Feeding the world is no small task and addressing growing global demand for healthy, sustainable food sources will undoubtedly take many industries working together; but the aquaculture industry is uniquely poised to play a pivotal role.
The practice of raising aquatic life in a controlled environment is not new, but with a 120% increase in consumption of aquatic foods worldwide in the past 30 years, it is stepping farther into the spotlight. In fact, aquaculture is growing the fastest out of all sectors in the global food industry, contributing half of consumable aquatic products with the expectation that its contribution will rise to 60 percent by 2030.
As this industry grows, the need to produce food sustainably, reduce production losses, maintain fish health, monitor water parameters, and stay in compliance with ever-changing global regulations grows along with it. When dealing with living animals and plants, small changes in environments can have swift and far-reaching impacts, and the better data you have, the more time you have to adequately react to any variances before they result in fish die-off. Just collecting and sending in information required by regulatory bodies worldwide can be incredibly time-consuming.
The solution to addressing these challenges lies in advances in big data management tools that both digitize the collection process and help turn raw time series data into usable information that is available when you need it.
Understanding Time Series Data Analysis
In aquaculture monitoring, valuable information and insights are often gained from using time series data, or data collected chronologically at discrete and regular points over a period of time. Time series data analysis helps provide understanding for the past behavior of a metric and can help forecast future behavior. Whether you have heard the phrase “time series data” or not, you are certainly familiar with it. For example, the data collected from monitoring water parameters hourly is time series data.
When working on time series data analysis, one key step is visualization of the data. Without it, you only have sets of numbers and the critical information contained within them can be hard to see. Simply having a time series graph that displays your single-variable (univariate time series) data on one axis and the time it was collected on another can lay the foundation for understanding and predicting behavior. For example, you can see if there is a trend over time such as increasing quantities of feed needed for fish throughout a lifecycle, or you can detect seasonal trends in water temperature.
In aquaculture, like most industries, expanding analysis to include multiple variables (multivariate time series) can provide even greater insight and contribute to better forecasting through machine learning. However, analysis increases with complexity as more variables are introduced.
Benefits of Time Series Data in Aquaculture Monitoring
Time series data analysis offers several practical, tangible benefits to the aquaculture industry from hatching to processing and packaging. It will help you identify patterns, detect anomalies, and forecast future behavior of variables. Specifically, it can help you:
- Visualize processing and packaging operations across facilities
- Forecast growth models to find efficiency opportunities in feeding conversion and trajectories
- Identify potential changes in yields and overall aquaculture conditions
- Understand fluctuations in water parameters and their root causes
In addition, time series data analysis based on both historical and real-time data allows for machine learning in aquaculture, ultimately allowing you to detect anomalies, find patterns, and look ahead to identify possible bottlenecks, labor inefficiencies, and opportunities for increased production.
Big Data Management Tools for Aquaculture
Time series data analysis is a valuable tool, but in an industry like aquaculture, you are working against the clock. Temperature changes, algae blooms, and spoilage of fresh fish require swift action. Traditional data management techniques mean both manual collection and analysis of data—a time-consuming process that delays your ability to react quickly. That’s where big data management tools, like Sightline EDM, become critical to detecting and anticipating issues.
Sightline uniquely caters to the aquaculture industry and is the only software on the market designed to digitize and automate aquaculture data collection and analysis to get you actionable insights quickly, while streamlining regulatory reporting. In turn, this helps aquaculture operations seamlessly maintain compliance regardless of what changes in regulatory requirements may occur.
Sightline’s software seamlessly integrates with different hardware sensors and software to:
- Provide live data collection, visualization, and automatic reporting of real-time data on all parameters of an aquaculture operation, including at remote locations.
- Leverage aquaculture machine learning to empower you to project key elements for growth models, conversion, and feeding trajectories.
- Utilize artificial intelligence to account for changes in environmental conditions to optimize feed and oxygenations, ultimately leading to optimized biomass.
- Minimize the impact of algae blooms on fish in the pen.
- Provide 24/7 aquaculture monitoring to alert you to changes in water oxygen, temperature, salinity, algae blooms, contamination, weather, or escape threats.
- Give whole-picture visualization of hatcheries, grow-out systems, and feed requirements.
- Access advanced forecasting reports and analysis of processes and production.
- Prevent escapes by measuring and assessing water currents, wind, waves, anchor moorings, and netpen security.
- Report real-time data to regulatory agencies on required metrics.
Ultimately, Sightline EDM can help position seafood farmers to take advantage of the opportunities presented by the growing aquaculture industry.
Book a conversation today with an EDM expert to learn more about how to gain insights into your aquaculture operation and streamline data collection, analysis, and regulatory reporting with Sightline Systems.
FAQs:
Time series data is collected chronologically at discrete and regular points over a period of time. Time series data analysis is a set of tools that help interpret the data to offer real-time insights into past behaviors of a metric and helps predict future behavior.
Time series data analysis helps the aquaculture industry identify patterns, detect anomalies and forecast future behavior of variables such as water parameters and feeding conversion and trajectory.
Sightline EDM is uniquely suited to aquaculture monitoring and data analysis, which is especially time-sensitive, and is designed to offer actionable insights quickly and allow you to leverage machine learning in aquaculture, while streamlining regulatory reporting.