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GithubIn marine ecological conservation and scientific research monitoring, the real-time identification of various underwater organisms (such as starfish, sea urchins, corals, etc.) is crucial for studying biodiversity and changes in water quality environments.
Traditional manual diving observations are constrained by environmental factors, exhibiting low efficiency and insufficient accuracy.
To this end, the marine ecological monitoring enterprise has introduced SingTown's OpenMV intelligent camera recognition technology, utilizing AI machine vision and image recognition algorithms to achieve automatic underwater multi-target identification and classification.
This system can be applied in scenarios such as marine life census, habitat monitoring, and ecological anomaly detection, significantly enhancing the efficiency and accuracy of marine ecological data acquisition.

Marine Ecological Monitoring Enterprise utilizes SingTown Technology's OpenMV intelligent camera recognition technology to achieve automatic identification and classification labeling of various marine organisms.
The system deploys visual monitoring modules underwater, utilizing high-definition cameras to capture real-time seabed images and identify various aquatic organisms such as starfish, sea urchins, and shellfish.
The system employs a deep convolutional neural network (CNN) algorithm, trained on thousands of labeled samples, enabling it to distinguish objects based on their morphology, color, and edge texture. Even in complex scenarios such as underwater lighting variations, bubble disturbances, or minor drifts, the system maintains stable recognition performance.
During operation, the camera utilizes target detection, feature matching, and region classification algorithms to automatically generate colored rectangular boxes for each target in the frame, annotating them with category names and confidence levels (e.g., SingTown 0.83, echinus 0.88).
يتم حساب نتائج الكشف في الوقت الحقيقي بواسطة شريحة الذكاء الاصطناعي الطرفية لكاميرا OpenMV الذكية، والتي يمكنها تنفيذ التعرف والتعليق التوضيحي وتغليف البيانات بشكل مستقل تحت الماء. ثم يتم إخراج النتائج إلى محطة المراقبة الأرضية عبر المنفذ التسلسلي أو الشبكة اللاسلكية لإجراء الإحصاءات البيئية أو تحليل التلوث.
This solution achieves automatic detection, classification, counting, and visual annotation of multiple biological targets, providing an efficient, reliable, and locally deployable machine vision solution for marine ecological protection, scientific research surveys, and underwater environmental assessment.
Through SingTown Technology's OpenMV intelligent camera recognition technology, marine ecological monitoring enterprises have achieved an intelligent upgrade from manual observation to AI visual recognition and data-driven analysis.

AI Sentinel Based on OpenMV: Automatic Alert for Unlocked Key Locations
Automatically detects whether the door of a key location has remained open for an extended period and issues a timely alert.

Personnel crossing the boundary triggers an alarm; OpenMV defines the “sense of security boundary.”
Detecting personnel or equipment crossing boundaries via virtual alert lines.

“AI城管” is here: An automated system for detecting illegal street vending, built on OpenMV
Automatically identifies illegal street vending activities to support daily urban governance.

Is the gas cylinder placed haphazardly? Use OpenMV to automatically trigger a hazard alert
Automatically identifies unauthorized placements of gas cylinders to detect potential gas safety hazards in advance.

Did you perform live-line work without wearing insulating gloves? OpenMV will immediately alert you!
Automatically identifies whether workers are wearing insulating gloves to assist in safe operations.

Utilizing the OpenMV smart camera to detect surface defects on aluminum plates in real time
Online detection of surface defects on aluminum plates, such as scratches and dents, to support quality control.