, the size distribution, the wild-to-hatchery ratio, the timing of sub-groups within the run. Do you trust all of that?

Our guess is that for most operators, the honest answer involves some qualification. The count is probably close. The species data is probably a sample. The rest is mostly modeled from that sample. And the whole dataset is probably weeks to months old by the time it reaches the people who need to make decisions from it.

That's not a criticism of the people running these programs. It's a reflection of what traditional fish scanning equipment can and can't do. Visual sampling by trained staff is accurate within limits. Sonar counts are useful for aggregate throughput. PIT tag arrays are excellent for tagged fish and invisible for everything else. The composite picture these methods produce is the best that was achievable with the tools available when these programs were designed.

Why Does This Matter More Now Than It Did Ten Years Ago?

The stakes have changed. Climate-driven shifts in run timing, migration behavior, and water temperature are happening faster than historical reporting cycles can track. Invasive species pressure is increasing in most river systems in North America. Regulatory frameworks are tightening around compliance documentation and the evidentiary standard for fisheries license renewals.

All of that creates pressure on monitoring programs to deliver more current, more specific, and more verifiable data than traditional methods were built to provide. The gap between what's needed and what's available is widest in summer, when conditions are changing fastest and migration windows are most compressed.

What Does Modern Fish Scanning Equipment Actually Deliver?

The FishL Recognition system from Whooshh Innovations is built around six cameras, three near-infrared and three visible spectrum, capturing 18 images per fish as each individual passes through the imaging zone. AI algorithms process those images in milliseconds. The output for each fish includes species classification, fork length, girth, adipose fin status, injury presence, tag detection, and environmental data like water temperature and flow rate at the time of passage.

That's not a sample. It's a complete record. Every fish that moves through the system gets its own data entry, with images attached, logged automatically to cloud or local storage.

Here's what that changes operationally compared to traditional monitoring approaches:

• No observer variability: classification is algorithmic and consistent across every fish, every shift, every season

• No sampling gaps: the system processes fish at up to 40 per minute, 24 hours a day, without fatigue or scheduling constraints

• No data latency: records are available in near-real time for remote access by authorized users

• No prior tagging required: every fish is assessed on imaging alone, not dependent on previous mark-recapture enrollment

• Full audit trail: image files attached to every record provide verification that manual sampling programs cannot match

Where Has This Equipment Been Deployed?

The FishL system was installed at the Bonneville Adult Fish Facility on the Columbia River, one of the most significant salmon monitoring sites in North America. In a single season, it generated over 220,000 classified fish images from 12 species. That dataset was presented to the National Marine Fisheries Service and produced insights into run health and composition beyond what the existing monitoring program had been able to generate.

Beyond dam sites, the system has been deployed at hatcheries, university research programs, USGS river monitoring stations, and Native Tribe fisheries management programs. Its modular design means it can be used as a standalone scanner or integrated into the full PassagePortal passage system.

Explore what the FishL Recognition system can do for your monitoring program specifically. And if you've been following the fish scanning and sorting conversation, the published blog Why Fish Scanning and Sorting is the Next Big Thing in Aquatic Management covers the broader context. Contact us when you're ready to talk through your specific site.