The Challenge
Accurate fish passage monitoring is essential for understanding migratory fish populations and supporting effective fisheries management. Traditional monitoring, however, can require technicians to spend hours observing fish passage in real time or reviewing recorded underwater video.
Many monitoring sites are also located in remote or highly secure areas, making seasonal staffing and coordination difficult. These labor-intensive methods can create challenges related to cost, data consistency, and coverage, with missing observations or errors potentially affecting management decisions.
Our Solution
Spheros Environmental and its partners developed BlueFish, an innovative computer vision system designed to improve the collection and distribution of fish enumeration data. The system combines an edge-computing camera with customized software to continuously monitor fishways and deliver data remotely over the internet.
BlueFish enables around-the-clock monitoring while reducing the need for continuous on-site observation. Integrated quality control helps identify potential issues early, while cloud-based data management makes statistically robust results accessible to managers, biologists, and technicians on demand.
The platform also incorporates machine learning capabilities that allow the system to expand its ability to identify species and distinguishing characteristics over time, supporting continued advancement toward increasingly automated fish counts.
Technology Developer and Fisheries Consultant
Results +What makes this unique
BlueFish has been successfully tested and deployed at federal and regional hydroelectric projects across the Pacific Northwest, improving fishery management by increasing fish count accuracy and expanding monitoring into hours and locations where human staffing can be challenging.
The system has made data collection two-thirds faster than manual live or video counts while reducing labor costs and staff coordination requirements. Its integrated quality control, cloud-based data access, and machine learning capabilities further streamline how fish passage information is collected, reviewed, and distributed.
By combining fisheries expertise with computer vision, edge computing, cloud-based data management, and machine learning, BlueFish demonstrates how digital innovation can transform traditional environmental monitoring and give resource managers more timely, reliable information for decision-making.