Top 4 AI Solutions for Aquaculture Biomass Monitoring

The fish and seafood industry are important because it gives us lots of yummy food every year. But to make sure it’s done in a good way that keeps everything in balance, we need to be careful about how many fish there are.


Guess what helps us do this better? It’s like having a super-smart computer friend called Artificial Intelligence, or AI for short. This friend is changing how fish farms work by making sure we know exactly how many fish there are and how to take care of them.


In this article, we’ll talk about four cool ways AI is helping fish farms be even better at keeping things in balance. It’s like having superhero tools that make sure we have enough fish to eat and take care of our planet at the same time!


1. Computer Vision-Based Biomass Estimation



Imagine if cameras and smart computers worked together to keep an eye on fish in a farm. That’s what computer vision does! It takes pictures or videos of the fish and uses super-smart tools to figure out how many there are. It’s like having a robot friend that helps farmers know exactly what’s happening with the fish in their tanks or cages.

How It Works:

  • · Cameras are strategically placed in the aquaculture facility to capture images or videos of the fish.
  • · AI algorithms identify and track individual fish, measuring their size and weight.
  • · By analyzing data from multiple cameras over time, the system estimates the total biomass of the fish population.


  • · Continuous, non-invasive monitoring without disturbing the fish.
  • · Real-time data for better decision-making, including feeding schedules and harvest timing.
  • · Improved growth and feed efficiency, leading to cost savings and reduced environmental impact.

2. Environmental Monitoring and Data Integration



Think about having cameras and clever computers team up to watch over fish on a farm. Well, that’s what computer vision does! It takes pictures or videos of the fish and uses really smart tools to count how many there are. It’s like having a friendly robot that helps farmers know everything about what’s going on with the fish in their tanks or cages.


How It Works:

Sensors are deployed in tanks or cages to continuously measure environmental parameters.


AI algorithms analyze this data alongside biomass data to identify correlations and trends.


Alerts and recommendations are generated based on real-time conditions, helping prevent disease outbreaks and optimize feeding regimes.



  • · Proactive management of water quality and environmental factors.
  • · Reduced mortality rates and disease risks.
  • · Enhanced sustainability by minimizing the environmental impact of aquaculture operations.

3. Acoustic Biomass Estimation



Advancements in acoustic technology have brought about significant progress in the realm of aquaculture. This method utilizes underwater sonar alongside AI algorithms, offering a non-invasive and highly accurate means of estimating biomass in open-water farms, like net pens.

How It Works:

  • · Sonar devices emit sound waves that bounce off fish and return as echoes.
  • · AI algorithms analyze these echoes to determine fish density and size distribution.
  • · The system calculates biomass based on the density and size data.


  • · Non-invasive monitoring in open-water environments.
  • · Reduced labor and costs associated with manual sampling and counting.
  • · Enhanced accuracy, particularly for species that are challenging to observe directly.
  • · FAQs:

4. Machine Learning-Based Growth Prediction



Machine learning algorithms are being employed to predict the growth and development of aquaculture species. By analyzing historical data and environmental factors, these AI systems can forecast the

expected growth rates of fish or other aquatic organisms, aiding in efficient resource allocation and harvest planning.

How It Works:·

Historical data on growth rates, feeding schedules, and environmental conditions are collected.

  • · Machine learning models are trained to identify patterns and correlations within the data.
  • · These models can then predict the future growth trajectory of the aquaculture population.


  • · Optimized feeding schedules and resource allocation.
  • · Reduced feed wastage and operating costs.
  • · Enhanced sustainability by minimizing overfeeding and underfeeding.


Accuracy depends on factors like camera placement, image quality, and algorithm performance. With proper setup and calibration, computer vision systems can achieve high levels of accuracy, often exceeding manual methods.

Yes, computer vision-based biomass estimation is adaptable to various species, including fish, shrimp, and even mollusks. The key is to train the AI algorithms for the specific characteristics of the target species.

The cost of implementing AI solutions in aquaculture can vary widely depending on the specific technology, farm size, and complexity. However, over time, the benefits, such as increased productivity and reduced losses, often outweigh the initial investment.

Privacy concerns may arise if AI systems involve video monitoring of workers or visitors to the farm. It’s important for aquaculture operators to communicate their use of AI for monitoring and ensuring compliance with privacy regulations and best practices

Yes, AI solutions can be tailored to the scale of aquaculture operation. Some technologies may be more cost-effective for smaller farms, and they can still provide valuable insights and improvements in efficiency and sustainability.

AI systems can monitor a wide range of parameters, including temperature, dissolved oxygen, pH, ammonia levels, turbidity, and salinity, among others.

AI can detect early signs of stress or anomalies in the environmental data, which may indicate disease threats. By acting on these alerts promptly, farmers can take preventive measures, such as adjusting water quality or isolating affected fish.

While machine learning can detect patterns that may indicate disease risks, it is not a substitute for dedicated disease monitoring systems. It can, however, complement disease management efforts by providing early warning signs.

Acoustic technology is particularly well-suited for open-water farms like net pens. In closed systems or tanks, other methods like computer vision may be more appropriate

The depth at which acoustic technology can effectively monitor biomass depends on the specific equipment and environmental conditions. In some cases, it can operate at significant depths, making it suitable for various aquaculture scenarios.

Our Last Word...

Imagine if computers could help fish farms in a big way! That’s what’s happening with AI, which is like a smart computer brain. AI is making sure that fish farms are doing better and being more careful with the environment.


There are cool things AI does for fish farms. First, it can look at pictures to figure out how many fish there are – like counting them really fast! Then, AI also checks if the water where the fish live is good for them, like checking the temperature and other important things. And guess what? AI can even use sound to understand how many fish are in big underwater nets!


All of these smart AI tricks are changing how fish farms work. They make things more exact, faster, and better for the planet. As more people want fish to eat, AI helps fish farms do a great job while being kind to nature. So, using AI is like having a superhero helping fish farms to be super smart and good for everyone!



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