Welcome to my podcast, which is named "Understanding Underwater," when we approaching the end of this season final, i want to focus an important topic at aquaculture’s tomorrow. Artificial intelligence is everywhere in our lifes anymore, and aquaculture is definitely not falling behind.

Today, we are looking for the short summary of using artificial intelligence at aquaculture. If you wear your hi-tech glasses, lets do!

When we think about water, it has very extreme conditions for people to work with it or work in it. At the same time, with or without each other, too many parameters to be kept under control must be carefully monitored, regardless of the size of the aquaculture operation.

AI; artificial intelligence is one of the most important technologies that the scientist work on today. When it comes to financial technologies defined as Fintech and Software as service, we benefit from artificial intelligence in more and more areas every day and receive services from it.

Our basic requirement to work in the field of aquaculture-related artificial intelligence is that we are already literate enough to be able to do business about fisheries, practically or theoretically, it doesn't matter. As listed in the main topics of the areas where artificial intelligence can be used and the solution proposals of the companies working in these topics, to successfully conclude an artificial intelligence-supported research, to bring the product to the market or simply to try a prototype, it is related to water, interaction with water, life in water and water. mastering many dynamics is a must.

The carrer path of an expert in aquaculture with AI

After gaining extensive knowledge of fisheries and fish farming, there are master's and doctoral programs where you can become an expert in artificial intelligence. These programs are very strongly intertwined with computer science, even interconnected. Unlike a course you can watch online or a bootcamp you attend, it offers a holistic and comprehensive approach to the event.

If you want to move forward in a more experimental and experience-based model of working in this field, you can start learning basic and career-advancing skills in the subject by attending online courses and boot camps. If you are looking for paid or free courses online, you can take a look at the resources of Coursera, edX, Udemy, and Google.

With its inputs and outputs, a water-based manufacturing operation has a lot to keep under control. This means that thousands will be made from the chemical structure of the water that will enter the facility to the end of the Nitrogen and Phosphorus compounds in the used water that will be separated from the facility, and it is not possible to keep all of them under control as it should be, with human power. As a result of the increasing human population, the increase in the settlements on the land and the chemical structure of the waters due to climate change and the fact that they have a more acidic tendency and become unsuitable for life increase the pressure on yield and productivity.

For example, basically,
- Monitoring of Water Quality and Chemistry
- Automatic Integration of Feeding with Monitoring Technologies
- Taking Precautions in Cages by Being Informed in Advance of Algae Blooms with Early Warning Systems
- Positioning Cages within the Water Column due to Storm

will be effective in reducing production losses and improving the well-being of the facility.

We should not overlook the closed circuit aquaculture facilities, which are one of the areas where aquaculture supported and strengthened with artificial intelligence is most needed. In such facilities, where it is imperative to keep all the dynamics under control, the fight against diseases caused by viruses and pathogens is one of the most remarkable topics. Computer-aided and artificial intelligence-supervised sensors, sensors, and surveillance tools, and tools capable of reacting to any adverse situation detected by these tools, will be the right keys to prevent epidemics that can increase the risk of production-related loss.

Time is everything in the aquaculture business, and managing time correctly while aquaculture increases efficiency. One of the fastest ways to manage time correctly is to access data in the right way and at the right time.

Now sit back and think with your eyes closed; How many places do you receive notifications from in your facility when you stay at your chair?

While some of this data that is constantly raining down on you is organized through the tools you use, most of it is raw. So it's unprocessed, unedited, and it really hasn't been decided whether to reach you or not. Artificial intelligence helps us use time efficiently with its ability to process raw data and organize it. Each facility has a big data pool that it creates with the raw data coming from it. Data always flows from the water entering the facility, the treatment system, the tanks, the feed, the oxygenation system, the sterilizer, and it is really difficult to put the instant data coming from them into a meaningful form. Even if you have the data, if you don't read it, it's no different than you don't have the data.

Data processing is not always an easy and effortless task, and the cost is not at all low. Even for this reason, an artificial intelligence model that can process the data coming from the systems in the facility and take the necessary reactions by understanding this data will be one of the indispensable components of an orderly and efficient production facility.

Usage areas of AI

Good examples of usage AI at aquaculture Farm 4.0, a project developed to bring aquaculture operations in the European Union to a better place, is one of the best examples of artificial intelligence supported new generation aquaculture. Farm 4.0 is a very important, valuable, and remarkable example in aquaculture in terms of using sensors, robotic technologies, and artificial intelligence to optimize feed and monitor water quality instantly.

Farm 4.0 is simply related to the concept of Industry 4.0, based on the integration of autonomous, decentralized technologies that can communicate with each other, work kollobrativli collaboratively. Representing the fourth industrial revolution, 4.0 is also directly related to concepts such as cloud technologies, artificial intelligence, smart production models, and cloud data.

Aquaculture in Europe provides 1.25M tonnes/year of marine seafood worth over €4B according to European Union figures. This volume is not enough to meet the demands of Europe, and this leads to a great dependence on foreign markets. EU aquaculture needs to increase its competitiveness through expansion in terms of space, production, and new value chains.

The European Commission introduced Aquaculture 4.0 in its Horizon 2020 Innovation Action Call in October 2017. In this call, Industry four point o technologies such as the internet of things (IoT) and artificial intelligence are encouraged to develop sustainable smart breeding programs and feeding methods for aquaculture. 

The future of AI usage in aquaculture

The Aquaculture 4.0 concept can be extended to fisheries management strategies that include data collection and exchange between connected nodes and real-time cloud computing processes. Many different technologies that are currently at an early stage of implementation can be embodied in Aquaculture four point o (4.0), such as recirculating aquaculture systems (RAS), mission automation to create smart or unmanned facilities offshore. Another example is Integrated Multi-trophic Aquaculture (IMTA), which consists of growing different species in such a way that the uneaten food and waste of one species is used to feed other species.

Although mobile technologies are now very common and the remote working method for aquaculture is not very common at the moment, the fact that the measurements are transferred to an internet-based platform and accessible from there and presented with clear visuals from a distance is appreciated by users; especially in marine farms where cages are sometimes not available quickly and in a timely manner.

Seems that growers will like the real-time monitoring of water and plant conditions with technologies supported by artificial intelligence. These technologies are good developments to save time for all professionals. They will allow for more accurate planning of aquaculture activities, triggering of alarms in unsafe water conditions, instant correction of duration or intensity of fish care tasks, enabling action to be taken at intervals of minutes or even seconds.

On the science side, they will provide a comprehensive database to enable scientists to conduct studies that will enable them to make fish farming facilities more detailed and efficient.

It seems that the transformation in aquaculture will continue with the developments in the digital world deeply affecting this sector. In the future, we will need more brain power to improve the efficiency of aquaculture and the sustainability of the operation, while leaving the body power to automated systems when raising fish.