AI Shrimp Detection: Smart IoT-Based Monitoring for Growth Tracking and Research Efficiency

ICAR-CIBA

UN SDG 12 - Responsible Consumption and Production

Chennai - TN

Pain Points

Manual shrimp measurement and inconsistent data slowed research accuracy.

Manual Growth Monitoring

Researchers measured shrimp manually, leading to errors and inconsistent growth data.

Lack of Real-Time Insights

No live monitoring of shrimp size and movement limited timely research updates.

High Labor Dependency

Manual observation required more manpower and time, affecting research productivity.

Our Offerings

IoT-based AI system for automated shrimp detection, growth tracking, and live data access.

AI-Driven Shrimp Detection

AI identifies and counts shrimp automatically with precision using vision models.

Real-Time Growth Monitoring

Continuous tracking of shrimp size and activity for accurate growth trend analysis.

IoT Cloud Integration

Data uploaded to a secure cloud for visualization and research analytics.

Alert & Reporting Dashboard

Provides reports and alerts for abnormal shrimp behavior or growth deviation.

AI identifies and counts shrimp automatically with precision using vision models.

Continuous tracking of shrimp size and activity for accurate growth trend analysis.

Data uploaded to a secure cloud for visualization and research analytics.

Provides reports and alerts for abnormal shrimp behavior or growth deviation.

Outcomes

Enhanced Research Accuracy

Automated detection eliminated human error in shrimp growth measurement.

Time and Labor Savings

Reduced manual observation time, enabling faster research cycles.

Improved Data Reliability

Consistent AI monitoring ensured uniform and traceable growth records.

Real-Time Insight Access

Researchers accessed live shrimp data for quicker analysis and decision-making.

AI-based detection improved our research accuracy and reduced manual workload.

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