10 Applications of AI in Aquaculture

Cultivation of any livestock requires determination, strength, and innovation. Be it agriculture or aquaculture, using equipment is the key to manifesting a profitable business and an expandable career in the field. 

 

Aquaculture refers to the cultivation of aquatic animals and plants in various water environments for commercial purposes. While most people would assume that aquaculture is only referred to as the breeding and harvesting of fish, it is much more than that. 

 

Unlike agriculture, aquaculture involves a variety of techniques and more complicated processes so as to breed a better lot of aquatic organisms and keep up with the prevalent standards. This requires advanced technology and related equipment to work throughout the clock and take care of the livestock. 

 

Aquaculture can be carried out in 2 different settings - marine and freshwater environments. Marine aquaculture refers to the raising, breeding, and harvesting of aquatic livestock in a natural water body like the ocean. 

 

This is a natural setting and requires the practitioner to visit the setting day by day. On the other hand, freshwater aquaculture refers to the cultivation of aquatic cultivation in a man-made setting such as a pond or an artificial lake. 

 

This allows the professional to remain close to the aquaculture site from day to night and adjust the settings as and when s/he wants and seems fit. 

 

A number of factors like water temperature, dietary routine, and oxygen level are essential to maintain the supreme quality of aquaculture livestock and maintain a suitable environment for the same. 

 

This way, it is appropriate for the professionals to produce commercially profitable livestock that outruns the ordinary standards of the livestock. 

 

Simply put, aquaculture is farming in water. With the emergence of this practice, many farmers have taken up the job to produce environmentally sustainable sources of food in optimal environments for the masses. 

 

Also Read | AI in Agriculture

 

Applications of AI in Aquaculture

 

While aquaculture is a vast industry in itself that has spread across the world like a wildfire, it is not as simple as it may sound. With the emergence of innovative technologies in aquaculture, fish farming technology has fairly progressed in a bid to advance itself and make way for more technologies to invade its arena. 

 

Artificial Intelligence in aquaculture is one such technology that can be used and applied for better outcomes and results in the long run. Here are the top 10 AI applications in aquaculture that will be discussed in this segment. 

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Applications of AI in Aquaculture

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1. Automated Feeding System

 

The very first application of artificial intelligence in fisheries is the automated feeding system. Even though freshwater aquaculture allows the cultivator to stay in the vicinity of the farming location, feeding the fish can be a tiresome process. 

 

Likewise, farmers can sometimes forget or they may even remain unavailable for some reason. This is where AI can be extremely helpful and step into the cultivators’ shoes using automation feeding systems. 

 

Using the technology of an automated feeding system, AI can facilitate automatic feeds for the fish. This can happen with AI-empowered tools that release a registered amount of feed for fish to intake and sustain. This is also a very helpful way to minimize food wastage and optimize food consumption among the livestock.

 

“Feeding represents the biggest cost to fish farmers, so optimisation in this area always means better profitability.”

 

2. Remote Monitoring and Maintenance

 

AI in aquaculture allows the cultivator to remotely monitor and maintain the farming location. This involved alarming the farmer about any blockages, exhaustion of food supplies, or any other concern that might be important to resolve on an immediate basis. 

 

The purpose of remote monitoring and maintenance is that it allows the farmers to freely roam around while being able to monitor their aquaculture sites with accuracy. Thanks to AI, the need to constantly remain present around the field is no longer viable. 

 

3. Growth Statistics

 

The third application for AI in Aquaculture is that it provides the facility to monitor and interpret growth statistics for your livestock so that you can substantially evaluate the correct strategies. 

 

This means that by using the power of AI, farmers can not only identify the loopholes in their cultivation practice but also be mindful of the upcoming steps and damage control to ensure that their livestock turns out to be just fine. 

 

The use of growth statistics is also a major contribution to the collection of big data and big data analytics to help others in analyzing the correct practices and steps for the same. 

 

4. Temperature Optimization

 

Freshwater aquaculture is a hub for experimentation and adjusting the circumstances so as to identify what affects the culturing of the livestock. This calls for the need to discuss the significance of temperature. 

 

In aquaculture, temperature plays a big role in keeping the thermal environment around the fish optimal and ensuring that it remains balanced throughout. 

