The SWIMTAG wristbands use a number of sensors to accuratly record the swimmers arm movements in the pool, data from these sensors is uploaded to our processing servers and translated into the swim results that are published to the swimmers account using a number of proprietory software algorithms.

These algorithms have been developed over more than 10 years and 4 million swims uploaded to the platform. Our Swim Editor tool allows users to check their own swim data (when using a SWIMTAG band) and make adjustments, they can 'rate' the accuracy of their results which means any innacurate data is fed back to us for review.

The SWIMTAG team have developed a robust machine learning model for processing swim data from the SWIMTAG wristbands sensors, the model has been trained from over 100,000 uploads that have been manually tagged from a database of more than 1 million swims

Our ML model continues to evolve as we gain more feedback from our swimmers and new data is uploaded however with less than 0.001% of our swims reported with errors we are confident it is producing consistently reliable and accurate data.

Our ML models can be used with data from SWIMTAG wristbands or any other 3rd party accelerometer output. If you are interested in learning more about leveraging our technology Denne e-postadressen er beskyttet mot programmer som samler e-postadresser. Du må aktivere javaskript for å kunne se den.