Machine Learning Counting Fish? Using ML for Data Processing Needs

Machine Learning Counting Fish? Using ML for Data Processing Needs
Use cases such as machine learning counting fish become possible when using ML to handle data processing tasks. This lies at the heart of the Aquafalcon.

AI provides many significant advantages to organizations able to successfully leverage this technology innovation. Did you know this includes machine learning counting fish? Yes, even unique use-cases like this become possible when using ML to handle huge data processing tasks.

In fact, the ability of machine learning to count things lies at the heart of the Aquafalcon. This innovative product helps fish farms manage the scourge of sea lice, which have an adverse affect on the process of raising salmon. Here’s a quick analysis of a great example of the benefits of using machine learning on your company’s next product.

Raising Salmon Effectively by Using Machine Learning for Counting Fish 

Raising salmon on a fish farm requires a proactive approach to preventing sea lice. When left untreated, these parasites attach themselves to the fish, feeding off of their skin and blood. Not surprisingly, this causes devastation to the supply of farm-raised salmon, which provides an important protein source to feed a growing planet.

While chemical treatments are possible, their overuse adversely affects the fish; with the lice eventually building a resistance to the chemicals being used. Given this scenario, the Falcon Sea Lice Detection System (also known as the Aquafalcon) offers great hope to fish farmers. The system relies on the work of a machine learning software agency for counting fish and intelligently detecting sea lice. Let’s take a closer look at its features and functionality.

The Aquafalcon Enables Fish Farmers to Protect Their Investment 

Leveraging underwater cameras, the Aquafalcon system monitors salmon within a fish farm. This distinct ability of machine learning for counting fish also determines which salmon are infected with sea lice. Farmers now easily identify the level of lice in their pens, allowing them to proactively react to any infestation. Healthier salmon leads to better yields, and a more productive and profitable fish farm.

The Aquafalcon uses machine learning routines to deliver intelligent and actionable data to the farmer on his desktop computer. It automatically counts and classifies fish numbers; saving time while reducing risk to farm employees. All data gets stored in the cloud for accurate reporting, especially when compared to manual processes. This real-time information over a 24/7 window helps farmers effectively deploy lice treatments with surgical precision as necessary.    

Ultimately, the Aquafalcon provides a great example of the massive data processing power of machine learning. Even if not counting fish, a development agency experienced with a one of a kind use-case like this can help bring your company’s next idea to fruition. So connect with the team at NineTwoThree to discuss your plans for the future!

Tim Ludy
Tim Ludy
Articles From Tim
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