*LOFOTEN-VESTER ÅLEN OCEAN OBSERVATORY (LOVE OCEAN)* Scientists use artificial intelligence to analyze data flowing from a regional current and uncover clues about ocean health.
Over a decade, LoVe Observatory has gathered more than 100 terabytes of data from fiber optic subsea cables and sensor nodes that cover more than 52 kilometers from land to deep sea; just one terabyte is enough storage space to hold about 6.5 million document pages. Capgemini leveraged Amazon SageMaker to search through and plot this data in an end-user application for faster discovery.
Since adopting the solution, scientists are discovering completely new tidal patterns and whale behaviors. Capgemini built a system with Amazon Web Services (AWS) that’s capable of getting smarter, learning to identify anomalies on its own—with the goal to begin delivering useful analysis to the broader scientific community. Also, the system continues to evolve, including the recent addition of a web application to offer improved data visualization and allow researchers to tag anomalies in a graphical user interface.
Keeping oceans healthy means the world to the earth. The underwater universe covers more than 70 percent of the globe's surface and is critical to climate regulation. Oceans produce more than 50 percent of Earth's oxygen and store 50 times more carbon dioxide than the atmosphere.
Lofoten-Vesteralen Ocean Observatory (LoVe Ocean) is uniquely positioned one mile off Norway's shore, where the ocean floor quickly dives to great depths. Flowing through the region is the Norwegian Coastal Current, an area that teems with marine life and affects ecological systems such as ice formation. At the LoVe Observatory, analysts study this current as an important bellwether for overall climate health.
Global Data Science Challenge to develop an Amazon Web Services (AWS) Cloud-based solution using artificial intelligence (AI) to quickly analyze the sheer volume of information and put it to use.
The solution looks for oceanic patterns relevant to specific depths to identify deviations and trends-animal migrations, ocean temperature, fish stocks, salinity, PH levels, and more. Importantly, it seeks anomalies only detectable when data is viewed as a whole. So instead of analysts sifting through an ocean's worth of data to find an irregularity, the AI solution can quickly scan and showcase results that deserve a closer look, including oceanic patterns and sea life behaviors never before seen.
Now scientists can gather useful insights quickly, giving more time to drive research-helping make sense of what is happening deep within oceans and surfacing insights that may impact the wider world.
