Case Study – Prince William
Accurately Detecting and Counting
Fish to Aid in Weather Research
The Prince William Sound Science Center (PWSSC) is an independent Alaskan research and education non-profit dedicated to promoting, cataloging, and sharing relevant science for the benefit of residents, resource managers, and other local stakeholders. PWSSC plays a crucial role in understanding ecological changes, especially in a world where shifts in atmospheric and ocean climates threaten livelihoods and present complex challenges for those managing and enhancing the planet’s vital living resources. However, the center faced significant pain points in accurately collecting and analyzing data on fish populations and environmental conditions.

TECH STACK

CLIENT
Prince William
SERVICE PROVIDED
Application Design, Application Development






The Challenges
- Inaccurate Data Collection: PWSSC needed to detect and count four classes of fish moving upstream and downstream in Prince William Sound, but the current system was inefficient and inaccurate, resulting in unreliable data.
- Impact on Research: The unreliable data compromised scientific research on weather patterns and ecological changes, hindering effective resource management and conservation efforts.

Key Requirements
Accurately count the number of fish moving upstream and downstream and identify their species.
Transmit the data to the cloud for further analysis.
Deploy the system on Jetson Nano.
Use underwater ZED cameras.
Capture and save frames when fish cross the cameras.
Maintain a frame rate (FPS) of 10.


AI Computer Vision
Artificial intelligence (AI) trains computers to interpret and understand the visual world. By using digital images from cameras and videos as well as deep learning models, computers can accurately identify and classify objects and then react to what they “see” in a manner defined by their programming. This technology combines machine learning and pattern recognition to mimic the way the human vision system works, but with the ability to process and analyze data at a scale and speed that humans cannot match.
Our Solution
AI Computer Vision
Nyx Wolves utilized deep learning to train the model on labeled images of the four classes of fish. The system runs the model on the ZED 2 camera’s view, tracking fish across frames using the tracker module. The analytics module performs counting and line crossing detection, sending data to the communication buffer, which then transmits it to cloud storage for further analysis.
System Deployment
The solution was deployed on Jetson Nano with underwater ZED cameras, achieving the desired frame rate of 10 FPS.
Enhanced Accuracy
The AI-based computer vision system provided high accuracy in fish detection and counting, outperforming manual methods.
Non-intrusive Monitoring
The system allowed for non-invasive monitoring, reducing stress on fish and minimizing ecosystem disruption.
Precision Meets
the Ocean.
Explore the perfect synergy of technology and ecology. Our AI-powered solution ensures accurate fish monitoring without disturbing their natural environment. By streamlining data collection and analysis, we’re enabling researchers to uncover patterns that drive better conservation and resource management.

Development Process
01
Discover
User Research /
In-Depth interviews
02
Design
Product Hypothesis /
User Stories
03
Develop
Style Guide /
Hi-Fi Wireframe
04
Deliver
User Interface /
Adaptive Design


Where every choice leads
to meaningful change
With The Prince William Sound Science Center , every choice counts. Drive sustainability, embrace innovation, and focus on creating a brighter tomorrow. Turn challenges into opportunities and let The Prince William Sound Science Center lead your path toward meaningful change.

Results

The new AI-based system has significantly improved the accuracy and efficiency of fish counting in Prince William Sound. The data collected is invaluable for scientific research, aiding in the understanding of weather patterns and ecological changes. PWSSC continues to expand its capabilities and partnerships, leveraging advanced technology to enhance its research and educational missions.
Accuracy and
Efficiency
The system accurately detects and counts the number of fish moving upstream and downstream, classifying them by species with high accuracy.
Data
Transmission
The collected data is reliably sent to cloud storage, where it is used for further analysis in scientific research on weather patterns.
Enhanced
Performance
Achieving the desired FPS of 10, the system is more efficient and reliable than previous methods, providing valuable insights for ecological and weather-related studies.