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Boulder AI Case Study

Using AI To Automate Fish Passage Counts

A fish passage count is a vital metric for anyone concerned about wildlife management. It’s important for officials and dam operators to have an accurate count of the fish crossing a dam (via a fish ladder).

Currently, most fish passage counts are conducted by video:

  1. A video camera monitors a fish ladder
  2. As fish pass thru the ladder, they cross in front of the camera
  3. A trained fish counter reviews the video footage and tabulates the results

This is a tedious process, and often times sub-sampling is used to save time (with varying levels of accuracy). But this is the old way of doing things. We’ve invented a new way…

Fish counting room
Here's what a fish counting room looks like. Note the video camera.
DNNCam
The DNNCam™
Fish counting thru glas
Our software can determine species, length, and direction of travel.

Boulder AI Counts Fish With Technology

Using our DNNCam system and proprietary software, Boulder AI has developed an automated system for counting fish passage. A machine vision camera system with an AI algorithm monitors the fish ladder. As a fish swims by, the camera system automatically categorizes and counts the fish.

  • Our system can identify fish species with 96% accuracy
  • Our system can measure fish length within 2cm of actual size
  • Our system works even in turbid conditions (up to 50NTU in some cases)

The end result is a table of count data, along with size information, and even an actual photo of each fish (as desired).

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