Stereo camera systems are foundational tools in precision aquaculture, providing 3D spatial data that 2D cameras cannot. By using two synchronized lenses to capture overlapping images, these systems enable non-invasive, high-precision monitoring of both biological and structural components of fish farms

Core Applications
-Biomass & Size Estimation: Stereo cameras are primarily used to measure fish fork length and width without physical handling. These 3D measurements are converted into weight estimates with high accuracy (often <1–5% error), critical for optimizing feeding and harvest timing.

-Behavioral Analysis: They track 3D swimming speed, trajectory, and social interactions. Behavioral anomalies, such as changes in swimming depth or speed, serve as early indicators of stress, disease, or hypoxia.

-Structural Inspection: Mounted on ROVs or fixed points, stereo cameras perform detailed 3D inspections of containment nets, mooring lines, and brackets. They can identify and quantify defects like mesh tears, corrosion, or biofouling accumulation.

-Feeding Management: Real-time 3D feedback monitors pellet distribution and fish feeding intensity, allowing operators to adjust feed delivery to minimize waste and environmental runoff.

Technical Implementation System Configuration: Standard setups use a side-by-side (binocular) orientation. A "short baseline" (small distance between lenses) is often used to keep systems compact and reduce light refraction errors in close-range measurements. Deep Learning Integration: Modern systems utilize AI for automated detection (e.g., YOLOv11) and 3D reconstruction. "Post-detection fusion" is the most common method, where 2D key points (snout, tail) are detected in both images and then triangulated to 3D coordinates.

BUILDING A SMARTER AI FUTURE

CATALYZING THE AI REVOLUTION

WHAT TO EXPECT

JOIN THE FUTURE OF AI