After buying her own surfboard on Craigslist, Jasmine Simmons, a fourth-year UC San Diego CSE undergraduate, taught herself to surf. Now, she is using her board to ride waves and gather important ocean data through the Smartfin Project.
A collaboration between the Scripps Institution of Oceanography (SIO) and the Surfrider Foundation, Smartfin analyzes data from near-coastal ocean regions, where people surf and play.
The program is an offshoot of the Coastal Data Information Program (CDIP), which collects information on wave heights, periods, directions, sea surface temperatures and other ocean parameters.
Near-coastal areas are particularly important because they are harder for satellites to measure, and sea surface temperatures and wave patterns are largely unknown. With more real-time information about wave movement, lifeguards can make informed decisions about how waves affect the people they protect.
Simmons learned about Smartfin, and began working under senior research engineer Phil Bresnahan, during her Research Experience for Undergraduates. Bresnahan helped create Smartfin’s hardware: a surfboard fin with embedded sensors. Since 2016, these fins have been distributed to surfers worldwide through the Surfrider Foundation. The data is uploaded after each surfing session.
Simmons and other computer scientists are examining the ocean data from Smartfin to develop a data processing framework to analyze CDIP’s ocean parameters. But the platform can be a challenge. Raw data can be biased by surfer movement. Simmon’s team is calculating significant wave heights, peak periods and peak directions. They also hope to plot surfers’ paths to determine where they started and ended and where their best waves were.
From her work on the project, Simmon’s has become interested in data mining and machine learning. This interest has melded with her minors in mathematics and ethnic studies. Since learning about biases in the artificial intelligence systems used by high-level corporations, Simmons has wanted to combine her passion for social justice and data visualization to create non-biased artificial intelligence systems with cleaner data sets. Read more.