 

Temperature optimization can be performed through artificial intelligence and machine learning algorithms that allow farmers to set their preferences and extract customized models for their farming site. 

 

For instance, AI can help farmers to reduce the temperature in the daytime under the presence of the sun while increasing it at night. 

 

5. Water Quality Regulation

 

Another advantage of using AI in aquaculture is that it can easily detect water quality and regulate it. Water quality is another very important factor that determines the health and survival of livestock throughout the process of cultivation. 

 

If any foreign particle tends to contaminate the quality of the water that the fish are living in, AI-empowered sensors can easily inform the farmer and lead to regulatory measures. 

 

This involves filtering the water, replacing the water, or even releasing antibodies to nullify the effect of contaminated particles. This particular application of AI makes the industry of aquaculture very advanced yet progressive. 

 

6. Consistent Aeration

 

As mentioned earlier in this blog, oxygen is a very important factor for the survival of livestock. That said, consistent aeration and release of oxygen help the fish to breathe and survive easily as opposed to other environments where the lack of oxygen can easily lead to a massacre of livestock. 

 

Thus, AI is again helpful in managing and maintaining the oxygen level in the water that the fish are being raised in. This takes place through a machine learning model that allows the release of oxygen at regular intervals. 

 

Furthermore, if the oxygen level becomes too much or too less, then the sensors can immediately report the same and lead to a balanced environment for livestock. 

 

7. Smart Sensors

 

Imagine someone is trying to break into your house in the absence of all your family members. How will you get to know? Artificial Intelligence. 

 

Smart sensors, a well-known application of AI, have long been used to alarm house owners, bank officials, and aquaculture farmers. As soon as toxin levels go up, or oxygen is too less, smart sensors with built-in AI technology are capable of alarming the farmers in no time. 

 

This real-time information travels within a span of seconds so that the farmer can get to know as soon as possible. The use of smart sensors is more of an advantage than an application for the farmers as it is very helpful and insightful at the same time. 

 

8. Human-less Filtration

 

As opposed to the earlier days when aquaculture farmers had to manually filter the water and maintain the water quality, the contemporary era has become much more advanced. 

 

Powered by AI, human-less water filtration can be easily performed with the help of pre-installed machinery. Hence, the use of AI in aquaculture negates the need for farmers to manually perform tedious activities and invest long hours into the same. 

 

It is important to note that all these functions can take place simultaneously in order to keep up with the demands of the livestock and lead to better outcomes for the practice altogether. 

 

9. Predictive Measures

 

Ever heard of predictive analytics? Well, one of the biggest applications of artificial intelligence, predictive analytics paves the way for aquaculture practitioners to not only strategize their upcoming actions but also work along the lines of the forecasted notions so that they can do the best for their livestock. 

 

Using predictive analytics, they can certainly procure insights into possible future outcomes and prepare against them. 

 

Like any other field, aquaculture too can largely benefit from the sole application of predictive measures alone. Based on the past data and findings, AI can point you in the right direction so as to produce better results. 

 

10. Big Data Analytics

 

The last application of AI in aquaculture is that it employs big data analytics to accumulate records of information and help others in taking the right steps. 

 

With the help of big data, farmers can very well comprehend the risks and challenges that they might face in the process and take appropriate steps to ensure that they are on the right path. 

 

So, big data analytics not only provides you with a summary of the practice but also capitulates the dos and don'ts in order to help farmers. 

 

“Artificial intelligence is improving aquaculture by making farmers understand the analytics of how their inputs affect fish growth under various conditions.”

- Big Data Analytics in Aquaculture 

 

Also Read | How Big Data Analytics is using AI?

 

 

Future of Aquaculture

 

Aquaculture is a profession that emerged more than 4000 years ago. With the increasing dependency of humans on aquatic animals and plants, the need for aquaculture is growing rapidly. 

 

With a long history and an even longer journey of innovation and evolution, aquaculture still has a long way ahead. However, with the use of AI, the scope and margins of aquaculture as a profession and a cultivation practice have become widened. 

 

In the wake of advanced technology, aquaculture is moving towards a more developed and evolved world of technology and related advancements where one day fish could even be cultivated in the metaverse! 

 

To sum up, aquaculture is a distinct field that could have possibly not been able to apply AI in its aspects. However, with the beneficial scope of the technology, aquaculture has fairly seemed to grow in the day of light.