Learn about tomorrow's waves and predict trauma: how AI and Big Data are changing surfing

How new technologies come to surfing

Athletes have different attitudes towards different new gadgets: their

You can use it in moderation or, on the contrary, try everything that has been invented.

For example, South African surfer Bianca Buitendag uses apps and websites for her workouts to assess wind and wave conditions ahead of a competition.

And surfer Carissa Moore, who beat Buitendag at the Tokyo Olympics by almost 6.5 points, trains on artificial waves and usesA wearable ring to track your sleep quality and other vital signs. 

Big Data to improve results

On the one hand, the latest equipment and clothing are created for athletes, for example,However, the other side is weather modeling, which helpsDetermine where and how to hold competitions: how to find optimal conditions. 

Machine learning algorithms will continue to shape surfing and will be used to:

  • improved wave forecasting
  • prevention of injuries,
  • analysis of the performance of athletes.

There are so many variables that you can't control, such aswinds, tides. 

Kevin Dean, Medical Director of Surfing in the United States.

In 2019, scientists experimented with biomechanics data they obtained using camerasThey quantified the jumping and landing mechanisms and were able to obtain data on the minor movements that performThe authors also studied the force that the athlete exertsto the board. 

Typically, there is an imbalance between each limb, and this imbalance can be a critical factor that either the athlete controls or does not control and this leads to injury.

Tracy Axel, U.S. Surfing Data & Analytics Manager

The Surfing Data and Analytics Organization in the U.S. is developing a machine learning system that could analyze some of the same information based on photos of a surfer riding.

In January 2021, the team developed a prototype of the program: it canidentify the main maneuvers and the most frequent posture when riding.

It is planned that the future AI-based program will be able to help teams choose the best surfers, prevent injuries and review their own mistakes in order to avoid them later.  

Artificial and Surfing Waves

The Flowrider artificial wave was invented by the American company Waveloch in 1991.This is an elastic cloth stretched over the frame at an angle of 17 degrees, to which a powerful flow of water is supplied.

The thickness of the water layer is about five centimeters, and the flow rate is about 50 km/h, which makes it possible toThe velocities of the flow and the rider cancel each other out, so that in fact the riderMaybe just balancing in place. 

Today there is a whole clusterwaves, which can be called artificial waves, since they have the same dynamics as ocean waves: a push is made from behind, a wave rises, a wall is formed along which a surfer can move.

Technologies to monitor the health of surfers

Wearable technology can track performancesurfers health: cardiovascular system, sleep patterns, heart rate and injury rate. Also, specifically for surfers, factors that can affect performance have been studied.

For example, scientists have shown that ankle stiffness and hip stability influenced a surfer's ability to land “in the air”.

Wave forecasting

Wave prediction app is the most popular machine learning-based app for surfers.  

Wave forecasting has recently benefited from some technological advancements, such as image and voice recognition. In part, this is what the Surfline Inc. team has enabled. Help identify the surf beach where the Olympic competitions will be held.Despite the fact that Japan is not that popular for its surf beaches, the employees of Surfline Inc.Using decades of climate data to determine the optimal location for the Olympic Games. 

Surfline Inc. also uses and analyzes a lot of data, including satellite imagery, ice cows in the Arctic Circle, the shape of the seabed, the nature of theWind.

We have a computer that processes all this data to help us make decisions based on the predicted state of the waves.For Olympic competitions, Surfline's models helped determine which days the athletes would becompete.

Kevin Wallis, Director of Forecasting, Surfline

For forecasts, they also use feedback from surfers and data from a network of 800 cameras, on the basis of which employees analyzeWave patterns. 

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