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How to Choose a Specialized Underwater Camera for Fish Farming?
Hits: 1350 Time: September 10,2025




For fish farming, prioritize selection in the order of "visible → clear → durable → cost-effective": first determine the depth/waterproof rating and power supply method, then select imaging quality and lens, supplement lighting and transmission functions, and finally evaluate the ROI (Return on Investment) of automatic recognition and supporting services.

Four-Step Quick Selection Method

  1. Determine depth and power supply: Clarify the water environment (seawater/freshwater), breeding mode (cage/pond), and whether long-term deployment is required; select the corresponding pressure resistance level and power supply solution (shore power/battery/solar energy).
  2. Select imaging quality and lens: Prioritize low-light sensitivity, while considering resolution and field of view; for turbid water, prioritize wide-angle lenses and penetrating fill light.
  3. Configure lighting and transmission: Choose fill light power and beam angle based on water depth/turbidity; for long-distance or multi-point monitoring, prioritize wired transmission; for flexible inspections, consider ROV (Remotely Operated Vehicle)/UAV (Unmanned Aerial Vehicle) -mounted cameras.
  4. Calculate ROI: Estimate the annual cost of manual inspections and disease losses, and compare the equipment investment with the expected payback period.


Key Indicators and Trade-Offs

Indicator Farming Focus Common Choices Trade-Offs
Waterproof/Pressure Resistance Seawater corrosion, long-term deployment IP68 / 10–100 m; higher ratings for deep sea Higher performance = higher cost; match on demand
Low-Light Performance Visibility at night/turbid water Low-light CMOS / starlight-level sensors + fill light Pixels ≠ clarity; prioritize low-light performance first
Resolution/Frame Rate Fish behavior and disease identification 1080P / 30–60fps; 4K for specific needs 4K requires higher bandwidth/storage
Lens/Field of View Full cage coverage, low distortion Wide-angle (≈120°–142°); fixed focus preferred Ultra-wide angles may have edge distortion (needs correction)
Fill Light Penetrating turbid water, no fish disturbance White/warm white LEDs with adjustable brightness Strong light may disturb fish schools
Transmission/Power Supply Long-distance/multi-point monitoring Wired (USB/coaxial) = more stable; ROV/AUV = more flexible Wireless is affected by distance/environment
Automatic Recognition Fish counting/sizing/growth curves Binocular vision or AI algorithms Requires computing power and species-specific calibration
Supporting Services Installation, maintenance, training One-stop solutions, local technical support Long-term stability matters more

Quick Matching for Three Typical Scenarios

1. Fixed Long-Term Monitoring (Cages/Ponds)

  • Key Indicators: 10–100 m pressure resistance, low-light 1080P resolution, 120°–142° wide-angle lens, wired power/transmission, adjustable white fill light, corrosion-resistant housing.
  • Advantages: Stable operation, low cost, minimal maintenance.

2. Mobile Inspection (Flexible Positioning)

  • Solution: ROV/underwater drone + high-resolution anti-shake camera + adjustable high-power fill light; expandable with water quality sensors and robotic arms.
  • Applicable Scenarios: Large-area inspections, night troubleshooting, emergency response.

3. Growth Assessment & Automatic Recognition (Scientific Research/Large-Scale Farming)

  • Solution: Binocular vision + edge/cloud computing power to realize fish counting, sizing, growth curve tracking, and health alerts.
  • Key Requirement: Species-specific adaptation, calibration, and continuous algorithm optimization.

Pitfalls to Avoid

  • Overlooking low-light performance and lens distortion while only focusing on pixels, leading to blurry images in turbid/night environments.
  • Ignoring power supply and transmission distance, resulting in unstable operation or high retrofitting costs.
  • Using excessively strong fill light (disturbs fish) or insufficient fill light (poor penetration in turbid water).
  • Blindly adopting AI for automatic recognition without planning for species-specific adaptation and computing power support.


For more information about underwater aquaculture camera, please visit the homepage.



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