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AI-Powered Automated Aquatic Species Counting System for Sustainable Aquaculture

neurosys.com

Environmental Services

Agriculture

Food & Beverage

Challenges in Manual Aquaculture Monitoring

Current manual sampling methods for aquatic species monitoring cause measurement inaccuracies, stress to organisms, physical damage, and inefficiencies in tracking critical metrics like population size, growth rates, and biomass levels. This limits effective resource management and quality control in aquaculture operations.

About the Client

Research institution specializing in marine and polar ecosystem studies with focus on sustainable aquaculture innovation

Objectives for Automated Aquatic Monitoring System

Develop non-invasive computer vision system for species counting
Achieve <7% relative counting error across diverse environmental conditions
Enable cross-species applicability (shrimp, salmon, lobster, clams)
Support real-time data acquisition for improved production planning

Core System Functionalities

Automated object counting using CNN models (YOLOv5, Faster R-CNN)
Adaptive data augmentation for varying lighting/density conditions
Streamlit-based dashboard for inference visualization
Multi-species detection capability
High-density object overlap resolution

AI & Computer Vision Technologies

Computer Vision

Deep Neural Networks

Convolutional Neural Networks (CNN)

Object Detection Models

Density Map Estimation

Data Augmentation Techniques

System Integration Requirements

Farm management software APIs
Industrial camera systems
Cloud storage for dataset management

Performance & Scalability Requirements

Scalable to 200+ objects per image
95% accuracy on out-of-distribution test data
Real-time processing capability
Secure data handling for sensitive agricultural data
Cross-platform compatibility for farm equipment

Expected Impact on Aquaculture Operations

Implementation of this AI solution will reduce manual labor costs by 70%, improve biomass estimation accuracy for better harvest forecasting, enable sustainable farming practices through precise population management, and create opportunities for commercial expansion across multiple aquaculture sectors.