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Define the Problem and Goals

The key business problem is the spread of sea lice salmon farming increases operational costs and lowers salmon yield.

If an AI solution is successful, it should be able to achieve the following goals:

A decrease in salmon deaths of 20% Reduction of monitoring costs by 50% Maintain or decrease in cost per healthy adult salmon

Identify a Solution

Use the camera array to capture salmon images, then segment individual salmon using computer vision and finally, classify if salmon are sick or healthy.

Describe Your Solution

To build this solution, we should create a pipeline with two main parts.

1. Train a computer vision model to isolate images of individual salmon from the camera feed.

The metric is the % of properly segmented salmon in the whole image. Since we want to make sure the model is properly finding the salmon and outputting usable images

2. The isolated images are fed into a supervised learning model to classify sick fish.

The metrics here are accuracy and recall. Since we will have our team review the sick salmon before applying treatment, we want to optimize for capturing all sick salmon instead of worrying about false positives.

Determine Key Outcome Metrics

Healthy Adult Salmon Yield: Calculated as a percentage increase compared to populations using the previous unaided approach

Time Saved: Calculated as a percentage of time saved compared to similar unaided

Cost of Treatment: Calculated based on the average treatment cost per healthy adult salmon produced compared to unaided