The Future of Data Management and Analysis in Aquaculture

Aquaculture farms have always faced unique challenges in managing their operations, with production being highly dependent on water quality, environmental conditions, and the health of its fish. As artificial intelligence continues to become more popular in day-to-day operations, big players in the aquaculture industry have begun to learn how to leverage technology to improve their operations, with data being at the forefront of these innovations.

What is Data Analysis?

Data analysis is the process of examining and modelling data with the intention to extract useful information. This can help farms make important decisions with data-backed conclusions. It involves using various techniques and tools to identify patterns, relationships, and trends within an ocean of data. While this can seem complicated for some, learning to use statistical methods can derive insights and unlock trends that will greatly benefit the company in the long-run. The insights gained from data analysis can help with creating business strategies, increase production, optimize operations, and much more.

Data Analytics and AI

ReelData AI is creating artificial intelligence tools for the under-served land-based industry and aiming to revolutionize the way aquaculture companies manage and analyze their data. Where data analysis is used to gain insights into a particular focus, machine learning uses that data to learn patterns and create predictive models to make accurate predictions on new data. Their products offer a streamlined approach to data analysis, with ReelAppetite and ReelBiomass monitoring feed output and biomass estimation, respectively, all within one platform. Machine learning (or artificial intelligence) has become increasingly popular in aquaculture over the past few years, as farmers have begun to see the benefits of receiving real-time insights that help improve accuracy in day-to-day operations. This helps farmers make quick and informed decisions on the day-to-day management of their operation, helping to protect company-wide investments while minimizing risks. Fully utilizing ReelData’s products can unlock a higher-level of control over the functionality of your tank and help you reach your goals.

One of the key features that data analytics offers is its predictive capabilities. By analyzing historical data within a tank, it’s possible to forecast future trends and events, helping businesses to plan and prepare for potential challenges. This can be especially helpful in aquaculture, where environmental conditions can fluctuate and impact the health and appetite of its fish. Leveraging technology such as ReelData’s platform, will help businesses make informed decisions that increase their chances of success.

Bruce Ferguson is a Principal Machine Learning Engineer at ReelData. He has a wealth of knowledge and experience in data analytics, having held such positions as Senior Data Scientist, Lead Machine Learning Engineer, and AI/Machine Learning Advisor before joining ReelData in 2023. He believes that one of the most crucial components for a company leveraging data-driven machine intelligence, is its commitment to “continuous learning” as well as its “alignment with client needs.”  He elaborates further by stating that “Our team at ReelData is dedicated to providing the best possible solutions through which aquaculture businesses can manage risk and return. We’re constantly researching and developing new technologies to ensure that our platform remains at the forefront of data analysis and management.”

In addition to improving efficiency and decision-making, ReelData AI can also help businesses reduce costs associated with manual data entry, analysis, and reporting. ReelAppetite functions as a tool to monitor feed output and appetite. By analyzing data from wasted feed pellets, our AI is able to predict the perfect ratio where fish are never starved or overfed, creating the optimum ratio for growth, water quality, and profits.

Data Analytics in the Future

Focusing more research into data analytics could be the answer to solving many of the challenges the land-based aquaculture industry faces. After asking some of the machine learning experts at ReelData, we’ve collected a list of the top three ways we may see the industry improve as data analytics becomes more popular:


1. Disease Detection

By analyzing data on pH, dissolved oxygen, temperature, and other parameters, farmers can identify potential issues that could impact fish health and growth. It can also be used to detect early signs of disease outbreaks in fish populations. By monitoring data on fish behavior, growth rates, and mortality, farmers can identify potential issues and take corrective action before the outbreak becomes widespread. Automating these processes can save time and resources while minimizing losses and reducing the need for expensive treatments.


2. User Interfaces and Key Performance Indicators

ReelData AI offers user interfaces that provide businesses with a clear and concise overview of their data. This allows businesses to easily monitor key performance indicators (KPIs) and track progress towards their goals. With this level of transparency, businesses can quickly identify areas that require improvement and make necessary changes.The platform is built for scalability, meaning that it can be used by businesses of all sizes and can handle large volumes of data. This makes it an ideal solution for businesses looking to grow and expand their operations.


3. Risk Mitigation

Looking towards the future, data analysis and management in aquaculture can be used to monitor other aspects of day-to-day operations, by examining the functionality and longevity of a farm’s equipment. Collecting and analyzing data from equipment sensors and maintenance logs will help mitigate the risks of equipment failure before they occur. It can help with the scheduling of predictive maintenance and planning of replacement parts, reducing downtime. This has the potential to save entire tanks worth of stock and eliminate the fallout from these crises.

Using data for predictive maintenance can also help find root causes for future problems, eliminating issues and preventing them from happening again. This can also help with decision making when preparing to scale, by determining the equipment most suitable for your farm and eliminating the guesswork in the productivity and longevity of your materials.


Conclusion

In the future, data analytics will play a crucial role in the aquaculture industry, enabling farmers to harness its full potential for growth. By properly analyzing and managing data, farmers can improve their operations, reduce costs, and mitigate risks to unlock the industry’s vast potential for growth. ReelData AI offers comprehensive solutions that are well positioned to drive the future of the aquaculture industry. With its commitment to staying at the forefront of technological advancements in data-driven machine intelligence, ReelData AI can empower businesses to thrive in this dynamic industry by unlocking valuable insights from data, propelling the aquaculture industry to new heights of success.

Caitlyn Parsons
Marketing and Public Relations Associate
ReelData AI
caitlyn.parsons@reeldata.ai