Scientific research in marine biology and ecology is entering a new era, thanks to the power of AI algorithms to tap into the massive amounts of statistical marine data now available to scientists. The field is entering a new era of intelligence as the integration of AI and traditional data models is helping researchers address a wide range of global challenges. Everything from improving marine safety and solving the problems of water pollution to monitoring marine biodiversity, investigating deep-sea resources, and predicting tides, sea ice, and climate are all now in the domain of the marine AI researcher.
Use Cases for AI in Marine Biology
The following are a number of important use cases for AI in the marine biology ecosystem.
Monitoring Marine Biodiversity
AI is able to analyze a high volume of multi-parameter data points to monitor complex marine ecosystems, helping to build a robust, widely distributed monitoring network for marine environments. Because of the complexity and specificity of marine ecology, older data solutions are insufficient to monitor these environments. AI-powered monitoring tools enable automatic identification, classification, and prediction of data events. In one example, a research team was able to train a neural network to identify humpback whale songs in more than 187,000 hours of acoustic data that was gathered over a 14-year period.
Modeling Deep-sea Resources
Scientists have always been challenged with modeling seabed resources, and today a combination of AI algorithms is helping to build an innovative 3D modeling approach to improve re-transportation of sediments in the water and reconstruction of the seabed. Scientists created an AI-powered mathematical model to estimate the distribution of cobalt-rich manganese crusts by analyzing sensor data from an autonomous underwater vehicle (AUV), and a light-profile mapping system to create a 3D color reconstruction of the seafloor.
Observing Seal Populations
Ecologists have monitored seal populations around the world for many years, but counting the number of seals in photos requires hours of painstaking work to identify animals in each image. Today, scientists are using deep-learning models to count seal numbers in archived photos taken in the past. They can sort through 100 images in less than one minute, compared to a full hour for a human to perform the same task. The new model eliminates the need to first label individual seals beforehand, then count them in each picture. These developments will provide important new insights into how seal populations have evolved over time.
Counting and Categorizing Fish
AI is helping marine biologists better monitor plankton and fish stocks, using AI algorithms to count the fish, monitor their size, and even distinguish one type of fish from another. The observation and counting process used to be a manual task conducted by individuals who had to sort through hours of film footage to gather the information, all very time consuming. Now with AI, they can automate the observations to get different fish species and size, and they get the information immediately. AI can distinguish not only different species but also different individual fish, giving researchers deeper insights into how a fish lives over several years.
Predicting Critical Ocean Parameters
Important parameters such as sea surface temperature, tide level, and sea ice can all impact climate and marine ecosystems. One scientific team created a deep learning model that captures the correlation of surface temperatures over time and over large spaces. The new models were proven to outperform older methods when analyzing data in the East China Sea, providing the promise for more accurate daily predictions of sea surface temperatures.
Analyzing Marine Life With Cameras
Cameras mounted on AUVs can collect vast amounts of data in the ocean, but the bottleneck still takes place by humans having to analyze and process it. AI-driven computer vision systems were shown to be 80 percent accurate in identifying different animals on the seabed, and 93 percent accurate for specific species being investigated if enough data is used to train the algorithm. Scientists can deploy this type of technology to study marine animals and plants in order to increase the amount of data available for conservation research and biodiversity management.
AI to Protect Ocean Environments
AI is also helping scientists protect ocean resources. Two key areas that are having a big impact on ocean ecology:
- Reducing Plastic Pollution: Marine life experiences major damage from plastic pollution, with one million birds and 100,000 marine animals dying from plastic dumping every year. New AI models are helping to build more informed tactics to reduce plastic pollution, including using AI tools to extract plastics more efficiently and ultimately restore coastal environments.
- Saving Coral Reefs and Marine Life: Coral reefs have highly diverse ecosystems and provide habitat to more than one quarter of all marine life. Researchers are using AI to monitor, classify and analyze the health of coral reefs, using data from underwater cameras equipped with video analytics systems.
Stay ahead of the tech-game with our PG Program in AI and Machine Learning in partnership with Purdue and in collaboration with IBM. Explore more!
Conclusion: AI Can Help Save Ocean Resources
It’s good to see advanced technologies like AI contribute to worthy causes like saving the Earth’s natural resources and protecting marine life. Anyone can get involved these days in the fun by acquiring the necessary skill sets in the fields of AI and machine learning to apply to marine biology. It’s the perfect entry point to making a difference in the world!